Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
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Genome biology
IDEAL-Age: an interpretable deep learning framework for single-cell resolution profiling of immunological aging
Immunosenescence increases susceptibility to infection and reduces vaccine responsiveness, yet bulk transcriptomic clocks obscure the cellular heterogeneity underlying this process. Here, we present IDEAL-Age, an interpretable deep learning framework that operates directly on single-cell PBMC transcriptomes. Benchmarking against 35 methods across independent cohorts demonstrates superior predictive performance. The framework's interpretability uncovers linear and non-linear gene contribution trajectories that reveal phase-specific physiological transitions, and identifies youth-associated or aging-associated cellular roles. Application to systemic lupus erythematosus reveals accelerated immunological aging driven by interferon-associated monocyte shifts. IDEAL-Age establishes a high-resolution computational framework for deciphering systemic immune aging.
27 July 2026
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Mobile health strategies to improve HPV vaccination uptake among parents of adolescent girls: a scoping review
BACKGROUND: Human papillomavirus (HPV) vaccination is a highly effective primary prevention strategy against cervical cancer. However, despite strong evidence of vaccine efficacy and safety, uptake among adolescent girls remains suboptimal globally, particularly in low- and middle-income countries. Mobile health (mHealth) technologies have emerged as promising tools to address parental concerns, reduce vaccine hesitancy, and strengthen parental engagement in vaccination decision-making. OBJECTIVE: This scoping review aimed to synthesize evidence on the types of mHealth strategies implemented to improve HPV vaccine uptake among parents of adolescent girls and to examine the outcomes of these interventions. METHODS: A systematic search of major databases identified studies evaluating mHealth interventions targeting parental decision-making regarding HPV vaccination. Eligible interventions included text messaging, mobile applications, chatbots, web-based educational platforms, and other digital health tools. Data were charted and synthesized narratively. KEY FINDINGS: mHealth interventions were associated with significant improvements in HPV vaccine uptake across multiple settings. SMS-based interventions consistently increased vaccination rates, while chatbot, web-based, and mobile app interventions improved parental knowledge, vaccine literacy, intention to vaccinate, and, in several studies, actual vaccine uptake. However, intervention effectiveness varied by socioeconomic context, digital access, and cultural factors. CONCLUSION: mHealth technologies represent cost-effective and scalable strategies to improve HPV vaccine uptake by enhancing parental knowledge, reducing hesitancy, and supporting informed decision-making. Future implementation should prioritize culturally tailored, equity-focused approaches and integrate digital interventions with community-based engagement to maximize impact.
12 July 2026
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