Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 112 appraisals
Rheumatic diseases clinics of North America
Toward Artificial Intelligence-driven Clinical Decision Support Tools in Rheumatology
Clinical decision support systems (CDSS) have the potential to enhance rheumatology practice by assisting with differential diagnosis, treatment decisions, and predicting patient outcomes. Rheumatic conditions are complex diseases largely diagnosed clinically rather than with a predefined set of clinical, laboratory, or imaging findings. Newer artificial intelligence (AI)-driven CDSS, known as machine-learning-based systems, may be better suited for applications to rheumatic conditions compared to knowledge-based systems, which rely on a set of predefined rules. This report reviews existing studies on CDSS in rheumatology and highlights the potential benefits and pitfalls of incorporating AI-driven CDSS into rheumatology practice.
1 Aug 2026
Read appraisal →Proceedings of the National Academy of Sciences of the United States of America
Magnetically actuated microrobotic system for sequential treatment of biofilm
Biofilm-associated infections present a critical therapeutic challenge due to antibiotic resistance and impaired tissue healing. Here, we present a microrobotic system (MZ-8) that integrates real-time human-steered navigation with autonomous, microenvironment-responsive therapy to actively eradicate biofilms and promote tissue regeneration. This microrobotic system features a spine-inspired structure for mechanical biofilm disruption, a pH-responsive ZIF-8 coating for immunomodulatory Zn2+ release, and closed-loop actuation under second near-infrared fluorescence guidance. In a rat model of periprosthetic joint infection, MZ-8 achieved effective biofilm removal, induced a pro-regenerative immune response by polarizing macrophages toward the M2 phenotype, and significantly enhanced tissue regeneration. Transcriptomic analysis further revealed the activation of immunomodulatory pathways and upregulation of M2-associated genes, confirming the system's sequential shift from eradication to repair. Moreover, validation in a rabbit model and human knee joint confirmed its operational feasibility under clinical imaging guidance and excellent biosafety. This work establishes that integrating physical eradication, biochemical immunomodulation, and interactive control within a single system is essential for advancing from infection clearance to functional tissue restoration. Thus, it provides a therapeutic paradigm for biofilm-associated diseases and lays a foundation for future intelligent, clinically adaptive anti-infective systems.
15 July 2026
Read appraisal →Journal of neurology
The dual role of mTOR in multiple sclerosis pathophysiology: a systematic review
Multiple sclerosis (MS) is a chronic autoimmune disease characterized by demyelination, neuroinflammation, and progressive neurodegeneration. The mechanistic target of rapamycin (mTOR) pathway plays a key role in regulating immune responses, cell metabolism, autophagy, and repair processes. Although the role of mTOR in neurodegeneration has been explored in previous reviews, a systematic assessment of its function in MS across different models is still lacking. This systematic review aimed to examine the role of mTOR signaling in the pathophysiology of MS. Following Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines, we screened preclinical and clinical studies using two databases and assessed the risk of bias specific to the study types. A total of 189 records were identified, of which 90 met the inclusion criteria for qualitative analysis. Studies using in vitro and in vivo (mainly rodent models, both sexes) models of MS, as well as MS patient tissue or data, consistently demonstrated that mTOR is involved in the MS-related processes neuroinflammation, myelination, autophagy, gliosis, mitochondrial dysfunction, and oxidative stress. mTOR inhibition reduces pro-inflammatory signaling and may enhance autophagy, offering neuroprotection. In contrast, activation of mTOR promotes remyelination by enhancing oligodendrocyte differentiation and maturation. These remyelinating effects may be masked in inflammatory environments, because activation of mTOR supports immune cell expansion and glial reactivity, inducing inflammation and oxidative stress. Overall, our findings underscore a dual role of mTOR in MS pathology, with important implications for disease stage and timing of intervention. Although mTOR is mechanistically important in MS, its therapeutic modulation is unlikely to be readily clinically translatable without a substantial risk of unintended and context-dependent effects.
5 July 2026
Read appraisal →Rheumatology international
Pruritus associated with systemic sclerosis: a systematic review of treatment-based clinical trials
This paper aims to examine the latest research on treatments for itch (pruritus) in people with systemic sclerosis (SSc), identify areas where information is lacking, and propose suggestions for future studies.A comprehensive literature search was performed in PubMed and Scopus in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify studies evaluating therapeutic interventions for pruritus in SSc. Eligible studies included randomized controlled trials, cohort studies, and case series comprising a minimum of three patients. Data extraction encompassed study design, patient demographics, pruritus assessment instruments including validated and non-validated measures, and clinical outcomes. Studies were excluded if they concerned localized scleroderma, irrelevant populations, case reports, systematic reviews, lacking relevant outcome data, or incomplete trials. Ten studies met criteria, evaluating immunomodulatory agents, mast cell stabilizers, opioid receptor antagonist, and lysophosphatidic acid receptor antagonists. Pruritus assessment varied and was often secondary to fibrosis outcomes. Oral lenabasum improved pruritus in a phase II trial; low-dose opioid receptor modulators and rituximab also showed qualitative improvement. Pruritus is a frequently overlooked yet clinically significant symptom in systemic sclerosis (SSc) that negatively impacts patients' quality of life. Existing evidence regarding effective therapeutic options remains limited. Future research should prioritize pruritus as a predefined outcome and utilize validated assessment instruments to inform treatment strategies and enhance patient quality of life.
23 June 2026
Read appraisal →Biological psychiatry
Systematic Review and Mega-Analysis of the Peripheral Blood Transcriptome in Depression Implicates Dysregulation of Lymphoid Cells and Histones
BACKGROUND: Depression has been associated with transcriptomic changes in peripheral blood. However, the contribution of specific immune cell subsets or pathways remains unclear, and findings have been variable across previous studies, which have not tended to account for sample cellular composition. METHODS: We performed a systematic review of peripheral blood transcriptome studies in depression. For the 5 datasets meeting criteria (total N = 6011), we performed harmonized reprocessing and cell composition-adjusted differential gene and transcript analyses, followed by a bias- and inflation-adjusted weighted z score mega-analysis. We investigated the biological pathways and cell subsets implicated by the results. We also performed a sex-stratified gene network mega-analysis using consensus weighted gene coexpression network analysis (WGCNA). RESULTS: Few genes showed robust differential gene expression (DGE) in depression. Depression was reproducibly associated with decreases in replication-dependent histones and with a decrease in oxidative phosphorylation pathways in females only. Cell source analyses implicated lymphoid cells (T cells and natural killer cells) as likely contributors to the depression differential expression signature. WGCNA mega-analysis revealed multiple consensus modules associated with depression, with a PUF60-related module upregulated in both female and male depression in sex-stratified analyses. Two genes predicted to be causally relevant to depression by transcriptome-wide association studies (GPX4 and GYPE) showed significant DGE. CONCLUSIONS: These results are convergent with immunogenetic evidence implicating lymphoid cell dysregulation in depression, while also highlighting histone alterations as a key molecular signature in depression. They also indicate the importance of large-scale datasets for biomarker discovery in the context of heterogeneous disorders such as depression.
16 June 2026
Read appraisal →Journal of affective disorders
Multiple peripheral inflammatory markers in adolescents with major depressive disorder treated with repeated esketamine infusions: results from a randomized controlled trial
OBJECTIVE: While inflammatory dysregulation is well-documented in major depressive disorder (MDD), its response to esketamine treatment in adolescents remains poorly understood. We aimed to examine the effects of esketamine on the inflammatory cytokines in adolescent MDD. METHODS: This randomized, double-blind trial assigned 49 adolescents with MDD to receive three infusions of esketamine or midazolam over five days between December 2020 and April 2022. Suicidal ideation (measured by Columbia Suicide Severity Rating Scale, C-SSRS), depressive symptoms (measured by Montgomery-Åsberg Depression Rating Scale, MADRS) and plasma levels of 10 inflammatory markers were assessed at baseline, Day 6, and Day 12. RESULTS: Linear mixed model revealed significant time effects for all markers, but no significant drug main effect was observed. In esketamine group, alterations in IL-8 were associated with the reduction of C-SSRS Intensity at Day 6 (r = 0.444, p = 0.026), and alterations in IFN-γ were correlated with the reduction of MADRS (r = 0.399, p = 0.048) and C-SSRS Intensity (r = 0.427, p = 0.033) at Day 12. Baseline C4 negatively related to the reductions of MADRS and C-SSRS Ideation at Day 6 and 12 (all p < 0.005). CONCLUSIONS: Our study found no significant drug main effects for inflammatory markers, with most changes representing time effects observed in both groups. Exploratory results indicate that IL-8, IFN-γ, and C4 may warrant further investigation as potential biomarkers of esketamine response in adolescent MDD.
15 June 2026
Read appraisal →International immunopharmacology
Antimicrobial peptides in malaria and tuberculosis management: a systematic review of emerging evidence
AMPs (Antimicrobial peptides) are small molecules that are crucial components of biological activities, viz wound healing, angiogenesis, antimicrobial activity, immune regulation, and exhibit anticancer properties. This systematic review summarizes the origin, sequence, efficacy, and structure-activity mechanisms of AMPs against tuberculosis and malaria, the world's leading killer infectious diseases, employing the AMP database (APD3) (till June 2025) and PubMed search (January 1965 to June 2025). The comprehension is well addressed by covering the inhibitory activity, SAR (structure-activity relationships), and action mechanisms of AMPs (natural and synthetic) against Mycobacterium tuberculosis and Plasmodium spp., as both pathogens exhibit multidrug resistance. The review also illustrates how these specific motifs, along with their properties such as hydrophobicity, charge, or amphipathicity, influence the AMPs activity against the pathogens. Moreover, challenges in the AMPs use and the way forward, including the recent breakthroughs employing nanocarriers, inhalable formulations for TB, and targeted erythrocyte delivery for malaria, are also highlighted. AMPs have illustrated promising anti-TB and antimalarial efficacy owing to their unique structure and novel mode of action, despite exhibiting varying extents of toxicity. Anti-malarial AMPs are grouped in defensins and cecropins, while the majority of natural anti-TB AMPs are classified as bacteriocins, defensins, and cathelicidins. Synthetic AMPs, in contrast, are designed to enhance activity and selectivity while reducing toxicity and the development of resistance. AMPs have α-helical, β-sheet, or random-coil structures and are cationic, amphipathic, and highly hydrophobic, attributes that contribute to observed anti-TB and anti-malarial potential. A comprehensive understanding of AMP's structure and function, along with the use of artificial intelligence (AI) and machine learning, can provide impetus for AMP therapy as an alternative to tackle tuberculosis and malaria.
15 June 2026
Read appraisal →Human vaccines & immunotherapeutics
Immunogenicity and safety of AS03-adjuvanted A/Astrakhan/3212/2020 (H5N8)-like influenza vaccine in adults: Phase 1/2, observer-blinded, randomized trial
Influenza pandemics arise from novel influenza A viruses. Recent emergence of a new clade (2.3.4.4.b) of the highly pathogenic H5N1 in animals and humans highlighted its pandemic potential. We evaluated the immunogenicity and safety of GSK's AS03-adjuvanted H5N8 vaccine in adults. In this phase 1/2, observer-blinded, age-stratified, randomized trial, healthy US adults (age, ≥18 y) received two intramuscular doses of hemagglutinin antigen (3.75 or 7.50 μg) with AS03A or AS03B, administered 21 d apart. Immunogenicity - seroprotection rates (SPRs), seropositivity, geometric mean titers (GMTs), geometric mean fold rise (GMFR), and seroconversion rates (SCRs) - was evaluated on day 43 using hemagglutination inhibition (HI) and microneutralization (MN) assays. Safety was monitored throughout the study. Of 520 enrolled participants, 518 were vaccinated. On day 43, the US Food and Drug Administration's (FDA) Center for Biologics Evaluation and Research criteria for influenza vaccines were met. HI SPRs, seropositivity rates, SCRs, GMTs, and GMFR appeared to be higher in the AS03A vs AS03B group. Immune responses were generally higher in younger (aged 18-64 y) vs older (aged ≥65 y) adults. Immune responses were also detected in MN assays, with a correlation between HI and MN responses on day 43 across age groups and vaccine formulations. Safety was acceptable, with no increase in adverse events post-dose 2. Reactogenicity appeared more common in younger adults. The antigen-sparing potential of AS03 was demonstrated, with an acceptable safety profile. The benefit/risk profile was favorable for all formulations tested, including 3.75 µg AS03A (licensed in the US).ClinicalTrials.gov registration: NCT05975840. Influenza pandemics occur when new influenza viruses emerge, causing widespread illness. A recent study investigated a new vaccine, GSK’s AS03-adjuvanted H5N8 influenza vaccine, for its ability to trigger an immune response and its safety in adults aged 18–64 y and older adults aged ≥65 y. Overall, 518 participants received at least one dose of the vaccine, with different amounts of hemagglutinin antigen (3.75 or 7.50 µg) combined with different concentrations of AS03 adjuvant. Immune responses were assessed at multiple time points, with the primary endpoint measured on day 43 post-vaccination. The vaccine produced a strong immune response in both age groups, with younger adults showing slightly better responses than older adults. The vaccine met the required standards for an immune response set by the US Food and Drug Administration (FDA). AS03A typically induced greater immune response than AS03B. Safety monitoring showed that the vaccine was generally well tolerated, with the most common side effects being mild, such as injection-site pain and muscle ache. This study confirmed that the AS03-adjuvanted H5N8 vaccine has the potential to provide protection against influenza with an acceptable safety profile, making it a valuable candidate for pandemic preparedness.
14 June 2026
Read appraisal →BMJ open gastroenterology
Safety and efficacy of advanced combination therapies for treating inflammatory bowel disease in adults: a systematic review and meta-analysis
OBJECTIVES: To systematically synthesise available evidence on the safety of advanced combination therapy (ACT) in adults with inflammatory bowel disease (IBD), with secondary exploratory evaluation of efficacy outcomes. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Searches of Embase (via Ovid), MEDLINE and PubMed were initially undertaken on 9 May 2025 and updated on 8 April 2026. Additional studies were identified through hand-searching and reference list screening. Eligible publications were restricted to those published between 1 January 2015 and 31 March 2026. ELIGIBILITY CRITERIA: We included randomised controlled trials as well as observational and descriptive studies. Conference abstracts, reviews, editorials and commentaries were excluded. Inclusion was restricted to publications in English. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently screened studies, extracted data and assessed risk of bias using Joanna Briggs Institute tools and Cochrane RoB-1. Pooled proportions of total adverse events (TAEs), serious adverse events (SAEs) and treatment discontinuations were calculated using random-effects meta-analysis. Subgroup analyses were conducted by drug class. Where meta-analysis was not appropriate, findings were narratively synthesised. RESULTS: Fifty-two studies (n=2022 participants) were included. The most frequent combinations were anti-TNFa plus integrin inhibitors and interleukin (IL) 23 plus integrin inhibitors. Pooled analyses demonstrated low rates of SAEs (eg, anti-TNFa plus integrin inhibitors: 2.7%, 95% CI 0.22% to 6.86%) and discontinuations (6.38%, 95% CI 2.36% to 11.58%), although heterogeneity was substantial and certainty of evidence was very low, with some analyses based on small sample sizes. CONCLUSION: ACT may be associated with low rates of SAEs in selected patients with refractory IBD; however, the evidence is limited by small sample sizes, heterogeneity and predominantly observational designs. Robust conclusions regarding safety and efficacy cannot be made due to very low GRADE certainty. PROSPERO REGISTRATION NUMBER: CRD420251025883.
13 June 2026
Read appraisal →Human vaccines & immunotherapeutics
Safety and immunogenicity of a booster dose of COVAC-2, a Sepivac SWE™ adjuvanted SARS-CoV-2 recombinant protein vaccine in previously vaccinated healthy adults; a randomized controlled multicentre trial.
This Phase 1 clinical trial evaluated the safety and immunogenicity of COVAC-2, a recombinant protein subunit vaccine as a heterologous booster in adults previously immunized with authorized COVID-19 vaccines (NCT05226702). COVAC-2 contains the SARS-CoV-2 S1 spike protein subunit adjuvanted with Sepivac SWE™, an open-access oil-in-water adjuvant. Sixty participants were randomized to receive a single intramuscular dose of COVAC-2 (10 µg or 25 µg) or placebo, with follow-up through Day 180. The vaccine was well tolerated, with most adverse events being mild or moderate; no serious adverse events were attributed to vaccination. Immunogenicity assessments included spike-binding antibody ELISA, pseudovirus neutralization assays (PNA), ELISpot, and flow cytometry. The 25 µg dose elicited the strongest humoral and cellular responses, with peak antibody titers observed 14 d after COVAC-2 vaccination. While titers waned, they were sustained above baseline through Day 180. ELISpot and flow cytometry revealed elevated IFN-γ and IL-2 responses indicating antigen-specific T-cell activation. Minimal IL-4 and IL-13 responses were demonstrated by flow cytometry. These findings support the safety and immunogenicity of COVAC-2 as a heterologous booster, particularly at the 25 µg dose level. The favorable safety profile, induction of immune responses, and thermal stability of the vaccine formulation suggest its potential utility in global vaccination strategies, especially in low- and middle-income countries. COVAC-2 may offer a scalable and accessible platform for enhancing protection against COVID-19.Clinicaltrials.gov: NCT05226702 - Registered 22 Jul 2022.
13 June 2026
Read appraisal →Journal of ethnopharmacology
Exploring the molecular mechanism of Shenling baizhu formula in the treatment of ulcerative colitis via the cGMP-PKG signaling pathway
ETHNOPHARMACOLOGICAL RELEVANCE: Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by symptoms such as persistent diarrhea. Shenlingbaizhu Formula (SLBZ), a classical Chinese herbal formula with centuries of clinical application, has long been used to treat such gastrointestinal disorders. This historical efficacy provides a strong ethnopharmacological rationale for investigating its therapeutic potential and underlying mechanisms in UC. AIM OF THE STUDY: To elucidate the molecular mechanism by which SLBZ ameliorates UC by restoring the intestinal barrier via the sGC-cGMP-PKG signaling pathway. MATERIALS AND METHODS: To systematically investigate the therapeutic effects of SLBZ on UC, we established a dextran sulfate sodium (DSS)-induced colitis model in 57BL/6 mice. Comprehensive evaluations were conducted to assess intestinal barrier function and elucidate underlying mechanisms, including histological analysis, immunofluorescence staining of tight junction proteins, 16S rDNA sequencing for gut microbiota profiling, transcriptomic analysis for gene expression patterns, and Western blot validation of key proteins. Furthermore, a multi-tiered experimental strategy was employed, integrating molecular modeling, machine learning algorithms, graph neural network (GNN) approaches and in vitro experiments using Caco-2 cell monolayers, to systematically validate the sGC-cGMP-PKG signaling pathway and identify bioactive compounds responsible for SLBZ's therapeutic effects. RESULTS: SLBZ treatment markedly alleviated UC symptoms in mice and restored intestinal barrier function through dual mechanisms: upregulation of tight junction proteins (ZO-1/Occludin) and modulation of gut microbiota composition. Transcriptomic analysis pinpointed the cGMP-PKG signaling pathway as a central therapeutic target. Through an integrated approach combining molecular docking, machine learning (random forest algorithm), and deep neural network analysis, we identified soluble guanylate cyclase (sGC) as the primary molecular target, with Choerospondin emerging as a key bioactive component. Mechanistic investigations demonstrated that SLBZ robustly activated the sGC-cGMP-PKG axis both in vivo (colon tissues) and in vitro (Caco-2 cells), culminating in significant suppression of intestinal epithelial apoptosis. CONCLUSION: SLBZ alleviates UC by activating the sGC-cGMP-PKG pathway to restore intestinal barrier function through tight junction upregulation and microbiota modulation. Our study both validates SLBZ's traditional use and identifies this pathway as a novel therapeutic target for UC.
12 June 2026
Read appraisal →Vaccine
Can a DNA vaccine protect against Chagas disease? A systematic review of preclinical studies.
Chagas disease, caused by Trypanosoma cruzi, remains a major neglected tropical disease with limited treatment options. DNA-based vaccination has been explored as a preventive strategy, but its overall efficacy and translational value remain uncertain. Despite encouraging preclinical findings, the evidence on DNA-based vaccines against T. cruzi remains heterogeneous and has not been systematically integrated across outcomes. A comprehensive review is therefore needed to contextualize the current knowledge and define the translational relevance of this platform. To systematically review preclinical in vivo evidence on the efficacy of DNA-based vaccination against T. cruzi, focusing on parasitological, immunological, histopathological, and cardiac outcomes. PubMed/MEDLINE, Scopus, Embase, and Web of Science were searched without date restrictions. Eligible studies were controlled in vivo experiments evaluating DNA vaccines against T. cruzi in animal models. Two reviewers performed study selection, data extraction, risk-of-bias (SYRCLE) and certainty of evidence (GRADE) assessment independently. Thirty preclinical studies were included. Murine models predominated, especially BALB/c, C57BL/6, and C3H/He mice, although canine studies added translational relevance. Naked plasmid DNA, Salmonella-delivered constructs, and adjuvanted DNA vaccines were the most common platforms. The principal antigens belonged to the trans-sialidase family and amastigote surface proteins. Overall, vaccination was associated with reduced parasitemia, improved survival in several murine models, Th1 immune responses characterized by increased IFN-γ, IgG2a, and CD8+ T-cell activation, as well as attenuation of inflammatory, histopathological, and cardiac damage. In canine models, vaccination also reduced parasite burden and myocardial inflammation, although protection remained incomplete. Confidence in the evidence was limited by substantial heterogeneity in animal background, antigen selection, parasite strain, inoculation route, dosing regimens, and follow-up duration. Frequent unclear risk of bias and incomplete reporting prevented meta-analysis and constrain causal inference. DNA-based vaccination against T. cruzi can induce Th1 immunity and reduce parasitological and tissue injury outcomes, but protection is often partial and rarely sterilizing.
11 June 2026
Read appraisal →Biochemical and biophysical research communications
Efferocytosis-related biomarkers and immune infiltration in pancreatic ductal adenocarcinoma based on single-cell sequencing and machine learning: a comprehensive bioinformatics analysis and experimental validation
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly invasive and lethal malignancy, with its complex tumor microenvironment (TME) severely limiting therapeutic efficacy. Efferocytosis, a key process by which macrophages clear apoptotic cells, has been demonstrated to influence tumor initiation and progression by modulating immune responses, promoting M2 polarization, and facilitating immune evasion. Yet, the function and predictive significance of genes linked to efferocytosis in PDAC are still not fully understood. METHODS: This study integrated TCGA-PDAC, GTEx, and GEO datasets with single-cell transcriptomics to screen and analyze expression patterns and functions of efferocytosis-related genes (ERGs) in PDAC. Differential analysis, single-cell clustering, cell communication, and pseudo-time analysis revealed heterogeneity in macrophage efferocytosis. Subsequently, a six-gene prognostic model (CD36, ITGAV, PANX1, PPARG, S100A4, THBS1) was constructed and validated using Cox and LASSO regression. Concurrently, GSEA pathway analysis, immune infiltration assessment, and immunotherapy response prediction were conducted. Key gene functions were validated through molecular docking, RT-qPCR, western blotting, and functional experiments. RESULTS: Single-cell analysis revealed that macrophages exhibit the highest efferocytic activity within the PDAC microenvironment, demonstrating significant subpopulation heterogeneity. Differential analysis identified 23 key intersecting genes, ultimately yielding a risk model comprising six core genes. The model exhibited strong predictive accuracy in both the training and validation groups (notable AUC). Additional examination showed that patients at high risk showed a heightened presence of pathways linked to the reprogramming of energy metabolism and inflammatory reactions, along with heightened genomic instability and immunosuppressive TME traits, suggesting a grim prognosis. Experimental validation confirmed that knockdown of THBS1 significantly inhibited the proliferation, migration, and invasion of PDAC cells. CONCLUSION: The research clarifies the diverse nature of macrophage efferocytosis in PDAC and its crucial function in the restructuring of TME. It establishes and validates a six-gene risk prediction model, clarifying the functional significance of core genes, including THBS1. These findings provide novel molecular tools for PDAC prognosis assessment and identify potential targets for immunotherapy and personalized treatment strategies.
11 June 2026
Read appraisal →Vaccine
Immunogenicity and safety of Sabin-strain inactivated poliovirus vaccine in infants: a systematic review and meta-analysis
BACKGROUND: Poliomyelitis remains a threat to children under five despite global vaccination efforts. The Sabin-strain inactivated poliovirus vaccine (sIPV) has emerged as a safer alternative to conventional Salk-strain IPV (cIPV) due to lower biosafety requirements. This systematic review and meta-analysis evaluated the immunogenicity and safety of sIPV compared with cIPV in healthy infants completing the primary IPV series. METHODS: PubMed, Embase, Scopus, and Cochrane Library were searched for RCTs. Outcomes included seroconversion rates, seroprotection rates, geometric mean titers (GMTs), and adverse events. Data were pooled using random-effects models, and evidence certainty was assessed using RoB 2.0 and GRADE. RESULTS: Seven RCTs with 4646 infants were included. Seroconversion rates were comparable: PV1 100% (RR 1.00, 95% CI 1.00-1.01), PV2 102% (RR 1.02, 95% CI 0.98-1.07), PV3 100% (RR 1.00, 95% CI 0.99-1.01). GMTs were higher for sIPV after PV1 (MD 1.50, 95% CI 0.98-2.02) and PV2 (MD 0.52, 95% CI 0.06-0.98). Local adverse events were similar (OR 1.27, 95% CI 0.95-1.71), while systemic adverse events were higher with cIPV (OR 1.36, 95% CI 1.15-1.60). Fever (OR 1.50, 95% CI 1.20-1.87) and allergic reactions (OR 2.19, 95% CI 1.02-4.69) were slightly more frequent with sIPV. CONCLUSIONS: sIPV provides immunogenicity comparable to cIPV with an acceptable safety profile in infants. Its lower biosafety requirements support its use in global polio eradication programs.
11 June 2026
Read appraisal →Human vaccines & immunotherapeutics
Safety and immunogenicity of 4CMenB and MenACWY-CRM meningococcal vaccines when administered concomitantly in healthy adolescents: A phase 3b, randomized, observer-blind study.
Meningococcal vaccination of adolescents/young adults is recommended in various countries, including the United States (US). This phase 3b, observer-blind study (NCT04318548) evaluated the safety, reactogenicity, and immunogenicity of serogroup B vaccine, 4CMenB, and quadrivalent conjugate vaccine, MenACWY-CRM, when co-administered to healthy individuals aged 16-18 y, as per US Advisory Committee on Immunization Practices recommendations. Adolescents, who had received MenACWY vaccination ≥4 y previously, were randomized (N = 940; 1:1:1) to one of three groups to assess co-administration versus 4CMenB and MenACWY-CRM administered alone. Co-primary objectives were to demonstrate the non-inferiority of antibody responses after concomitant administration to antibody responses after 4CMenB (two doses administered 2 months apart) and MenACWY-CRM (single dose), as measured by human serum bactericidal assay (hSBA). Vaccine safety and reactogenicity were assessed as another primary objective. The co-primary endpoints were met: the lower limit of 2-sided 95% confidence intervals for all between-group ratios of hSBA geometric mean titers was >0.5 for the concomitant administration group versus 4CMenB group and MenACWY-CRM group. hSBA data after two 4CMenB doses and one MenACWY-CRM dose showed comparable between-group geometric mean ratios versus baseline, and percentages of participants with 4-fold rises in titers and titers ≥lower limit of quantitation. The safety profile of 4CMenB co-administered with MenACWY-CRM was comparable with that of 4CMenB administered alone. In conclusion, 4CMenB and MenACWY-CRM co-administration was well tolerated in adolescents aged 16-18 y and immune responses were comparable versus administration of each vaccine alone, which is consistent with a previous study of co-administration in infants. Invasive meningococcal disease, caused by the bacterium Neisseria meningitidis, poses a life-threatening risk but can be prevented through vaccination. Effective vaccines are available against the most common disease-causing meningococcal serogroups, A, B, C, W, and Y. Evidence from clinical studies and immunization programs over the last decade with the 4-component meningococcal serogroup B vaccine, 4CMenB, and serogroups A, C, W, and Y vaccine, MenACWY-CRM, confirms the effectiveness of both vaccines in population age groups at higher risk of meningococcal disease, including infants and adolescents. It was previously shown that the administration of 4CMenB and MenACWY-CRM to healthy infants at the same visit induced good immune responses and was well tolerated by young children. Adolescent vaccination with 4CMenB and MenACWY-CRM is recommended in various countries, including in the United States. We conducted a study to test the safety of concomitant administration and its ability to induce immune responses in 945 healthy adolescents aged 16–18 y; 834 from the United States and 111 from Italy. We found that most reactions to the 4CMenB and MenACWY-CRM injections were mild or moderate, and were similar whether the vaccines were given together or separately, with no unexpected side effects. Co-administration to adolescents induced robust immune responses against serogroup B and serogroups A, C, W, and Y. These results support the use of concomitant meningococcal vaccinations in adolescent immunization programs.
11 June 2026
Read appraisal →Gene
Based on WGCNA and machine learning studies, SMURF2 drives NSCLC malignant transformation, ferroptosis, and macrophage polarization by ubiquitinating SPP1
BACKGROUND: Non-small cell lung cancer (NSCLC) is a common type of lung cancer with poor prognosis and high mortality in advanced stages. Although secreted phosphoprotein 1 (SPP1) is associated with the progression of NSCLC, its specific mechanisms remain to be explored. METHODS: Through integrated bioinformatics analysis combining weighted gene co-expression network analysis (WGCNA), differential expression analysis, gene enrichment analysis with the Kyoto Encyclopedia of Genes and Genomes (KEGG)/Gene Ontology (GO), and machine learning techniques incorporating database predictions, core genes were identified. Experimental validation was conducted using Western blot, co-immunoprecipitation (Co-IP), cycloheximide (CHX) chase assay, Ubiquitin Immunoprecipitation (Ub-IP), colony formation, flow cytometry, transwell assay, reactive oxygen species (ROS) detection, and quantitative real-time PCR (qRT-PCR). The functional impact of SPP1 on tumor growth was further confirmed through mouse models and immunohistochemistry (IHC). RESULTS: Based on WGCNA and machine learning, SPP1 was identified as a core gene. SMURF2 ubiquitinated and degraded SPP1. Rescue experiments confirmed that SMURF2 inhibited proliferation and invasion, and promoted apoptosis in NSCLC cells, which were reversed by SPP1 overexpression. Furthermore, SMURF2 enhanced ferroptosis and modulated macrophage polarization via the same ubiquitination mechanism. Animal studies verified that SMURF2-mediated ubiquitination and degradation of SPP1 suppressed tumor growth. CONCLUSION: This study aims to investigate the role of SMURF2-mediated ubiquitination of SPP1 in inhibiting malignant progression, promoting ferroptosis, and modulating macrophage polarization in NSCLC, thereby providing a theoretical foundation and new insights for understanding and targeting NSCLC.
10 June 2026
Read appraisal →Journal of theoretical biology
Subtypes estimation in single-cell multi-omics data via S-multi-SNE
Single-cell RNA sequencing (scRNA-seq) has rapidly become an essential method in modern biology, as it allows global characterisation of transcriptomics in individual cells from different tissues, or organisms. scRNA-seq data are collected from a single individual organism and they are composed as mRNA count matrices with rows representing the cells and columns the genes. New technologies further allow multi-omics data to be obtained on the same set of single cells. In this paper, multi-SNE and S-multi-SNE, two multi-view dimensionality reduction approaches, are adapted for visualization and classification of cellular subtypes, two important challenges in the analysis of scRNA-seq data. S-multi-SNE has been adapted for cell subtype estimation of scRNA-seq data. In a series of experiments we illustrate that it is possible to identify cell subtypes by leveraging information from individuals from the same species, from different species, and when data are generated by different sequencing technologies. In the conducted analyses, we show that S-multi-SNE consistently outperformed several other machine learning techniques and, in most comparisons, surpassed existing reference-based single-cell classification algorithms. We further illustrate how two single-cell multi-omics datasets, scATAC-seq and scRNA-seq, can be integrated together through S-multi-SNE for improved cell subtype identification.
7 June 2026
Read appraisal →Lancet (London, England)
Efficacy and safety of a bodyweight-adjusted higher dose of ocrelizumab in relapsing (MUSETTE) and primary progressive (GAVOTTE) multiple sclerosis: two multicentre, randomised, double-blind, parallel-group phase 3b trials.
BACKGROUND: Ocrelizumab is a humanised anti-CD20 monoclonal antibody approved for people with relapsing (RMS) or primary progressive multiple sclerosis (PPMS). In a post-hoc analysis of phase 3 trials in RMS and PPMS using a 600 mg dose, higher exposure to ocrelizumab was associated with greater B-cell depletion and lower risk of confirmed disability progression. Here, we prospectively assessed the efficacy and safety of a high dose of ocrelizumab in patients with RMS or PPMS. METHODS: Two multicentre, double-blind, phase 3 controlled trials were conducted to compare high-dose ocrelizumab with the approved 600 mg dose of the drug in patients with RMS (MUSETTE) and PPMS (GAVOTTE) aged 18-56 years. MUSETTE involved 122 centres in 21 countries and GAVOTTE involved 149 centres in 22 countries. Participants were randomly assigned 2:1, with a permuted-block randomisation method, to high-dose ocrelizumab (1200 mg or 1800 mg for baseline body weight <75 kg or ≥75 kg, respectively) or 600 mg ocrelizumab. Patients, investigators, and the sponsor were blinded to treatment allocation. Patients received ocrelizumab infusions every 24 weeks for a minimum 120 weeks and until a prespecified minimum number of confirmed disability events (MUSETTE, 205; GAVOTTE, 357) had occurred. In both trials, the primary endpoint was time to onset of 12-week composite confirmed disability progression (cCDP), assessed by prespecified increases in Expanded Disability Status Scale, Timed 25-Foot Walk Test, or 9-Hole Peg Test scores. Efficacy endpoints were evaluated in all randomised participants and safety endpoints were evaluated in participants who received at least one ocrelizumab infusion. These studies are registered with ClinicalTrials.gov: MUSETTE, NCT04544436; GAVOTTE, NCT04548999. FINDINGS: Participants in MUSETTE were enrolled between Nov 26, 2020, and Aug 30, 2022; participants in GAVOTTE were enrolled between Dec 3, 2020, and May 15, 2023. In MUSETTE, 860 patients were randomly assigned (high-dose ocrelizumab, n=577; 600 mg ocrelizumab, n=283) and had median overall treatment duration of 184·4 weeks. In GAVOTTE, 753 patients were randomly assigned (high-dose ocrelizumab, n=500; 600 mg ocrelizumab, n=253) and had median overall treatment duration of 174·1 weeks. In MUSETTE, the percentage of patients with 12-week cCDP was 34% (198 of 577) with high-dose ocrelizumab versus 37% (104 of 283) with 600 mg ocrelizumab (hazard ratio [HR] 0·93 [95% CI 0·73-1·18]; p=0·53). In GAVOTTE, the percentage of patients with 12-week cCDP was 47% (235 of 500) with high-dose ocrelizumab versus 49% (124 of 253) with 600 mg ocrelizumab (HR 0·95 [95% CI 0·76-1·18]; p=0·64). Safety profiles were similar for the high-dose ocrelizumab and 600 mg ocrelizumab; in MUSETTE, rates of adverse events (552 [96%] of 577 and 267 [94%] of 283), serious adverse events (77 [13%] of 577 and 34 [12%] of 283), and fatalities (four [1%] of 577 and one [<1%] of 283) were comparable, as were rates of adverse events (447 [90%] of 499 and 230 [91%] of 254), serious adverse events (61 [12%] of 499 and 29 [11%] of 254), and fatalities (two [<1%] of 499 and three [1%] of 254) in GAVOTTE. INTERPRETATION: In both studies, high-dose ocrelizumab did not further improve control of disability progression in either RMS or PPMS, and no new safety concerns were identified. FUNDING: F Hoffmann-La Roche.
1 June 2026
Read appraisal →Acta microbiologica et immunologica Hungarica
Characteristics of fungaemia caused by Trichosporon species in South-Eastern Europe
The incidence of fungaemia caused by rare yeasts, particularly Trichosporon species, is rising globally, posing diagnostic and therapeutic challenges-especially in immunocompromised patients. This systematic review aims to analyse the epidemiology, diagnostic approaches, antifungal susceptibility, and clinical outcomes of Trichosporon fungaemia (TF) in South-Eastern Europe, including Turkey. A comprehensive search was conducted in PubMed and Scopus in August 2025. A total of 59 cases from 12 studies were identified, with Trichosporon asahii being the most prevalent species (86.4%). Cases originated from Turkey (79.7%), Greece (18.6%), and Croatia (1.7%). Diagnostic techniques varied, with phenotypic methods still widely used. MALDI-TOF MS and DNA sequencing were mainly applied as confirmatory methods. Haematologic disorders were the most frequently reported underlying conditions among the patients. Sixteen breakthrough fungaemia cases-occurring despite empirical or prophylactic antifungal therapy-were identified. Although rare, TF represents a severe infection with significant mortality in South-Eastern Europe. Early and accurate species identification-facilitated by advanced diagnostic tools-is crucial for effective management. In addition to diagnostic difficulties, treatment is also challenging. Voriconazole appears to be the preferred antifungal agent, even in breakthrough fungaemia cases. Enhanced awareness, routine use of molecular diagnostics, and ongoing epidemiological monitoring are essential to improve patient outcomes.
1 June 2026
Read appraisal →Archives of microbiology
AI-driven big data analysis and predictive modeling of infectious disease immunity: from correlates to causal, multiscale understanding
The ability to reliably predict protective immunity against infectious diseases remains a central challenge in immunology, vaccine development, and public health. Despite major advances in immunological measurement, immunity prediction has historically relied on simplified correlates most notably antibody titers that often fail to generalize across pathogens, populations, and time. The emergence of large-scale, high-dimensional immune datasets spanning multi-omics, longitudinal cohort studies, electronic health records, and pathogen genomics has created new opportunities for artificial intelligence (AI)-driven modeling. However, early applications reveal that predictive accuracy alone is insufficient and is frequently undermined by spurious correlations, limited generalizability, and a lack of biological interpretability. This review synthesizes current advances and limitations in AI-based immunity prediction, arguing that meaningful progress requires embedding machine learning within immune biology, causal reasoning, and rigorous validation frameworks. We examine the biological foundations of immunity relevant to modeling including innate immune programming, trained immunity, adaptive immune dynamics, and immune memory and map these processes to appropriate data modalities and model classes. We critically evaluate predictive tasks across individual and population scales, from early infection outcomes and vaccine responsiveness to immunity waning and herd-level protection. Emphasis is placed on validation beyond internal cross-validation, on interpretability grounded in immune mechanisms, and on robustness under demographic diversity and pathogen evolution. We conclude that immunity is best understood and predicted as a dynamic, probabilistic, and multiscale system rather than as a static trait. AI has substantial potential to improve infectious disease preparedness and clinical decision-making.
1 June 2026
Read appraisal →Human vaccines & immunotherapeutics
Safety and durability of influenza and SARS-CoV-2 antibody responses through 6 months after a single dose of mRNA-1083, a multicomponent influenza and COVID-19 vaccine, in adults ≥50 years.
Seasonal influenza and SARS-CoV-2 continue to contribute substantially to global morbidity and mortality. mRNA-1083 is an investigational multicomponent mRNA vaccine targeting seasonal influenza and SARS-CoV-2. In this phase 3, observer-blind, active-controlled trial (NCT06097273), adults (aged ≥50 y) were randomly assigned (1:1) to receive mRNA-1083 (40 µg; plus placebo) or age-appropriate licensed comparator vaccines for influenza and COVID-19. Two substudies were included: Cohort A (≥65 y) and Cohort B (50-64 y). Primary objectives were to demonstrate noninferiority of mRNA-1083 versus comparators for influenza hemagglutination inhibition (HAI) responses and SARS-CoV-2 neutralizing antibody (nAb; PsVNA) responses at Day 29 after vaccination and to evaluate safety and reactogenicity of study vaccines. Here, we report safety, reactogenicity, and immunogenicity of mRNA-1083 through Day 181 in adults aged ≥50 y. mRNA-1083 induced HAI titers against all vaccine-matched influenza strains that were maintained through 6 months and were generally comparable to, or higher than, comparator responses. SARS-CoV-2 nAb responses remained higher for mRNA-1083 than comparators through 6 months. Reactogenicity was predominantly grade 1-2 in severity, and vaccination-related unsolicited adverse events were similar between groups. No serious adverse events or deaths related to vaccination were reported through 6 months. In adults aged ≥50 y, mRNA-1083 elicited durable influenza and SARS-CoV-2 humoral immune responses with an acceptable safety profile through 6 months. These findings support the use of mRNA-1083 as a multicomponent vaccine.ClinicalTrials.gov identifier: NCT06097273 (https://clinicaltrials.gov/study/NCT06097273).
1 June 2026
Read appraisal →Lancet (London, England)
Efficacy and safety of ocrelizumab in primary progressive multiple sclerosis, including older patients and those with more advanced disease (ORATORIO-HAND): a multicentre, double-blind, randomised, placebo-controlled, phase 3b study
BACKGROUND: The ORATORIO trial showed that ocrelizumab reduced the risk of disability progression versus placebo in patients with primary progressive multiple sclerosis (PPMS). We aimed to elucidate the effect of ocrelizumab in older and more disabled patients with PPMS, particularly regarding hand function preservation. METHODS: ORATORIO-HAND was a multicentre, double-blind, randomised, placebo-controlled, phase 3b study with 138 sites across 22 countries. Patients with PPMS aged 18-65 years and Expanded Disability Status Scale (EDSS) score of 3·0-8·0 were randomly assigned 1:1 to intravenous ocrelizumab 600 mg or placebo every 6 months for 144 weeks or until a prespecified number of progression events occurred. Masking was achieved by use of a placebo solution administered in the same manner as ocrelizumab. Double-blinding across all periods was maintained through separation of investigators responsible for efficacy and safety assessments. MRI scans were evaluated by a masked central reader, and laboratory parameters that could reveal treatment allocation were masked to site personnel until the primary analysis. Two coprimary estimands were defined, with the endpoint of time to onset of 12-week composite confirmed disability progression (12W-cCDP) in 9-Hole Peg Test or EDSS evaluated in all randomly assigned patients, and the same endpoint evaluated in a subset of patients with MRI activity at baseline. This study is registered with ClinicalTrials.gov, NCT04035005 and is ongoing and not recruiting. FINDINGS: Between Aug 12, 2019, and Dec 10, 2024, of 1360 patients assessed for eligibility, 1013 were randomly assigned (ocrelizumab [n=505]; placebo [n=508]). The proportion of patients with 12W-cCDP was 165 (33%) of 505 with ocrelizumab and 205 (40%) of 508 with placebo (hazard ratio, 95% CI 0·70 0·57-0·86; relative risk reduction=30%; p=0·0007). In the MRI-active subgroup, a significant risk reduction was also observed in 12W-cCDP (risk reduction=55%; p<0·0001). The overall safety profile was similar in both groups. More infections (245 [48%] of 506 vs 226 [45%] of 506) were observed with ocrelizumab, but not after COVID-19 was excluded (38% vs 37%). Rates of serious adverse events and serious infections were similar between groups. INTERPRETATION: Ocrelizumab was superior to placebo in delaying disability progression, with stronger effect on hand function, in a broad PPMS population including older patients and those with more advanced disease, while maintaining a manageable safety profile. FUNDING: F Hoffmann-La Roche.
31 May 2026
Read appraisal →PLoS medicine
Characterization of the VHH-Fc construct rimteravimab in healthy adults and patients hospitalized for mild-to-moderate COVID-19: Two Phase 1 randomized clinical trials
BACKGROUND: Variable Heavy domain of Heavy chains (VHH) are innovative tools to target unique epitopes, yet few have been developed as heavy chain-only antibodies for clinical use. Rimteravimab (referred to here as XVR011) is a humanized antibody developed for the treatment of mild-to-moderate coronavirus disease 2019 (COVID-19), consisting of two identical VHHs targeting the receptor binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike, with a human immunoglobulin (Ig) G1 fragment constant of antibody (Fc), silenced for Fc effector functions. We conducted two Phase 1 studies in healthy volunteers or hospitalized COVID-19 patients to evaluate its safety, tolerability, pharmacokinetics and immunogenicity. METHODS AND FINDINGS: A randomized, double-blinded, single-center, placebo-controlled, single ascending dose study was performed in healthy volunteers (Phase 1a, EXEVIR0102, EudraCT 2021-003707-17), in parallel to an open-label, multi-center, single ascending dose study in patients hospitalized for mild to moderate COVID-19 (Phase 1b, EXEVIR0101, EudraCT 2020-005299-36, NCT04884295). Participants received a single intravenous infusion of 250, 500 or 1,000 mg of XVR011. The primary objective for both trials was the safety and tolerability of XVR011. Pharmacokinetics were evaluated as a secondary objective in Phase 1a and as an exploratory objective in Phase 1b. Efficacy (evaluated as respiratory parameters and COVID-19 clinical status) and antiviral activity in patients were evaluated as a secondary objective in Phase 1b. Immunogenicity was evaluated as an exploratory objective. Part 2 of the EXEVIR0101 study (initially a phase 1b/2 study) was not conducted due to the loss of XVR011 potency against SARS-CoV-2 Omicron BA.2. Demographics, safety, efficacy, and immunogenicity were analyzed using descriptive statistics, while pharmacokinetics were analyzed with noncompartmental pharmacokinetics (PK) modeling. In the Phase 1a study, there were no infusion-related reactions, serious treatment-emergent adverse events (TEAEs) or TEAEs grade ≥3. 22/30 volunteers (73.3%) reported 53 TEAEs (49 Grade 1, 4 Grade 2) with none being related to XVR011. The most common TEAE was headache (n = 8, 26.7%) in various treatment groups. In the Phase 1b study, 27 hospitalized patients were enrolled, and followed up to 30 days. Seven patients (25.9%) reported a total of 15 TEAEs, the majority (80%) being mild to moderate (Grade 1-2). There were no treatment-related serious TEAEs. All TEAEs resolved by the end of the study. Peak exposure (maximal concentration, Cmax) and systemic exposure (area under the curve, AUC0-t, and AUC0-inf) for XVR011 increased dose-proportionally. Geomean half-life ranged from 15.4 to 17.0 days in Phase 1a, while individual half-life ranged from 11.4 to 15.6 days in Phase 1b. SARS-CoV-2 viral load, as detected in nasopharyngeal samples by reverse transcription and quantitative polymerase chain reaction (RT-qPCR), decreased similarly in all cohorts compared to baseline. No treatment-induced anti-drug antibodies (ADA) were detected in Phase 1a. In Phase 1b, higher XVR011 concentrations increased the likelihood of ADA formation, without impacting pharmacokinetics and pharmacodynamics. No obvious dose-response in COVID-19 clinical status or respiratory parameters was observed. Technological limitations included study size, absence of placebo for the Phase 1b, absence of repeated dosing, evolving SARS-CoV-2 variants and standard-of-care. CONCLUSIONS: XVR011 displayed a favourable safety, tolerability, pharmacokinetics, and immunogenicity profile, both in healthy volunteers and in patients hospitalized for mild to moderate COVID-19. These data pave the way for the design and clinical development of VHH-Fc constructs.
31 May 2026
Read appraisal →Human vaccines & immunotherapeutics
Comparison of safety and immunogenicity between high-dose and low-dose quadrivalent influenza vaccines in children aged 6-35 months in China: A randomized, double-blind clinical study
Influenza vaccines for children aged 6-35 months are typically low-dose (0.25 mL, 7.5 μg hemagglutinin per strain). However, studies have shown that high-dose influenza vaccines (0.5 mL, 15 μg hemagglutinin per strain) can enhance protective efficacy without increasing the risk of adverse reactions. We conducted a randomized, double-blind clinical study in children aged 6-35 months in China. A total of 3,000 participants were randomized (1:1:1) to receive two doses of either an investigational high-dose quadrivalent influenza vaccine (H-QIV), an investigational low-dose quadrivalent influenza vaccine (LQIV-01) or a commercially available low-dose quadrivalent influenza vaccine (LQIV-02). Hemagglutination inhibition (HI) antibody titers 30 d post-vaccination were measured and vaccine safety and tolerability within 6 months post-vaccination were evaluated in these participants. The primary objectives were to demonstrate the non-inferiority of investigational vaccines to the commercially available vaccine in immunogenicity and to compare the H-QIV to L-QIVs. Both investigational vaccines demonstrated non-inferiority, with their seroprotection rates (SPRs), seroconversion rates (SCRs) and geometric mean titers (GMTs) meeting immunogenicity criteria. The H-QIV exhibited >11-fold increases in GMTs against H1N1, H3N2, B/Yamagata and B/Victoria strains compared to pre-vaccination levels, with SPRs exceeding 95% and SCRs exceeding 89%. The H-QIV was superior to both L-QIVs as it induced a stronger immune response to influenza viruses. All vaccines showed comparable safety profiles. The H-QIV can provide greater protection and benefits to this high-risk population.
29 May 2026
Read appraisal →Polish archives of internal medicine
Biologic and targeted synthetic treatment of SAPHO syndrome: systematic literature review
INTRODUCTION: SAPHO syndrome is a rare autoimmune / autoinflammatory disorder with no approved therapies or standardized management guidelines. Biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) are increasingly used off‑label. OBJECTIVES: This review aimed to systematically evaluate the evidence for the efficacy of b/tsDMARDs in SAPHO. PATIENTS AND METHODS: A PRISMA‑guided search of PubMed database was conducted through March 31, 2025. Studies of any design reporting outcomes of b/tsDMARDs in patients with SAPHO fulfilling the modified Kahn criteria were included. Exclusion criteria were non‑English language, inaccessible full text, and insufficient treatment details. Data on patient characteristics, drug class, follow‑up duration, and treatment response were extracted. As all the included studies were case reports or case series, the risk of bias was not assessed. Treatment responses were summarized using descriptive statistics. RESULTS: Of 1610 screened records, 106 studies comprising 385 instances of b/tsDMARD use met the inclusion criteria; no randomized controlled trials were identified. Tumor necrosis factor inhibitors (TNFis) were used in 203 patients, with complete skeletal and skin responses in 81% and 72%, respectively. The use of Janus kinase inhibitors (JAKis) in 77 patients was associated with complete response rates of 89% (skeletal) and 94% (skin). Other b/tsDMARD classes-including interleukin 17 (IL‑17), IL‑23, IL‑1, and IL‑6 inhibitors, as well as phosphodiesterase‑4 inhibitors-demonstrated variable and generally lower efficacy. CONCLUSIONS: Evidence for b/tsDMARD efficacy in SAPHO remains limited to low‑quality, uncontrolled studies with substantial heterogeneity and probable publication bias. TNFis and JAKis are among the most consistently effective therapies reported in the available literature, but high‑quality research, including randomized trials or prospective registries, is urgently needed to inform evidence‑based management.
29 May 2026
Read appraisal →Autoimmunity
IgA Vasculitis with necrotizing arteritis: a multicenter retrospective study from the French Vasculitis Study Group and systematic review of the literature
IgA vasculitis (IgAV) primarily affects small vessels, but rare cases with necrotizing arteritis (NA) raise questions about overlap with polyarteritis nodosa (PAN). To characterize IgAV with necrotizing arteritis (IgAV-NA) and compare its phenotype with classical IgAV and PAN. We performed a multicenter retrospective study combined with a systematic literature review (1990-2025). Patients fulfilled EULAR/PRINTO/PRES IgAV criteria, had pathological or imaging evidence of NA in small or medium arteries, and were ANCA-negative. Thirty patients were included (7 from databases, 23 from the literature). NA was confirmed by biopsy (n = 16) or vascular imaging (n = 14). Clinical features, treatments, remission, and mortality were compared with 257 adult IgAV and 196 PAN patients. Median age was 54.5 years. IgAV-NA was characterized by severe manifestations, including gastrointestinal bleeding, perforation, surgical abdomen, neuropathy, pancreatitis, and livedo. Compared with classical IgAV, IgAV-NA showed significantly higher rates of multi-organ involvement and mortality. Compared with PAN, IgAV-NA shared vascular complications but had less fever and neuropathy. Despite arterial involvement, patients did not fulfil PAN criteria. IgAV-NA represents a rare, severe IgAV phenotype with life-threatening complications rather than an IgAV-PAN overlap. Severe or atypical IgAV presentations should prompt vascular imaging and intensified immunosuppression.
28 May 2026
Read appraisal →The Cochrane database of systematic reviews
Steroid avoidance or withdrawal for kidney transplant recipients.
RATIONALE: Steroid-sparing strategies aim to reduce the adverse effects associated with steroid use. The main concern has been a potential increase in the risk of rejection, as reported in previous systematic reviews. In recent years, improvements in immunosuppressive regimens and a significant decline in the incidence of acute rejection have renewed interest in steroid-sparing strategies. More contemporary trials suggest that reducing steroid exposure might be safe. This is an updated review, previously published in 2009 and 2016. OBJECTIVES: To evaluate the benefits and harms of steroid withdrawal or avoidance for kidney transplant recipients. SEARCH METHODS: We searched the Cochrane Kidney and Transplant Specialised Register, CENTRAL, MEDLINE, Embase and two trials registers up to 29 April 2025. ELIGIBILITY CRITERIA: All randomised and quasi-randomised controlled trials that evaluated steroid avoidance or withdrawal after kidney transplantation. OUTCOMES: Critical outcomes were all-cause death, graft loss and biopsy-proven acute rejection. Important outcomes were post-transplant diabetes mellitus, cardiovascular events, infection, malignancy, and kidney function measures. RISK OF BIAS: Risk of bias was assessed with the Cochrane RoB 1 tool. SYNTHESIS METHODS: Assessment of risk of bias and data extraction were performed independently by at least two authors, and disagreements were resolved through discussion. Statistical analyses were performed using the random-effects model, and dichotomous outcomes were reported as risk ratios (RRs) and continuous outcomes as mean differences (MDs) with 95% confidence intervals (CIs). The certainty of the evidence was assessed using the GRADE approach. INCLUDED STUDIES: This updated review includes 53 studies (261 reports, 8317 randomised kidney transplant recipients). Of these, three studies were conducted in children (204 randomised participants). SYNTHESIS OF RESULTS: The overall certainty of the evidence of the included studies was low, ranging from moderate to very low. Factors downgraded on GRADE were primarily risk of bias and imprecision. Over 50% of the included studies did not adequately report random sequence generation or allocation concealment. Only five of 53 studies blinded participants and investigators. Incomplete outcome data was judged to be low in 26 studies, and 41 were free of selective reporting. Studies in adult kidney transplant recipients Steroid avoidance versus steroid maintenance The evidence is very uncertain about the effect of steroid avoidance on all-cause death up to one year (RR 0.84, 95% CI 0.51 to 1.39; 13 studies, 2126 participants; very-low-certainty evidence). Steroid avoidance may reduce death by one to five years (RR 0.61, 95% CI 0.39 to 0.96; 9 studies, 1607 participants; low-certainty evidence), and has little to no effect on graft loss censored for death up to one year (RR 0.95, 95% CI 0.62 to 1.46; moderate-certainty evidence). Steroid avoidance may increase the risk of biopsy-proven acute rejection up to one year (RR 1.58, 95% CI 1.11 to 2.25; 10 studies, 1845 participants; low-certainty evidence), although subgroup analysis showed no increase in risk when steroid avoidance was used in combination with tacrolimus, an antimetabolite and induction therapy. Steroid avoidance may reduce the risk of post-transplant diabetes mellitus up to five years (RR 0.70, 95% CI 0.59 to 0.84; 13 studies, 2390 participants; low-certainty evidence), but may have little to no effect on cardiovascular events (RR 0.73, 95% CI 0.46 to 1.18; 6 studies, 1417 participants; low-certainty evidence), infection (all) (RR 0.96, 95% CI 0.87 to 1.05; 11 studies, 2426 participants; low-certainty evidence), and probably has little to no effect on cytomegalovirus (CMV) infection (RR 1.01, 95% CI 0.80 to 1.27; 9 studies, 2155 participants; moderate-certainty evidence). Steroid withdrawal versus steroid maintenance Compared to steroid maintenance, steroid withdrawal may have little to no effect on all-cause death up to one year (RR 0.69, 95% CI 0.35 to 1.37; 9 studies, 1884 participants; low-certainty evidence) or one to five years (RR 1.17, 95% CI 0.67 to 2.03; 8 studies, 1189 participants; low-certainty evidence), and probably has little to no effect on graft loss censored for death up to one year (RR 1.19, 95% CI 0.72 to 1.96; 8 studies, 1854 participants; moderate-certainty evidence). Steroid withdrawal may have little to no effect on biopsy-proven acute rejection up to one year (RR 1.41, 95% CI 0.89 to 2.23; 5 studies, 1406 participants; low-certainty evidence). Steroid withdrawal probably has little to no effect on post-transplant diabetes mellitus up to five years (RR 0.82, 95% CI 0.55 to 1.21; 8 studies, 1647 participants; moderate-certainty evidence), and may have little to no effect on cardiovascular events up to five years (RR 0.91, 95% CI 0.42 to 1.97; 3 studies, 712 participants; low-certainty evidence) or infection (all) up to five years (RR 1.06, 95% CI 0.83 to 1.36; 6 studies, 1924 participants; low-certainty evidence). Steroid withdrawal probably has little to no effect on CMV infection up to five years (RR 1.10, 95% CI 0.85 to 1.43; 7 studies, 1956 participants; moderate-certainty evidence). Steroid avoidance versus steroid withdrawal The evidence is very uncertain regarding the effects of steroid avoidance compared with steroid withdrawal (4 studies, 466 randomised participants). Studies in paediatric kidney transplant recipients The evidence is very uncertain regarding the effects of steroid-sparing regimens in paediatric kidney transplant recipients (3 studies, 204 randomised participants). AUTHORS' CONCLUSIONS: There was no evidence to suggest a difference in patient death or graft loss up to one year after transplantation with steroid avoidance or withdrawal compared to maintenance, but steroid avoidance may reduce patient death at five years in adult kidney transplant recipients. Steroid avoidance may increase the risk of biopsy-proven acute rejection, but the risk may be similar when steroid avoidance is paired with tacrolimus, antimetabolite and induction therapy. The risk of biopsy-proven acute rejection in steroid withdrawal regimens may be similar to steroid maintenance regimens. We found no evidence to suggest differences in cardiovascular events or infection, but steroid avoidance compared to steroid maintenance may reduce the risk of post-transplant diabetes mellitus. FUNDING: LO is supported by a Río Hortega predoctoral fellowship from the Instituto de Salud Carlos III. REGISTRATION: Protocol and previous versions available via https://doi.org/10.1002/14651858.CD005632, https://doi.org/10.1002/14651858.CD005632.pub2, and https://doi.org/10.1002/14651858.CD005632.pub3.
27 May 2026
Read appraisal →Journal of computer-aided molecular design
In silico discovery of novel small-molecule PD-L1 inhibitors through a multi-stage computational workflow integrating machine learning and molecular dynamics
Cancer immunotherapy targeting the PD-1/PD-L1 pathway has transformed modern oncology; however, developing small-molecule inhibitors as viable alternatives to monoclonal antibodies remains a major challenge. In this study, an integrated computational framework is established in which machine learning, molecular docking, molecular dynamics simulations, and binding free-energy calculations are combined to enable the discovery and optimization of novel PD-L1 inhibitors. A validated ML-QSAR model was constructed using the XGBoost algorithm (R2_train = 0.925, R2_test = 0.743) on a dataset of 74 known inhibitors with consistent assay conditions. Through virtual screening of FDA-approved drugs, Pralatrexate was subsequently identified as a promising repurposing candidate, demonstrating a higher predicted binding affinity than the reference inhibitors. Structure-based modification of Pralatrexate yielded the derivative D1, which exhibited improved computational binding properties across all evaluation methods. Molecular dynamics simulations indicated that the D1-PD-L1 complex achieved greater stability than both the free protein and the reference complex, with reduced RMSD fluctuations and preserved key interactions with tyrosine residues Tyr56(A/B). MM-GBSA calculations further confirmed D1's superior binding affinity (-86.21 kcal/mol vs. - 73.65 kcal/mol for the reference), and predicted IC50 values suggested enhanced inhibitory potential. This multi-stage computational workflow effectively integrates machine learning predictions with atomic-level binding analyses, providing a robust platform for accelerated drug discovery. The optimized derivative D1 thus represents a promising candidate for experimental validation and further development as a potential cancer immunotherapeutic agent.
26 May 2026
Read appraisal →Rheumatology international
Diffuse splenic calcifications in systemic lupus erythematosus: a case-based review
Systemic lupus erythematosus (SLE) is a multi-organ autoimmune disease with a wide spectrum of splenic manifestations. In recent literature, splenic calcifications have increasingly been recognized as a rare manifestation of SLE. We describe a patient presenting with fever in whom abdominal imaging revealed splenomegaly with diffuse splenic microcalcifications, prompting further diagnostic evaluation that ultimately led to the diagnosis of SLE. To contextualize this finding, we performed a systematic case-based literature review and identified 29 previously reported cases, resulting in a total of 30 cases including our own. Across reported cases, no distinct serological or clinical phenotype could be identified. However, a characteristic imaging pattern emerged, predominantly consisting of diffuse, small, round-to-rod-shaped splenic calcifications. When longitudinal data were available, calcifications were usually stable, although progression was reported in association with disease flares, sometimes evolving to functional autosplenectomy. This case illustrates that splenic calcifications may represent an early or presenting manifestation of SLE and that an incidental detection should prompt consideration of autoimmune disease in the broad differential diagnosis. By synthesizing previously scattered reports, this review provides an updated overview to support clinical interpretation and awareness.
25 May 2026
Read appraisal →Lancet (London, England)
Safety and efficacy of astegolimab for COPD with frequent exacerbations regardless of baseline blood eosinophil counts (ALIENTO and ARNASA): randomised, double-blind, placebo-controlled, phase 2b and 3 trials
BACKGROUND: Interleukin-33 and its receptor, ST2, are implicated in neutrophilic and eosinophilic inflammation during chronic obstructive pulmonary disease (COPD) exacerbations. We aimed to assess the efficacy and safety of astegolimab, an anti-ST2 human IgG2 monoclonal antibody, which were evaluated in two COPD pivotal trials. METHODS: In two randomised, double-blind, placebo-controlled trials (phase 2b ALIENTO and phase 3 ARNASA), current or former smokers with COPD and a history of frequent exacerbations, irrespective of baseline blood eosinophils, were randomly assigned (1:1:1; stratification by smoking status and region) to receive subcutaneous astegolimab 476 mg every 2 weeks, every 4 weeks, or placebo, alongside optimised inhaled maintenance therapy over 52 weeks. The primary endpoint (analysed in participants receiving one or more doses) was annualised rate of moderate or severe exacerbations. Missing data were considered similar to data from other participants in the same treatment group with the same baseline characteristics. The trials were registered with ClinicalTrials.gov (NCT05037929 and NCT05595642). FINDINGS: In ALIENTO, 1301 participants (astegolimab every 2 weeks, n=433; astegolimab every 4 weeks, n=437; and placebo, n=431) initiated treatment between Oct 5, 2021, and Feb 19, 2024. In ARNASA, 1375 participants (astegolimab every 2 weeks, n=459; astegolimab every 4 weeks, n=459; and placebo, n=457) initiated treatment between Jan 9, 2023, and June 25, 2024. Adjusted rate ratios versus placebo for the primary endpoint were 0·85 (95% CI 0·72-1·00; p=0·049) for astegolimab every 2 weeks and 0·93 (0·79-1·10; p=0·38) for astegolimab every 4 weeks in ALIENTO, and 0·85 (0·72-1·01; p=0·068) for astegolimab every 2 weeks and 0·82 (0·70-0·98; p=0·024) for astegolimab every 4 weeks in ARNASA. Adverse events were balanced between treatments, with most participants experiencing one or more adverse events (1093 [84·0%] of 1301 participants in ALIENTO and 1176 [85·5%] of 1375 in ARNASA). The most common non-COPD adverse event was nasopharyngitis in ALIENTO and upper respiratory chest infection in ARNASA. Deaths occurred in 40 (3·1%) of 1301 participants in ALIENTO and in 44 (3·2%) of 1375 participants in ARNASA, and were balanced across treatment groups. Across both trials, a total of three deaths (0·1%) were considered to be related to treatment by investigators. INTERPRETATION: In ALIENTO, astegolimab every 2 weeks was associated with a lower annual rate of exacerbations versus placebo in patients with COPD and a history of frequent exacerbations. In ARNASA, these findings did not meet statistical significance. Together, these findings suggest a role for targeting the ST2/IL-33 pathway to reduce the frequency of COPD exacerbations in patients with limited treatment options. FUNDING: Genentech, a member of the Roche Group, and F Hoffmann-La Roche.
23 May 2026
Read appraisal →Lupus science & medicine
Can disease activity and treatment responses be captured by a core set of domains in SLE clinical trials? An analysis of phase III belimumab trial data.
OBJECTIVE: Outcome measures used in SLE randomised controlled trials (RCTs) have impeded trial success and drug approval. In an ongoing global project to develop a novel outcome measure for SLE RCTs, a 'core set' of domains with which to determine treatment response was chosen via consensus. We investigated the impact of restricting disease activity assessment to this core set on responder classification in RCTs. METHODS: Using pooled baseline and week 52 data from two phase III SLE RCTs (Belimumab in Subjects with Systemic Lupus Erythematosus (BLISS)-52, NCT00424476; BLISS-76, NCT00410384), we divided items from the British Isles Lupus Assessment Group (BILAG) disease activity index into core and non-core sets. The core set included 30 of 86 BILAG items across five domains: mucocutaneous (rash, alopecia, mucosal ulcers), haematological (thrombocytopenia, haemolytic anaemia), arthritis, serositis and nephritis. We analysed baseline disease activity and treatment response at week 52. RESULTS: We analysed 1526 patients. At baseline, the core set captured the majority of disease activity captured using the full BILAG (1426/1526 (93.5%) of patients). Cutaneous vasculitis, non-haemolytic anaemia, leucopenia, dyspnoea and fatigue were the most common non-core set manifestations present. At week 52, about 1278/1426 (89.5%) patients demonstrated concordant treatment responses measured with the core set only versus all BILAG items. Discordance was again driven by cutaneous vasculitis, non-haemolytic anaemia, leucopenia and fatigue. CONCLUSIONS: Limiting the classification of treatment response to a core set of domains has the potential to simplify SLE RCT endpoints without a significant negative impact on patient inclusion or responder classification.
23 May 2026
Read appraisal →The Journal of dermatological treatment
Sustained on/off-treatment disease control with abrocitinib for moderate-to-severe atopic dermatitis.
PURPOSE: Achieving sustained on- and off-treatment disease control is an important therapeutic goal in atopic dermatitis (AD). This study evaluated achievement of off-treatment disease control in patients randomized to placebo following 12 weeks of abrocitinib 200 mg. MATERIALS AND METHODS: In the phase 3 JADE REGIMEN study, patients with moderate-to-severe AD who achieved Investigator's Global Assessment (IGA) of 0/1 (with ≥2 grades of improvement) and ≥75% improvement in Eczema Area and Severity Index (EASI) after 12 weeks of abrocitinib 200 mg were randomized (1:1:1) to placebo, abrocitinib 100 mg, or abrocitinib 200 mg for 40 weeks. This post-hoc analysis evaluated patients by flare status (protocol flare definition: ≥50% loss of initial EASI post-randomization response and IGA score ≥2). EASI, IGA, Peak Pruritus Numerical Rating Scale (PP-NRS), and Dermatology Life Quality Index (DLQI) were evaluated. RESULTS: There were no off-treatment flares in 21.3% of patients in the placebo arm. The no-flare group had EASI, IGA, PP-NRS, and DLQI mean scores indicating clear/mild AD at week 52 (2.9, 1.0, 2.6, and 3.5, respectively). CONCLUSIONS: After 12 weeks of abrocitinib 200 mg, some patients achieved 40 weeks of sustained off-treatment disease control, with assessments demonstrating clear/mild AD, suggesting attainment of disease remission. TRIAL REGISTRATION: NCT03627767.
22 May 2026
Read appraisal →Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Safety and Immunogenicity of a Fourth Dose of Omicron BA.1-Adapted BNT162b2 COVID-19 Vaccines in Adults 18-55 Years Old
BACKGROUND: Emergence of severe acute respiratory syndrome coronavirus 2 sublineages warrants the use of sequence-adapted vaccines to provide protection against coronavirus disease 2019. METHODS: In this phase 3 trial, adults 18‒55 years old who had previously received three 30 μg doses of BNT162b2 vaccine were randomized to receive a 60 or 30 μg dose of bivalent Omicron BA.1‒adapted BNT162b2 comprising equal amounts of ancestral and monovalent messenger RNA BA.1 (bivalent BA.1) or a 60 μg dose of monovalent Omicron BA.1‒adapted BNT162b2 (monovalent BA.1). Safety (local reactions, systemic events, adverse events [AEs], and serious AEs) was the primary objective. Exploratory analyses assessed immune responses against Omicron BA.1, BA.4, and BA.5 subvariants and ancestral strain. RESULTS: Among the 1054 randomized participants who received monovalent BA.1 or bivalent BA.1, frequencies of local reactions, systemic events, and AEs were slightly higher with 60 µg monovalent BA.1 than either bivalent BA.1 dose level. One month after vaccination, bivalent BA.1 (30 and 60 μg) and monovalent BA.1 (60 μg) induced substantial neutralizing responses against Omicron BA.1 (50% neutralizing titer geometric mean fold rises [GMFRs], 15.4 [95% CI 12.4-19.2], 17.1 [13.7-21.4], and 24.6 [19.3-31.4], respectively) and ancestral strain (GMFRs, 6.2 [5.1-7.6], 7.3 [6.0-8.9], and 7.0 [5.7-8.7], respectively). In a smaller (n = 30/treatment arm) sentinel cohort, all study vaccines modestly neutralized Omicron BA.4 and BA.5. CONCLUSIONS: Bivalent and monovalent BA.1‒adapted vaccines had a safety profile similar to the original BNT162b2 30 μg and induced substantial neutralizing responses against Omicron BA.1 and ancestral strains. CLINICAL TRIALS REGISTRATION: NCT04955626.
22 May 2026
Read appraisal →PloS one
Computational models for the classification of antibody specificity using heavy chain features
BACKGROUND: Antibodies play a critical role in immune defense, with their antigen specificity primarily governed by the unique sequences of their heavy chains, rendering them invaluable tools in research and diagnostics. High-throughput sequencing technologies have facilitated comprehensive profiling of the immune repertoire, generating vast antibody sequence datasets that necessitate advanced analytical methods. METHODS: In this study, we utilized curated antibody sequences from NCBI databases to develop computational classification models for categorizing antibodies into predefined antigen classes. We extracted multifaceted features from the heavy chain sequences, encompassing physicochemical properties, structural composition, sequence order, and evolutionary information. These features were input into machine-learning classifiers to predict antigen specificity across five classes of antibodies: anti-dengue virus, anti-influenza virus, anti-tetanus bacillus, anti-SARS-CoV-2, and anti-Mycobacterium tuberculosis. RESULTS: Five tree-based machine-learning models were employed, with CatBoost achieving the highest accuracy of 0.7713. To further enhance predictive performance, we developed a stacking model leveraging multiple algorithms, resulting in an improved accuracy of 0.7803. Additionally, a Feature-Based Transformer deep-learning architecture was implemented, yielding an accuracy of 0.7399 and an F1-score of 0.6761. To elucidate the key determinants of antibody-antigen interactions, we applied the SHAP framework to assess feature importance. Among the top 30 contributing features, those representing sequence order and evolutionary information predominated, with amino acids such as cysteine (C), isoleucine (I), histidine (H), and phenylalanine (F) exhibiting notable SHAP values. Notably, cysteine (Cys) emerged as the most influential feature, underscoring its critical role in antibody structure and function. Specific antibodies contributed variably to these key features; for instance, the anti-tuberculosis antibody accounted for approximately 11% of a sequence order feature associated with alanine (A), while the anti-SARS-CoV-2 antibody contributed about 9.26% to a feature associated with isoleucine (I). CONCLUSIONS: Our study demonstrates the efficacy of machine-learning and deep-learning approaches in classifying antibodies into specific antigen categories, providing sequence-based insights into features associated with antibody specificity. These findings have significant implications for the mechanistic understanding, isolation, and development of potential therapeutic antibodies.
22 May 2026
Read appraisal →Cell systems
Learning multi-cellular representations of single-cell transcriptomics data enables characterization of patient-level disease states
Single-cell RNA sequencing (scRNA-seq) is a prominent tool for studying human disease biology. The availability of massive scRNA-seq datasets and advanced machine learning has driven the development of single-cell foundation models that provide versatile cell representations based on expression. To understand disease states, we need to account for entire tissue ecosystems, simultaneously considering many different interacting cells. Here, we tackle this challenge by generating patient-level representations derived from multi-cellular expression contexts measured with scRNA-seq of tissues. We develop PaSCient, a machine learning model that employs a multi-level representation learning paradigm and provides importance scores at the cell and gene levels for fine-grained analysis of disease characteristics. We apply PaSCient to a large-scale scRNA-seq atlas of 12.5 million cells from over 2,700 patients. Comprehensive benchmarking demonstrates the superiority of PaSCient in disease classification and multiple downstream applications, including dimensionality reduction, feature prioritization, and patient subgroup discovery.
22 May 2026
Read appraisal →Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Respiratory Syncytial Virus Vaccination in Solid Organ Transplant Recipients: Interim Findings From a Phase 3 Trial of mRNA-1345
BACKGROUND: Solid organ transplant (SOT) recipients are at increased risk for severe respiratory syncytial virus (RSV) disease due to chronic immunosuppression. METHODS: In this ongoing, open-label, phase 3 trial, adults ≥18 years with a history of liver, kidney, or lung transplant received 2 doses of mRNA-1345 RSV vaccine (50 µg) 56 days apart. Primary endpoints were tolerability, safety, and RSV-A/RSV-B neutralizing antibody (nAb) responses on Day 85; secondary endpoints included immunogenicity on Days 29 and 181. Cell-mediated immunity was an exploratory endpoint assessed in a subset of participants. RESULTS: 146/150 participants (median: age, 57 years; time since transplant, 4.7 years) received both doses. Reactogenicity was mild to moderate and transient. No vaccine-related discontinuations, deaths, adverse events of special interest (AESIs), or events of transplant rejection were reported within 28 days after any dose. One dose was immunogenic across all SOT types, with 4.9- and 3.4-fold increases in RSV-A/RSV-B nAb GMTs by Day 29, respectively. A second dose resulted in modest additional increases over baseline (RSV-A, 7.1-fold; RSV-B, 5.2-fold). Added benefit of the second dose was more apparent in participants with kidney and lung transplant, <2 years post-transplant, and on mycophenolate. Responses remained above baseline through Day 181. Polyfunctional CD4⁺ T-cell responses were robust and sustained; CD8⁺ responses were also observed. CONCLUSIONS: mRNA-1345 was well tolerated and immunogenic in SOT recipients. A single dose induced nAb responses across subgroups, with potential additional benefit from a second dose in specific groups. Durable antibody and cellular responses support mRNA-1345 as a preventive strategy for RSV in this vulnerable population. CLINICAL TRIALS REGISTRATION: NCT06067230.
22 May 2026
Read appraisal →Postgraduate medical journal
Next-generation cancer therapies: translating experimental advances into clinical practice
Recent advancements in cancer therapy have led to the emergence of innovative approaches that offer new hope to patients. This review provides a comprehensive overview of the latest cutting-edge technologies and strategies in cancer treatment, including clinically approved therapies and experimental modalities in preclinical or early clinical development, with a focus on their potential to improve patient outcomes. We examined next-generation therapies, including personalized immunotherapies, targeted molecular treatments, gene editing approaches, and artificial intelligence-driven strategies. By evaluating the current landscape of these therapies, we highlighted their benefits, limitations, and future directions. The integration of these advanced modalities into clinical practice holds promise for enhancing their efficacy, reducing side effects, and ultimately transforming cancer care.
22 May 2026
Read appraisal →Rheumatology international
Targeting type I interferon in lupus panniculitis: a case-based systematic literature review
Lupus panniculitis (LEP) is a rare form of cutaneous lupus (CLE) characterised by progressive, often disfiguring course and poor response to treatment. Type I interferon inhibition through anifrolumab (ANF) is effective in CLE but limited data are available for its use in LEP. To address this issue, we screened patients with CLE and/or systemic lupus erythematosus (SLE) for biopsy-proven diagnoses of LEP and treatment with ANF. Besides demographics, general clinical features, concomitant treatments before and after ANF and safety signals, we measured disease activity and damage with the SLE disease activity index 2000 (SLEDAI-2 K), the CLE Disease Area and Severity Index activity (CLASI-A) and damage scores and the SLE International collaborating clinics/American College of Rheumatology damage index. The same data were retrieved, when available, from existing cases extracted from systematic literature review. Sixteen cases were identified, including 3/421 newly described patients, with two receiving ANF as first-line immunosuppressant and one as an early treatment devoid of oral corticosteroids. All patients had a good response to treatment and most of them could taper or discontinue corticosteroids. CLASI-A scores were markedly reduced after ANF treatment [11.5 (7-29)] to 0 (0-2); p = 0.005]. The time to response was within five months in most cases. No significant adverse events were reported. Taken together, our data suggest that ANF might be effective in LEP and used as a first-line treatment to prevent LEP-related damage accrual.
21 May 2026
Read appraisal →The British journal of dermatology
Efficacy and safety of stapokibart in adolescents with moderate-to-severe atopic dermatitis: a multicentre randomized double-blind placebo-controlled phase III trial
BACKGROUND: Moderate-to-severe atopic dermatitis (AD) imposes a significant burden on adolescents and their families, leading to a substantial reduction in quality of life. Treatment options remain limited. Stapokibart, a novel humanized monoclonal antibody that targets interleukin-4Rα, has been approved in China for the treatment of adults with moderate-to-severe AD. OBJECTIVES: To evaluate the efficacy and safety of stapokibart in adolescents with moderate-to-severe AD. METHODS: In this randomized double-blind placebo-controlled phase III trial (NCT06277765), eligible patients were randomized (2 : 1) to stapokibart 300 mg (loading dose 600 mg) or placebo for 18 weeks. Patients with a baseline weight ≥ 60 kg received subcutaneous stapokibart or placebo every 2 weeks (Q2W), while those weighing 30 to < 60 kg received treatment every 3 weeks (Q3W). All patients were given moisturizers during the entire study period. Co-primary endpoints were the proportions of patients achieving a ≥ 75% improvement from baseline in Eczema Area and Severity Index (EASI 75) and an Investigator's Global Assessment (IGA) score of clear or almost clear (IGA 0 or 1) with ≥ 2-point reduction from baseline (IGA response) at week 18. Safety was also assessed. RESULTS: Of the 180 enrolled patients, 120 received stapokibart (Q2W, n = 54; Q3W, n = 66) and 60 received placebo (Q2W, n = 26; Q3W, n = 34). In total, 178 (98.9%) patients completed the double-blind treatment. At week 18, higher proportions of patients treated with stapokibart than those treated with placebo achieved EASI 75 [73.9% (n = 88/119) vs. 43% (n = 26/60); difference: 30.5% (95% confidence interval 15.3-44.3; P < 0.001)] and an IGA response [57.1% (n = 68/119) vs. 25% (n = 15/60); difference: 31.8% (95% confidence interval 16.6-44.4; P < 0.001)]. The proportion of patients achieving ≥ 4-point reductions in weekly average of daily Peak Pruritus Numerical Rating Scale score was also significantly higher in the stapokibart group than in the placebo group [36.1% (n = 43/119) vs. 15% (n = 9/60); difference: 21.1% (95% confidence interval 7.4-32.4; P = 0.004)]. The incidence of adverse events was similar between the stapokibart (62.5%; n = 75/120) and placebo (62%; n = 37/60) groups. No conjunctivitis was seen. CONCLUSIONS: Stapokibart has a high efficacy and favourable safety in adolescents with moderate-to-severe AD. An author video to accompany this article is available online. Atopic dermatitis is a long-term skin condition. It causes intense itching and painful patches of dry skin. It is more commonly known as eczema. Adolescents with moderate or severe eczema often need long-term treatment to control the symptoms. In China, a drug called ‘stapokibart’ has recently been approved to treat adults with moderate or severe eczema. This study was done in 32 hospitals in China. We included adolescents with moderate or severe eczema. We treated them with stapokibart or placebo (an inactive or ‘dummy’ medication) for 18 weeks. The patients received their treatment via an injection under their skin. Depending on their weight at the start of the study, patients received treatment every 2 or every 3 weeks. After 18 weeks, patients treated with stapokibart were less itchy and had more of an improvement in their skin than those treated with the placebo. Over half of the patients achieved clear (or almost clear) skin. Finally, we found that stapokibart was safe to take. Undesired results from taking the medication (called ‘adverse events’) were mild or moderate. Our results suggest that stapokibart is an effective and safe treatment option for adolescents with moderate or severe eczema.
20 May 2026
Read appraisal →Revista do Instituto de Medicina Tropical de Sao Paulo
Molecular biomarkers associated with ATLL and HAM progression in HTLV-1 infection: a systematic review
Human T-lymphotropic virus type 1 (HTLV-1) infects approximately five to 10 million individuals worldwide, although only a minority develop severe outcomes such as adult T-cell leukemia/lymphoma (ATLL) or HTLV-1-associated myelopathy (HAM). Proviral load (PVL), while widely used, shows limited sensitivity and specificity, reinforcing the need for complementary biomarkers. Omics-based approaches have emerged as promising tools to improve risk prediction. We conducted a systematic review following PRISMA guidelines, searching PubMed, Web of Science, Virtual Health Library (BVS), and CAPES Periodicals databases for studies published between May 2020 and May 2025. Eligible studies included original observational designs investigating genomic, proteomic, and metabolic biomarkers associated with progression to ATLL or HAM. Methodological quality was assessed using tools from the National Heart, Lung, and Blood Institute (NHLBI). In total, 35 studies met the inclusion criteria, most conducted in Brazil, Japan, and Iran. A total of 67 biomarkers were identified: 37 genomic, 27 proteomic, and three metabolic with potential clinical applications in risk stratification, prognosis, and therapeutic monitoring of HTLV-1 infection. PVL remained the most frequently investigated marker but lacked predictive power in isolation. Additional candidates with strong potential included IFN-γ, CXCL10, Neopterin, AnxA1, and sTNFR2. This review highlights the potential of integrated multiparametric panels-combining PVL with omics-derived biomarkers-as a promising strategy to improve risk stratification, prognosis, and therapeutic monitoring in people living with HTLV-1 (PLHTLV-1). However, further longitudinal and clinically validated studies are needed to confirm their applicability and support their translation into early intervention strategies, particularly during the asymptomatic phase.
20 May 2026
Read appraisal →Journal of virology
Is the molecular microenvironment of the latent HIV reservoir predictable using deep learning approaches?
Although current antiretroviral therapy effectively suppresses viral replication in infected individuals, infections remain incurable. One of the main reasons for this is the uncertainty of the molecular microenvironment of the latent HIV reservoir. If this microenvironment can be precisely targeted, the effectiveness of current antiretroviral therapy can be leveraged. To better depict the potent microenvironments of the latent HIV reservoir, it is crucial to first understand the mechanisms that make some viruses transcriptionally active and others silent in the first place. It is currently feasible to predict gene activity from DNA sequence, coupled with epigenetics, using deep learning approaches. Substantial progress has been made in creating multidimensional data sets related to the HIV latent reservoir. The implementation of deep learning to mine potent attributes, enabling the characterization and prediction of the microenvironment of the latent HIV reservoir, is thus imperative. This minireview discusses potent features that can be integrated into deep learning methodologies to predict the likelihood of the potential microenvironment from different tiered levels of the latent HIV reservoir organization, and proposes the principal workflow to tackle this question using deep learning approaches.
20 May 2026
Read appraisal →Analytical chemistry
Adaptive Deep Learning for High-Fidelity Quantitative Single-Molecule Imaging
Accurate quantification of molecular dynamics in live cells is critical for elucidating receptor signaling and guiding therapeutic strategies. Yet current deep learning methods for fluorescence imaging often distort intensity and lack robustness under diverse imaging settings, limiting quantitative utility. We present an adaptive deep learning framework that constructs in situ training data sets from ongoing sequences and integrates a self-feedback algorithm to preserve absolute molecular intensities. This approach achieves ≥ 3.9-fold gains in signal-to-noise and 1.6-fold improvements in localization precision across organic dyes, quantum dots, and fluorescent proteins. By maintaining both spatial and intensity fidelity, it enhances super-resolution reconstruction, stepwise photobleaching analysis, and live-cell single-molecule tracking. Applied to programmed death-ligand 1 (PD-L1), it uncovers density-dependent clustering, with small-molecule inhibitors inducing dimerization and reduced mobility, while antibodies increase diffusivity. Combined treatments exert complementary effects on PD-L1 membrane organization. This adaptive and intensity-preserving framework provides a broadly applicable platform for high-precision quantitative bioimaging across modalities and experimental conditions.
20 May 2026
Read appraisal →Cell reports methods
A lightweight TcrLM model predicts T cell receptor and epitope binding specificity.
Immune responses depend on specific interactions between T cell receptors (TCRs) and peptides presented by antigen-presenting cells (APCs). The vast diversity of the TCR repertoire makes accurate prediction of TCR-antigen binding specificity highly challenging. Here, we present a lightweight, masked language model, tcrLM, to address this problem. We pretrain tcrLM on a large-scale TCR CDR3 sequence dataset and use the pretrained encoder to extract informative features for pTCR binding prediction. tcrLM achieves competitive performance on hold-out and external test sets and shows comparatively robust zero-shot generalization relative to several baselines on a large, unseen-COVID-19 peptide set. The model effectively captures biochemical properties and positional preferences of amino acids within TCR sequences. In an exploratory melanoma cohort, the predicted TCR-neoantigen binding scores correlate with immunotherapy response and clinical outcomes. These results highlight the potential of tcrLM for advancing immunotherapy and personalized medicine.
20 May 2026
Read appraisal →Lupus science & medicine
Incidence of serious infections, herpes zoster and hepatitis B virus reactivation among patients with SLE: a cohort study using a health claims database in Japan
OBJECTIVES: To investigate the real-world incidence of serious infections (SI), herpes zoster (HZ) and hepatitis B virus (HBV) reactivation among patients with SLE. METHODS: This retrospective, non-interventional cohort study used an insurance claims database in Japan to calculate the incidence of SI requiring hospitalisation, HZ and HBV reactivation in patients with SLE from 1 April 2017 to 31 March 2021. As an exploratory analysis, HRs and 95% CIs were estimated for clinically relevant patient characteristics for SI and HZ, adjusting for age and sex. RESULTS: Among 10 865 patients with SLE (female: 83.1%, median age: 53.0 years), including those who had previously experienced each complication, the incidence rates (per 100 patient-years) for SI, HZ and HBV reactivation were 4.80 (95% CI 4.53 to 5.08), 0.52 (0.44 to 0.61) and 0.37 (0.30 to 0.45), respectively. For those who had no previous history of each complication, incidence rates were 3.67 (3.44 to 3.92), 0.48 (0.40 to 0.58) and 0.25 (0.20 to 0.32), respectively. Incidence rates in specific subgroups were as follows: history of each complication (SI: 37.93, HZ: 4.19, HBV reactivation: 72.01), history of SI (HZ: 1.51, HBV reactivation: 1.75) and glucocorticoid pulse therapy during follow-up (SI: 64.23, HZ: 3.10, HBV reactivation: 4.85). CONCLUSIONS: These results provide data on the occurrence of selected infections in SLE and may inform safety management.
18 May 2026
Read appraisal →Clinica chimica acta; international journal of clinical chemistry
Exploring clinical feasibility of zero-shot learning in a large language model for immunofixation electrophoresis image interpretation
INTRODUCTION: Immunofixation electrophoresis (IFE) is the gold standard method for detecting and typing monoclonal immunoglobulins, but its interpretation requires expert evaluation and remains susceptible to subjectivity and variability. Recent advances in multimodal large language models (LLMs) have enabled zero-shot visual reasoning without task-specific training. This study aimed to evaluate the feasibility and diagnostic performance of zero-shot multimodal LLMs for automated interpretation of IFE images. MATERIALS AND METHODS: A dataset of 487 immunofixation electrophoresis images representing ten semantic classes (AK, AL, GK, GL, K, L, LGL, MK, ML, and NONE) was retrospectively collected and annotated by expert laboratory specialists. Two multimodal LLMs, ChatGPT-5.2 and Gemini3 Pro, were evaluated using a zero-shot visual question answering (ZS-VQA) framework without additional training or fine-tuning. Each image was analyzed using two prompt configurations: a simple prompt and a detailed prompt with structured diagnostic guidance. Model performance was assessed using precision, recall, F1-score, and confusion matrix analysis. RESULTS: Gemini outperformed ChatGPT across most classes, particularly with detailed prompts, achieving high F1-scores in clinically relevant monoclonal categories such as MK (89.80), AK (84.75), and GK (71.54). Detailed prompting consistently improved recall and F1-scores, underscoring the importance of prompt design. In contrast, ChatGPT showed lower recall, F1-scores, and classification consistency. Both models performed less effectively in visually subtle patterns. CONCLUSIONS: Zero-shot multimodal LLMs, particularly Gemini, show promising potential for interpreting IFE images without task-specific training. However, performance variability and limitations in certain classes indicate that further optimization and validation are required before clinical implementation.
18 May 2026
Read appraisal →European journal of pediatrics
Leveraging artificial intelligence to predict non-adherence to pediatric immunization schedules: a systematic review
UNLABELLED: Immunization is one of the most effective interventions to prevent infectious diseases. Identifying individuals at risk of non-adherence to immunization schedules could enable early interventions to improve coverage. With the increasing availability of large datasets with sociodemographic, medical, and geographic data, artificial intelligence (AI) offers new possibilities for identifying predictive patterns. We performed a systematic literature review of original studies that used AI to predict immunization non-adherence in children. Searches were conducted in PubMed, Embase, and Web of Science and no restrictions were applied regarding publication year, language, or study design. Study characteristics, dataset size, AI methods, performance metrics, and validation approaches were extracted. Risk of bias was assessed using PROBAST + AI. A total of 843 records were identified; after screening, 12 studies were included. Nine of 12 studies were conducted in low- and middle-income countries, used cross-sectional survey data, and analyzed vaccines from routine immunization schedules. Model performance was generally high; 9/12 studies reported an accuracy or an area under the receiver operating characteristic curve exceeding 80%, but no study conducted external validation. Predictors clustered into seven categories: maternal, paternal, family, child, geographic, wealth, and others. Among maternal and child-related factors, prenatal care and previous immunization history had a high predictive weight. CONCLUSION: AI demonstrates a promising potential for identifying individuals at risk of vaccine non-adherence. However, the lack of external validation raises concerns about model overfitting and limits real-world applicability. Demographic health surveys were routinely repeated across countries and time periods and could therefore represent an ideal resource for external validation. WHAT IS KNOWN: • Geographic, sociodemographic, and medical factors contribute to non-adherence to the immunization schedule. • Identifying these individuals can guide early interventions to improve immunization coverage. WHAT IS NEW: • Artificial intelligence can reveal unknown influential factors; prenatal care and delivery setting emerged as key factors in this systematic review.
17 May 2026
Read appraisal →International immunopharmacology
NY-ESO-1 in Triple-Negative Breast Cancer: Systematic Review, Meta-Analysis, and Immunotherapeutic Implications
Breast cancer remains one of the most common types of cancer, including the subtype triple-negative breast cancer (TNBC) which is challenging to treat due to its aggressiveness. Cancer-testis antigens (CTAs), especially New York Esophageal Squamous Cell Carcinoma 1 (NY-ESO-1), have become promising immunotherapeutic targets attributable to their restricted expression profile in normal tissues but overexpressed in TNBC, leading to immunogenicity. This review provides comprehensive discussion of NY-ESO-1 including its structural basis of NY-ESO-1 recognition by T cell receptors (TCRs) and antibodies, epigenetic regulation via DNA methylation or histone modifications, and expression patterns or clinical relevance in TNBC. A systematic meta-analysis of 12 studies comprising 1,545 TNBC patients showed a pooled NY-ESO-1 expression prevalence of 16.1% (95% CI: 11.4-22.2%), with heterogeneity (I2=83.7%) attributable to antibody clone used for NY-ESO-1 detection (E978: 15.1% vs. D8.38: 32.6%, p<0.0001) and scoring methods (composite scoring: 15.9% vs. dual scoring: 16.9% vs. H-score: 10.1% vs. simple threshold: 32.6%, p<0.001). Structural analyses reveal NY-ESO-1157-165 recognition by TCRs, antibodies, and engineered binding scaffolds. We examine preclinical and clinical evidence for NY-ESO-1-targeted therapies, including adoptive cell therapy and peptide vaccines, which show manageable safety profiles and induce immunological responses. Epigenetic regulation is a therapeutic avenue, whereby hypomethylating agents and histone deacetylase inhibitors can upregulate NY-ESO-1 expressions that promote tumor immunogenicity. Nonetheless, challenges persist such as NY-ESO-1 expression heterogeneity, lack of TNBC-specific clinical trials, and inadequate immunogenicity. Future research should standardize NY-ESO-1 detection protocols to identify TNBC patients for NY-ESO-1-targeted immunotherapy, prioritize TNBC-specific trials and combinations with epigenetic priming agents.
16 May 2026
Read appraisal →Journal of neurology, neurosurgery, and psychiatry
Intravenous methylprednisolone as add-on induction therapy for chronic inflammatory demyelinating polyradiculoneuropathy: a randomised controlled trial
BACKGROUND: Most patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) require maintenance treatment. We aimed to determine whether combined treatment with intravenous immunoglobulin (IVIg) and intravenous methylprednisolone (IVMP) increases remission rates compared with IVIg and placebo. METHODS: We performed a randomised, double-blind, placebo-controlled study. Adults with CIDP who were treatment naive, relapsed after a remission or required continued treatment after a single IVIg dose were included. Participants were treated with IVMP (1000 mg) or placebo (sodium chloride) every 3 weeks for 18 weeks. All participants received IVIg treatment consisting of a loading dose (2 g/kg) and serial maintenance treatments (1 g/kg). The primary outcome was remission, defined as sustained improvement on disability scales at 52 weeks without need for further treatment. RESULTS: Enrolment was halted after the inclusion of 77 of the 96 planned participants because of safety concerns: four thromboembolic events occurred in the IVIg/IVMP group compared with none in the IVIg/placebo group. 14 of 37 (38%) participants in the IVIg/IVMP group were in remission at 52 weeks compared with 11 out of 40 (28%) in the IVIg/placebo group, with a difference of 10% (95% CI -11 to 31; p=0.47). Several secondary outcomes showed a greater magnitude of improvement in disability and impairment at 18 and 52 weeks in the IVIg/IVMP group. CONCLUSIONS: The study was prematurely stopped due to safety concerns after four thromboembolic events in the IVIg plus IVMP group. Combined treatment did not lead to significantly more frequent remissions than IVIg alone in the doses used in this study. TRIAL REGISTRATION NUMBER: ISRCTN15893334.
16 May 2026
Read appraisal →The New England journal of medicine
A Phase 3 Trial of Brepocitinib in Dermatomyositis
BACKGROUND: Brepocitinib is a first-in-class, oral, selective TYK2-JAK1 inhibitor that blocks cytokine signaling, which has been implicated in dermatomyositis. METHODS: In this phase 3, double-blind, randomized, placebo-controlled trial, adults with dermatomyositis were assigned in a 1:1:1 ratio to receive once-daily oral brepocitinib at a dose of 30 mg, brepocitinib at a dose of 15 mg, or placebo for 52 weeks. Standard therapies were continued, and glucocorticoids were tapered. The primary end point was the Total Improvement Score, a validated composite myositis index (with scores ranging from 0 to 100 and higher scores indicating greater improvement) at week 52. Key secondary end points, including skin disease activity, glucocorticoid tapering, and physical function, were tested in a multiplicity-controlled sequence. RESULTS: A total of 241 patients underwent randomization: 81 to receive brepocitinib 30 mg, 81 to receive brepocitinib 15 mg, and 79 to receive placebo. At week 52, the mean Total Improvement Score was 46.5, 37.5, and 31.2, respectively (difference with brepocitinib 30 mg vs. placebo, 15.3; 95% confidence interval [CI], 6.7 to 24.0; P<0.001; difference with brepocitinib 15 mg vs. placebo, 6.3; 95% CI, -2.4 to 14.9). Brepocitinib 30 mg was superior to placebo across all nine key secondary end points, including skin disease activity, systemic glucocorticoid tapering, and functional disability, with improvements observed as early as week 4. Serious infections were more frequent in the brepocitinib 30-mg group than in the placebo group (10% vs. 1%). No deaths occurred during the trial. CONCLUSIONS: In adults with dermatomyositis that was resistant to previous therapy, the use of brepocitinib at a dose of 30 mg (but not at a dose of 15 mg) resulted in significant benefits with respect to a composite myositis index, skin disease severity, glucocorticoid tapering, and functional disability. (Funded by Priovant Therapeutics; ClinicalTrials.gov number, NCT05437263.).
15 May 2026
Read appraisal →Molecular neurobiology
Gut Microbiota Dysbiosis and Neuroinflammation in Alzheimer's Disease: a Systematic Review of Mechanistic Insights
This systematic review aims to identify microbial species associated with Alzheimer's disease and clarify how they influence Alzheimer's disease pathology, including immune system interactions and blood-brain barrier integrity. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, 18 studies were analyzed, revealing significant differences in gut microbiota composition between patients with Alzheimer's disease and controls. Key findings include reduced beneficial bacteria, such as Faecalibacterium prausnitzii and Roseburia hominis and increased pro-inflammatory species like Escherichia coli. Mechanistically, Escherichia coli produces lipopolysaccharides, triggering the release of pro-inflammatory cytokines such as tumor necrosis factor-alpha. This response correlates with elevated YKL-40 levels and reduced beneficial bacteria like Turicibacter. Additionally, reductions in butyrate-producing bacteria impair blood-brain barrier integrity, while bile acid metabolism disruptions impair signaling pathways, exacerbating amyloid-beta aggregation. These findings highlight the interplay between gut microbiota-derived metabolites and neuroinflammation, suggesting that targeting the gut microbiota for novel diagnostic and therapeutic approaches in Alzheimer's disease.
14 May 2026
Read appraisal →Lancet (London, England)
Impact of introducing RTS,S/AS01E malaria vaccine on mortality in young children in Ghana, Kenya, and Malawi: an observational evaluation of a cluster-randomised implementation programme
BACKGROUND: Malaria vaccines have been added to immunisation schedules in 25 sub-Saharan African countries, with the expectation that deaths in young children would be prevented. The introduction of the RTS,S/AS01E malaria vaccine (RTS,S) in Ghana, Kenya, and Malawi in 2019 was evaluated over 4 years to show the impact on mortality in young children and to monitor severe malaria admissions, vaccine uptake, and safety. Favourable evidence on safety and impact on severe malaria admissions during the first 2 years contributed to WHO's recommendations on malaria vaccines. Here, we report the primary analysis of the impact on mortality at 46 months. METHODS: Clusters of administrative units (districts in Ghana, subcounties in Kenya, and groups of immunisation clinics in Malawi), each with an estimated annual birth cohort of about 4000 children, were randomly assigned 1:1 to introduce the RTS,S malaria vaccine in 2019 (implementation areas), or to implement later (comparison areas). RTS,S was delivered in a four-dose schedule, at age 6, 7, 9, and 24 months in Ghana and Kenya, and at age 5, 6, 7, and 22 months in Malawi. Surveillance for post-neonatal mortality in children younger than 5 years was established throughout by a network of 26 000 local reporters who notified deaths in their community. The families were then visited at home by study staff to confirm details and complete a verbal autopsy. Surveillance for severe malaria and other conditions was strengthened in 18 sentinel hospitals serving part of the study area and maintained for 46 months. Uptake of RTS,S and other vaccines was monitored by the Expanded Programme on Immunisation in each country and independently through three household coverage surveys, at baseline, and at about 18 months and 30 months after introduction of RTS,S. The primary outcome of this impact evaluation was mortality due to any cause, except injury, in children eligible to receive three doses of RTS,S. Mortality rate ratios were estimated by comparing the ratio of deaths among vaccine-eligible age groups to deaths in non-eligible age groups between implementation and comparison areas. This evaluation is registered on ClinicalTrials.gov (NCT03806465) and is complete. FINDINGS: 158 clusters (66 in Ghana, 46 in Kenya, and 46 in Malawi) were selected and randomly assigned; 79 areas served as implementation areas and 79 as comparison areas. By the end of the 46-month evaluation period, 1 289 504 children had received the first dose of RTS,S, 1 158 850 had received the second dose, 1 068 039 had received a third dose, and 436 527 had received a fourth dose. Coverage assessed in 2022 was 82·8% (95% CI 80·7-84·9) for the first dose, 71·1% (68·8-73·5) for the third dose, and 39·9% (36·9-42·9) for the fourth dose. Excluding deaths due to injury, there were 5576 deaths in implementation areas versus 6152 in comparison areas in children eligible to have received the third dose of RTS,S, and 7534 versus 7044 deaths among non-eligible children. The mortality rate ratio was 0·87 (95% CI 0·77-0·97; p=0·016). INTERPRETATION: Introduction of the RTS,S malaria vaccine in routine immunisation programmes was associated with a significant reduction in mortality in young children, averting about one in eight deaths, in areas with moderate coverage of three doses of the vaccine and low uptake of the fourth dose. These results highlight the urgency to accelerate the deployment of malaria vaccines in areas of Africa where malaria continues to be a leading cause of child mortality. FUNDING: WHO; Gavi, the Vaccine Alliance; the Global Fund to Fight AIDS, Tuberculosis and Malaria; and Unitaid. TRANSLATIONS: For the French translation of the abstract see Supplementary Materials section.
13 May 2026
Read appraisal →Journal of chemical information and modeling
HLABrew for Human Leukocyte Antigen Class I-Presented Epitope Recognition and Mimotope Discovery
Accurate identification of human leukocyte antigen (HLA) class I-presented epitopes is essential for developing personalized vaccines and immunotherapies. Here, we present HLABrew, a unified deep learning framework for HLA class I epitope prediction and allele-specific mimotope design. By integrating the Transformer, variational autoencoder, and dual cross-attention, HLABrew achieves state-of-the-art performance with hierarchical and allele-aware representations. HLABrew accurately deconvolves multiallelic immunopeptidomics data to recover allele-specific binding motifs and expand epitope coverage. Leveraging its generative capacity, HLABrew further designs mimotopes guided by learned peptide-HLA binding preferences, with the potential to enhance antigen presentation and provide candidates for downstream immunogenicity evaluation.
13 May 2026
Read appraisal →Vaccine
The immune response of the mRNA vaccine CS-2034 as a heterologous booster before and after breakthrough infection: A follow-up study.
BACKGROUND: The emergence of highly mutated SARS-CoV-2 variants challenges vaccine protection. Evaluating long-term immune protection from boosters is crucial. The experiment compares neutralizing antibody dynamics and ACE2-RBD binding inhibition induced by mRNA and inactivated vaccine boosters, and assesses the impact of breakthrough infections and age on immune responses. METHODS: This study is based on a previous randomized, double-blind, parallel controlled trial. Healthy participants aged ≥18 who had received ≥3 inactivated COVID-19 vaccine doses. Volunteers (32 aged 18-59 and 32 ≥ 60) were stratified by age and vaccine type (24 mRNA, 8 inactivated in each age group). Pregnant women, those with severe chronic diseases or a history of allergies are excluded. Neutralizing antibodies were measured via microneutralization assay, and ACE2-RBD binding inhibition by high-sensitivity electrochemiluminescence. The study assessed changes in antibody levels and ACE2-RBD binding inhibition pre- and post-infection across age groups to evaluate vaccine efficacy and durability. (Registed number: ChiCTR2200064575). RESULTS: The neutralizing antibody titers from mRNA vaccine showing stronger and more consistent responses against the original strain and variants like XBB and BA.5. After breakthrough infections, mRNA-vaccinated individuals show a significant and lasting boost in antibodies, while the increase in inactivated vaccine recipients is modest. By age, mRNA-vaccinated people over 60 experience a faster antibody decline post-vaccination, whereas the inactivated vaccine group sees an initial rise at three months before declining. For ACE2-RBD binding inhibition, mRNA vaccines maintain higher early-phase rates, while inactivated vaccines show a delayed rise at three months followed by decline. CONCLUSIONS: mRNA vaccines induce stronger neutralizing antibodies and broader immunity than inactivated vaccines. Breakthrough infections boost antibody levels more in mRNA recipients than in inactivated vaccine recipients. Antibody decline is faster with mRNA vaccines in people over 60, while inactivated vaccines show a modest but weaker antibody increase against variants in the elderly.
13 May 2026
Read appraisal →Journal of ethnopharmacology
Moxibustion with Artemisia argyi H.Lév. & Vaniot in rheumatoid arthritis animal models: A meta-analysis linking clinical efficacy to inflammasome and cytokine signaling mechanisms
ETHNOPHARMACOLOGICAL RELEVANCE: Moxibustion, a traditional Chinese healing method, uses mugwort (Artemisia argyi H.Lév. & Vaniot) to apply heat to specific points, treating conditions like "Bi Zheng", which is akin to rheumatoid arthritis (RA). According to traditional theory, its therapeutic actions are attributed to warming the meridians and regulating the flow of Qi and blood. AIM OF THE STUDY: To quantitatively evaluate the therapeutic efficacy of moxibustion and to map its anti-arthritic mechanisms in animal models of RA. MATERIALS AND METHODS: The protocol was registered with PROSPERO (CRD42024503829) and reported according to PRISMA 2020. Eight databases were searched through 28 July 2025 for randomized controlled animal studies comparing moxibustion with the control in RA models. The primary outcome was arthritis severity, assessed by the arthritis index, paw volume, and histopathological score. Secondary endpoints included serum or tissue levels of pro-inflammatory cytokines (IL-1β, TNF-α, IL-6), immunomodulatory cytokines (IL-10, IL-4), and key signaling proteins (NF-κB, NLRP3, TLR4, MyD88). The SYRCLE tool was used to assess the risk of bias. RESULTS: Seventy-three studies were included. Meta-analysis showed that moxibustion significantly reduced arthritis severity (arthritis index: SMD -3.72, 95% CI -4.25 to -3.20; paw volume: SMD -4.59, 95% CI -5.54 to -3.63; histopathological score: SMD -2.24, 95% CI -2.80 to -1.67). Moxibustion also lowered the levels of pro-inflammatory cytokines: IL-1β (SMD -3.52, 95% CI -4.19 to -2.86), IL-6 (SMD -3.17, -4.17 to -2.16), and TNF-α (SMD -3.38, -3.97 to -2.79) and suppressed key signaling pathways, including NF-κB (SMD -2.29, 95% CI -3.20 to -1.37), NLRP3 (SMD -1.74, 95% CI -2.49 to -0.99), TLR4 (SMD -6.72, 95% CI -12.54 to -0.90), and MyD88 (SMD -9.16, 95% CI -15.28 to -3.04). CONCLUSION: This meta-analysis suggests that moxibustion alleviates arthritis severity and histopathological damage in RA animal models, potentially through modulating inflammatory networks and inhibiting key pathways such as NF-κB and NLRP3. These findings provide preclinical evidence supporting the rationale for future clinical investigation of moxibustion as a potential adjunct therapy for RA.
13 May 2026
Read appraisal →Vaccine
Factors influencing rabies vaccines immunogenicity during post-exposure prophylaxis: a systematic literature search and meta-analysis
BACKGROUND: Rabies post-exposure prophylaxis (PEP) requires timely appropriate wound management and vaccination (including concomitant rabies immunoglobulin [RIG], depending on vaccination history and wound severity) to ensure rapid increases in rabies virus neutralizing antibody (RVNA) titers, a surrogate marker of protection. In this systematic review and meta-analysis, we assessed factors influencing the immunogenicity of rabies vaccines administered as PEP. METHODS: PubMed, Embase, and The Cochrane Library were systematically searched for randomized controlled trials published in English, French, Spanish, or Portuguese from January 1, 1983 to March 28, 2022 reporting the immunogenicity of rabies vaccines, specifically rabies human diploid cell vaccine (Imovax Rabies), purified Vero cell rabies vaccine (Verorab), and purified chick embryo cell rabies vaccine (RabAvert/Rabipur), as part of PEP in healthy individuals. Pooled RVNA geometric mean titers (GMTs) and seroconversion rates at Day 14 (D14) post-vaccination, determined by rapid fluorescent focus inhibition test, were estimated using random effects meta-analyses. RESULTS: We identified 1040 studies, of which 67 (9689 participants across 140 intervention groups) were included. The pooled RVNA GMT across all vaccines at D14 post-vaccination was 8.19 (95% CI: 6.73-9.98) and did not differ significantly by vaccine, administration route, or RIG use; however, there were significant interlaboratory differences. Meta-regression analysis, including titration year, demonstrated a negative association with log-transformed RVNA GMTs, equating to a 4.18% reduction (95% CI: -5.89 to -2.44) in log-transformed GMTs per year during the period assessed. Across all vaccines assessed, the pooled seroconversion rate by D14 post-vaccination was 98% (95% CI: 97-98; n = 7023; I2 = 64%) and was not impacted by vaccine, administration route, RIG use, test laboratory, or titration year. CONCLUSIONS: Although RVNA GMTs appear to have decreased by titration year, there was no clinically meaningful impact on immunogenicity, and the three licensed rabies vaccines assessed are expected to provide similar protection.
13 May 2026
Read appraisal →mAbs
Machine learning predictions of IgG1 and IgG4 self-association and high-concentration solution properties
To meet the widespread demand for subcutaneous delivery of antibody therapeutics, candidates with low viscosity, high solubility, and/or low aggregation propensity in concentrated formulations must be identified. Moreover, early identification of candidates with low self-association increases the likelihood of success at later stages of the development process. Here, we experimentally profile the self-association behavior of a panel of clinical-stage antibodies as a function of pH, excipient content, and antibody isotype. We find that acidic formulations (pH 5) with proline (200 mM) are most effective at suppressing self-association for both IgG1 and IgG4 variants. Moreover, our self-association measurements are correlated with antibody viscosity measurements and inversely correlated with antibody recovery after their concentration using membrane filters. Notably, we developed interpretable machine learning-based classifier and regressor models for predicting IgG1 and IgG4 self-association and demonstrated that they identify antibodies with favorable high-concentration properties. These findings are expected to improve the antibody development process by facilitating the identification of drug-like molecules during their discovery and optimization.
13 May 2026
Read appraisal →Vaccine
Effect of time-of-day vaccination on the antibody response to mRNA and protein COVID-19 vaccine in adults
Time-of-day vaccination has been suggested as a feasible method to boost COVID-19 vaccine immunogenicity particularly in high-risk groups. However, several studies report inconsistent findings. We explored if time-of-day vaccination influences antibody responses to a fourth dose of mRNA (Moderna bivalent vaccine; mRNA-1273.214/mRNA-1273.222) or protein (Novavax; NVX-CoV-2373) COVID-19 vaccine as part of a randomised controlled trial (RCT) in Melbourne, Australia. Furthermore, we assessed if time-of-day vaccination effects differed by vaccine type or sex. At day 28 post-vaccination, antibody responses to all SARS-CoV-2 variants tested were higher for morning compared to afternoon vaccination in the Moderna group. Males in the Moderna group responded with higher antibodies to all SARS-CoV-2 variants tested after morning vaccination while responses in females were unaffected by time-of-day vaccination. Time-of-day vaccination had no effect on the response to Novavax, regardless of sex. Larger randomised trials are needed to confirm these findings to optimise vaccine timing strategies.
13 May 2026
Read appraisal →Vaccine
Effects of candidate vaccines against Zika virus infection: A systematic review of the clinical trials
INTRODUCTION: The 2015-2016 Zika virus (ZIKV) pandemic revealed a pathogenic potential, including Guillain-Barré syndrome and Congenital Zika Syndrome (CZS). Despite the decline in incidence, the potential for future circulation and the absence of specific antivirals underscore continued scientific interest in prophylactic vaccine development. OBJECTIVE: To synthesize evidence from clinical trials regarding the safety and preliminary immunogenicity of current ZIKV vaccine candidates. METHODS: This systematic review followed PRISMA guidelines (CRD420251056463). Searches were performed in MEDLINE, Embase, Web of Science, SciELO, and LILACS for clinical trials published between 2015 and 2025. Risk of bias was assessed using the Cochrane RoB 2 tool. RESULTS: Ten Phase 1 clinical trials were included, evaluating four platforms: inactivated virus (ZPIV, TAK-426, VLA1601), DNA (GLS-5700, VRC5283), mRNA (mRNA-1325, mRNA-1893), and viral vector (Ad26.ZIKV.001). All candidates demonstrated acceptable safety profiles, with predominantly mild-to-moderate and transient adverse events (e.g., injection site pain, fatigue, and headache); no vaccine-related serious adverse events were reported. Most platforms induced robust neutralizing antibody responses. Specifically, TAK-426 showed immune persistence for up to two years, while mRNA-1893 maintained responses for 13 months. The viral vector vaccine (Ad26.ZIKV.001) achieved 100% seroconversion with a single dose. Previous orthoflavivirus exposure did not significantly hinder vaccine-induced immunogenicity. Most studies presented a low risk of bias. CONCLUSIONS: ZIKV vaccine candidates across diverse technological platforms are safe and highly immunogenic. The evidence of long-term durability and the success of single-dose or mRNA regimens support the progression of the most promising candidates to Phase 2/3 trials.
12 May 2026
Read appraisal →Journal of ethnopharmacology
Anti-inflammatory properties of Dendrobium: A systematic review of pharmacological mechanisms
ETHNOPHARMACOLOGICAL RELEVANCE: In Traditional Chinese Medicine (TCM), Dendrobium species have long been used to alleviate various inflammatory conditions, particularly those characterized by Yin deficiency with internal heat and stomach deficiency-heat, including impaired fluid production, stomach Qi dysfunction, and poor appetite. The inflammatory response is regulated by multiple signaling pathways that drive disease pathogenesis, making these pathways promising targets for anti-inflammatory therapy. Medicinal Dendrobium, enriched with anti-inflammatory bioactive constituents, exhibits substantial systemic anti-inflammatory activity. Its growing research interest stems from favorable properties such as low toxicity, broad therapeutic efficacy, and minimal risk of drug resistance. AIM OF THE STUDY: Medicinal Dendrobium and its bioactive constituents have demonstrated significant anti-inflammatory properties, underscoring their pharmacological potential. Nevertheless, substantial efforts remain an urgent priority to advance the translation of basic research findings into clinical applications. Therefore, pharmacological studies published within the past six years were systematically reviewed to elucidate the mechanisms by which Medicinal Dendrobium and its bioactive constituents modulate inflammatory processes, thereby evaluating their potential as multi-targeted natural anti-inflammatories. This will facilitate the translation of anti-inflammatory research on medicinal Dendrobium from basic research to clinical investigation, thereby laying a solid foundation for its eventual clinical application in managing inflammatory diseases. MATERIALS AND METHODS: A literature search and screening strictly followed the PRISMA 2020 guidelines and employed a predefined Boolean strategy. A comprehensive search was conducted across Web of Science, PubMed, Elsevier, ScienceDirect, Scopus, CNKI, Wanfang Data, Baidu Scholar, and Google Scholar. No language restrictions were applied; this review includes key findings from Chinese-language literature. The predefined keywords included "Dendrobium," "Shihu," "bioactive constituents," "anti-inflammatory," "cytokines," "signaling pathways," as well as their corresponding Chinese terms. Taxonomic validation was conducted using the World Flora Online (http://www.worldfloraonline.org) and the Medicinal Plant Names Services (http://mpns.kew.org) databases. RESULTS: Eight Medicinal Dendrobium species and their bioactive constituents-such as polysaccharides, alkaloids, flavonoids, bibenzyls, polyphenols and stilbenoids-exert anti-inflammatory effects by modulating multiple signaling cascades, including NF-κB, MAPK/NF-κB, TLR4/NF-κB, PI3K/AKT, Nrf2/HO-1, JAK/STAT, and AMPK/SIRT1 pathways, indicating their multi-target therapeutic potential for inflammatory diseases. This review further underscores the innovative role of Dendrobium in regulating these pathways and its potential for integration with conventional pharmacological treatments, supporting its synergistic use in precision medicine. CONCLUSIONS: Medicinal Dendrobium represents a promising ethnopharmacological resource, exhibiting broad-spectrum anti-inflammatory effects through multi-target, multi-pathway, and multi-organ mechanisms. To advance its modernization, therapeutic development, and clinical translation, future research should prioritize several key directions: establishing standardized quality control system and prioritizing the structures of core bioactive constituents; applying a multi-omics approach combined with artificial intelligence-assisted modeling, network pharmacology and advanced molecular imaging techniques to systematically map its systemic anti-inflammatory regulatory network; strengthening systematic pharmacokinetic and bioavailability studies; exploring precision and synergy delivery formulations; and conducting rigorous assessments of safety profiles and side-effect management. By focusing on these priorities, research can further elucidate the systemic anti-inflammatory mechanisms of medicinal Dendrobium, thereby bridging its traditional use with contemporary precision medicine, and supporting integrated interventions for complex inflammatory diseases.
12 May 2026
Read appraisal →Vaccine
Effect of neonatal BCG vaccination on oral herpes in early childhood: A nested study within a randomised controlled trial
BACKGROUND: Bacille Calmette-Guérin (BCG) vaccine, primarily used against tuberculosis, has off-target (non-specific) immunomodulatory effects, including potential protection against recurrences of latent herpes simplex virus (HSV) infections. Recurrent episodes of HSV herpes labialis (oral 'cold sores') affect a substantial proportion of the population, including young children, and there is currently no effective preventive intervention. METHODS: This pilot study, nested within the MIS BAIR randomised controlled trial (RCT), explored whether neonatal BCG vaccination, compared with no BCG vaccination, reduces the incidence and recurrence of herpes labialis during the first five years of life. FINDINGS: Among the 563 children (44% of 1272 randomised) who completed the 5-year follow-up, children in the BCG group were less likely to develop herpes labialis, compared with the control group (5% vs 8%; 38% relative risk reduction, p = 0.1). Risk of recurrence was significantly lower in the BCG group (33% vs. 71%; 53% relative risk reduction, p = 0.02). BCG-vaccinated children also reported a later onset of symptoms and a reduced impact on fluid intake during episodes. INTERPRETATION: This exploratory study suggests a protective role for neonatal BCG against HSV in children. However, its limitations, including its sample size, incomplete follow up and lack of virological confirmation, mean further studies are needed to confirm these findings. FUNDING: National Health and Medical Research Council (NHMRC) of Australia and others, as detailed in the acknowledgements.
12 May 2026
Read appraisal →Immunologic research
An integrated AI-driven vaccine design process: a systematic review of workflows from generative design to translational prediction
Traditional vaccine development faced significant hurdles, including lengthy timelines and high costs, which hindered rapid responses to pathogens. Although the emergence of AI offered transformative potential, the necessity for a fully integrated workflow was often overlooked in studies focusing on individual tools. This review addressed a critical gap by synthesizing AI technologies across the vaccine design process, focusing on the integrated workflow from antigen discovery to clinical translation. A systematic framework was required to connect disparate tools and ensure seamless transitions. Consequently, this study provided a comprehensive roadmap for pandemic preparedness and vaccine discovery. A systematic analysis based on the PRISMA framework (2015-2024) was conducted, and 19 landmark articles were reviewed.It was demonstrated that the paradigm shift from predictive to generative AI offered unprecedented opportunities for developing novel antigens and adjuvants with superior immunogenicity. Synthesis of the literature revealed rapid progress toward sophisticated deep learning. Transformer models and Protein Language Models emerged as dominant for epitope prediction, while AlphaFold2 became the standard for structural modeling. The advent of generative AI for de novo antigen design represented the leading edge of the discipline. Additionally, AI-enhanced molecular dynamics and digital twin simulations accelerated clinical validation and manufacturing scalability. The "Integrated AI Workflow for Vaccine Design and Development" was emphasized as a comprehensive system and a prerequisite for sustainable innovation. Overall, this analysis served as a strategic roadmap for utilizing AI as a transformative framework for next-generation vaccine discovery and pandemic preparedness.
12 May 2026
Read appraisal →Journal of neuro-oncology
cGAS-STING agonists in preclinical glioblastoma animal models: a systematic review of tumor microenvironment modulation and survival outcomes
BACKGROUND/PURPOSE: Glioblastoma (GBM) is characterized by an immunosuppressive tumor microenvironment and poor responsiveness to immune checkpoint blockade, driving interest in cGAS-STING pathway activation to stimulate antitumor immunity. We performed a systematic review of preclinical in vivo studies evaluating STING agonists in glioblastoma, with emphasis on immune microenvironment effects and survival outcomes. METHODS: A systematic review of PubMed, Cochrane, and Embase was conducted through February 2025 following PRISMA guidelines. Studies were included if they evaluated STING agonists in live animal models of GBM and reported survival outcomes or tumor microenvironment changes. Two reviewers independently screened studies and extracted data. Risk of bias was assessed qualitatively based on study design and reporting characteristics. Given heterogeneity in models, treatments, and outcomes, results were synthesized descriptively. RESULTS: Fourteen studies met the inclusion criteria, spanning synthetic and natural cyclic dinucleotides and non-cyclic STING agonists. Across diverse delivery methods, including intracranial injection, hydrogels, and nanoparticle systems, STING agonists were associated with increased CD8 + T-cell and NK cell infiltration and repolarization of tumor-associated macrophages toward pro-inflammatory phenotypes. Several studies reported prolonged survival, including long-term tumor clearance in select models. Combination therapies with immune checkpoint inhibitors or radiotherapy showed synergistic effects in some studies. CONCLUSIONS: STING agonists can enhance anti-tumor immune responses and prolong survival in preclinical GBM models by promoting cytotoxic lymphocyte recruitment and remodeling the tumor-associated myeloid landscape. However, translation remains challenging due to limitations of current models, the limited clinical traction STING modulation has thus far achieved in other cancer types, incomplete understanding of cell-type-specific STING activation in the brain, and the possibility that sustained STING signaling may drive maladaptive inflammation rather than durable antitumor immunity.
12 May 2026
Read appraisal →Cancer immunology, immunotherapy : CII
Artificial intelligence-powered H&E-based quantification of spatial tumor-infiltrating lymphocyte distribution identifies prognostic immune niches in colorectal cancer
PURPOSE: The prognostic significance of tumor-infiltrating lymphocytes (TILs) in colorectal cancer (CRC) is well established; however, existing approaches inadequately capture their spatial distribution. We investigated the prognostic implications of TIL spatial distribution in CRC using an artificial intelligence (AI)-based method. METHODS: A total of 202 patients with stage II-III CRC were included. TIL densities in intratumoral (iTIL) and stromal (sTIL) regions were quantified using AI-based analysis of hematoxylin and eosin (H&E)-stained images. Based on proximity to the tumor-stromal border (TSB), TILs were subclassified into core iTIL, bounding iTIL, bounding sTIL, and outermost sTIL. Immunoscore was calculated from CD3+ and CD8+ T-cell densities in the tumor center and invasive margin. RESULTS: Correlations between AI-based and pathologist assessments (iTIL: r = 0.57; sTIL: r = 0.70) were comparable to inter-pathologist correlations (iTIL: r = 0.47; sTIL: r = 0.70). In univariate Cox regression analysis, bounding iTIL, bounding sTIL, and outermost sTIL were significantly associated with recurrence-free survival (RFS), whereas core iTIL was not. Composite TIL and TSB scores were developed by incorporating the prognostically significant regions. In multivariable analysis, the TIL score (p = 0.001), TSB score (p < 0.001), and Immunoscore (p < 0.001) independently predicted RFS. In microsatellite instability-high tumors, only the TSB score remained prognostically significant. CONCLUSION: AI-powered spatial analysis of TILs, particularly the TSB score, demonstrated prognostic performance comparable to conventional Immunoscore, thereby supporting the value of spatial immune profiling and AI-driven analysis of H&E-stained slides for improved risk stratification in CRC.
11 May 2026
Read appraisal →Molecular pharmaceutics
mRNASyner: An Integrative Framework for Full-Length mRNA Sequence Optimization via Multimodule Synergistic Design
Messenger RNA (mRNA) technology holds great promise in biomedicine; however, its therapeutic efficacy relies heavily on translation efficiency and the in vivo stability of mRNA sequences, both of which are governed by dynamic interactions between the coding and noncoding regions. Existing optimization approaches typically focus on individual sequence components and lack the capacity for global, synergistic optimization. Moreover, their performance is often limited when processing long sequences or supporting iterative sequence refinement. To overcome these challenges, we propose a unified and interpretable in silico framework for full-length mRNA sequence design, integrating CDS optimization, UTR generation, and degradation modeling. In silico case studies based on respiratory syncytial virus (RSV) vaccine design demonstrated that mRNASyner achieved a favorable balance between translational accessibility and structural stability. mRNASyner thus enables the design of full-length mRNA sequences, supports long-sequence optimization, and offers a novel solution for the development of personalized mRNA therapeutics.
11 May 2026
Read appraisal →Annals of laboratory medicine
Evaluation of the Performance of Advanced Large Language Models in Laboratory Medicine Using Residency Examinations
BACKGROUND: Recent advancements in large language models (LLMs) have accelerated their integration into clinical domains, including laboratory medicine. The performance of LLMs in answering board-level laboratory medicine questions has not been comprehensively evaluated. Given the importance of diagnostic accuracy in this field, rigorous and objective evaluations of LLM capabilities are essential. METHODS: We assessed 12 LLMs from OpenAI, Anthropic, and Google using 320 Korean Residency Examination questions (2021-2024) spanning six laboratory medicine subspecialties. Standardized prompts were provided via their application programming interfaces under deterministic settings (temperature=0). Questions were administered thrice to assess response reproducibility. Outputs were compared with validated answers and analyzed for accuracy, reasoning quality, and error typology. RESULTS: Google's Gemini 2.0 Pro achieved the highest accuracy (80.0%), followed by OpenAI's GPT-4.5 (77.2%) and Anthropic's Claude 3.7 Sonnet (74.1%). Accuracy decreased as the difficulty of questions increased (78.0% for easy vs. 45.1% for challenging). Subspecialty performance varied. Al models underperformed on questions on transfusion medicine (mean accuracy: 38.8%), primarily because of limitations in domain-specific and regional knowledge representations. Incorrect answers primarily resulted from reasoning errors. Reproducibility exceeded 95% for most models; however, some residual non-determinism appeared even with greedy decoding (temperature=0). CONCLUSIONS: LLMs demonstrated substantial potential for integration into laboratory medicine, particularly in clinical chemistry and immunology. Performance inconsistencies (particularly for high-difficulty questions) and knowledge gaps (notably for transfusion medicine) highlight the necessity for further development-potentially including domain-specific fine-tuning and retrieval-augmented generation integration-and robust expert oversight before clinical application.
6 May 2026
Read appraisal →Journal of proteome research
NetMHCIIphosPan: A Machine Learning Tool for Predicting HLA Class II Antigen Presentation of Phosphorylated Peptides
Phosphorylated peptides presented by human leukocyte antigen (HLA) class II molecules play pivotal roles in immune regulation, yet their characterization and prediction remain challenging due to data noise and limited HLA coverage. Here, we introduce NetMHCIIphosPan, a prediction method for HLA-II antigen presentation of phosphorylated peptides, developed using mass spectrometry (MS)-based immunopeptidomics data sets. Employing a refined peptide identification workflow, we reanalyzed earlier HLA-II phospholigand data sets and trained predictive models, achieving superior performance compared to models trained on the original data. Binding motif analysis revealed that HLA-specific preferences for phospholigands closely aligned with those of unmodified ligands. Incorporating unmodified ligands into training further enhanced predictive accuracy, particularly for HLA-DP and HLA-DQ molecules. NetMHCIIphosPan outperformed existing tools, such as NetMHCIIpan-4.3 and MixMHC2pred-1.3, for prediction of HLA antigen presentation of phosphorylated peptides, demonstrating robustness and utility. This work establishes NetMHCIIphosPan as a state-of-the-art tool for understanding the HLA-II phospholigandome, with potential applications in immunotherapy and vaccine design.
4 May 2026
Read appraisal →Computer methods in biomechanics and biomedical engineering
Multiple instance learning method based on convolutional neural network and self-attention for early cancer detection.
Early cancer detection using T-cell receptor sequencing (TCR-seq) and multiple instances learning methods has shown significant effectiveness. We introduce a multiple instance learning method based on convolutional neural networks and self-attention (MICA). First, MICA preprocesses TCR-seq using word vectors and then extracts features using convolutional neural networks. Second, MICA uses an enhanced self-attention mechanism to extract relational features of instances. Finally, MICA can extract the crucial TCR-seq. After cross-validation, MICA achieves an area under the curve (AUC) of 0.911 and 0.946 on the lung and thyroid cancer datasets, which are 7.1% and 2.1% higher than other methods, respectively.
4 May 2026
Read appraisal →Journal of computer-aided molecular design
Resolving the ambiguous binding site of quercetin at the calcineurin subunit junction using funnel metadynamics with deep learning collective variables
Calcineurin represents a prominent target for immunosuppressive drugs, where conventional macrocyclic inhibitors utilize an immunophilin-dependent mechanism for their inhibition but are consequently hindered by adverse effects and variable pharmacokinetics. The flavonoid quercetin has been shown to inhibit calcineurin in a non-competitive, immunophilin-independent manner, but its exact binding site remains ambiguous at the junction between calcineurin subunits A and B, with the open solvent-exposed nature of this region proving challenging to model. In this study, we employ funnel metadynamics with collective variables derived from a deep learning model to identify the binding site of quercetin. A selective strategy using multiple simulations with stricter funnel definitions and a smaller number of carefully chosen descriptors for model training proved more effective than a broad-based approach. These simulations were able to effectively distinguish the binding site of quercetin from three experimentally suggested sites, with a calculated free energy of binding of -8.36 ± 0.60 kcal/mol showing excellent agreement with experiment. Ligand-tryptophan distances similarly corroborated measurements from FRET assays with a r2 of 0.85. The corresponding binding pose showed that quercetin inserts itself into a channel between Arg122, Gly123, Tyr124 on one side and Phe160, Thr161, and Asn345 on the other, stabilizing its binding through a network of hydrogen bonds. The findings of this study provide insights into the modelling of challenging binding sites and ligands using deep learning driven metadynamics simulations and provide the foundations for rational development of immunophilin-independent inhibitors of calcineurin.
3 May 2026
Read appraisal →PLoS computational biology
MsgaBpred: A B-cell epitope predictor integrating AlphaFold3-predicted structures with multi-scale GCNs and pre-trained language model ESM-C
Accurate prediction of B-cell epitopes plays a key role in facilitating advancements in vaccines, therapeutics, and diagnostics. In contrast to labor-intensive experimental approaches, computational strategies provide a more economical and efficient means of identifying potential epitopes. Existing methods are often limited by their reliance on experimentally resolved protein structures or by the use of lower-accuracy predicted structures. Sequence-based approaches, while fast, largely fail to capture the 3D spatial context essential for conformational epitopes. With the breakthroughs achieved by AlphaFold3 in predicting protein structures, we present MsgaBpred, the model to apply AlphaFold3-derived structures to B-cell epitope identification. Given only a protein sequence, our model employs a multi-scale graph convolutional network and additive attention to capture complex structural dependencies without relying on experimentally determined structures. The multi-scale design allows for effective modeling of both local and global contexts by aggregating information across different neighborhood ranges. Additionally, we leverage ESM-C, a more expressive protein language model than ESM-2, to enhance feature representation for B-cell epitope prediction. Extensive evaluations across multiple benchmark datasets demonstrate that MsgaBpred achieves competitive and robust performance; notably, it yields a statistically significant improvement in AUC compared to existing state-of-the-art methods. Moreover, the modular and scalable architecture of MsgaBpred holds promise for broader applications, including the structural analysis of other biomolecular entities such as nucleic acids and carbohydrates.
3 May 2026
Read appraisal →Journal of chemical information and modeling
Generative AI Uncovers Novel Chrebp/Txnip Axis Inhibitors with Potential Anti-inflammatory Activity
Type 2 diabetes is driven in part by metabolic inflammation, where activation of the Chrebp/Txnip axis promotes NLRP3 inflammasome assembly, leading to pancreatic β-cell dysfunction and pro-inflammatory cytokine release. Despite the therapeutic relevance of this pathway, the Chrebp-14-3-3 (regulatory-protein client) protein-protein interaction (PPI) remains largely underexplored, with only a limited number of small-molecule modulators reported to date. To address this gap, we developed an artificial intelligence-driven generative design framework for de novo discovery of selective PPI-targeting compounds. A conditional recurrent neural network (cRNN), implemented as a quantitative structure-property relationship-guided generative network (QSPR-GEN), was pretrained on a large, chemically diverse corpus to learn general SMILES syntax and structural priors, and subsequently fine-tuned on a curated, target-focused data set of approximately 5900 compounds, achieving high scaffold uniqueness (94.6%). Selectivity-oriented physicochemical descriptors were incorporated as conditional inputs to bias generation away from promiscuous chemotypes, while maintaining anchoring to a known active seed. Structure-based refinement was further applied by focusing on the noncanonical α-helical epitope unique to the Chrebp regulatory-protein interface, establishing a dual-layered strategy for selective PPI modulation. The integrated pipeline, combining virtual screening, molecular dynamics simulations, and MM/PBSA free-energy calculations, prioritized lead candidates with favorable binding energetics and pharmacokinetic profiles. In THP-1 macrophages under metabolic stress, the top candidate T7 markedly suppressed Txnip and NLRP3 expression, reduced IL-1β secretion, and attenuated pyroptotic cell death, outperforming a reference inhibitor. Collectively, this study presents a robust computational framework for the inverse design of challenging PPIs and demonstrates its utility through the identification and experimental validation of mechanistically precise lead compounds, exemplified by T2 and T7.
2 May 2026
Read appraisal →Science advances
Repertoire-scale antibody structural prediction informs therapeutic design
We present AF3-TurboAb, a scalable framework that makes a repertoire-scale antibody-antigen complex structural decoding routine for antibody engineering. By eliminating preprocessing bottlenecks, AF3-TurboAb enables end-to-end complex modeling in 0.5 minutes per seed on a single GPU while preserving near-experimental interface fidelity, as validated on ~1000 posttraining Protein Data Bank (PDB) benchmarks and 12 experimentally determined cryo-electron microscopy nanobody-antigen structures. Applying this capability to 275,371 immunization-derived antigen-specific nanobodies produced 28,013 high-confidence complex predictions, substantially expanding the structural landscape of antibody recognition. The resulting atlas reveals hundreds of previously unmapped epitopes, extensive coverage of solvent-exposed surfaces, and recurrent affinity hotspots enriched in aromatic and charged residues. Despite wide sequence diversity, we observe structural convergence at shared epitopes and consistent physicochemical and geometric features that complement and extend existing PDB entries. We demonstrate translational utility by (i) designing durable (escape-proof), multiepitope neutralizers against highly evolved viruses, (ii) identifying cross-species and glycoform-specific binders to a cancer checkpoint, and (iii) enabling near-real-time in silico binder triage. The models and metadata will be shared for community use, establishing repertoire-scale structural decoding as a practical design modality that transforms the scale and speed of structure-guided antibody engineering.
27 Apr 2026
Read appraisal →Clinical chemistry and laboratory medicine
Serum GFAP as a biomarker for progression in multiple sclerosis: assay comparison and a large reference database of healthy controls
OBJECTIVES: Compare Elecsys (Roche) and Simoa (Quanterix) immunoassays for serum glial fibrillary acidic protein (GFAP) using our reference database and Z scores, and evaluate their prognostic value for progression independent of relapse activity (PIRA) in multiple sclerosis (MS). METHODS: Platform correlation was assessed in 612 samples from healthy controls (n=188; median [interquartile range, IQR] age 45.1 [36.4-61.7] years) and people with MS (n=424; 45.3 [35.2-53.9] years). Elecsys values were converted to Z scores via Passing-Bablok-derived regression and validated in fingolimod (n=414), and B-cell depleting therapy (BCDT; n=353) cohorts. Z scores and hazard ratios (HRs) for time-to-PIRA were compared using Cox regression. RESULTS: GFAPSimoa and GFAPElecsys measurements were correlated (r=0.94), with Elecsys values ∼54 % lower (GFAPElecsys, ng/L=2.847 [95 % confidence interval, CI: 1.335 - 4.98] + 0.457 [0.434 - 0.478] * GFAPSimoa, ng/L). In univariable Cox models, GFAPSimoa and GFAPElecsys Z scores were associated with time-to-PIRA in both validation cohorts. In multivariable Cox models, higher GFAPSimoa Z scores were associated with shorter time-to-PIRA in fingolimod cohort (HR: 1.27 [95 % CI 1.08 - 1.50], p=0.0031) and trended toward significance in BCDT (1.18 [0.99 - 1.41, p=0.0693). In contrast, GFAPElecsys Z scores were associated with time-to-PIRA in both cohorts (fingolimod: 1.27 [1.09 - 1.48], p=0.0023; BCDT: (1.19 [1.00 - 1.40], p=0.0487). CONCLUSIONS: Serum GFAP measured by Elecsys shows a comparable association with time-to-PIRA as Simoa, and GFAPSimoa Z scores can be successfully bridged to GFAPElecsys Z scores, supporting Elecsys`s potential for clinical implementation.
25 Apr 2026
Read appraisal →Journal of medicinal chemistry
Automated Molecular Design in BRADSHAW, Applied to the Optimization of ERAP1 Inhibitors
Generative design and machine learning are increasingly prevalent in medicinal chemistry. To pilot the comprehensive use of automated molecular design on a project, the BRADSHAW platform was used to optimize a series of inhibitors of Endoplasmic Reticulum Aminopeptidase 1 (ERAP1), an emerging target in cancer immunotherapy and autoimmune diseases. Through four consecutive iterations applying in silico molecular generation, property prediction and filtering, we conducted a multiparameter optimization of potency, physicochemical properties and pharmacokinetics. Continuous refinement of Machine Learning (ML) models led to improved scoring accuracy and compound quality, culminating in identification of in vitro and in vivo tool molecules. We also discuss our reflections on the pilot and integration of automated design into medicinal chemistry projects, including observations of the human factors resulting from increased use of computational design, and recommendations for future projects.
25 Apr 2026
Read appraisal →Antonie van Leeuwenhoek
Faecalibacterium prausnitzii and Akkermansia muciniphila: driving the multiple sclerosis-a systematic review
The gut microbiota (GM) is a complex microbial ecosystem, and its alteration contributes to the development of several diseases including multiple sclerosis (MS). Progressive research concerning neurodegenerative diseases and GM reveals that GM dysbiosis has been linked to fostering the development and progression of MS. Among existing bacteria, F.prausnitzii and A.muciniphila are key species implicated in this disease. Thus, the present study systematically reviewed and synthesized the research on the involvement of F. prausnitzii and A. muciniphila in MS patients versus healthy individuals. We systematically searched PubMed, MEDLINE, EMBASE, and Web of Science databases for relevant published articles from January 2010 till January 2023. Out of 400 articles, 16 met the required criteria. The included research investigations originated from the US, Germany, Norway, Egypt, Iran, Brazil, China, the UK, and Romania. Most publications reported decreased levels of F. prausnitzii and increased levels of A. muciniphila in MS patients compared to controls. This review underscored the importance of the F. prausnitzii and A. muciniphila in MS, which could explain the chronic inflammation that characterizes this disease and not only help in understanding its etiology and progression but also open new avenues for the treatment strategies focusing on gut health. Moreover, understanding the role of F. prausnitzii and A. muciniphila could lead to novel biomarkers for early detection and progression monitoring MS.
25 Apr 2026
Read appraisal →Journal of neurology
Efficacy and safety of monoclonal antibodies in the treatment of relapsing remitting multiple sclerosis: a systematic review
INTRODUCTION: In relapsing-remitting multiple sclerosis (RRMS), conventional immunomodulatory and immunosuppressive therapies are widely used. However, in many cases, optimal control of inflammatory activity and disease progression is not achieved, which has led to the use of biological drugs such as monoclonal antibodies that act specifically on key components of the immune system. The aim was to evaluate the efficacy and safety of monoclonal antibodies compared to other drugs or placebo in adult patients with RRMS. METHODS: A systematic review was performed based on randomized, double-blind, phase III controlled clinical trials published between 2012 and 2025 in the PubMed, Cochrane Library, and Web of Science databases, assessing efficacy and safety in adult patients with RRMS. The review was carried out following the PICO methodology and PRISMA guidelines. RESULTS: A total of 11 studies were included, evaluating 5 monoclonal antibodies: alemtuzumab, daclizumab, ocrelizumab, ofatumumab, and ublituximab. These therapies showed superior efficacy compared to conventional treatments in reducing the annual relapse rate, MRI inflammatory activity and MRI activity, particularly in patients with highly active disease. However, effects on disability progression were heterogeneous across trials and not consistently significant. In addition, decreases in biomarkers of axonal damage were observed. Nevertheless, relevant adverse effects were identified, including infections, autoimmune reactions, hepatic and cutaneous toxicity, whose incidence varies depending on the drug, requiring close clinical monitoring. CONCLUSIONS: Monoclonal antibodies are an effective option in RRMS, with clinical and radiological benefits superior to those of conventional treatments. Their use requires individualized assessment and close follow-up due to the risk of adverse effects, especially in high-risk patients.
25 Apr 2026
Read appraisal →Cell reports methods
A high-speed attention network for MHC-bound peptide identification and 3D modeling
We developed SwiftMHC, an ultra-fast and accurate structure-based framework for peptide-MHC (pMHC) modeling and binding affinity prediction. Using task-specific deep learning trained on physics-derived synthetic data, SwiftMHC predicts pMHC binding affinities in 0.009 s per case on a single A100 GPU when running in batch mode, offering improved speed compared with leading sequence-based tools such as netMHCpan and MHCflurry while maintaining competitive accuracy. In addition, SwiftMHC generates all-atom 3D pMHC structures with a median Cα-RMSD of 1.32 Å against crystallographic benchmarks, matching or exceeding state-of-the-art methods such as AlphaFold2-finetune but at a lower computational cost. Optimized for HLA-A∗02:01 9-mer peptides but readily extensible to other alleles, SwiftMHC unites structural insight with high-throughput scalability to accelerate safe and effective epitope discovery in cancer immunotherapy.
24 Apr 2026
Read appraisal →The Journal of clinical endocrinology and metabolism
Secukinumab in Moderate-to-Severe Graves Orbitopathy: A Randomized, Double-Blind, Placebo-Controlled, Multicenter Study
CONTEXT: Interleukin (IL)-17, a key proinflammatory cytokine, drives inflammation and fibrosis in Graves orbitopathy (GO), and elevated IL-17 and Th17 cells correlate with disease activity and severity. OBJECTIVE: The ORBIT study aimed to evaluate the efficacy and safety of secukinumab, an IL-17A inhibitor, in individuals with active, moderate-to-severe GO. METHODS: A randomized, double-blind, placebo-controlled, parallel-group, multicenter trial was conducted. Adults with active, moderate-to-severe, non-sight-threatening GO randomly (1:1) received secukinumab 300 mg or placebo subcutaneously over a 16-week double-blind treatment period, followed by an additional 16-week open-label treatment phase for proptosis nonresponders. Safety parameters, thyroid-related hormones, and autoantibodies were also assessed. The primary end point was overall response of reduced Clinical Activity Score (CAS) of 2 or more points and a reduction of 2 mm or greater in proptosis from baseline without worsening in the fellow eye at week 16. RESULTS: Twenty-eight adult GO patients with a CAS of 4 or greater were enrolled (secukinumab, n = 14; placebo, n = 14). None in either the secukinumab or placebo group achieved an overall response at weeks 16 and 32, respectively, when all patients received open-label secukinumab. No clinically meaningful changes were observed in ophthalmic symptoms and signs, proptosis, lid aperture, eye muscle motility, CAS, and health-related quality of life either at week 16 or week 32. No meaningful effect on serum levels of thyroid-related hormones and antibodies was observed. Secukinumab was well tolerated, with mostly mild adverse events. Neither treatment-induced study discontinuation nor new safety signals were registered. CONCLUSION: Secukinumab did not show clinical efficacy vs placebo when treating patients with active, moderate-to-severe GO.
24 Apr 2026
Read appraisal →PloS one
Identification and clinical implications of immune-related hub genes in psoriasis
BACKGROUND: Psoriasis, a chronic inflammatory skin disease affecting 2-3% of the global population, is driven by dysregulated immune responses. Despite advancements in biologic therapies, treatment challenges persist due to high recurrence rates. This study aimed to identify immune-related hub genes and elucidate their clinical implications in psoriasis pathogenesis and therapy. METHODS: Multiple microarray datasets from psoriasis patients (GSE30999, GSE106992, GSE14905, GSE78097, and GSE117468) were obtained to identify immune-key genes by differential gene analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Subsequently, immune-related hub genes were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Protein-Protein Interaction (PPI) networks, with further validation through Gene Set Enrichment Analysis (GSEA) and Receiver Operating Characteristic (ROC) curves to assess exploratory within-sample discrimination. Pearson correlation analysis evaluated the relationship between hub genes, skin lesion severity, and treatment outcomes. The study also conducted immune infiltration by using the Cell-type Identification by Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm and identified potential therapeutic targets by the Drug-Gene Interaction Database (DGIdb). RESULTS: Thirty-one immune-related key genes were identified, and six hub genes (CLEC7A, CXCL1, IRF1, S100A12, S100A8, S100A9) were validated as central players in immune signaling pathways. These genes exhibited within-sample discrimination (AUC > 0.9) and correlated with disease severity and biological therapy efficacy. Immune infiltration analysis revealed increased activated memory CD4+ T cells and M1 macrophages in lesional skin, which was strongly associated with hub gene expression. Additionally, drug-gene interaction analysis identified potential therapeutic agents targeting these genes. CONCLUSION: This study identified six immune-related hub genes that were closely linked to the severity of psoriasis, the effectiveness of biological treatments, and infiltrated activated memory CD4+ T cells and M1 macrophages. Our findings elucidate a novel immune-related hub gene network in psoriasis and provide potential targets for the development and application of biologics.
23 Apr 2026
Read appraisal →Journal of hematology & oncology
Uncoupling toxicity from efficacy in donor selection for allogeneic hematopoietic cell transplantation: a retrospective cohort study using double machine learning
Haploidentical hematopoietic cell transplantation (HCT) offers potent graft-versus-tumor effects but is historically limited by higher non-relapse mortality (NRM) compared to matched unrelated (MUD) or related donors (MRD). To algorithmically decouple the competing risks of NRM and relapse, we analyzed 1,713 adult patients (MD Anderson discovery cohort) and 6,829 patients (registry replication cohorts) using a double machine-learning framework of Causal Survival Forests to estimate individualized treatment effects, while Random Survival Forests defined absolute prognostic risk. We found biological uncoupling of relapse and NRM: relapse was driven by disease biology, while NRM was governed by physiological reserve. Specifically, cardiovascular or cerebrovascular comorbidities acted as selective amplifiers of haploidentical toxicity-a "vascular penalty" that doubled mortality risk in the bootstrapped model (sub-distribution hazard ratio 2.09, 95% confidence interval 1.26-3.35). We developed a 3-factor nomogram (recipient age, vascular comorbidity, B-leader matching status) to identify an "Optimized Haploidentical" phenotype. Exploratory multivariable modeling suggested MUD consistently maximized predicted disease-free survival across all subgroups. Among haploidentical versus MRD comparisons, B-leader mismatch appeared to favor MRD across ages, while B-leader matched haploidentical donors in older patients (≥ 60 years) modeled near-equivalent DFS to MRD, representing a hypothesis-generating "zone of equivalence" requiring prospective validation.
22 Apr 2026
Read appraisal →Proceedings of the National Academy of Sciences of the United States of America
Making invisible excited-state structures of pro-interleukin-18 visible by combining NMR and machine learning
NMR spectroscopy is a powerful tool for studies of protein dynamics over timescales extending more than twelve orders of magnitude, with motion queried at many of the backbone and sidechain positions in the molecule of interest. NMR experiments can, in principle, provide atomic resolution descriptions of excited conformational states that are sparsely populated and transiently formed-i.e., invisible, and there are examples of such structures in the literature. However, in other cases, the NMR data are not sufficient for generating structural ensembles of rare and transient higher energy conformers of the protein of interest. One example is provided by the precursor form of the proinflammatory cytokine interleukin-18, pro-IL-18, studied here. Although NMR studies show that pro-IL-18 adopts two sparsely populated (<0.5%) and transiently formed (ms lifetimes) excited-state conformations in exchange with a highly populated ground state conformer and localize regions undergoing exchange to a pair of short β-strands that are preserved in at least one of the excited states, additional structural information is not forthcoming. Here, we develop a protocol whereby the NMR data are used to select alternative conformers of pro-IL-18 from ensembles predicted by the generative machine learning model AlphaFlow that are then evaluated through further NMR experiments. The method identifies distinct conformers that correspond to the pair of excited states reported by NMR, combining experiment with computation to characterize the pro-IL-18 energy landscape in ways that are not possible with either approach alone.
20 Apr 2026
Read appraisal →Nature communications
Donor-derived regulatory dendritic cell infusion and early immunosuppressive drug withdrawal in living-donor liver transplantation: a phase I/IIa trial
Operational tolerance (OT) following complete immunosuppression withdrawal (ISW) is rare ( ~ 13%) in eligible adult liver transplant recipients when initiated 1-2-years post-transplant. Regulatory dendritic cells (DCregs) promote transplant tolerance in pre-clinical models and attenuate immune effector cells in humans. Here, we completed a first-in-human phase I/IIa trial (2-year recruitment; 5 ± 0.5 years follow-up) to evaluate the feasibility, safety and preliminary efficacy of pre-emptive donor-derived DCreg (ddDCreg) infusion 7-days pre-transplant in 15 prospective living-donor liver recipients. Two patients were excluded from analysis for reasons unrelated to the study. ISW began one year post-transplant in candidates with a quiescent/permissive protocol biopsy. ddDCreg infusions were safe, reproducible, and well-tolerated. One-year post-transplant, 8/13 patients were eligible for ISW, 4 achieved complete ISW, 3 remained off all immunosuppression for >1 year. These 3 remained drug-free for 3.0 ± 0.17-years, reflecting a 37.5% OT rate in ISW-eligible recipients. Given the exploratory nature of this trial, additional studies to evaluate efficacy are needed. ClinicalTrials.gov registration number NCT03164265.
19 Apr 2026
Read appraisal →Stem cell reports
Cellular immunotherapy for COVID-19-induced acute respiratory distress syndrome: Results of the CIRCA-19 phase 1 safety and phase 2 randomized controlled trials
The ability of immunomodulatory mesenchymal stromal cells (MSCs) to improve COVID-19-associated acute respiratory distress syndrome (ARDS) in clinical trials is uncertain. We assessed whether freshly cultured umbilical cord (UC)-derived MSCs improved outcomes in patients with severe COVID-19 ARDS. We enrolled 37 patients with severe COVID-19 ARDS: 15 in the phase 1 dose escalation and open label extension studies (NCT04400032), and 22 patients in the phase 2b randomized clinical trial (NCT04865107). Delivery of up to 270 × 106 MSCs in three divided daily doses was well tolerated and resulted in qualitative improvement in all clinical outcomes. Furthermore, MSCs resulted in resolution of lymphopenia, consistent with an important immunomodulatory effect, with significant improvement in patient reported quality-of-life measures (SF-36) at 6 months pointing to possible durable clinical effects. These findings suggest a potential benefit of freshly cultured, UC-MSCs in severe COVID-19 ARDS, associated with biological evidence of favorable immunomodulatory activity.
17 Apr 2026
Read appraisal →Modern rheumatology
Epidemiological and clinical insights into Behçet's disease in Japan: a 2019 nationwide analysis
OBJECTIVES: To clarify contemporary epidemiological and clinical trends of Behçet's disease in Japan by analysing the 2019 National Database of Designated Intractable Diseases (MHLW), describing patient demographics, organ involvement, impact on daily life, and treatment patterns. METHODS: This study analysed the 2019 data from the National Database of Designated Intractable Diseases of Japan, provided by the Japanese Ministry of Health, Labour and Welfare. We focused on age distribution, symptom frequency, daily life impact, and treatment trends. RESULTS: In the 2019 database, 10 406 patients with BD were registered. The median age was 55 years, with a higher proportion of women affected (53.2%). Serious manifestations such as ocular, vascular, and central nervous system involvement were more frequent in males, whereas females showed more mucocutaneous and articular symptoms, representing mild forms of the disease. Pharmacological treatment was common (93.8%), with corticosteroids (44.3%), colchicine (50.9%), infliximab (17.0%), and adalimumab (9.6%) being frequently used. BD significantly affected daily life, with nearly one-third experiencing impaired mobility or depression. CONCLUSIONS: This nationwide analysis highlighted sex-based differences in clinical features and found that BD continues to substantially affect quality of life. The widespread use of biologics suggests a shift in therapeutic strategies.
16 Apr 2026
Read appraisal →International immunopharmacology
CXCL9 as a key feature for deep learning-based immune subtyping and prediction of immune checkpoint blockade response in triple-negative breast cancer
BACKGROUND: Immune checkpoint blockade (ICB) therapy has provided a promising treatment option for patients with triple-negative breast cancer (TNBC). However, existing efficacy prediction strategies based on programmed death-ligand 1 (PD-L1) expression and Tumor Mutational Burden (TMB) have significant limitations, leading to inaccurate patient selection. METHODS: This study integrated multi-omics data obtained from GEO, TCGA, and GTEx datasets. Based on ComBat correction results, two deep learning-driven unsupervised clustering methods were constructed to identify potential immune subtypes. These identified TNBC subtypes were subjected to comprehensive bioinformatics analyses to investigate their differences in overall survival, immune cell infiltration, and functional enrichment analysis, which clarified the biological rationale of the proposed classification. Subsequently, differential expression analysis (DEA) and multiple machine learning algorithms were applied to identify subtype-specific features, with the expression and differentiation status of the key feature in immune cells further validated using single-cell sequencing (scRNA-seq). Finally, co-expression networks at multiple cellular levels were constructed to predict the co-expressed regulatory targets of the key feature, and the hypothesized regulatory mechanism was preliminarily validated in in vitro experiments (qRT-PCR, western blotting, immunofluorescence, and ELISA). RESULTS: After 5-fold cross-validation, the AE-K-means clustering method classified TNBC into three distinct latent subtypes. This algorithm exhibited superior classification efficacy compared with the other models (including NMF, ConsensusClusterPlus and VAE-GMM), as demonstrated by markedly elevated Silhouette Coefficients (training: 0.585 ± 0.030; test: 0.698 ± 0.103; validation: 0.611) and substantially reduced Davies-Bouldin Index values (training: 0.623 ± 0.032; test: 0.385 ± 0.218; validation: 0.558) at K = 3. These three identified TNBC subtypes displayed significant differences in overall survival and exhibited pronounced immune heterogeneity. Specifically, the K2 subtype was characterized by high PD-L1 expression and abundant M1 macrophage infiltration, while the K3 subtype displayed an opposing, immunosuppressive microenvironment. Feature selection results from multiple machine learning models were intersected to identify key features including CXCL9, and an RF model constructed based on these intersected genes showed high efficacy, particularly in distinguishing the K2 and K3 subtypes (AUC = 0.941). Further scRNA-seq analysis revealed that CXCL9 was specifically highly expressed in myeloid cells, and the proportion of CXCL9+ macrophages differed significantly between responders and non-responders. Given the strong positive correlation between CXCL9 and IDO1 expression, we subsequently treated macrophages with IDO1 inhibitors and observed a marked upregulation in both the expression and secretion of CXCL9, suggesting that IDO1 overexpression in macrophages may represent a potential mechanism underlying CXCL9 exhaustion in the tumor microenvironment. CONCLUSIONS: Our study developed a novel immune classification system for TNBC, identifying CXCL9 as a key biomarker positively correlated with ICB response and regulated by IDO1. These findings provide a basis for precision immunotherapy in TNBC and support the exploration of IDO1 inhibitors in combination with ICB.
15 Apr 2026
Read appraisal →International immunopharmacology
Multicentre development and validation of a risk model integrating immunotherapy and coagulation biomarkers for thrombosis in autoimmune neurological disorders
PURPOSE: Patients with Autoimmune Neurological Disorders (ANDs) require routine immunomodulatory therapy, which inherently increases thrombosis risk. Despite this recognised association, reliable tools for thrombosis prediction remain limited, highlighting the need for accurate risk stratification to inform targeted prevention strategies. PATIENTS AND METHODS: This multicentre retrospective study developed a machine learning-based thrombosis risk prediction model using data from 786 patients with ANDs receiving immunomodulatory therapy. The model was trained on data from three centres and externally validated on an independent fourth centre, evaluating six algorithms based on the area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), and Brier score. Feature selection and Shapley Additive Explanations (SHAP) analysis were applied to ensure model interpretability. RESULTS: Among all algorithms tested, XGBoost (XGB) demonstrated the best performance. On the external validation set, the XGB model achieved an AUROC of 0.949, AUPRC of 0.544, and Brier score of 0.045, significantly outperforming the traditional Padua score. SHAP analysis identified the top three thrombotic risk factors: elevated D-dimer levels, prolonged immobilisation, and advanced age. The total doses of intravenous immunoglobulin and glucocorticoid were also confirmed as significant contributors. The model further enabled stratification into low-, intermediate-, and high-risk groups, offering a practical tool for individualised thromboprophylaxis. CONCLUSION: This study presents a high-performing, interpretable model for early thrombosis risk prediction in patients with ANDs, which facilitates timely clinical decision-making and targeted preventive strategies to reduce thromboembolic complications.
15 Apr 2026
Read appraisal →International immunopharmacology
Machine learning derived proliferating T cell-related signature: a novel biomarker for prognosis and treatment efficacy in clear cell renal cell carcinoma
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) exhibits profound molecular heterogeneity, and reliable biomarkers for predicting clinical outcomes are urgently needed. Proliferating T cells (Tprolif) are central to immune system activation but their related signatures in predicting prognosis and therapeutic effect of ccRCC patients remains unexplored. METHODS: We developed a Tprolif-related RCC score (TRRS) using an integrative machine learning framework. Transcriptomic data from the CheckMate025 trial formed the discovery cohort. The model was validated across multiple independent cohorts, including IMmotion151, JAVELIN Renal 101, TCGA-KIRC, and West China Hospital (WCH) cohort from our center. Multi-omics analyses, including spatial and single-cell transcriptomics, were employed to investigate the associated biology and identify key mediators. RESULTS: The final TRRS model, built from 7 genes, demonstrated robust performance in stratifying patients for overall survival (OS) and progression-free survival (PFS) in training and all validation sets. TRRS was a powerful predictor of improved outcomes not only for immune checkpoint inhibitor (ICI) monotherapy but also for ICI-based combination therapy and targeted therapies. Biologically, a high TRRS was associated with aggressive tumor hallmarks, a distinct metabolic profile favoring aerobic glycolysis and glutamine metabolism, and an immunosuppressive tumor microenvironment despite high immune cell infiltration based on WCH cohort transcriptome expression profile. Through multi-omics screening, we identified CST3 as a key target, with spatial and single-cell analyses confirming its role in promoting tumor malignancy and enhancing cell-cell communication among microenvironment components. CONCLUSION: The TRRS is a novel, validated biomarker that effectively predicts prognosis and therapeutic responses in advanced ccRCC. It reflects critical biological features of tumor aggressiveness and immune evasion, with CST3 emerging as a potential central mediator and therapeutic target.
15 Apr 2026
Read appraisal →Blood advances
Targeting Aurora kinase A to prevent GVHD and relapse after myeloablative allogeneic hematopoietic cell transplantation
The success of posttransplant cyclophosphamide (PTCy) for graft-versus-host disease (GVHD) prophylaxis has driven efforts to optimize partner therapies that balance GVHD and relapse prevention. We report phase 1 dose-finding results of PTCy, sirolimus (SIR), and VIC-1911, a selective oral Aurora kinase A (AURKA) inhibitor, after myeloablative allogeneic hematopoietic cell transplantation (allo-HCT). Results from murine and in vitro studies informed the development of the novel drug combination. In the phase 1 trial, patients aged 18 to 60 years received myeloablative conditioning, followed by PTCy (50 mg/kg; days +3/+4), SIR (from day +5; target 8-12 ng/mL), and VIC-1911 (25, 50, or 75 mg twice daily; days +5 to +45). The primary end point was achieving <54% phosphorylated histone H3 serine 10 expression in CD4+ T cells by day +21. Preclinical models show that combining SIR with AURKA inhibition suppresses signaling downstream of CD28, enhancing GVHD prevention while leveraging the antileukemia activity of AURKA inhibition. In the phase 1 trial, the optimal VIC-1911 dose achieving target pathway inhibition without dose-limiting toxicities was 75 mg twice daily. Clinical outcomes included no grade 3 to 4 acute GVHD through day 180 (0%) and low rates of moderate/severe chronic GVHD (6%) and relapse (0%) through 1 year (5/16 received maintenance). The 1-year overall survival for this cohort was 94%. VIC-1911 at 75 mg twice daily, combined with PTCy and SIR, effectively suppressed AURKA activity, offering promising GVHD and relapse prevention with a favorable safety profile and promising early clinical outcomes. The trial was registered at www.clinicaltrials.gov as NCT05120570.
15 Apr 2026
Read appraisal →Nature communications
A group 1 hemagglutinin stem vaccine elicits broad humoral responses against influenza in phase 1/2a study
Vaccines targeting the conserved stem region of influenza hemagglutinin (HA) may induce broad immunity and reduce reliance on strain-matched seasonal formulations. This Phase 1/2a study evaluates safety and immunogenicity of a universal influenza vaccine component comprising a soluble trimeric stabilized group 1 HA-stem protein (INFLUENZA G1 mHA). Healthy adults aged 18-to-45 received one or two doses at 45 µg or 135 µg, with or without Al(OH)₃. Primary endpoints were safety and reactogenicity. All regimens were well-tolerated with no vaccine-related serious adverse events. Secondary and exploratory endpoints included binding, neutralizing, and ADCC responses compared to a matched quadrivalent seasonal influenza vaccine cohort. A single dose induced robust binding antibody responses to H5 HA and homologous stem HA, with 6.5-16.4-fold increases at Day 29 versus baseline, exceeding responses elicited by the seasonal influenza vaccine. Additionally, we demonstrate broader binding to a panel of group 1 HAs, with responses maintained for at least one year. Neutralizing antibody and ADCC responses at Day 29 showed 7.9-15-fold and 4.9-8.6-fold increases, respectively. Importantly, serum from vaccinated participants protect mice against lethal heterologous H5N1 challenge. This study provides proof of concept that the HA stem vaccine elicits broad and durable influenza A group 1-directed immunity. This trial is registered with ClinicalTrials.gov (NCT05901636).
15 Apr 2026
Read appraisal →Blood advances
Neutrophil CD14 is a driver and a therapeutic target for deep vein thrombosis.
Neutrophil-mediated persistent inflammation and neutrophil extracellular trap formation (NETosis) are critical in the pathogenesis of deep vein thrombosis (DVT). Identifying the mechanisms controlling these proinflammatory and prothrombotic functions is critical for designing and developing new therapeutics for DVT. However, how neutrophils acquire these phenotypes during the early stages of DVT remains poorly understood. Here, multiomic analyses (RNA sequencing, proteomics, and flow cytometry) of bone-marrow neutrophils 3 hours after DVT, revealed consistent overexpression of CD14. Concurrently, mice with DVT exhibited significantly elevated plasma granulocyte colony-stimulating factor (G-CSF) and neutrophil hyperactivation. Mechanistic studies using a geometric deep learning model (DeepPBS) and chromatin immunoprecipitation revealed that elevated G-CSF drives CD14 overexpression by upregulating the transcription factor C/EBPα (leucine zipper CCAAT-enhancer binding protein α). Importantly, neutrophil-specific CD14 knockdown using a novel lentiviral short hairpin RNA approach significantly improved DVT outcomes by lowering thrombus burden, thrombosis incidence, and intrathrombus neutrophil and citrullinated histone H3 accumulation. Studies in G-CSF stimulated primary human neutrophils revealed that CD14 inhibition reduces markers of inflammation and NETosis (activated gasdermin D, citrullinated histone H3, and S100A8/A9), while increasing apoptosis, thus demonstrating translational relevance. Collectively, our study uncovers an essential role of neutrophil CD14 in DVT pathogenesis and establishes it as a promising therapeutic target for DVT.
14 Apr 2026
Read appraisal →Medicine
Comparative evaluation of human T lymphocytes in HIV patients treated with lamivudine + zidovudine combined with nevirapine versus efavirenz
This study aimed to explore the efficacy of lamivudine + zidovudine plus nevirapine and efavirenz in the treatment hf human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS). A total of 100 patients with HIV/AIDS admitted to our hospital from June 2021 to September 2024 were selected and randomly assigned into nevirapine and efavirenz groups (n = 50 per group). The nevirapine group was treated with lamidudine plus zidovudine combined with nevirapine, and the efavirenz group was treated with lamidudine plus zidovudine plus efavirenz. The primary outcomes measured were the changes of lymphocyte count and adverse effects after 3 months of treatment. There was no statistical difference in baseline information between the 2 groups. After treatment, CD3 + and CD4 + levels were higher in the nevirapine group than in the efavirenz group (P <.05, 95% CI: 45.2-98.7 for CD3 + and 32.8-76.4 for CD4+), and CD8 + levels were lower in the nevirapine group than in the efavirenz group (P <.05); the overall incidence of adverse effects in the nevavirapine group was significantly lower than that in the efavirenz group (P <.05). In HIV/AIDS patients, treatment with lamivudine + zidovudine combined with nevirapine resulted in significantly improved CD4 + T cell counts, enhanced immune function, and fewer adverse reactions compared to treatment with lamivudine + zidovudine plus efavirenz, suggesting superior clinical value of the nevirapine-containing regimen.
12 Apr 2026
Read appraisal →Medicine
Real-world safety profile of anifrolumab: An observational disproportionality analysis of the FAERS database
Anifrolumab is a type I interferon receptor antagonist approved for the treatment of moderate-to-severe systemic lupus erythematosus. While its efficacy has been demonstrated in clinical trials, its long-term safety remains understudied in the real world. This study extracted relevant data from the FDA Adverse Event Reporting System (FAERS) to evaluate the post-marketing safety profile of anifrolumab in real-world clinical practice and to identify potential safety signals. We analyzed 1293 reports involving 3542 adverse events (AEs) from the FAERS database (Q3 2021-Q1 2025) using disproportionality analysis. Reports in which anifrolumab was designated as the "primary suspect" drug were included. Safety signals were identified using the reporting odds ratio and the Bayesian confidence propagation neural network, with a signal defined as positive only if it met both criteria: a lower limit of the reporting odds ratio's 95% confidence interval > 1 and the 95% lower credibility interval for the information component of the Bayesian confidence propagation neural network > 0. Additionally, multivariable logistic regression analyses were performed for key AEs to rule out potential confounding. The study identified 97 positive safety signals associated with anifrolumab. In addition to the labeled AEs, such as infusion-related reactions and infections, several unexpected AEs were also identified, including renal-related, cardiovascular-related, and neurological AEs. Multivariable logistic regression analyses for key AEs showed that concomitant immunosuppressants, comorbidities, and disease severity were not significant independent predictors (all P > .05), supporting the robustness of the identified signals. This pharmacovigilance study provides hypothesis-generating evidence on the post-marketing safety profile of anifrolumab and highlights several potential safety signals that warrant further evaluation. It is crucial to emphasize that these findings are derived from the FAERS, a spontaneous reporting database that cannot establish causality due to inherent limitations, such as underreporting, missing data, and lack of exposure information. Therefore, these results require confirmation in well-designed observational studies and clinical trials. Clinicians should be aware of these potential associations and consider appropriate monitoring.
12 Apr 2026
Read appraisal →PloS one
Risk factors for spontaneous abortion following hepatitis E vaccination during and shortly before pregnancy: Further analysis from a cluster-randomized trial
BACKGROUND: A recent randomized trial of Hepatitis E Vaccine (HEV239) found an elevated risk of spontaneous abortion (SAB) in women given HEV239 during or within ninety days before pregnancy. Here we present additional analyses to better understand this risk. METHODS: We investigated whether maternal risk profiles of SAB or gestational age at SAB differed between women receiving HEV239 versus control Hepatitis B vaccine (HBV). We also assessed whether HEV239-vaccinated women who experienced SABs had distinct short-term adverse reactions compared to HEV239-vaccinated women who had live births, exploring potential inflammatory mechanisms. Finally, we assessed maternal exposure to HEV239 in narrowly defined pre-last menstrual period (LMP) windows to more precisely demarcate pre-LMP at which HEV-239 vaccination was associated with an elevated risk of SAB. Chi-square tests and Mann-Whitney U tests were performed for bivariate comparisons. Poisson models were used for multivariable analyses. FINDINGS: Baseline maternal risk factors for SAB (age, body mass index, parity, and histories of SAB, hypertension, or diabetes) were similar between the SABs in HEV239 and HBV groups. Median gestational age at SAB was comparable (10.5 weeks [IQR 10-13] for HEV239 vs. 11 weeks [IQR 9-12.2] for HBV, p = 0.783). No increased short-term adverse events (pain: 9% vs. 9%; fever: 2% vs. 1%) were observed among HEV239 recipients who experienced SABs compared to those who did not. An elevated risk of SAB was observed in HEV239 recipients vaccinated 31-60 days pre-LMP (Relative Risk 4.3 [95% CI 1.3-19.3], p = 0.026). INTERPRETATION: Our analyses did not uncover associations pointing to a biological mechanism underlying the original observation of an increased SAB rate connected to HEV239 vaccination shortly before or during pregnancy. Targeted studies such as placental examinations and genetic testing are needed to investigate potential mechanisms.
11 Apr 2026
Read appraisal →Human mutation
Use of Single-Cell Data and scPagwas Analysis to Identify T Cell Subsets and Construct a Prognostic Model for Clear Cell Renal Cell Carcinoma
BACKGROUND: Clear cell renal cell carcinoma (KIRC), the most prevalent pathological renal cell carcinoma (RCC) subtype, makes up approximately 75%-84% of total cases. KIRC is characterized by high heterogeneity, high metastasis rates, and a poor prognosis. Its incidence rate has continued to rise in recent years. We sought to construct new prognostic models to optimize treatment decisions, improve clinical benefits, and explore potential therapeutic targets. METHODS: This study integrated various omics data including single-cell RNA seq (GSE171306), TCGA-KIRC, GWAS, and validation datasets (GSE29609 and E-MTAB-1980). The scPagwas algorithm combines GWAS with scRNA-seq to identify immune subgroups with high feature correlation. Key genes are identified through the combination of weighted correlation network analysis (WGCNA) with differentially expressed genes (DEGs). We built a clinical prognostic model by using machine learning algorithms and validated it through survival rate and receiver operating characteristic (ROC) analysis. We used cancer drug sensitivity genomics data to analyze drug sensitivity and performed molecular docking to identify potential therapeutic drugs. RESULTS: Using single-cell RNA seq data, we identified T cell subsets as characteristic cell subsets in KIRC through scPagwas analysis. In single-cell analysis, key genes in T cell subsets and genes with PCC values > 0.05 were combined with the core genes in DEGs and WGCNA modules, thus yielding 86 intersecting genes. These genes were significantly enriched in immune-related pathways. We established a clinical prognostic model containing seven risk genes. Low-risk patients exhibited substantial survival advantages. Time-dependent ROC analysis indicated the prognostic model's excellent clinical predictive value. Functional enrichment, immune infiltration, and somatic mutation analyses highlighted different biological mechanisms among risk populations. The SHAP values of the XGBoost and LightGBM machine learning algorithms indicated DOCK8 as a potential biomarker. Drug prediction and molecular docking predicted five potential drugs targeting DOCK8 (finasteride, nocodazole, palonosetron, pifithrin alpha, and topiramate). CONCLUSION: Our systematic analysis of the immune microenvironment, key genes, and prognosis of KIRC highlighted the critical roles of T cell subsets. We additionally established an effective clinical prognostic model. Our findings provide new insights and potential targets for the precise diagnosis and targeted KIRC therapy.
11 Apr 2026
Read appraisal →Cerebellum (London, England)
Clinical Spectrum of SEZ6L2 Autoimmunity: A Case Report and Systematic Review
Since the initial report of seizure‑related 6 homolog-like 2 (SEZ6L2) autoimmunity in a patient with cerebellar ataxia and retinopathy, subsequent reports have expanded the phenotype. Although rare, timely recognition is essential because this condition is immunotherapy-responsive. To describe a case of SEZ6L2 autoimmunity and conduct a systematic review (2014-2025) to characterize this rare disease. An 87-year-old man presented with subacute gait disturbance and cognitive decline, progressing to wheelchair dependence within 4 months. Examination showed dysarthria, appendicular and axial ataxia, dysmetria, tremor, and postural instability. Brief Ataxia Rating Scale (BARS) was 19.5. CSF studies and brain MRI were unremarkable, whereas FDG-PET demonstrated diffuse cerebellar hypometabolism. Malignancy screening was negative. After empiric intravenous immunoglobulin (IVIg) 2 g/kg, SEZ6L2 antibody assays returned positive in serum and CSF. Monthly IVIg was continued with mild improvement (BARS 18 at 7 months). Systematic review identified 12 articles (18 patients). Including our case, 19 patients (median age 60 years, 63% female) were analyzed. All had subacute cerebellar ataxia. Cognitive dysfunction and Parkinsonism were seen in 78.9% and 42.1%, respectively. Other symptoms included depression, pyramidal signs, nausea, tremor, sleep disturbance, and dysautonomia. Treatment was heterogeneous, with 47.4% showing partial improvement. SEZ6L2 autoimmunity is a rare, immunotherapy-responsive cause of subacute cerebellar ataxia, often with parkinsonism and cognitive changes. Presentations may extend beyond these manifestations.
11 Apr 2026
Read appraisal →Psychological medicine
Inflammatory cytokine alterations in genetic and clinical high risk groups of psychosis: a systematic review and network meta-analysis
BACKGROUND: Inflammation has been implicated in psychosis, but its role in individuals at clinical (CHR) and genetic (GHR) high-risk remains unclear. We therefore conducted a network meta-analysis (NMA) to compare circulating cytokine levels across CHR, GHR, and healthy control (HC) groups. METHODS: We systematically searched multiple databases up to February 2025, extracting cytokine levels (plasma/serum) from CHR, GHR, and HC groups. Standardized mean differences (SMDs) with 95% confidence intervals (CIs) were estimated using random-effects models. Given that no direct head-to-head comparisons between CHR and GHR were available, indirect comparisons were performed through the common comparator (HC). The transitivity assumption was assessed by comparing key study and participant characteristics across comparisons. RESULTS: Thirty studies were included (CHR: 1601, GHR: 675, HC: 1980). NMA estimates indicated higher IL-6 levels in CHR compared with GHR, while IL-6 and IL-1β levels were lower in GHR compared with HC. In pairwise subgroup analyses, CHR converters showed higher IL-13 levels than non-converters. The evidence network was sparse and star-shaped, with all CHR-GHR estimates relying exclusively on indirect comparisons. CONCLUSIONS: This study represents the first NMA to synthesize cytokine alterations in individuals at high risk for psychosis using indirect evidence. Elevated IL-6 in CHR individuals suggests immune activation, whereas reduced IL-6 in GHR may reflect a distinct immune profile. Increased IL-13 levels in converters highlight potential involvement of Th2-related pathways during transition to psychosis. However, the sparse nature of the evidence network necessitates cautious interpretation of the findings, and larger, standardized multi-center studies are required for confirmation.
11 Apr 2026
Read appraisal →JCI insight
Cutaneous adipose tissue carries a strong inflammatory signature in patients with psoriasis.
This study provides a comprehensive evaluation of the cutaneous adipose tissue (CAT) transcriptome in patients with psoriasis and investigates the effects of IL-17 blockade on CAT inflammation through a randomized placebo-controlled trial using secukinumab (ObePso-S study, ClinicalTrials.gov NCT03055494). RNA sequencing analysis of CAT biopsies from 82 patients with psoriasis revealed 2132 differentially expressed transcripts compared with healthy controls. Notably, significant gene dysregulation was observed in both lesional skin (LS)-CAT and non-lesional (NL)-CAT, including activation of IL-17-driven pathways, antimicrobial peptide-related, and neutrophil degranulation signatures. Stratification by obesity demonstrated that obese psoriatic CAT exhibited a more than 2-fold higher number of differentially expressed genes than non-obese counterparts, suggesting a synergistic interaction between psoriasis and obesity in driving CAT inflammation. Treatment with secukinumab markedly improved inflammatory signatures in psoriatic CAT, with greater improvements observed in obese patients. These findings reveal a pronounced and partially IL-17-dependent inflammatory phenotype in psoriatic CAT, challenge the conventional concept of psoriasis as a solely superficial skin disease, and highlight CAT as an important contributor to systemic inflammation in psoriasis.
10 Apr 2026
Read appraisal →Lupus science & medicine
Efficacy and safety of anifrolumab in patients with systemic lupus erythematosus without prior immunosuppressant use: post hoc analysis of phase 3 TULIP-1 and TULIP-2 trials
OBJECTIVE: Although current treatment recommendations for systemic lupus erythematosus (SLE) provide the option for biologic agents without prior failure of immunosuppressants (IS), data on this treatment approach are limited. This study evaluates the efficacy and safety of anifrolumab by IS exposure. METHODS: Pooled data from the Phase 3 TULIP-1 (NCT02446912) and TULIP-2 (NCT02446899) trials were analysed post hoc to compare patients with moderate-to-severe SLE treated with intravenous anifrolumab 300 mg or placebo alongside standard therapy by reported IS use. Efficacy outcomes by IS use included Definition of Remission in SLE (DORIS) remission and Lupus Low Disease Activity State (LLDAS) attainment, analysed using a stratified Cochran-Mantel-Haenszel approach; all p values are nominal. Safety was summarised descriptively. RESULTS: In this analysis, 257 patients had no reported IS use (IS-inexperienced; anifrolumab 300 mg, n=127; placebo, n=130), and 469 were IS-experienced (anifrolumab 300 mg, n=233; placebo, n=236). At Week 52, DORIS remission and LLDAS attainment rates were higher with anifrolumab versus placebo in both IS subgroups (DORIS, IS-inexperienced, 16.2% vs 6.0%, p=0.0242; IS-experienced, 14.6% vs 7.3%, p=0.0304; LLDAS, IS-inexperienced, 34.0% vs 26.2%, p=0.1718; IS-experienced, 27.7% vs 16.2%, p=0.0038). Anifrolumab was well tolerated, regardless of reported IS history; safety was more favourable among IS-inexperienced versus IS-experienced patients. CONCLUSIONS: This post hoc analysis of pooled TULIP-1/TULIP-2 data supports the efficacy and tolerability of anifrolumab in patients with moderate-to-severe SLE regardless of IS treatment history.
10 Apr 2026
Read appraisal →Lupus science & medicine
Unsupervised clustering of clinical and laboratory features of systemic lupus erythematosus: insights from a multicentre cohort
OBJECTIVE: This study explored the relationship between clinical phenotypes and immuno-molecular features of systemic lupus erythematosus (SLE) using unsupervised machine learning and multi-omics integration. METHODS: A multicentre cohort of 1065 SLE patients from five teaching hospitals was studied. Unsupervised clustering was performed using integrated clinical and laboratory data to identify distinct phenotypic clusters. Multi-omics profiling, including proteomics and transcriptomics, was conducted for each cluster, comparing with healthy controls. In addition, 899 patients were prospectively followed for over 1 year to assess therapeutic responses and remission outcomes. RESULTS: Unsupervised clustering identified five distinct clusters of SLE based on clinical phenotypes and immunological signatures, and an intrinsic association was found between each cluster and immune-inflammatory features. Cluster 1 (renal; 14.27%) had predominant renal involvement (87.5%) and high disease activity. Cluster 2 (mucocutaneous; 39.53%) exhibited mainly cutaneous manifestations (72.45%) with mild visceral involvement and the highest rates of achieving low disease activity state (46.42%). Cluster 3 (neuropsychiatric; 14.74%) had a high frequency of neuropsychiatric manifestations (96.18%) and anti-U1 ribonucleoprotein antibodies positivity (42.04%). Cluster 4 (haematologic; 22.63%) was characterised by haematologic involvement, predominantly cytopenia (95.85%), with frequent antiphospholipid antibody positivity and direct Coombs positivity (87.55%). Cluster 5 (cardiopulmonary; 8.83%) exhibited prominent cardiopulmonary involvement (97.87%) and serositis, with enrichment of inflammatory CD161+ regulatory T cells. Transcriptomic and proteomic analyses confirmed distinct molecular signatures and cluster-specific enrichment of biological pathways. Key molecule apolipoprotein A4 was validated using enzyme-linked immunosorbent assay. Regarding therapeutic outcomes at 1 year follow-up, Cluster 2 had the highest proportions achieving lupus low disease activity state (46.42%) and tapering glucocorticoids. Cyclophosphamide use was associated with greater clinical improvement (r=0.284; p=0.023) in Cluster 3, while in Cluster 5, rituximab use was associated with favourable responses (r=0.286; p=0.019). CONCLUSIONS: We identified five SLE clusters with distinct clinical, immunological features and treatment outcomes, demonstrating an intrinsic link between clinical involvement and immune-inflammatory alterations.
9 Apr 2026
Read appraisal →The New England journal of medicine
Immunogenicity and Safety of vYF, a Yellow Fever Vaccine - A Phase 2 Trial
BACKGROUND: A next-generation, live-attenuated yellow fever vaccine, vYF, was developed in Vero cells to improve vaccine supply and availability. The safety of and immune response to vYF as compared with those of the licensed yellow fever vaccine, YF-VAX, are unclear. METHODS: In this year 1 interim analysis of a phase 2, observer-blinded, randomized, active-controlled trial, we randomly assigned healthy adults 18 to 60 years of age in a 2:1 ratio to receive vYF or YF-VAX as a single vaccine injection on day 1. Neutralizing antibody titers were measured on day 29, month 6, and year 1. The primary analysis focused on the per-protocol population, which included participants with no history of yellow fever infection or vaccination and with no protocol deviations. Noninferiority would be shown if the lower limit of the two-sided 95% confidence interval of the between-group difference in the percentage of participants with seroconversion was greater than -5 percentage points on day 29. RESULTS: A total of 568 participants were enrolled: 382 in the vYF group and 186 in the YF-VAX group; 329 and 156 participants, respectively, were included in the per-protocol population for the noninferiority analysis. Seroconversion by day 29 occurred in 99.7% of participants receiving vYF and 99.4% of those receiving YF-VAX (difference, 0.3 percentage points; 95% confidence interval, -1.2 to 3.2, which met the criterion for noninferiority). Neutralizing antibody geometric mean titers were similar in the two vaccine groups, peaking on day 29 (in the vYF group, 1:2654 among participants with no history of yellow fever infection or vaccination and 1:1312 among participants with a history of yellow fever infection or vaccination; in the YF-VAX group, 1:3147 and 1:1079, respectively), then decreasing through 1 year after vaccination (in the vYF group, 1:401 among participants with no history of yellow fever infection or vaccination and 1:490 among participants with a history of yellow fever infection or vaccination; in the YF-VAX group, 1:548 and 1:646, respectively). No major safety concerns were identified. The safety profiles were similar in the two vaccine groups: solicited adverse events were reported by 208 of 367 participants (56.7%) in the vYF group and 113 of 185 participants (61.1%) in the YF-VAX group, and unsolicited adverse events were reported by 99 of 379 participants (26.1%) and 39 of 186 participants (21.0%), respectively. CONCLUSIONS: In this trial, vYF had immunogenicity and safety profiles similar to those of YF-VAX. (Funded by Sanofi; ClinicalTrials.gov number, NCT04942210.).
9 Apr 2026
Read appraisal →BMJ open
Identification of immunomodulators associated with atrial fibrillation reporting to better understand AF immunologic mechanisms: a Vigibase retrospective disproportionality analysis and a literature review
OBJECTIVES: Growing evidence exists about the pivotal role of immune mechanisms in the physiopathology of atrial fibrillation (AF). Drugs that modulate the immune system (immunomodulators) may contribute to the development of AF. We aimed to identify immunomodulators that are associated with AF to better define their safety profile, and elucidating their mechanisms of action could yield novel insights into AF's immune physiopathology. DESIGN: A descriptive and disproportionality analysis of claims data. SETTINGS: World pharmacovigilance database VigiBase until 1 March 2025. PRIMARY AND SECONDARY OUCTOMES: First, we ascertained the association of immunomodulators with AF over-reporting with a disproportionality analysis evaluating the multivariable-adjusted reporting odds ratio (aROR) for AF reporting performed for 141 immunomodulators in VigiBase. Then, a literature review was done to explore the underlying mechanisms of AF through immunomodulator mechanisms. RESULTS: A total of 6 148 556 reports encompassing at least one of the 141 immunomodulators were identified in Vigibase. Our primary analysis revealed 20 immunomodulators associated with AF over-reporting. The three immunomodulators with the greatest signal were: recombinant interleukin-11 with an aROR=20.91 (99.96% CI 12.08 to 36.17), efgartigimod alfa with an aROR=6.75 (99.96% CI 3.96 to 11.52) and recombinant interleukin-2 with an aROR=6.15 (99.96% CI 3.62 to 10.45). A derivative literature review posited a hypothetical immune 'vicious circle' promoting AF, involving T helper cells, macrophages and natural killer cells which could lead to electrophysiologic and histologic atrial remodelling. CONCLUSIONS: Twenty Food and Drug Administration (FDA)-labelled immunomodulators are associated with AF overreporting in Vigibase with a substantial signal on recombinant IL-11. These data contribute substantively to the prevailing understanding of the safety profile of these immunomodulators. Moreover, these findings support a multidirectional interaction between the immune system and AF development and might lead to considering future therapeutic targets. TRIAL REGISTRATION NUMBER: NCT06095791.
9 Apr 2026
Read appraisal →Neurology
Efficacy of Pyridostigmine in Myasthenia Gravis: A Randomized, Double-Blind, Placebo-Controlled Crossover Trial
BACKGROUND AND OBJECTIVES: Pyridostigmine, an acetylcholinesterase inhibitor, is a symptomatic drug approved for the treatment of myasthenia gravis (MG), but no randomized controlled trials substantiate its widespread use. We aimed to assess the efficacy and cost utility of pyridostigmine in patients with anti-acetylcholine receptor-positive MG (AChR MG). METHODS: A randomized, double-blind, placebo-controlled crossover trial was conducted at Leiden University Medical Center, a tertiary center for the treatment of MG in the Netherlands. Main eligibility criteria were current use of pyridostigmine and a stable dose of other MG treatments. Participants were assigned to a sequence of 2 treatment periods for 5 days separated by a 2-day washout, in which patients either first received placebo and then pyridostigmine, or vice versa. Pyridostigmine dosing matched each participant's prestudy regimen. The primary outcome was change in the Myasthenia Gravis Impairment Index (MGII) score. Secondary efficacy outcome measures included the Myasthenia Gravis Activities of Daily Living (MG-ADL) scale, the Quantitative Myasthenia Gravis (QMG) score, and the revised 15-item Myasthenia Gravis Quality of Life (MG-QOL15r) questionnaire. For the post hoc cost-utility analysis, a mathematical model was developed to translate the observed study results into long-term annual effect on societal costs and quality-adjusted life years (QALYs). RESULTS: A total of 19 patients (median age 59 years, 58% female) were recruited between March 23, 2023, and February 21, 2024. The estimated mean difference in the MGII score between pyridostigmine and placebo interventions was 5.3 (95% CI 1.9-8.7, p = 0.004). Secondary efficacy outcome measures showed estimated mean differences of 1.4 (95% CI 0.5-2.3) for the QMG score, 1.2 (95% CI 0.5-1.8) for the MG-ADL score, and 2.0 (95% CI 0.03-3.91) for the MG-QoL15r score. The post hoc cost-utility analysis showed lower annual societal costs (€6,565, 95% CI €328-€15,945) and annual improved QALYs (0.106, 95% CI 0.019-0.210) for patients using pyridostigmine. DISCUSSION: This trial showed that, in patients with AChR MG chronically treated with pyridostigmine, pyridostigmine demonstrated benefit over placebo across all efficacy outcome measures and substantially reduced societal costs. TRIAL REGISTRATION INFORMATION: The trial was registered at EudraCT (2021-004110-20, registration date: July 12, 2022) and ClinicalTrials.gov (NCT05919407, registration date: June 16, 2023). First patient enrolled: March 23, 2023. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that, in adults with AChR ab-positive ocular or generalized MG on stable standard-of-care therapy and currently using pyridostigmine, pyridostigmine improves MG symptoms compared with placebo.
9 Apr 2026
Read appraisal →mAbs
Deep learning assessment of nativeness and pairing likelihood for antibody and nanobody design with AbNatiV2.
Most immune-system created antibodies balance good binding and stability with low toxicity and self-reactivity. Quantifying the nativeness of a candidate sequence - its likelihood of belonging to natural immune repertoires - has thus emerged as a valuable strategy for hit selection from synthetic libraries, optimization and humanization, and for guiding de novo design toward developable candidates. We previously introduced AbNatiV, a transformer-based VQ-VAE for nativeness assessment, which proved effective across multiple nanobody engineering tasks. However, AbNatiV1 operated on unpaired sequences, limiting applicability to conventional VH-VL antibodies. Moreover, its performance on nanobody nativeness was constrained by the limited number and diversity of nanobody repertoires available at the time. Here, we sequenced new camelid repertoires, curated additional recent datasets, and present AbNatiV2: an enhanced architecture comprising various models each trained on ≥20 million sequences. AbNatiV2 improves nanobody nativeness classification across held-out and diverse test sets, and more robustly detects nativeness changes upon CDR grafting. We also introduce p-AbNatiV2, a cross-attention model fine-tuned on 3.7 million paired human sequences. p-AbNatiV2 provides residue- and sequence-level humanness for VH/VL pairs and learns pairing-likelihood via noise-contrastive training. On held-out tests, it assigns the native pair a higher score in 74% of cases, substantially outperforming recent pairing models. Together, AbNatiV2 and p-AbNatiV2 extend nativeness assessment and engineering to both nanobodies and conventional antibodies, supporting design decisions at single-residue, Fv-sequence, and paired-domain levels. AbNatiV2 is available as downloadable software and webserver.
8 Apr 2026
Read appraisal →Vaccine
Applied immunoinformatics in modern vaccine design: a comprehensive review of available computational tools
The rapid evolution of computational biology has transformed vaccine design from a largely empirical process into a rational, data-driven discipline. At the center of this transformation lies immunoinformatics, which integrates immunology, molecular biology, and data science to accelerate the identification, evaluation, and optimization of vaccine candidates. By enabling the systematic transition from genomic data to viable immunotherapeutic candidates, these approaches offer an unprecedented capacity to shorten development timelines, reduce costs, and broaden population coverage compared to traditional trial-and-error vaccine pipelines. This review provides a state-of-the-art overview of the currently available immunoinformatic tool that underpins modern vaccine design. From identification of conserved and functionally essential pathogen targets, advances in structural prediction, epitope mapping, safety assessment, and systems-level analyses of host-pathogen interactions, immunoinformatics allows researchers to design vaccines with enhanced success rate. Special emphasis is placed on the shift from purely predictive models toward generative frameworks, where artificial intelligence and deep learning now support not only the evaluation, but also the rational engineering of optimized vaccine candidates. For this review, we systematically examined more than 250 computational tools and algorithms spanning every stage of the vaccine discovery pipeline. From this extensive survey, we distilled and discussed the approaches that currently demonstrate the highest performance and practical usability, thereby providing researchers with a curated overview of some the most reliable resources available.
5 Apr 2026
Read appraisal →The European respiratory journal
A European multicentre, randomised controlled trial of pirfenidone in bronchiolitis obliterans syndrome after bilateral lung transplantation
BACKGROUND: Chronic lung allograft dysfunction (CLAD) is a major obstacle to improving outcomes after lung transplantation. Bronchiolitis obliterans syndrome (BOS), characterised by progressive decline in forced expiratory volume in 1 s (FEV1) due to fibrotic scarring of the small airways, accounts for most CLAD cases. Pirfenidone, an antifibrotic agent used for idiopathic pulmonary fibrosis, was assessed for treating progressive BOS. METHODS: An investigator-initiated, international, multicentre, randomised, double-blind, placebo-controlled phase II trial was conducted in nine European lung transplant centres. Adults with bilateral lung transplants and progressive BOS were randomised (1:1) to receive pirfenidone 2403 mg·day-1 or placebo with standard care for 26 weeks. The primary end-point was change in FEV1 from baseline to week 26, with imputation for missing values. FINDINGS: From 1 May 2015 to 1 December 2019, 477 patients were screened, and 90 were randomised to pirfenidone (n=48) or placebo (n=42). Both groups showed continued decline in FEV1 from baseline to week 26, with no significant difference in intention to treat (ITT), ITT with imputation, or per-protocol analyses. Secondary end-points (graft loss, death, re-transplantation) were similar between groups. Treatment-related serious adverse events were distributed equally. INTERPRETATION: Pirfenidone did not show superiority over placebo and standard care in this exploratory trial. It cannot be recommended for treating BOS. Further research is needed to explore other treatments for CLAD to improve long-term outcomes after lung transplantation.
4 Apr 2026
Read appraisal →Journal of biophotonics
Cell-MICS: Detecting Immune Cells With Label-Free Two-Photon Autofluorescence and Deep Learning
Multiphoton imaging has been widely used for deep-tissue imaging. Although its label-free, metabolic contrast is ideal for investigating inflammation, the label-free two-photon induced autofluorescence is often regarded as less specific compared to conventional antibody markers. In this work, we investigate the potential for multiphoton imaging with computational specificity (MICS) by training a convolutional neural network on images of different immune cells. A low-complexity squeezeNet architecture was able to achieve reliable immune cell classification results (0.89 ROC-AUC, 0.95 PR-AUC for binary classification between T cells and neutrophils; 0.689 F1 score, 0.697 precision, 0.748 recall for multi-class classification between six isolated cell types). Perturbation tests confirmed that the model was not confused by the extracellular environment and that 2P-AF from NADH and FAD is equally important for the classification. In the future, deep learning could provide computational specificity for specific immune cells in unstained tissues, with great potential for label-free in vivo endomicroscopy.
4 Apr 2026
Read appraisal →IEEE transactions on medical imaging
Self-Paced Learning for Images of Antinuclear Antibodies
Antinuclear antibody (ANA) testing is a critical method for diagnosing autoimmune disorders such as Lupus, Sjögren's syndrome, and scleroderma. Despite its importance, manual ANA detection is slow, labor-intensive, and demands years of training. ANA detection is complicated by over 100 coexisting antibody types, resulting in vast fluorescent pattern combinations. Although machine learning and deep learning have enabled automation, ANA detection in real-world clinical settings presents unique challenges as it involves multi-instance, multi-label (MIML) learning. In this paper, a novel framework for ANA detection is proposed that handles the complexities of MIML tasks using unaltered microscope images without manual preprocessing. Inspired by human labeling logic, it identifies consistent ANA sub-regions and assigns aggregated labels accordingly. These steps are implemented using three task-specific components: an instance sampler, a probabilistic pseudo-label dispatcher, and self-paced weight learning rate coefficients. The instance sampler suppresses low-confidence instances by modeling pattern confidence, while the dispatcher adaptively assigns labels based on instance distinguishability. Self-paced learning adjusts training according to empirical label observations. Our framework overcomes limitations of traditional MIML methods and supports end-to-end optimization. Extensive experiments on one ANA dataset and three public medical MIML benchmarks demonstrate the superiority of our framework. On the ANA dataset, our model achieves up to +7.0% F1-Macro and +12.6% mAP gains over the best prior method, setting new state-of-the-art results. It also ranks top-2 across all key metrics on public datasets, reducing Hamming loss and one-error by up to 18.2% and 26.9%, respectively. The source code can be accessed at https://github.com/fletcherjiang/ANA-SelfPacedLearning.
4 Apr 2026
Read appraisal →N Engl J Med
Adenoviral Inciting Antigen and Somatic Hypermutation in VITT
BACKGROUND: Vaccine-induced immune thrombocytopenia and thrombosis (VITT) is a rare prothrombotic complication that occurs after adenoviral vector-based vaccination against coronavirus disease 2019; in rare cases, it can also occur after natural adenovirus infection. VITT is mediated by platelet-activating antibodies against the highly cationic protein platelet factor 4 (PF4). The underlying inciting antigen trigger and immunopathogenesis remain unknown. METHODS: We used antibody proteomics to determine the amino acid sequences of anti-PF4 antibodies from 21 patients with VITT and sequenced the genes encoding the immunoglobulin light-chain hypervariable region from 100 patients with VITT. To identify an adenoviral trigger, we used the antigen-binding fingerprints of anti-PF4 and anti-adenovirus protein antibodies to identify a shared serum clonotype and subsequently used adenovirus protein peptides and recombinant anti-PF4 VITT antibodies to map the mimicking linear epitope. RESULTS: Genomic and proteomic profiling of VITT antibodies revealed a shared immunoglobulin light-chain allele, IGLV3-21*02 or *03, harboring a critical somatic hypermutation, K31E. Only antibodies purified against adenoviral core protein VII (pVII) contained anti-PF4 species matching the VITT fingerprint; antibodies against intact virions or other adenoviral proteins did not. Cross-reactive IgGs were mapped to a basic linear epitope on pVII. A pathogenic anti-PF4 VITT antibody, back-mutated to germline (K31), lost its prothrombotic activity in vitro and in vivo and preferentially bound pVII, a finding that directly supported the role of the hypermutation in the antigenic shift from adenovirus pVII to PF4. CONCLUSIONS: The results of our study indicate that VITT occurs when, in persons with immunoglobulin light-chain allele IGLV3-21*02 or *03, a specific somatic hypermutation develops that affects antibodies that recognize a specific epitope on the adenoviral core protein pVII, which results in misdirection of antibody targeting toward PF4. (Funded by Deutsche Forschungsgemeinschaft and others; German Clinical Trials Register number, DRKS00025738; EU Post-Authorization Study Register number, EUPAS45098.).
1 Feb 2026
Read appraisal →Surv Ophthalmol
Relentless placoid chorioretinitis
Relentless placoid chorioretinitis (RPC) is a rare, vision-threatening posterior uveitis that predominantly affects young adults. The hallmark clinical findings are numerous scattered placoid chorioretinal lesions involving the midperipheral and far peripheral fundus as well as the posterior pole and a persistent or recurrent course resulting in lesions at different chronological stages, with fresh creamy placoid lesions and healing pigmented lesions being present at the same time. Although RPC is frequently described as a disease that is intermediate between acute posterior multifocal placoid pigment epitheliopathy (APMPPE) and serpiginous choroiditis, it more closely resembles APMPPE. It is important to identify those patients with RPC who present with an APMPPE phenotype so that appropriate immunomodulatory therapy is instituted without delay, as most cases of RPC are refractory to corticosteroid monotherapy. Examination findings may help differentiate RPC and APMPPE. Multimodal imaging, including ultra-widefield imaging, and selective investigations aid in distinguishing RPC from other placoid diseases and types of posterior uveitis.
1 Jan 2026
Read appraisal →Cell
Generation of antigen-specific paired-chain antibodies using large language models.
The traditional process of antibody discovery is limited by inefficiency, high costs, and low success rates. Recent approaches employing artificial intelligence (AI) have been developed to optimize existing antibodies and generate antibody sequences in a target-agnostic manner. In this work, we present MAGE (monoclonal antibody generator), a sequence-based protein language model (PLM) fine-tuned for the task of generating paired human variable heavy- and light-chain antibody sequences against targets of interest. We show that MAGE can generate novel and diverse antibody sequences with experimentally validated binding specificity against SARS-CoV-2, an emerging avian influenza H5N1, and respiratory syncytial virus A (RSV-A). MAGE represents a first-in-class model capable of designing human antibodies against multiple targets with no starting template.
1 Dec 2025
Read appraisal →Cancer Res
Artificial Intelligence and Multimodality Data Integration Decipher Tertiary Lymphoid Structure Maturity in Gastric Cancer
UNLABELLED: Tertiary lymphoid structures (TLS) are critical components of the tumor microenvironment in gastric cancer, but clinical assessment of TLSs is challenging. The development of automated annotation tools for histopathologic slide analysis could facilitate the identification of TLSs and enhance our understanding of the mechanisms driving TLS maturation. In this study, we generated a transformer-based deep learning model that enables quantitative characterization of TLS maturity from whole-slide images. Application of the model to a large gastric cancer cohort (n = 253) showed that higher TLS maturity correlated with improved patient survival. Integration of single-cell RNA sequencing data from 17 patients with gastric cancer combined with multiplex IHC, flow cytometry, and functional coculture assays identified a key immune circuit in mature TLSs involving CD8+ tissue-resident memory T cells, which recruit activated B cells via the CXCL13-CXCR5 axis to enhance tissue-resident memory T-cell cytotoxicity through granzyme B upregulation. Overall, this study established a clinically applicable artificial intelligence tool and uncovered key immune interactions that regulate TLS maturation and antitumor immunity in gastric cancer. SIGNIFICANCE: A deep learning model demonstrates that higher tertiary lymphoid structure maturity predicts improved gastric cancer patient survival and identifies a key immune circuit, offering a clinically applicable tool that could guide treatment. This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI.
1 Dec 2025
Read appraisal →Int J Surg
Multi-omic profiling reveals age-specific blood biomarkers and aging-driven B cell remodeling in osteoarthritis
BACKGROUND: Osteoarthritis (OA) pathogenesis involves age-related immune dysregulation, yet non-invasive diagnostic tools and mechanistic insights remain limited. METHODS: We integrated transcriptomic profiling of four OA-affected joint tissues with machine learning to identify potential peripheral blood biomarkers. Weighted gene co-expression network analysis was employed to explore gene modules and pathways associated with OA. Single-cell RNA sequencing was performed on 217 983 joint cells to delineate B cell differentiation trajectories. Flow cytometry was used to validate age-associated B cell imbalances in peripheral blood. RESULTS: We identified five peripheral blood biomarkers: MAPK1, MAP3K8, ING1, LDLR, and NUP153 in distinguishing OA patients from controls (the area under the curve [AUC] = 0.966). Importantly, these markers exhibited age-specific expression profiles; ING1, NUP153, and MAP3K8 were elevated, while MAPK1 was reduced in elderly compared to younger OA patients. A refined predictive model based on these age-specific markers demonstrated superior performance specifically for elderly Knee OA (KOA, AUC: 0.8 vs. 0.7 for younger KOA). These biomarkers correlated with immune cell infiltration and inflammatory cytokines. In osteoarthritic joint tissues, B cells predominantly originated from subchondral bone and synovium. Single-cell analysis identified age-specific B cell differentiation patterns, with elderly KOA patients enriched in an activated B cell cluster (C1). Furthermore, B cells from elderly KOA patients showed altered energy metabolism and increased proportions in peripheral blood, and functionally promoted chondrocyte damage. CONCLUSION: Our findings establish a novel blood-based diagnostic framework for OA and uncover aging-driven B cell remodeling as a key contributor to elderly OA pathogenesis. These findings offer non-invasive diagnostics and immunomodulatory targets for age-specific OA therapy.
1 Nov 2025
Read appraisal →Science
Deep generative models design mRNA sequences with enhanced translational capacity and stability
Despite the success of messenger RNA (mRNA) COVID-19 vaccines, extending this modality to more diseases necessitates substantial enhancements. We present GEMORNA, a generative RNA model that uses transformer architectures tailored for mRNA coding sequences (CDSs) and untranslated regions (UTRs) to design mRNAs with enhanced expression and stability. GEMORNA-designed full-length mRNAs exhibited up to a 41-fold increase in firefly luciferase expression compared with an optimized benchmark in vitro. GEMORNA-generated therapeutic mRNAs achieved up to a 15-fold enhancement in human erythropoietin (EPO) expression and substantially elicited antibody titers of COVID vaccine in mice. Additionally, GEMORNA's versatility extends to circular RNA, substantially enhancing circular EPO expression and boosting antitumor cytotoxicity in chimeric antigen receptor T cells. These advancements highlight the vast potential of deep generative artificial intelligence for mRNA therapeutics.
1 Nov 2025
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