Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 40 appraisals
Sleep medicine reviews
Machine and deep learning in REM sleep behavior disorder: a scoping review and analysis of reporting quality
Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia, and its isolated form is of particular interest, as it is an early phase alpha-synucleinopathy. Machine learning (ML) and deep learning (DL) models offer potential for automated detection, prediction of phenoconversion, and phenotyping. This scoping review identified 75 studies applying ML/DL in RBD and evaluated their methodological and reporting quality using the APPRAISE-AI tool. Most studies (73.3%) focused on RBD detection and mainly used polysomnographic data for this, while 16% addressed prediction of phenoconversion, with imaging data being the most employed modality. Sample sizes were generally small (most studies including only 20-100 individuals). According to APPRAISE-AI scores, 80% of studies had moderate overall methodological and reporting quality. Common deficiencies included lack of transparency in data and code sharing (23.3%), and poor reporting of hyperparameter tuning (17.1%), bias assessment (26.9%), and error analysis (0.66%). Data leakage was observed in 32% of studies. These issues hinder clinical translation and prevent incremental progress between research groups. Without transparent reporting and shared resources, replication and model comparisons become nearly impossible. Future work should adopt open science principles and rigorous validation to advance AI-based tools in sleep medicine.
3 Aug 2026
Read appraisal →Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Efficacy and safety of fecal microbiota transplantation in Parkinson's disease: a systematic review and meta-analysis of randomized controlled trials with GRADE assessment
BACKGROUND: Parkinson's disease (PD) is a common neurodegenerative disease that is a growing public health challenge. Recent evidence showed that gut microbiota dysbiosis is involved in the pathogenesis of PD, prompting interest in fecal microbiota transplantation (FMT) as a potential disease-modifying intervention. This systematic review and meta-analysis aim to evaluate the efficacy and safety of FMT in patients with PD. METHODS: We conducted a systematic literature review using PubMed, Scopus, Web of Science, and the Cochrane Library till June 4, 2026, to identify RCTs comparing FMT with placebo or control interventions in PD. After removal of duplicates alongside title and abstract screening, followed by full-text screening, seven randomized controlled trials were included in this systematic review and meta-analysis. RESULTS: A total of seven randomized controlled trials (RCTs) with 318 subjects were analyzed. FMT was delivered via oral capsules, nasojejunal tubes, or colonoscopy, with follow-up periods ranging from 12 to 52 weeks. The meta-analysis indicated a notable short-term enhancement in daily motor activities, as assessed by MDSUPDRS Part II, after one month (mean difference - 2.19, 95% confidence interval - 4.32 to -0.06; P = 0.044). Nevertheless, no significant estimates were noted for MDS-UPDRS Part III, aggregate MDS-UPDRS scores, motor complications, non-motor symptoms, or overall life quality at any assessed time frame. Some individual studies reported gains in cognitive ability, anxious feelings, quality of life related to constipation, and certain PDQ-39 categories, although these improvements were not uniformly observed. Overall, FMT was well tolerated by participants, with adverse reactions mostly comprising mild, self-resolving gastrointestinal issues and no major safety risks. CONCLUSIONS: FMT is a safe treatment for individuals with PD and may offer modest short-term advantages in performing daily motor tasks. However, current evidence does not indicate lasting enhancements in overall motor capabilities, non-motor symptoms, or life quality. More extensive and sufficiently powered trials utilizing standardized FMT procedures and longer observation periods are necessary to elucidate the therapeutic benefits of FMT in Parkinson's disease.
1 Aug 2026
Read appraisal →Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Handwritten signatures in neurological and psychiatric disorders: a systematic review with clinical and forensic implications.
BACKGROUND: Signature production represents a complex motor and cognitive behavior, highly automatized and repeated countless times throughout life. It ranks among the most durable graphic forms, often preserved even when writing processes are impaired. Studies examining signature characteristics in clinical cohorts are limited. The available evidence raises questions about its potential as a behavioral marker of neurological and psychiatric disorders. METHODS: We conducted a PRISMA-compliant systematic review up to 4th December 2025 to summarize evidence on how neurological and psychiatric conditions may affect signature features. Eligible articles on this topic were searched in Scopus, Web of Science, and PubMed databases. Sixteen papers were included, and their results were systematically described and qualitatively analyzed. RESULTS: The available literature suggests that signature production appears relatively independent of global cognitive decline, although it is sensitive to specific pathological conditions (e.g., micrographia in Parkinson's disease, increased tortuosity in cerebral small vessel disease, and alterations observed in mania, delirium, obsessive-compulsive disorder, and major depressive disorder). Alterations commonly affect kinematic parameters, as well as visuospatial and constructional features. However, no disorder-specific signature pattern emerges from current evidence, largely due to the methodological heterogeneity across studies. CONCLUSIONS: The handwritten signature holds promise as a behavioral marker of brain disorders, serving as a potentially useful, complementary - rather than a stand-alone - indicator of neurological and psychiatric conditions, which could be potentially useful in clinical settings. The implications for forensic applications remain largely theoretical and have not yet been standardized.
30 July 2026
Read appraisal →Brain imaging and behavior
Associations between olfactory dysfunction and structural MRI findings in Parkinson's disease: a systematic review
Olfactory dysfunction is a common and early non-motor symptom of Parkinson's disease (PD). Structural Magnetic Resonance Imaging (MRI) studies have reported changes in olfactory-related brain regions, but findings remain inconsistent. This review synthesizes MRI evidence to clarify neuroanatomical correlates of olfactory dysfunction in PD. We performed a systematic review to find the associations between olfactory dysfunction and structural MRI findings in people with PD. A systematic search in PubMed, Scopus, and Web of Science yielded 20 eligible studies. The eligible studies involved 1,092 patients with PD. Although there were inconsistent regions of interest and types of analysis, we identified structural changes in the olfactory sulcus and bulb, cortical gray matter, hippocampus, parahippocampus, and basal ganglia that are associated with olfactory dysfunction. Olfactory dysfunction in PD is linked to structural changes in primary olfactory, limbic, and cortical regions. These MRI findings may serve as early biomarkers, but standardized, longitudinal studies are needed to confirm their diagnostic or prognostic value.
10 July 2026
Read appraisal →Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Limb apraxia in Parkinson's disease and atypical parkinsonian syndromes: a systematic review
BACKGROUND: Evidence regarding the clinical manifestations, disease-specific profiles and diagnostic significance of limb apraxia in Parkinson's disease and Atypical Parkinsonian Syndromes (APS) is limited. OBJECTIVES: The present systematic review aims to consolidate current knowledge on limb apraxia across neurodegenerative disorders, including Parkinson's disease (PD), corticobasal syndrome (CBS), Progressive Supranuclear Palsy (PSP) and Multiple System Atrophy (MSA). METHODS: A systematic literature review was conducted in accordance with PRISMA guidelines. Studies were included if they enrolled ≥ 10 patients in at least one of the patient groups and ≥ 10 control subjects with quantitative data on apraxic deficits. Risk of bias assessment was assessed. RESULTS: Twenty-two studies met inclusion criteria (PD n = 11; CBS n = 10; PSP n = 7; MSA n = 3). Across PD and APS, praxis assessment primarily involved gesture imitation, pantomime, action sequencing, actual tool use and measures of fine motor coordination. CBS demonstrated the most severe/widespread apraxic impairment, affecting both meaningless and meaningful (transitive and intransitive) gestures, as well as action sequencing and fine motor control. In PD, apraxic deficits were generally milder but shared overlapping features with CBS. Direct comparative studies between PD and CBS remain scarce. PSP was characterized by less frequent and predominantly sequence-related impairments, whereas findings in MSA were heterogeneous and less pronounced. CONCLUSIONS: Limb apraxia phenotypes differ across PD, CBS, PSP and MSA and may contribute to their differential diagnosis. Future research should adopt standardized, multimodal praxis assessment protocols in larger cohorts including all major neurodegenerative parkinsonian disorders, to facilitate the direct comparison of limb apraxia across these diseases.
4 July 2026
Read appraisal →Brain topography
Local Field Potential Recordings Using Deep Brain Stimulation: A Practical Workflow and Open-Source Signal Processing Pipeline
Deep brain stimulation (DBS) systems with electrophysiological recording capabilities offer a unique opportunity to chronically record local field potentials (LFP) from implanted electrodes, enabling real-time monitoring of subcortical neural dynamics and the development of adaptive neuromodulation strategies. However, translating raw LFP into clinically relevant biomarkers remains challenging due to numerous technical considerations. To address this, we share both a practical guide for conducting LFP experiments and BrainWave-DBS, an open-source pipeline that implements the workflow and supports analysis of patient-derived LFP data. The pipeline covers data import, preprocessing, spectral analysis, and visualization, offering a reproducible framework for LFP analysis. Furthermore, we demonstrate the functionality of the pipeline using a representative Parkinson's disease dataset and highlight key technical insights gained through this work. By improving access to neural signal acquisition and analysis, our goal is to foster broader adoption of this technology, which could advance closed-loop neuromodulation of deep brain structures.
29 June 2026
Read appraisal →Journal of robotic surgery
Robot-Assisted versus non-robotic frame-based deep brain stimulation: a systematic review and meta-analysis of targeting accuracy and clinical outcomes
Deep brain stimulation (DBS) outcomes depend on accurate lead placement. Robot-assisted DBS (RA-DBS) has been increasingly adopted, yet its advantages over conventional non-robotic frame-based DBS (NRA-DBS) regarding targeting accuracy, operative efficiency, and clinical outcomes remain debated.To compare RA-DBS versus NRA-DBS for targeting accuracy and clinical outcomes in patients undergoing DBS for movement disorders.This meta-analysis and systematic review was registered in PROSPERO (CRD420261336001) and adhered to PRISMA. Patients with mobility disorders treated with RA-DBS versus frame-based NRA-DBS were included in comparative studies (RCTs and prospective/retrospective cohorts). Targeting accuracy measures (such as target point error, vector error, and radial error) and extreme targeting outliers were the main results. Operative time measurements, perioperative problems (such as cerebral bleeding), and motor improvement (UPDRS-III) were secondary outcomes. Fixed-effects or random-effects models based on heterogeneity were used to compute pooled odds ratios (OR) and weighted mean differences (MD) with 95% confidence intervals (CI). Nine high-quality comparative studies encompassing 495 patients (227 RA-DBS vs. 268 NRA-DBS) were synthesized. RA-DBS significantly minimized target point error (MD = -0.31 mm, 95% CI: -0.61 to -0.01; P = 0.04) and significantly reduced the incidence of clinically significant targeting outliers (OR = 0.15, 95% CI: 0.04 to 0.51; P = 0.002). Comprehensive three-dimensional vector error was marginally lower in the RA-DBS cohort (MD = -0.70 mm; P = 0.05), whereas two-dimensional radial error and total operating room time, surgical duration, anesthesia time, perioperative complications, and 12-month UPDRS-III motor improvements were statistically equivalent between groups. Subgroup analyses revealed that the spatial precision advantage of RA-DBS was geographically robust across East Asian and Western cohorts, whereas chronological efficiency was heavily dependent on the specific robotic platform used.Compared with conventional frame-based stereotaxy, robot-assisted DBS significantly enhances target point precision and reduces electrode deviations. However, these technical accuracy advantages do not translate into overall clinical superiority, as both approaches yield comparable operative efficiency, perioperative safety, and mid-term motor symptom relief.
23 June 2026
Read appraisal →Brain research bulletin
Neural substrates of apathy in Parkinson's disease: A systematic review of structural and functional neuroimaging studies
BACKGROUND: Apathy is a frequent and disabling non-motor symptom in Parkinson's disease (PD), characterized by diminished motivation, reduced goal-directed behavior, and emotional indifference. Growing evidence suggests that apathy in PD represents a distinct neuropsychiatric syndrome that may coexist with depression and global cognitive impairment, while also showing partially dissociable clinical and neural correlates. OBJECTIVE: This systematic review aimed to investigate the neural substrates of apathy in PD by synthesizing evidence from structural and functional neuroimaging studies. METHODS: Following PRISMA guidelines, we searched PubMed, Embase, Web of Science, and Scopus for studies assessing apathy in PD through neuroimaging techniques, including structural MRI, resting-state functional MRI, diffusion tensor imaging, PET/SPECT molecular imaging, and connectivity analyses. Apathy severity was evaluated using validated clinical scales, and findings were compared between PD population with and without apathy, as well as healthy controls. RESULTS: Across 16 heterogeneous studies, recurrent findings implicated structural, functional, and molecular alterations within fronto-striatal-limbic networks. However, differences in apathy measures and neuroimaging modalities limit direct comparability across studies and do not support a single unified imaging signature of apathy in PD. Apathetic PD subjects consistently exhibited reduced gray matter volume and altered spontaneous activity in the dorsolateral, inferior frontal gyri, anterior cingulate cortex (ACC), and nucleus accumbens, alongside disrupted functional and structural connectivity in fronto-limbic tracts. These alterations were significantly correlated with apathy severity and, in several studies, remained detectable after accounting for depressive symptoms or global cognitive status. Furthermore, the available findings suggest that apathy in PD may involve heterogeneous neurobiological mechanisms, including variable involvement of frontal, striatal, and limbic circuits; however, current evidence remains insufficient to support firm transmitter-based subtyping or treatment stratification. CONCLUSIONS: Current evidence suggests that apathy in PD involves partially dissociable neural correlates across prefrontal, striatal, and limbic systems. However, methodological heterogeneity across studies limits strong generalization, and future harmonized longitudinal studies are needed to clarify which findings are robust and clinically meaningful.
16 June 2026
Read appraisal →Lancet (London, England)
Efficacy and safety of intravenous prasinezumab in individuals with early-stage Parkinson's disease on stable symptomatic monotherapy (PADOVA): a phase 2b, multicentre, randomised, double-blind, placebo-controlled study
BACKGROUND: Prasinezumab has previously shown potential for reducing the progression of motor signs (Movement Disorder Society-sponsored Revision of the Unified Parkinson's Disease Rating Scale [MDS-UPDRS] Part III) in patients with early-stage Parkinson's disease who were treatment-naive or receiving monoamine oxidase type B (MAO-B) inhibitors. The aim of the PADOVA trial was to evaluate the efficacy and safety of prasinezumab in a broader population of patients receiving stable symptomatic medication. METHODS: This phase 2b, multicentre, double-blind, parallel-group, placebo-controlled, randomised, superiority trial recruited participants with early-stage Parkinson's disease (age 50-85 years, 3 months to 3 years from diagnosis, Hoehn and Yahr stage 1 or 2) on stable symptomatic medication from 110 centres in nine countries in Europe and North America. Participants were individually randomly assigned (1:1) via permuted blocks (stratified by symptomatic medication [levodopa or MAO-B inhibitor]) to intravenous prasinezumab (1500 mg) or placebo every 4 weeks for at least 76 weeks and until the target number of motor progression events was reached. Participants, investigators, and clinical assessors were masked to group assignment. The primary endpoint was time to a confirmed motor progression event (≥5-point increase in MDS-UPDRS Part III off-medication score), assessed in the full analysis set (all randomly assigned participants according to the treatment to which they were assigned). Safety and tolerability were assessed in all randomly assigned participants who received at least one dose of study drug, with participants grouped according to treatment received. The trial is registered with ClinicalTrials.gov (NCT04777331) and EudraCT (2020-004997-23), and is active, not recruiting. FINDINGS: Between May 5, 2021, and March 22, 2023, 787 individuals were screened. 586 were enrolled and randomly assigned (n=293 per group; mean age 64·2 years [SD 7·3]; 214 [37%] female and 372 [63%] male); 550 completed double-blind treatment (prasinezumab, n=277; placebo, n=273). The primary endpoint was not met; the primary analysis showed a non-significant delay in motor progression with prasinezumab versus placebo (hazard ratio 0·84 [95% CI 0·69-1·01]; p=0·066); median time to confirmed motor progression in the prasinezumab group was 61·1 weeks (95% CI 52·3-71·9), compared with 49·7 weeks (40·1-58·1) in the placebo group. The incidence of one or more serious adverse events was similar between groups (prasinezumab, 34 [12%] of 292; placebo, 34 [12%] of 290) and three recorded deaths were unrelated to the study drug (prasinezumab, n=1 [<1%]; placebo, n=2 [1%]). INTERPRETATION: Although PADOVA did not meet the primary endpoint, prespecified exploratory evidence suggests clinical activity of prasinezumab in early-stage Parkinson's disease, supporting continued investigation in the ongoing phase 3 PARAISO trial (NCT07174310). FUNDING: F Hoffmann-La Roche.
1 June 2026
Read appraisal →Journal of neurology
Artificial intelligence for gait and balance in neurological disorders: a scoping review of clinical applications and technologies
BACKGROUND: Artificial intelligence (AI) has rapidly emerged within healthcare systems and neurological rehabilitation with the potential to revolutionize clinical decision-making and therapeutic strategies. However, a comprehensive understanding of how AI is currently applied to gait and balance rehabilitation in stroke, Parkinson's disease (PD), and multiple sclerosis (MS) is still lacking. OBJECTIVE: To map the current use of AI in neurological rehabilitation, focusing on clinical purposes, geographical distribution, and applied technologies for gait and balance rehabilitation. METHODS: Following the PRISMA-ScR statement, we conducted a literature search through MEDLINE, Cochrane CENTRAL, EMBASE, and Google Scholar up to July 2025 to identify studies applying AI-based methods to gait and balance outcomes in adults with stroke, PD, or MS. Study characteristics, AI methods, validation strategies, clinical purpose, and motor outcomes were extracted and synthesized narratively. RESULTS: Eighteen studies published from 2009 to 2025 were included. Most studies were conducted in Asia (50%) and involved people with stroke (77.8%). AI was predominantly used for prognostic purposes (72.22%), such as predicting falls, gait recovery, or treatment response and diagnostic applications (33.3%). Machine learning was the most common approach (88.9%) with Random Forest, Support Vector Machine, logistic regression, and eXtreme Gradient Boosting being the most frequently applied algorithms. None of the included studies performed prospective or external validation on independent datasets. CONCLUSIONS: This scoping review provides a comprehensive overview of current AI applications, highlighting promising but still immature approaches in the neurological rehabilitation of gait and balance. However, substantial methodological limitations remain major barriers to clinical translation.
30 May 2026
Read appraisal →Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
How can social cognition be improved in neurological patients? a systematic review.
BACKGROUND: The neural network underlying social cognition (SC) may be vulnerable to different types of lesions, but also amenable to recovery through interventions that stimulate brain plasticity. This review assessed current non-pharmacological interventions (NPIs) and their effects on SC in neurological patients. METHODS: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Randomized controlled studies, cohort studies, cross-sectional studies, case series, case reports, and literature reviews were included if they reported a precise description of the NPI in subjects older than 6 years, with brain or cerebellar lesion. RESULTS: Among 5.077 screened articles, 17 fulfilled the eligibility criteria. These articles provided 19 face-to-face, online or hybrid methods, involving 344 patients with multiple sclerosis, stroke, Parkinson disease, cerebellar ataxia, traumatic brain injuries or mixed acquired brain injuries. The methods were applied in observational and randomized study designs using group or individual settings, involving SC, general cognition, and relational aspects. These NPIs, classifiable into training, rehabilitation or combined interventions, improved SC in patients with various diagnosis and age. CONCLUSIONS: Results show that NPIs for SC in neurological patients is being addressed with insightful methods and study designs with improvement possibility in children and adults suffering different pathologies. This is not sufficient for thorough consensus but can trigger a range of broader high-quality and interdisciplinary clinical and research applications.
27 May 2026
Read appraisal →Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Genetic Creutzfeldt-Jakob disease associated with 5-octapeptide repeat insertion in the PRNP gene: case and pedigree report and literature review
BACKGROUND: Genetic prion diseases caused by octapeptide repeat insertions in the PRNP gene are rare. 5-octapeptide repeat insertion (5-OPRI) is an uncommon subtype that usually manifests as Creutzfeldt-Jakob disease (CJD) but shows marked variability in clinical phenotype and disease course. DISCUSSION: We report a patient with rapidly progressive gCJD caused by a 5-OPRI mutation. A systematic PubMed review identified genetically confirmed 5-OPRI cases with available clinical data. Demographic characteristics, clinical features, ancillary investigations, disease course, and PRNP codon 129 polymorphisms were analyzed. A total of 25 patients from 14 families were included. Age at onset ranged from 26 to 63 years (mean 44.8 ± 9.9 years). Disease duration ranged from 4 to 192 months. Dementia was present in all patients, and 84% showed frontotemporal dementia-like features. Cerebellar signs, extrapyramidal symptoms, and myoclonus occurred in 68%, 60%, and 44% of patients, respectively. Periodic sharp wave complexes were detected in 29.4% of EEGs, and cerebral atrophy was observed in all patients with neuroimaging. Most patients carried the MM genotype at PRNP codon 129 (83.3%). A short disease course was associated with more frequent akinetic mutism and myoclonus, while MM carriers had a younger age at onset than MV carriers. CONCLUSIONS: 5-OPRI-associated CJD exhibits marked heterogeneity in clinical and disease duration. The PRNP codon 129 polymorphism appears to influence disease onset and progression.
26 May 2026
Read appraisal →Journal of rehabilitation medicine
The effect of combined motor and cognitive rehabilitation on motor performance in Parkinson's disease: a systematic review and meta-analysis
OBJECTIVE: To evaluate the effectiveness of sequential and simultaneous motor and cognitive treatment on motor functions, activities of daily living, and quality of life in people with Parkinson's disease. DESIGN: Systematic review and meta-analysis. SUBJECTS/PATIENTS: Patients with Parkinson's disease. METHODS: A search was conducted in PubMed, Embase, Scopus, Web of Science, and Cochrane Library. Functional mobility was assessed as the main outcome, and balance, gait, activities of daily living, and quality of life as secondary outcomes. Meta-analyses were conducted using mean difference or standardized mean difference with 95% confidence intervals and fixed or random effect models. Heterogeneity was explored, setting a cut-off value of I2 = 50%. RESULTS: Sixteen studies were included, with 8 -eligible for meta-analysis. Results showed that sequential combined treatment offered no clear advantage over motor rehabilitation alone for functional mobility, although a significant benefit was found for activities of daily living. Results on simultaneous combined treatment suggested improvements in quality of life, but no significant differences between treatments for functional mobility. CONCLUSION: Motor-cognitive approaches may enhance prefrontal cortex efficiency, supporting complex motor tasks and reducing the risk of falls. Future research should elucidate neural mechanisms and compare simultaneous and sequential strategies to develop personalized, multidisciplinary rehabilitation protocols.
26 May 2026
Read appraisal →Chemico-biological interactions
Carbon quantum dots exacerbate Parkinson's disease-like pathology through microglia-mediated neuroinflammatory responses with toxicological implications
The global burden of Parkinson's disease (PD) is projected to double by 2050, with early-onset cases demonstrating accelerated progression and limited therapeutic options. Recently, carbon quantum dots (CQDs) emerge as promising nanoplatforms for PD theragnostic, but their paradoxical role in exacerbating neuroinflammation and neurodegeneration shows the urgent need for mechanistic safety evaluations to bridge their therapeutic potential and neurotoxic risks. This study conducted a neuro-safety assessment of CQDs based on MPP+-induced mice and cell PD models to stimulate the theragnostic scenarios of CQDs in PD patients in the real-world. The results showed that CQDs not only promoted the onset and progression of PD-like damages in mice and cells but also exacerbated PD-related neurological dysfunction and structural damages in PD models. The microglia-mediated neuroinflammatory reactions were identified to be pivotal mediators of CQDs exacerbating PD-like damages based on machine learning (ML) approaches. According to these key toxic targets, we established molecular docking technology and network pharmacology to propose interventional strategies, including functional modification of CQDs and anti-neuroinflammatory drugs to alleviate the exacerbation of PD-like damages induced by CQDs, thereby ensuring the safe application of CQDs in the diagnosis and treatment of PD.
25 May 2026
Read appraisal →Journal of neurology
External sensory cueing on gait in Parkinson's disease: a systematic review and network meta-analysis
OBJECTIVE: This systematic review and network meta-analysis compares the individual and synergistic efficacy of external sensory cueing modalities to establish a treatment hierarchy for optimizing spatiotemporal gait parameters in individuals with Parkinson's disease (PD). METHODS: A systematic literature search was conducted across Scopus, PubMed, Cochrane CENTRAL, and ClinicalTrials.gov. Randomized controlled trials (RCTs) evaluating visual, auditory, somatosensory, or combined cueing modalities in individuals with PD were eligible. Trials were required to compare at least two active cueing modalities or an active modality against a control condition and report gait velocity and/or stride length. RESULTS: Thirty-three RCTs (n = 1118 participants) were included. For gait velocity, somatosensory (MD = 0.12 m/s; 95% CI 0.04-0.19) and visual cues (MD = 0.11 m/s; 95% CI 0.02-0.20) demonstrated significant improvements over control. For stride length, visual (MD = 11.46 cm; 95% CI 6.40-16.51), somatosensory (MD = 10.74 cm; 95% CI 7.04-14.44), and auditory cues (MD = 5.25 cm; 95% CI 0.43-10.06) all yielded statistically significant benefits. P-score rankings identified somatosensory cues as the top-ranked modality for gait velocity (P-score = 0.71) and visual cues for stride length (P-score = 0.83). Global heterogeneity was substantial (I2 = 64-90%), and no significant publication bias was detected. CONCLUSIONS: External sensory cueing improves spatiotemporal gait parameters in PD, with somatosensory and visual cues emerging as the most effective modalities for enhancing gait velocity and stride length. Both modalities outperformed standalone auditory stimulation, providing a data-driven hierarchy to guide evidence-based cueing selection in clinical practice.
24 May 2026
Read appraisal →Journal of neurology
A machine learning-derived speech index as a biomarker for Huntington's disease severity
BACKGROUND: The development of disease-modifying therapies for Huntington's disease (HD) necessitates sensitive, scalable, and objective biomarkers for patient stratification and tracking. Current clinical scales are rater-dependent and time-consuming, while neuroimaging is costly and inaccessible. We aim to develop and validate a novel Speech Index, derived from automated acoustic analysis, to stratify HD stages and predict the severity of disease. METHODS: We recruited 141 HTT gene carriers (37 premanifest, 104 manifest HD) and 69 healthy controls. Participants read a standardized passage, and the recordings were processed to extract 28 speech features. A composite Speech Index was constructed using Bootstrap LASSO Regression for feature selection. Its performance was validated against the HD stages, clinical scale scores and the volume of the caudate and putamen from MRI. RESULTS: The Speech Index significantly increased across HD stages (p < 0.001). The Index showed strong correlations with clinical measures (cUHDRS: ρ = -0.67; TMS: ρ = 0.57; SDMT: ρ = -0.63; all p < 0.001) and neuroimaging biomarkers (caudate: ρ = -0.55; putamen: ρ = -0.62; all p < 0.001). Generalized additive models confirmed the Index's high predictive value for these outcomes (pseudo-R2 from 0.430 to 0.596). CONCLUSION: We developed a fully automated, interpretable Speech Index that serves as a valid digital biomarker for HD severity. It holds promise for remote monitoring, clinical trial enrichment, and objective assessment of therapeutic efficacy.
23 May 2026
Read appraisal →JMIR formative research
Comparing Stakeholders' Perspectives on Parkinson Disease Management and Digital Technologies: Exploratory International Survey
BACKGROUND: Parkinson disease (PD) is a progressive neurodegenerative disorder that poses complex challenges for persons with PD, informal caregivers, and health care professionals. With growing interest in digital and predictive artificial intelligence (AI) tools for disease management, understanding the needs and digital readiness of these stakeholder groups is crucial. OBJECTIVE: This work aims to (1) identify digital practices for PD management among persons with PD, at-risk individuals, caregivers, and health care professionals; (2) compare these practices across groups; (3) explore stakeholder desires for AI-based tools; and (4) assess alignments and gaps to inform tailored AI solutions. METHODS: An anonymous cross-sectional online survey of an exploratory nature was distributed (from December 2024 to October 2025) in 5 languages and completed by 255 respondents. Descriptive statistics summarized responses to 41 questions, including stakeholder-specific items. χ2 tests were performed to examine stakeholder differences in desired AI features. RESULTS: Interest in predictive AI was high across stakeholder groups. Symptom tracking was the most desired feature (selected by more than 76% of the respondents), and personalized treatment recommendations came second for both persons with PD and health care professionals; however, stakeholder priorities diverged in other areas. Health care professionals rated improving patient and informal caregiver engagement as significantly more important than persons with PD did, χ21 (n=205)=34.78, P<.001, and Cramer V=0.41. Despite considerable interest, the reported use of digital tools was limited, as most persons with PD did not use symptom-tracking apps or wearables, nor were they currently monitoring their condition, although many expressed intentions to begin. CONCLUSIONS: While predictive AI tools were viewed positively across groups, there were significant gaps in stakeholder preferences, highlighting the importance of tailored, context-aware design. Early diagnosis was not prioritized by persons with PD or health care professionals, likely reflecting the complexity of diagnosing PD in the absence of disease-modifying therapies. Coupled with the emphasis placed on preventive lifestyle guidance by persons with PD and those at risk, this highlights the importance of actionability in AI-based monitoring and prediction. Such actionability may also enhance perceived relevance and uptake, given that reported interest in digital health tools and self-tracking exceeded actual use. These findings offer early-stage insight to guide the development of future AI-based solutions for PD.
21 May 2026
Read appraisal →Neurosurgical review
Short-and long-term responsiveness of deep brain stimulation on motor and cognitive outcomes in GBA vs. Non-GBA parkinson's disease: a systematic review and meta-analysis of observational studies
Deep brain stimulation (DBS) is an established therapy for motor complications in Parkinson's disease (PD). Patients carrying glucocerebrosidase (GBA) mutations exhibit distinct disease trajectories, raising questions regarding potential differences in clinical outcomes following DBS compared with non-carriers. To evaluate short- and long-term motor, medication, and cognitive outcomes following DBS in patients with GBA-PD compared with non-GBA PD. We conducted a systematic review and meta-analysis of studies reporting clinical outcomes in PD patients with and without GBA mutations who underwent DBS and had a minimum follow-up of one year. Random-effects inverse variance models were applied, with subgroup analyses according to GBA status. DBS was associated with significant improvements in motor function in the off-medication state and sustained reductions in levodopa equivalent daily dose in both GBA carriers and non-carriers, with no significant between-group differences. Cognitive performance declined over long-term follow-up in both groups. At five years, greater cognitive decline, assessed using the Mattis Dementia Rating Scale, was observed among GBA-PD mutation carriers compared with non-carriers. Motor improvement and medication reduction following DBS were comparable between PD patients with and without GBA mutations. Over long-term follow-up, greater cognitive decline was observed among GBA-PD carriers.
21 May 2026
Read appraisal →Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Parkinson disease severity detection based On OPtFuzNet with fused features
BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disorder affecting millions of people worldwide. It severely impairs patients' mobility. For effective treatment strategies, it is essential to determine the severity of the disease at an early stage. METHODS: In this study, an optimized feature-fusion framework is developed to detect the severity of Parkinson's disease using gait data via an Optimized Fuzzy Neural Network (OPtFuzNet). This feature-fusion framework can be categorized into three stages: pre-processing, feature extraction, and classification. In the pre-processing stage, a median filter is employed to reduce noise present in the gait images. During feature extraction, local and global features of the gait images are captured using SAE and IDCN, respectively. Subsequently, these features are fused and fed into the OPtFuzNet classifier, where parameter optimization is performed using IGWO-Lévy. RESULTS: The proposed model is evaluated on the GAIT-IT and GAIT-IST benchmark datasets using standard metrics, achieving superior performance with accuracies of 98.08% and 98.12%, respectively. Furthermore, a feature importance analysis is conducted to identify the most influential gait characteristics that contribute to determining the severity of the impairment, thereby enhancing the clinical interpretability of the model.The proposed model is evaluated on the GAIT-IT and GAIT-IST benchmark datasets using standard metrics, achieving superior performance with accuracies of 98.08% and 98.12%, respectively. Furthermore, a feature importance analysis is conducted to identify the most influential gait characteristics that contribute to determining the severity of the impairment, thereby enhancing the clinical interpretability of the model. CONCLUSION: These results validate the efficacy of the proposed feature fusion and optimization strategy in identifying discriminative gait patterns associated with the severity of Parkinson's disease. However, as the datasets are based on simulated gait patterns rather than real clinical data, further validation on real-world datasets is necessary for practical applicability.
20 May 2026
Read appraisal →Cerebellum (London, England)
Inhibitory Circuits of the Sensorimotor Network are Not Modulated By Cerebellar Transcranial Direct Current Stimulation in Isolated Cervical Dystonia
Impaired cerebellar influence on motor cortical excitability and plasticity has been reported in cervical dystonia (CD) patients, accompanied by the absence of cerebellar brain inhibition (CBI). Polarity-specific modulation of CBI in healthy individuals using cerebellar transcranial direct current stimulation (ctDCS) suggested that ctDCS could normalize abnormal cerebellar output and improve clinical symptom severity in CD. The objective of this study was to determine whether anodal or cathodal ctDCS can modulate neurophysiological parameters of cortico-cortical, cerebello-cortical or afferent inhibition and improve motor symptom severity in CD patients. Fifteen patients with isolated CD participated in a randomized, double-blinded crossover study consisting of three sessions of anodal, cathodal, or sham ctDCS. Before and after each intervention, motor symptom severity and inhibitory circuits of the sensorimotor network were investigated using transcranial magnetic stimulation (TMS), including short-interval intracortical inhibition (SICI), short-latency afferent inhibition (SAI) and CBI. Baseline TMS measurements showed inhibitory influence of SICI (p < 0.001) and SAI (p < 0.001) in CD patients, whereas CBI had no inhibitory effect (p = 0.281). The different ctDCS interventions caused no significant modulation in any of the inhibitory TMS paradigms investigated. Similarly, motor symptom severity remained unchanged after the ctDCS interventions. A single session of ctDCS was not effective to modulate inhibitory circuits of the sensorimotor network in isolated CD patients. Future studies focusing on repetitive ctDCS interventions or multifocal stimulation protocols are needed to assess the influence on network excitability and connectivity as well as on motor symptoms.
18 May 2026
Read appraisal →Journal of molecular neuroscience : MN
Transcriptomic Analysis and Multiple Machine Learning Approaches Identify ZDHHC20 and Its Highly Correlated Gene AK5 as Biomarkers in Multiple System Atrophy
Multiple system atrophy (MSA) is a fatal neurodegenerative disorder lacking effective diagnostic tools. While protein palmitoylation is crucial for neuronal function, its specific role in MSA pathogenesis remains unexplored. We integrated bulk and single-nucleus RNA sequencing (snRNA-seq) data from postmortem MSA brain tissues. Eight machine learning algorithms were utilized to screen palmitoylation-related genes. Downstream analyses, including functional enrichment, cellular deconvolution, and pseudotime trajectory inference, were then conducted. ZDHHC20 and its highly correlated gene, AK5, were identified as hub genes. Both demonstrated significant downregulation in MSA, particularly within the cerebellar white matter. Functional enrichment analysis linked this expression pattern to mitochondrial dysfunction and impaired energy metabolism. Furthermore, snRNA-seq revealed that ZDHHC20 and AK5 are predominantly expressed in oligodendrocytes and exhibit lower expression levels along the developmental trajectory in MSA compared to healthy controls. ZDHHC20 and AK5 represent promising biomarkers for MSA. These findings provide new insights into the diagnosis and treatment of MSA.
18 May 2026
Read appraisal →Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
When bad turns good: a systematic review on cholesterol and LDL in longitudinal patient cohorts with Parkinson's disease
BACKGROUND: While the aetiology of Parkinson's disease (PD) involves genetic and environmental factors, emerging evidence has suggested a surprising link between lipid metabolism - particularly serum total cholesterol (TC) and low density lipoprotein cholesterol (LDL-C) - and the pathogenesis of PD. Cholesterol plays a vital role in neuronal membrane integrity, myelination, and synaptic function. However, its peripheral concentration and regulatory mechanisms in the central nervous system (CNS), remain incompletely understood in the context of PD. OBJECTIVE: This review aims to systematically examine the current literature on the relationship between TC and LDL-C with the risk and progression of PD in longitudinal patient cohorts. METHODS: A systematic literature search was conducted using PubMed with the keywords "Parkinson's disease" AND "cholesterol" and "Parkinson's disease" AND "LDL." Inclusion criteria encompassed English-language longitudinal human studies published before October 2024, with data on cholesterol levels in relation to PD incidence or progression. Fourteen studies met the eligibility criteria. RESULTS: Twelve of the 14 included studies reported an inverse association between lower serum total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) levels and increased risk for PD onset as well as faster disease progression. Notably, this pattern was not uniform across all subgroups: age, sex, BMI, and statin use modulated the strength and direction of associations. CONCLUSION: Despite some heterogeneity across studies, there is growing evidence that lower TC and LDL-C may be associated with a higher risk and more rapid progression of PD. Future research should focus on mechanistic studies and stratified analyses to clarify whether and how cholesterol modulation could contribute to neuroprotective strategies in PD.
15 May 2026
Read appraisal →Annals of human biology
Machine learning combined with WGCNA reveals potential calcium uptake-associated biomarkers in Parkinson's disease
BACKGROUND: Parkinson's disease (PD) is the second most common neurodegenerative disease, characterised by progressive loss of dopaminergic neurons in the substantia nigra pars compacta. Although previous studies have suggested a correlation between calcium signal disruption and the development of PD, the role of genes associated with store-operated calcium entry (SOCE) in PD remains unclear. AIM: To combine machine learning methods with Weighted Gene Co-expression Network Analysis (WGCNA) to systematically screen and identify SOCE-associated candidate genes and evaluate their potential for assisting in discrimination. SUBJECTS AND METHODS: This study is based on the GSE6613 dataset, using ssGSEA and Weighted Gene Co-expression Network Analysis (WGCNA) to screen for co-expression modules related to SOCE, and combining LASSO, SVM-RFE, and random forest algorithm to identify feature genes. Subsequently, validation was conducted in GSE20163 and GSE22491, and in vitro experiments were carried out in 6-OHDA and MPP+ models of dopaminergic neurons derived from LUHMES. RESULTS: A total of 5 SOCE-associated feature genes (LPCAT3, CLCNKB, TXLNA, etc.) were identified, and their combined model showed moderate discriminative ability in external validation. Immune analysis showed immune dysfunction in PD patients, and in vitro experiments also observed consistent expression trends with patient samples. CONCLUSIONS: In summary, this study identified potential PD feature genes associated with SOCE, providing clues for further exploration of the molecular mechanisms of SOCE-associated calcium signalling in PD.
15 May 2026
Read appraisal →Experimental brain research
Subthalamic nucleus deep brain stimulation and associations with attention and processing speed in Parkinson's disease
Although subthalamic nucleus deep brain stimulation (STN DBS) is an effective treatment for the motor symptoms of Parkinson's disease (PD), its effects on cognitive functions are controversial. This cross-sectional study aimed to compare attention and processing speed in PD patients with STN-DBS and those receiving medical therapy, using a multimodal assessment combining P300 event-related potentials and neuropsychological tests. The study included 20 PD patients who underwent STN DBS and 17 PD patients who were followed with medical treatment. Demographic and clinical data for all patients were recorded. Cognitive functions were assessed using the P300 potential, the Stroop test (ST), and the Serial Digit Learning Test (SDLT). P300 potential latency and amplitude values, as well as neuropsychometric test results, were statistically compared between the two groups. P300 latency was shorter in the DBS-treated group than in the non-DBS group (p = 0.004). Performance times on Part III of the ST were shorter in the DBS-treated group (p = 0.03). In addition, a higher proportion of patients in the DBS-treated group performed normally on Part I of the ST compared to the non-DBS group (p = 0.03). There was no significant difference between the two groups in SDLT results. Shorter P300 latency and subtle differences in ST performance suggest a potential association between STN-DBS and the cognitive domains of attention and processing speed. Combining neuropsychological and electrophysiological assessments could provide a more comprehensive evaluation, and future large-scale, longitudinal studies are needed to clarify domain-specific cognitive effects.
14 May 2026
Read appraisal →Cerebellum (London, England)
Quantitative Ocular Motor / Vestibular Assessment in Patients with Spinocerebellar Ataxia Type 3 (SCA3, Machado Joseph Disease) - Systematic Review of the Literature
Spinocerebellar ataxia type 3 (SCA3 or Machado-Joseph disease) is the second most common autosomal-dominant hereditary ataxia and often presents with ocular motor and vestibular impairment. The value of ocular motor testing for early disease detection, monitoring disease progression and as a potential treatment biomarker has been acknowledged in several studies. This systematic review aims to summarise the current evidence supporting quantitative eye movement testing in SCA3. Studies reporting on quantitative ocular motor and/or vestibular measurements in SCA3 were searched for in MEDLINE and Embase. Thirty studies reporting on 432 SCA3 patients (including 64 pre-symptomatic carriers) were included. Information on various ocular motor parameters were extracted and correlations with other parameters (including clinical scales, imaging, and genetic testing) were assessed. Ocular motor abnormalities observed comprised (horizontal) pursuit eye-movement (PEM) gain reduction (14/19 patients), saccadic intrusions (principally square-wave jerks (SWJ, 29/45)), gaze-evoked nystagmus (GEN, 65/82), and rebound nystagmus (8/10). Additionally, saccades to target displayed increased latency (13/29), reduced peak velocity (16/49) and dysmetria (33/49). Vestibular deficits measured included vestibulo-ocular reflex (VOR) gain-reductions during quantitative head-impulse testing (qHIT, 117/133) and abnormal responses during caloric irrigation (7/9), impaired visually-enhanced VOR-responses (5/6), and impaired cervical (19/66) and ocular (10/14) vestibular-evoked myogenic-potential testing. In summary, impaired VOR-gains (qHIT), GEN, horizontal PEM-gain decreases, dysmetric saccades, and SWJ were most frequently reported and therefore seem most suitable as potential disease markers. The quantitative ocular motor/vestibular assessment may facilitate early diagnosis, distinction of disease stages and also potentially allow monitoring of disease progression and treatment response.
14 May 2026
Read appraisal →Cerebellum (London, England)
Novel Imaging Phenotype in Spinal Cerebellar Ataxia Type 8: Symmetrical White Matter Changes without Cerebellar Atrophy
Spinal Cerebellar Ataxia Type 8 (SCA8) is a rare autosomal dominant neurodegenerative disorder characterized by progressive cerebellar dysfunction. It is caused by pathogenic expansions of a CTG/CAG trinucleotide repeat sequence within the ATXN8OS/ATXN8 gene locus on chromosome 13q21. Although cerebellar atrophy is widely recognized as a cardinal neuroimaging feature of SCA8, the phenotypic spectrum remains incompletely characterized. This study identified two cases of SCA8 through genetic analysis. Pedigree information was gathered and analyzed for all available family members. A systematic literature review was conducted to identify all published SCA8 cases with available neuroimaging data. The distinctive clinical and radiological features of SCA8 were analyzed through detailed case characterization integrated with a comprehensive review of existing literature. We report two genetically confirmed SCA8 cases exhibiting a previously undescribed neuroimaging phenotype. Case 1: A 36-year-old woman presented with a one-year history of progressive gait ataxia. Brain MRI revealed confluent, symmetric white matter signal abnormalities without cerebellar atrophy. Repeat expansion analysis detected a pathogenic CTG/CAG expansion of 9/77 in the ATXN8 gene. Case 2: A 64-year-old man (father of case 1) exhibited significant gait abnormalities, cognitive impairment and dysarthria. Brain MRI showed symmetric white matter lesions similar to case 1, with a CTG/CAG repeat length of 17/73. Notably, our systematic review revealed no prior reports of SCA8 presenting with isolated, symmetric white matter abnormalities in the absence of cerebellar atrophy. These findings delineate a novel neuroimaging phenotype of SCA8, characterized by symmetric white matter alterations without cerebellar volume loss. This atypical presentation expands the radiological spectrum of SCA8 and underscores the importance of considering repeat expansion disorders in the differential diagnosis of leukoencephalopathies, even in the absence of classic neurodegenerative imaging signatures.
13 May 2026
Read appraisal →Neurosurgical review
Deep brain stimulation for freezing of gait in Parkinson's disease: An updated systematic review, meta-analysis, and a single-center clinical experience.
Freezing of gait is a disabling and treatment-resistant manifestation of Parkinson's disease (PD). The effectiveness of deep brain stimulation (DBS) for freezing of gait remains inconsistent across stimulation targets, frequencies, and medication states. We conducted a systematic review and meta-analysis following PRISMA guidelines to examine how DBS affects freezing of gait in patients with PD. We searched Medline, Scopus, Web of Science, and Cochrane up to September 28, 2025. For synthesis, we combined mean differences and 95% confidence intervals for the Freezing of Gait Questionnaire (FOG-Q) and the Unified Parkinson's Disease Rating Scale (UPDRS) part III across different medication and stimulation settings to calculate the final effect size. Thirty-one studies with 905 patients were included. Of these, 21 provided FOG-Q data, and all reported UPDRS-III results. DBS led to a modest decrease in FOG-Q scores (mean difference [MD] = - 2.99; 95% CI = - 5.69 to - 0.29). The biggest improvement in FOG was seen when stimulation was used while patients were off medication (Med-OFF/Stim-OFF vs. Med-OFF/Stim-ON: MD - 5.88; 95% CI - 9.28 to - 2.47). Stimulation during the medication-ON state had smaller effects (Med-ON/Stim-OFF vs. Med-ON/Stim-ON: MD - 2.65; 95% CI - 4.99 to - 0.32), and there was no significant benefit when comparing Med-ON/Stim-OFF to Med-OFF/Stim-ON (MD - 0.70; 95% CI - 3.88 to 2.48). UPDRS-III scores improved substantially in the medication-OFF state with stimulation (MD - 14.35; 95% CI - 17.39 to - 11.32). High-frequency stimulation targeting the subthalamic nucleus provided more consistent benefits, yet substantial variation persisted across studies. The results of our small cohort showed significant improvement in FOG-Q and UPDRS-III (P values = 0.034, 0.022, respectively). DBS improves freezing of gait primarily in the medication-OFF state, with greater effects observed using high-frequency stimulation and subthalamic nucleus targets. Significant heterogeneity and limited data for alternative targets warrant cautious interpretation and further controlled studies.
13 May 2026
Read appraisal →Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Efficacy and safety of GLP-1 receptor agonists in Parkinson's disease: a systematic review and meta-analysis of randomized clinical trials
BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disorder with no proven disease-modifying therapies to date. Because changes in cerebral glucose metabolism and insulin resistance have been linked to PD pathophysiology, glucagon-like peptide-1 receptor agonists (GLP-1RAs), widely used for diabetes, have been investigated as potential neuroprotective treatments. METHODS: This study systematically assessed the efficacy and safety of GLP-1RAs in PD through a systematic review and meta-analysis of randomized controlled trials identified in PubMed, Embase, and the Cochrane Library. The primary outcomes were motor function improvements measured by the MDS-UPDRS Part III in both on- and off-medication states at study endpoints and at intermediate timepoints of interest. Secondary outcomes included MDS-UPDRS Parts I, II, and IV, quality of life assessed by the PDQ-39, levodopa equivalent daily dose (LEDD), and the occurrence of adverse events. RESULTS: The meta-analysis found no statistically significant difference in favor of GLP-1RAs over placebo for motors and non-motors outcomes, except for PDQ-39 (MD: - 0.75; 95% CI: [- 1.34, - 0.17], P = 0.01). Regarding safety, GLP-1RAs were associated with a higher incidence of adverse events, especially gastrointestinal effects such as nausea, vomiting, and constipation. CONCLUSIONS: Overall, current evidence does not demonstrate consistent clinical benefit of using GLP-1RAs for treating motor or non-motor symptoms in PD nor support GLP-1RAs as disease-modifying therapy, underscoring the need for further research.
13 May 2026
Read appraisal →Journal of neurology
Identifying diagnostic biomarkers in functional motor disorders through multimodal behavioral, neurophysiological, and imaging assessment using explainable machine learning
BACKGROUND: Functional motor disorders (FMDs) represent a frequent and disabling neurological condition. The lack of reliable diagnostic biomarkers and their heterogeneity might affect diagnosis. We identified multimodal biomarkers distinguishing FMDs from healthy controls (HCs) using machine-learning approaches. METHODS: In this multicenter cross-sectional study, consecutive adults with a clinically established FMDs diagnosis (n = 75, 74.7% female; mean age 44.20 ± 12.92) and age- and sex-matched HCs (n = 75; 58.6% female; 48.42 ± 11.67) were recruited. All participants underwent standardized behavioral, neurophysiological, and brain MRI assessment exploring motor, exteroceptive, and interoceptive domains. A Random Forest (RF) classifier combined with repeated stratified k-fold cross-validation was trained on the collected features. Predictive performance was evaluated using accuracy, sensitivity, specificity, precision, F1-score, and AUC-ROC. SHapley Additive exPlanations interpreted feature importance. RESULTS: The strongest diagnostic biomarkers were lower dual-task effect scores for postural sway area under eyes-closed motor and cognitive conditions, and gait speed during the motor dual-task, followed by increased vDMN and basal ganglia networks functional connectivity, reduced baseline ipsilateral-contralateral R2 blink reflex area, and higher DNIC-to-baseline N2P2 amplitude ratios for the lower limb. The RF classifier achieved robust performance (accuracy 85.0%, sensitivity 83.9%, specificity 86.1%, F1-score 85.7%, AUC-ROC 0.921). CONCLUSIONS: Motor, functional neuroimaging, and neurophysiological markers demonstrated diagnostic value in distinguishing FMDs from healthy controls, addressing the current lack of objective tools and supporting more confident and accurate diagnosis of these heterogeneous conditions. TRIAL REGISTRATION: Trial registration number NCT06328790. Registered on 26 March 2024.
3 May 2026
Read appraisal →Journal of medical Internet research
Effects of a Soft Robotic Exoskeleton for Gait Training on Clinical Outcomes in Patients With Parkinson Disease: Randomized Controlled Pilot Study
BACKGROUND: Balance and gait disorders in Parkinson disease (PD) impair motor function and quality of life. OBJECTIVE: Evidence on soft exoskeleton robots (SERs) for PD rehabilitation is limited. This study evaluated the impact of SERs on motor dysfunction in PD. METHODS: A total of 56 people with PD (July 2023 to May 2024) were randomized to 2 groups: the control group (n=25, 44.6%) received conventional rehabilitation, and the experimental group (n=31, 55.4%) received conventional rehabilitation combined with SER training (ChiCTR2500111990). Training occurred 5 times per week for 20 minutes each session over 4 weeks. Primary outcomes included gait speed and stride length, while secondary outcomes assessed the percentage of swing phase, ankle joint range of motion, Unified Parkinson Disease Rating Scale total and motor scores, and Montreal Cognitive Assessment. Paired sample t tests (2-tailed) were used for within-group pre- and postintervention comparisons, and independent sample t tests (2-tailed) were used for between-group comparisons. Correlation analyses were conducted between gait parameters and improvements in ankle mobility. RESULTS: After 4 weeks, the experimental group showed significant improvements in gait and balance. Specifically, left stride length increased by a mean of 0.15 (SD 0.16; 95% CI 0.09-0.21) m (P<.001), right stride length by a mean of 0.15 (SD 0.15; 95% CI 0.10-0.21) m (P<.001), left ankle dorsiflexion by a mean of 2.84 (SD 1.46; 95% CI 2.32-3.36) degrees (P<.001), left swing phase percentage by a mean of 1.56% (SD 3.05%; 95% CI 0.44-2.68; P=.01), and right swing phase percentage by a mean of 1.6% (SD 2.72%; 95% CI 0.62-2.62; P=.002). The Unified Parkinson Disease Rating Scale Part III total score decreased by a mean of 2.80 (SD 3.98) points, and balance subscale scores decreased by a mean of 0.40 (0.58) points (P<.001). Montreal Cognitive Assessment scores increased by a mean of 1.23 (1.23; 95% CI 0.77-1.68) points (P<.01), and Barthel Index scores increased by a mean of 6.84 (7.14; 95% CI 4.22-9.46) points (P<.001). Other measures such as balance reaction time, reaction speed, maximum movement distance, and movement direction control showed significant improvement (P<.01). Compared to the control group, the experimental group demonstrated greater improvements in gait speed (P=.04), balance reaction time (P=.04), and maximum movement distance (P=.048). Correlation analysis revealed that improvements in left ankle dorsiflexion were positively correlated with improvements in gait speed, stride length, and swing phase duration (P<.05). CONCLUSIONS: SER-assisted training significantly improves gait, balance, and PD symptoms. Our work integrates multidimensional assessments (gait analysis, balance metrics, and clinical scales) and reveals that gains in ankle mobility directly correlate with gait improvements, suggesting a key mechanism. This study contributes by establishing SER as an effective adjunct to conventional therapy, supported by comprehensive quantitative data.
3 May 2026
Read appraisal →ACS sensors
Vertically Oriented Assembly of a Few-Layer Ti3C2Tx Grid by Electric Field Inducing and Freeze Drying for Wearable Levodopa Sensing in Sweat
Compared with the parallel assembly, the vertical assembly of MXene nanosheets on the substrate exhibits open three-dimensional porous structure, which is beneficial to the construction of high-performance electrodes. Herein, the vertically oriented assembly of Ti3C2Tx nanosheets is proposed by a novel preparation process of electric field inducing and freeze drying, resulting in the Ti3C2Tx grid with thin-wall and open porous structure. First, the electric field induces the formation of Ti3C2Tx hydrogel layer on the substrate. Second, freeze drying causes the growth of ice crystals for squeezing few-layer Ti3C2Tx nanosheets to stand up. More importantly, such a Ti3C2Tx grid with large surface area and intrinsic conductivity can effectively load electrocatalysts, resulting in the Au-Ti3C2Tx grid as a high-performance working electrode for the electrochemical detection of levodopa. The main parameters include 1-30 μM and 30-160 μM two-stage linear ranges and 37 nM detection limit. The structural advantages of Ti3C2Tx grid-based electrode materials are their three-dimensional conductive network and interconnected porous structure, which contribute to the penetration of the electrolyte, the diffusion of the analyte, and the electrocatalytic reaction. Furthermore, the self-adapting shape of the Ti3C2Tx grid leads to the fan-shaped Au-Ti3C2Tx grid collaborated with a self-designed leaf-like microfluidic. Ultimately, a wearable levodopa sensor composed of Au-Ti3C2Tx grid, microfluidic, flexible electronic system, and mobile phone client is established for detecting levodopa in human sweat, which is expected to help Parkinson's patients control the drug dosage. Our work proposes the vertically assembled Ti3C2Tx nanosheet loaded noble metal electrocatalysts to develop high-performance electrodes for electrochemical sensing.
26 Apr 2026
Read appraisal →Reviews in the neurosciences
Microstructural alterations of the amygdala in neurodegenerative and neuroinflammatory disorders: insights from diffusion tensor imaging
Diffusion tensor imaging (DTI) is a valuable method for evaluating microstructural changes in the amygdala associated with neurodegenerative and neuroinflammatory disorders. This systematic review examines amygdala microstructural alterations in Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), dementia with Lewy bodies (DLB), and multiple sclerosis (MS) using DTI metrics. Following PRISMA 2020 guidelines, we searched PubMed, Scopus, and Web of Science databases through August 2025, identifying 4,442 records. After screening and eligibility assessment, 13 studies were included, comprising 1,412 patients and 1,146 healthy controls. Due to sample heterogeneity and lack of standardized effect size measures, meta-analysis was not performed. Across disorders, elevated mean diffusivity (MD) emerged as the most consistent finding, present in 100 % of AD patients and observed in all examined conditions. Reduced fractional anisotropy (FA) was the second most frequent alteration, with 36.6 % of AD patients showing decreased FA. In MS, increased radial diffusivity (RD) was prominent, while longitudinal DLB studies revealed progressive free water (FW) increases. These DTI-based microstructural changes often preceded volumetric atrophy and correlated with clinical severity. Our findings demonstrate that DTI metrics, particularly MD and FA, serve as sensitive markers of amygdala pathology across neurodegenerative diseases and may facilitate early diagnosis, disease monitoring, and differential diagnosis of these conditions.
26 Apr 2026
Read appraisal →Biomedical physics & engineering express
A graph deep learning method for diagnosis of Parkinson's disease using brain functional connectivity features
Early and precise identification of Parkinson's disease (PD) is crucial for clinical intervention. Resting-state functional magnetic resonance imaging (rs-fMRI) provides a valuable approach for revealing PD-related differences in brain functional connectivity (FC). However, existing methods often focus solely on characterizing the spatial topology of FC while neglecting its time-varying dynamic fluctuations. Furthermore, they frequently exhibit limited generalization capability when dealing with small sample sizes, and their decision-making mechanisms lack interpretability. To address these limitations, this study proposes an interpretable graph convolutional network framework. This framework integrates both static and dynamic FC information to capture both the stable topological structure and the dynamic temporal characteristics of brain networks. Simultaneously, it models population relationships by constructing an inter-subject similarity graph to enhance the model's representational capacity. Additionally, this study incorporates interpretability analysis techniques to deeply dissect the model's decision-making mechanism and identify key brain regions critical for classification. Results demonstrate that the proposed model achieves superior performance in PD classification tasks and exhibits good generalization ability. More importantly, by interpreting the model's decisions, key brain regions associated with PD discrimination were successfully identified. This study provides an effective computational framework for PD identification and offers new insights into understanding its pathological mechanisms.
25 Apr 2026
Read appraisal →Journal of speech, language, and hearing research : JSLHR
Neuroimaging Advances in Brain Function of Laryngeal Dystonia: A Systematic Review
PURPOSE: This study aims to review neuroimaging research on brain function in laryngeal dystonia (LD), summarize current evidence on its pathophysiological mechanisms, and highlight directions for future investigation. METHOD: PubMed, Scopus, and Web of Science Core Collection were searched from database inception to November 2025. Two reviewers independently screened studies, extracted data, and assessed study quality using the Newcastle-Ottawa Scale. Eligible studies were synthesized through systematic review and visual analysis. RESULTS: A total of 33 studies were included. These studies employed imaging techniques such as functional magnetic resonance imaging and voxel-based morphometry to identify abnormalities in patients with LD. Structurally, key findings include gray matter alterations in sensorimotor areas, reduced thalamic volume, and impaired white matter integrity. Functionally, this manifests as sensorimotor integration dysfunction (characterized by M1/S1 and cerebellar hypoactivation alongside pallidal and thalamic hyperactivation) and network decoupling (e.g., weakened M1-S1 connectivity). CONCLUSIONS: The pathological mechanism of LD is a complex network imbalance involving the core "cortico-basal ganglia-thalamo-cerebellar" loop, driven primarily by sensorimotor integration dysfunction. Current research is limited in quantity and suffers from significant methodological heterogeneity. Future studies should further clarify the functional interactions among brain regions and their relationship with clinical symptoms, thereby providing a theoretical basis for the development of targeted therapies. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.31329103.
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 →Scientific data
Continuous observation of Parkinsonian symptoms using symptom diaries & wearable accelerometry
Treatment adjustments in Parkinson's Disease (PD) are often based on clinical evaluations at single time points which are insufficient to adequately assess real-life motor fluctuations. Patient-written symptom diaries on the other hand are highly subjective and require well-educated and adherent patients to provide reliable results. Wearable accelerometry might provide a reliable, objective, and continuous diagnostic method to assess PD motor symptoms & fluctuations. However, large datasets of simultaneous sensor data and symptom diaries are needed for such method development and validation. We here provide a well-described, open-science dataset of simultaneous, bilateral, wrist-worn accelerometry and symptom diary data from 66 participants (41 male, 25 female) with PD. On average, participants provided data for 6.0 consecutive days resulting in a total of 393.8 days for the dataset as a whole. Symptom diaries include data on kinetic state, tremor, freezing of gait, falls, and PD-related medication intake. Further demographic information is also provided. This dataset will support the development and validation of accelerometry-based approaches to assessing motor symptoms and fluctuations in PD.
11 Apr 2026
Read appraisal →Neurology
Neurovascular Unit Dysfunction and Cerebral Small Vessel Disease in Parkinson Disease: A Systematic Review and a Meta Analysis
BACKGROUND AND OBJECTIVES: Parkinson disease (PD) pathogenesis remains incompletely understood; beyond nigrostriatal loss, nondopaminergic mechanisms including neurovascular unit dysfunction may contribute to disability. Cerebral small vessel disease (CSVD) burden reflects neurovascular dysfunction in the form of white matter hyperintensities (WMH), lacunes, cerebral microbleeds (CMB), and enlarged perivascular spaces (ePVS). In PD cohorts, CSVD burden correlates with worse motor and gait scores. The aim of the study was to explore whether patients with PD exhibit greater CSVD burden than healthy controls (HC). METHODS: We conducted a PRISMA-conformant systematic review and meta-analysis of studies including adults with idiopathic PD and a HC group that presented data comparing CSVD burden in these 2 groups. Six databases (MEDLINE, Embase, CINAHL Plus, CENTRAL, Scopus, and Web of Science) were searched on May 14 and 15, 2024. Two reviewers independently screened records, extracted data, and assessed risk of bias, with discrepancies resolved by consensus. Continuous outcomes were pooled as standardized mean differences (SMD); dichotomous outcomes as odds ratios (ORs). We evaluated small-study effects for pooled analyses with 10 or more studies using funnel plots and Egger regression test. RESULTS: We examined 13,403 records. Forty-six studies (45 cross-sectional) met inclusion criteria, totaling 3,817 PD and 2,593 HC (mean ages: 66.9 and 66.5, respectively). WMH volume (k = 21) was higher in PD (SMD 0.36, 95% CI 0.11-0.62). Visual ratings also indicated higher WMH in PD: global (k = 14) SMD 0.27 (95% CI 0.08-0.46); periventricular (k = 11) SMD 0.32 (95% CI 0.12-0.51); deep (k = 8) SMD 0.20 (95% CI 0.09-0.31). Differences in CMB (k = 6; OR 1.18, 95% CI 0.57-2.42) and lacunes (k = 4; OR 1.48, 95% CI 0.58-3.78) were not significant. ePVS results were heterogeneous but trended toward greater burden in PD, most notably in the midbrain (k = 3; SMD 1.80, 0.15-3.44). Overall evidence quality was rated as low, reflecting the observational nature of the included studies. DISCUSSION: Our analysis showed PD to be associated with greater WMH burden and increased midbrain ePVS. Pooled differences in CMB and lacunes were not significant. Substantial heterogeneity and cross-sectional designs limit certainty; standardized imaging and prospective cohorts are needed to define mechanisms and clinical implications.
10 Apr 2026
Read appraisal →Journal of neurology
Systematic review of movement disorders mislabeled as functional: when incongruence misleads
BACKGROUND: Misdiagnosis of functional movement disorders (FMD) remains a concern for clinicians. We sought to review the phenomenology and clinical features associated with FMD misdiagnosis. METHODS: We conducted a systematic review of case reports, case series, and observational studies of adults diagnosed with FMD and subsequently reclassified as having another neurological or medical condition. PubMed was searched from inception to September 13, 2025, focusing on reported features of inconsistency, incongruence with known diseases, and low-validity features. Isolated (iMD) and mixed (mMD) movement disorders were analyzed separately. RESULTS: Forty-two included studies comprised 150 patients, of which 73 cases underwent detailed analysis. Gait disturbance (35%) and dystonia (27.5%) were the most common iMD phenomenologies (n = 40), while jerks and rigidity (24%) were the most common mMD phenomenology (n = 33). Incongruence with known diseases (50.7%), psychological factors (34.2%), and symptom variability (31.5%) were the main factors associated with misdiagnosis. Application of incongruence alone was associated with the highest rate of FMD misdiagnosis, similar to that of applying neither incongruence nor inconsistency (49% in both cases). Conversely, reliance on inconsistency alone was least associated with an FMD misdiagnosis (13.7%). Misdiagnoses of iMD were more likely in the absence of documented inconsistency (OR 3.94, 95% CI 1.32-12.82). CONCLUSIONS: FMD misdiagnoses, particularly of gait disorders and dystonia, were most commonly associated with the application of incongruence as diagnostic criterion. The lowest rate of FMD misdiagnosis was associated with ascertaining at least two positive neurological signs of inconsistency.
9 Apr 2026
Read appraisal →Brain : a journal of neurology
Leveraging machine learning to predict Parkinson's disease using pre-symptomatic proteomics data
In Parkinson's disease, non-motor symptoms precede the characteristic motor manifestations by up to 20 years. However, predicting the disease risk remains challenging. We applied machine learning to 2937 plasma proteins assayed in UK Biobank participants with Parkinson's disease to predict disease outcome up to 14 years before diagnosis. Of the 446 proteins found to be dysregulated in incident cases compared with controls, a subset of 23 predicted disease with an area under the curve (AUC) value of 0.78 in incident and 0.795 in prevalent cases. The utility of the identified proteomic signatures was validated in an independent cohort, based on 16 proteins shared across datasets, leading to a validation AUC of up to 0.76. Parkinson's disease-related pathways, including neuron death and amyloid-β clearance, were enriched up to 9 years before diagnosis. Furthermore, a co-expression network analysis revealed protein modules associated with disease risk and time-to-diagnosis. Our findings underscore the potential of applying machine learning to large-scale proteomics data from pre-symptomatic patients for early disease prediction.
9 Apr 2026
Read appraisal →Brain : a journal of neurology
Distinct cerebellar networks underpin clinical improvement in adolescent Tourette disorder.
Adolescence is frequently called the second period of brain maturation. In Tourette disorder (TD), the clinical trajectory of tics and associated psychiatric co-morbidities varies significantly across individuals during the transition from adolescence to adulthood. In this study, we aimed to identify patterns of resting-state functional connectivity that differentiate adolescents with Tourette disorder from their neurotypical peers, and to monitor symptom-specific functional changes over time. We employed a multivariate analysis based on a support vector machine (SVM) to predict patterns of resting-state functional connectivity in 64 adolescents with Tourette disorder and 61 sex- and age-matched healthy controls. Fifty-seven patients with Tourette disorder participated twice, with an interval of 15 months. Based on the results of the multivariate analysis, we implemented a general linear model to test within-group differences in resting-state functional connectivity over time, as well as their correlation with changes in severity of tics, depressive, obsessive-compulsive (OCD) and attention deficit and hyperactivity (ADHD) symptoms. The SVM significantly discriminated Tourette disorder from healthy controls with above-chance accuracy, specificity and sensitivity. The most discriminative connections were prefrontal, striatal and cerebellar networks. Between the visits, adolescents with Tourette disorder showed decreased functional connectivity between vermis 3 and the bilateral supplementary motor area and between vermis 4, 5 and the occipital cortex. The correlation analysis revealed that (i) an improvement between the visits in the severity of tics was associated with increased connectivity between the pre-supplementary motor cortex, anterior cingulate and inferior frontal gyrus; (ii) an improvement of ADHD was associated with decreased connectivity of the anterior cingulate cortex with the inferior temporal cortex; (iii) an improvement of OCD correlated with decreased cerebellar (lobule 8 and vermis 8, 9) connectivity with fronto-polar, superior temporal and superior frontal cortices, and increased cerebello-parietal connectivity, as well as fronto-parietal and fronto-frontal connectivity; and (iv) an improvement of depressive symptoms correlated with decreased connectivity of the cerebellum (lobules 4, 5 and vermis 6) with the precuneus. Our findings support pathophysiological models of Tourette disorder, in which aberrant patterns of functional connectivity are associated with specific comorbidities that may evolve differently throughout adolescence. Resting-state functional connectivity may provide unique endophenotypes, with developmental changes potentially linked to modifications in the severity of comorbid conditions. Distinct regions of the cerebellum and their connectivity with various frontal cortical regions emerge as candidate biomarkers to monitor, and possibly predict, the clinical trajectory of Tourette disorder symptoms, offering insights into disorder pathogenesis and likely guiding clinical decision-making.
9 Apr 2026
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