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Published Database Resources for Traditional, Complementary, and Integrative Medicine: Update of a Systematic Review.

BACKGROUND: Traditional, Complementary, and Integrative Medicine (TCIM) has been established in the academic context of universities. In recent years, strategies have been developed worldwide to strengthen the role of TCIM in supporting the health of the population. Online databases are a common way for obtaining evidence-based information. This article is an update of a former systematic review from 2010 on published databases resources for TCIM. METHODS: The databases CINAHL, CAMbase, Web of Science, MEDLINE/PubMed, and Google Scholar search engine were searched for databases related to TCIM published in peer-reviewed journals between 2010 and November 2024. All included databases were visited online, and information on the origin, content, and scope of the database was extracted. RESULTS: A total of 6579 articles were identified through the literature search. After exclusion of irrelevant articles, full-text screening of 127 articles yielded 37 new databases. Together with 16 still available old databases, these mainly contained information on herbal therapies (n = 15) and Traditional Chinese Medicine (n = 11) from 18 different countries. Newly identified medicinal plant databases offer various scientific resources such as crude drugs, indigenous plants, and structures for natural and phytochemical components with molecular biological content. CONCLUSIONS: This literature review illustrates the dynamic development in the database landscape over the last 15 years. While the number of bibliographic databases is shrinking, databases in the field of medical plants/herbal therapy content are on the rise, which might be due to advances in plant genomics and molecular biology.

Humans

GLP-1 Receptor Agonists and Musculoskeletal Outcomes: A Systematic Literature Review and Meta-Analysis.

INTRODUCTION: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are increasingly used for the treatment of type 2 diabetes and obesity, but their effects on musculoskeletal health remain completely misunderstood. OBJECTIVE: This systematic review/meta-analysis aims to synthesise clinical data on the effects of GLP-1 RAs on key relevant bone, muscle, and joint outcomes. METHODS: MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL) (both via Ovid&#xae; platform) and Embase were searched from inception to March 2025 to identify relevant randomised controlled trials (RCTs) or real-world evidence (RWE) studies to be included. This bibliographic search was completed manually. A random-effect model meta-analysis was performed for any outcome reported in at least 2 studies. Subgroup analyses were performed on the type of GLP-1 RAs, type of comparator used and study design. Sensitivity analyses (i.e., leave-out sensitivity analyses and analyses restricted to the most adjusted effect estimate) were performed to test the robustness of the data. The strength of evidence was assessed using GRADE. This work has been performed in adherence with PRISMA statement. (PROSPERO Record ID: CRD420251024082). RESULTS: From 1148 potentially relevant references, 60 articles (46 RCTs, 13 RWE studies and 1 pharmacovigilance study, comprising 1,250,717 individuals) met our inclusion criteria. Different GLP-1 RAs were represented across the panel of studies, i.e., semaglutide, liraglutide, exenatide, dulaglutide, tirzepatide (dual agonist gastric inhibitory polypeptide [GIP]/GLP-1) and others. No effect on bone outcomes (i.e., bone mineral density [all sites] and fractures [all sites]) were observed when the meta-analytical models included the most adjusted effect size. Regarding muscle outcomes, a significant decrease of lean body mass/fat-free mass was consistently observed with GLP-1 RAs in the global model (k = 28, standardised mean difference [SMD] 0.52, 95% confidence interval [CI] -0.8; -0.23, I2 88%, p-value for heterogeneity <0.0001), which remained robust in all sensitivity analyses. Subgroup analyses showed that the effect was mainly driven by liraglutide and semaglutide, with a decrease in lean body mass/fat-free mass observed when GLP-1 RAs were compared with placebo. No publication bias was found. Regarding joint outcome, models revealed no significant change in The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain, physical function and stiffness. CONCLUSIONS: This meta-analysis is the first to investigate the effects of GLP-1 RAs on a large panel of musculoskeletal health outcomes. While no significant effects were observed on bone- or joint-related outcomes, GLP-1 RAs were associated with reductions in lean body mass/fat-free mass, although the certainty of evidence was low and these changes appeared largely related to weight loss. Whether these changes translate into clinically meaningful impairments in muscle function or physical performance remains uncertain. Further studies in this field, including those looking at muscle function, strength or performance and using multivariate models considering confounding are needed to better reinforce the models and final findings.

Journal Article

Long-term consequences of childhood sexual abuse: An umbrella review of diagnostic meta-analyses.

BACKGROUND: Childhood sexual abuse (CSA) is a public health issue with an estimated worldwide prevalence of 12.7%, potentially leading to a host of lifelong and significant mental, physical, and behavioral health. The aim of this study was to comprehensively map the long-term consequences of childhood sexual abuse on physical, psychiatric, and behavioral health outcomes. METHODS: An umbrella review of meta-analyses of observational studies, registered on PROSPERO, was conducted to examine the diverse repercussions of childhood sexual abuse on adult health. Three bibliographic databases (PsycINFO, PubMed and Scopus) were searched from the inception of the respective databases to November 1st, 2022. Thirty-eight meta-analyses representing about 20 million individuals were analyzed, revealing a range of long-lasting consequences associated with CSA. RESULTS: Among physical pathologies, cervical cancer and functional neurological syndromes emerged as the most prominent, exhibiting significantly elevated odds ratios (ORs) of 4.18 IC95% and 3.30 IC95%, respectively. Sleep disorders and borderline personality disorders were the most prevalent mental health disorders associated with CSA, with respective ORs of 16.17 IC95% and 5.96 IC95%. Early sexual initiation (OR=3.59 IC95%, sexual assault (OR=3.36 IC95%, and prostitution (OR=3.24 IC95%) emerged as the most common behavioral consequences. Notably, no significant differences in the consequences of CSA were observed between men and women, except for reproductive health outcomes. DISCUSSION: When faced with certain pathologies, clinicians should consider and discuss sexual abuse with their patients. The consequences of abuse have a multifactorial origin, which is a weakness, as are the problems of defining abuse. The strength of our study is that it lists the consequences published in high-quality studies. CONCLUSION: This umbrella review provides compelling evidence of the profound and far-reaching impact of childhood sexual abuse on a broad spectrum of physical, mental, and behavioral health issues.

Humans

Global molecular and serological evidence of dengue and chikungunya infection: a systematic review and meta-analysis of 158,608 tested participants.

INTRODUCTION: Dengue virus (DENV) and chikungunya virus (CHIKV) are Aedes-borne arboviruses with overlapping clinical manifestations, shared vectors, and substantial diagnostic challenges in co-endemic settings. This systematic review and meta-analysis synthesized published evidence on molecular detection, serological positivity, and DENV-CHIKV dual positivity/co-infection in human clinical, surveillance, and community-based study populations. CONTENT: Following PRISMA 2020 guidance, five bibliographic databases (PubMed/MEDLINE, Scopus, Web of Science, ScienceDirect, and Google Scholar) and supplementary grey-literature/preprint sources were searched for English-language studies published from 1 January 1980 to 31 December 2024. No prospective PROSPERO or OSF protocol registration was available. Eligible records reported extractable numerators and denominators for DENV and/or CHIKV in humans using recognized molecular or serological assays. A total of 196 studies comprising 158,608 tested or suspected participants were included in the extraction table. The pooled CHIKV estimate was 14.0&#x202f;% (95&#x202f;% CI: 12.0-16.4; I2=97.5&#x202f;%), with molecular and serological estimates of 9.8 and 15.7&#x202f;%, respectively. The pooled DENV estimate was 13.8&#x202f;% (95&#x202f;% CI: 10.9-17.3; I2=99.0&#x202f;%), with molecular and serological estimates of 13.1&#x202f;% (95&#x202f;% CI: 7.9-21.0) and 14.3&#x202f;% (95&#x202f;% CI: 10.2-19.8), respectively. DENV-CHIKV dual positivity/co-infection was 52.9&#x202f;% (95&#x202f;% CI: 48.7-57.1) among studies that tested and reported both outcomes. Country-level estimates varied widely and should be interpreted as summaries of available studies rather than nationally representative burden estimates. Funnel-plot asymmetry was statistically significant in DENV analyses but not in the overall CHIKV analysis. SUMMARY: Available evidence indicates extensive but highly heterogeneous DENV and CHIKV positivity across selected clinical and surveillance populations. The pooled estimates should be interpreted cautiously because of substantial between-study heterogeneity, diagnostic variability, outbreak-period sampling, and uneven geographic representation. OUTLOOK: The findings support integrated arboviral surveillance, multiplex diagnostics, and vector-control preparedness in co-endemic regions.

Humans

Cardiorespiratory training for people with stroke.

RATIONALE: Low levels of cardiorespiratory fitness are common after stroke and are associated with post-stroke disability and increased risk of secondary stroke. Cardiorespiratory training interventions aim to increase cardiorespiratory fitness, improve physical function, reduce disability, and help prevent future strokes. Clinical guidelines recommend exercise as part of lifestyle modification for secondary prevention, and strongly recommend exercise for rehabilitation. This review is one of three reviews that were originally a single review on physical fitness training for stroke. OBJECTIVES: The primary objective of this review was to determine whether cardiorespiratory training after stroke has an effect on death, disability, adverse events, risk factors, fitness, walking, and indices of physical function when compared to a non-exercise control. SEARCH METHODS: In April 2025, we searched nine bibliographic databases and two trials registers to identify studies for inclusion in the review. We checked reference lists, tracked citations, and contacted experts. ELIGIBILITY CRITERIA: We included randomised controlled trials comparing cardiorespiratory training interventions with usual care, no intervention, or a non-exercise intervention in people with stroke. OUTCOMES: Our critical outcomes were death, disability, adverse events, risk factors, fitness, walking, and indices of physical function, assessed at the end of the intervention and the end of the longest follow-up. RISK OF BIAS: We used the Cochrane RoB 1 tool to assess the risk of bias in the included studies. SYNTHESIS METHODS: The studies evaluated different comparisons (e.g. cardiorespiratory training versus no intervention/waiting list control or versus attention control or versus usual care), which we synthesised into a single comparison: cardiorespiratory training versus control. We used random-effects meta-analysis on arm-level data (risk difference (RD) for dichotomous data, and mean difference (MD) or standardised mean difference (SMD) for continuous data, with 95% confidence intervals (CIs)). For outcome data that we did not meta-analyse, we followed Synthesis Without Meta-analysis (SWiM) guidance. We used GRADE to assess the certainty of the evidence for critical outcomes. INCLUDED STUDIES: We included 53 studies (2672 participants, with an average age of 61.9 years). Most studies recruited ambulatory participants in the early subacute (7 days to 3 months) or chronic (> 6 months) phases of recovery. Exercise duration recommendations were met in 49 studies, and frequency recommendations in 48. Twenty-eight studies lacked balanced exposure between groups. Programme duration was 12 weeks or more in 16 studies (maximum: 24 weeks). Sixteen studies had a post-intervention follow-up period (12 weeks to 12 months from baseline). One study planned a six-month follow-up but did not report it. SYNTHESIS OF RESULTS: Cardiorespiratory training does not increase or decrease deaths at the end of intervention (RD 0.00, 95% CI -0.01 to 0.01; 36 studies, 1563 participants; high-certainty evidence) or the end of follow-up (RD -0.00, 95% CI -0.02 to 0.02; 10 studies, 713 participants; high-certainty evidence). Cardiorespiratory training may improve indices of disability slightly at the end of intervention (SMD 0.35, 95% CI 0.12 to 0.57; 17 studies, 1073 participants; very low-certainty evidence), but the evidence is very uncertain. Re-expressed using the Barthel Index (0 to 20), the equivalent effect is MD 1.68, 95% CI 0.59 to 2.74. It is unclear if the effect is clinically meaningful (the minimal clinically important difference (MCID) is +1.85). The effect is unclear at the end of follow-up (SMD -0.14, 95% CI -0.36 to 0.08; 5 studies, 347 participants; low-certainty evidence). Cardiorespiratory training does not increase or decrease the incidence of secondary cardiovascular or cerebrovascular events at the end of intervention (RD -0.00, 95% CI -0.03 to 0.02; 8 studies, 544 participants; high-certainty evidence) and probably does not affect them at the end of follow-up (RD -0.02, 95% CI -0.08 to 0.04; 4 studies, 412 participants; moderate-certainty evidence). It is very uncertain whether cardiorespiratory training affects systolic blood pressure (mmHg) at the end of intervention (MD -2.12, 95% CI -5.81 to 1.57; 9 studies, 535 participants; very low-certainty evidence) (MCID -2 mmHg) or follow-up (MD 0.93, 95% CI -4.30 to 6.16; 3 studies, 155 participants; very low-certainty evidence); the 95% CIs include the MCID. Cardiorespiratory training probably results in a slight improvement in cardiorespiratory fitness (VO2 ml/kg/min) at the end of intervention (MD 2.37, 95% CI 1.39 to 3.36; 13 studies, 608 participants; moderate-certainty evidence); it is unclear if the effect is clinically meaningful (MCID +3.5 ml/kg/min). The effect may be similar at the end of follow-up (MD 2.76, 95% CI 1.36 to 4.16; 5 studies, 237 participants; low-certainty evidence). Subgroup analysis favoured longer interventions. Cardiorespiratory training probably results in a slight increase in comfortable walking speed (metres per second) at the end of intervention (MD 0.08, 95% CI 0.04 to 0.12; 16 studies, 647 participants; moderate-certainty evidence), but the effect is not clinically meaningful (MCID +0.13). The effect is unclear at the end of follow-up (MD 0.02, 95% CI -0.05 to 0.10; 3 studies, 182 participants; low-certainty evidence). Cardiorespiratory training may improve indices of balance at the end of intervention (SMD 0.31, 95% CI 0.15 to 0.47; 18 studies, 772 participants; very low-certainty evidence), but the evidence is very uncertain. Re-expressing using the Berg Balance Scale, the equivalent effect is MD 2.09, 95% CI 1.10 to 3.07; and it is unclear if it is clinically meaningful (MCID of +2). The effect is unclear at the end of follow-up (MD 0.90, 95% CI -1.32 to 3.12; 6 studies, 253 participants; low-certainty evidence). Overall, our certainty about the evidence is limited for most outcomes by imprecision (small number of studies and participants) or risks of bias (e.g. imbalanced exposure doses) or both. AUTHORS' CONCLUSIONS: Cardiorespiratory training after stroke does not affect mortality or the incidence of secondary events at the end of the aerobic exercise training programme or end of follow-up. It may increase fitness, reduce disability, increase walking speed, and improve balance at the end of intervention, but it is unclear if these improvements are clinically meaningful. Further well-designed randomised trials are needed to fully understand the potential benefits and long-term effects of cardiorespiratory training and the optimal exercise prescription. FUNDING: No dedicated funding REGISTRATION: Protocol (and previous versions) available via DOI 10.1002/14651858.CD003316.

Humans

An introductory practical guide to secondary data analysis in pediatric urology.

INTRODUCTION: Secondary data analysis (SDA) has become an increasingly important approach in pediatric urology, enabling the study of long-term outcomes, care variation, and disparities in populations with chronic or congenital urologic conditions. With the growing availability of large datasets, a structured approach to designing and conducting SDA studies is increasingly relevant. OBJECTIVES: To provide an introductory, practical guide to SDA in pediatric urology by (1) summarizing commonly used data sources with representative studies, (2) outlining a stepwise approach to designing and executing SDA studies, and (3) highlighting key methodological considerations, limitations, and opportunities for future work. STUDY DESIGN: Narrative review of existing literature and commonly used datasets relevant to pediatric urology, including administrative claims, hospital encounter databases, clinical registries, electronic health record networks, and population-based surveys. RESULTS: Data sources differ in scope, clinical granularity, longitudinal follow-up, and representativeness, and each is suited to specific research questions. We present a practical workflow for SDA, including dataset selection, cohort definition, and analytic planning. Linkage across datasets can provide a more comprehensive view of care patterns and outcomes, although feasibility is influenced by legal, technical, and data-quality constraints. DISCUSSION: SDA enables population-level analyses and the study of rare conditions that are challenging to evaluate through single-center or prospective designs. However, careful cohort definition, feasibility assessment, and awareness of data limitations are essential to ensure validity and interpretability. CONCLUSION: SDA provides a scalable, cost-efficient framework for generating meaningful evidence in pediatric urology. Continued efforts to harmonize data elements, improve linkage infrastructure, and support cross-institution collaboration will enhance the quality and impact of future research. This article provides a practical framework and examples to support the design and execution of SDA studies.

Humans

Computational metabolomics at scale: from open data to insight.

Metabolomics data are currently generated at scale thanks to the evolution of technologies that have led to marked improvements in the number of metabolites detected, spanning all chemical classes. These data are increasingly submitted to public repositories for data reuse, integration, and interpretation. Despite the availability of public resources and associated computational tools, the field still lacks a widely adopted, consistent data and analytics infrastructure capable of transforming this wealth of information into scientific insight. Indeed, the metabolomics field is just now scratching the surface of being able to harness the power of new computational technologies. In this review, we summarize discussions from the "Dagstuhl-Seminar 24181 Computational Metabolomics: Towards Molecules, Models, and their Meaning" with a focus on public data availability, open data standards, data and knowledge integration, and education. Our goal is to raise awareness and adoption of the latest open science resources while highlighting key areas needing further development.

Metabolomics

Assessing the public health impact of routinely collected electronic healthcare record data in NICE guidelines: A systematic review of CPRD research.

OBJECTIVES: Evidence used in NICE guidance has traditionally prioritised randomised controlled trials, but increasing availability of electronic health record (EHR) data has expanded opportunities for real-world evidence. The Clinical Practice Research Datalink (CPRD) is a commonly used UK primary care EHR resource, yet the extent to which CPRD studies have informed NICE guidelines in the past decade is unclear. STUDY DESIGN: The systematic review was conducted in accordance with PRISMA guidelines. METHODS: We conducted a systematic review of CPRD studies in PubMed, MEDLINE, and Embase published between 04/16-09/25. For each eligible CPRD study, targeted searches of NICE guidelines were performed to identify explicit citations in NICE guidelines. Two reviewers screened and extracted data independently, resolving disagreements by consensus or third reviewer. Guideline information, number of guidelines over time, type of guidelines, and disease area guidelines (using British National Formulary (BNF) chapters) were described. RESULTS: 7181 records were identified. After de-duplication, 2704 unique CPRD studies were screened against NICE guidelines. Of these, 92 CPRD-based studies met inclusion criteria and were cited across 67 NICE documents. The annual number of NICE guidelines citing CPRD studies increased between 2016 and 2025; 1.5% of identified guidelines published in 2016 and 27.7% in 2025. The guideline citing the most CPRD studies was cancer related. The most common types of guidelines included clinical guidelines (49.3%) and technology appraisals (32.8%). Guidelines made up 12 different BNF categories, most frequently central nervous system related (23.9%; n&#x202f;=&#x202f;16). CONCLUSION: Observational CPRD studies are increasingly referenced in NICE guidelines across multiple disease areas, supporting the growing role of EHR data in national guideline development.

Clinical studies

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning

Suicide in rural South Africa before and during COVID-19: evidence from forensic mortuary data in Limpopo Province.

Suicide is a growing public health concern in South Africa, with rural provinces such as Limpopo facing heightened vulnerability due to limited mental health services and socio-economic inequalities. Evidence on the impact of COVID-19 on suicide in rural contexts remains limited. This study examined suicide trends in Limpopo Province and changes associated with the COVID-19 period. A retrospective interrupted time series analysis was conducted using forensic mortality data from 1 January 2019 to 31 December 2021, allowing assessment of pre-existing trends and changes following COVID-19 lockdowns. Among 5770 unnatural deaths, 957 were suicides. The proportion of suicides increased from 29.5% in 2019 to 36.9% in 2021. Suicides predominantly occurred among males and young adults, with hanging accounting for over 90% of deaths throughout. Interrupted time series analysis revealed a significant downward trend in suicide cases during the strict national lockdown (Alert Level 5), with a 31% reduction in incidence (IRR = 0.69, 95% CI: 0.49-0.98). Less restrictive lockdown levels showed no significant effects. Suicide mortality increased prior to COVID-19, with a subsequent decline during the strictest lockdown period. Stable demographic patterns and methods highlight persistent vulnerabilities and the need for sustained suicide-prevention strategies beyond pandemic.

Humans

Recovering membrane interaction kinetics of single molecules from 3D tracking data.

Interactions between cytosolic biomolecules and the bacterial inner membrane are fundamental to many cellular processes, yet directly measuring their binding kinetics in living cells remains challenging. Conventional 2D single-molecule tracking analyses can be insufficient, particularly when membrane association does not markedly alter the diffusion rate. Here, we present a method to recover membrane interaction kinetics from 3D single-molecule trajectories in rod-shaped bacteria. Using simulated 3D tracking data, we identify membrane-associated motion by quantifying how well short trajectory segments follow the circular curvature of the cell membrane. The resulting measure is further analyzed using a hidden Markov modeling framework, enabling robust discrimination between cytosolic and membrane-bound states and capturing the dynamics of state transitions without requiring diffusion-rate changes or direct colocalization with membrane markers. This work establishes a general framework for extracting membrane interaction kinetics from 3D single-molecule tracking data in live bacteria and highlights the value of realistic microscopy simulations for quantitative interpretation and systematic bias assessment.

Kinetics

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans

Effects of H-coil TMS on suicidality in major depression: A secondary analysis of data from a multisite randomized trial comparing accelerated to once-a-day stimulation.

Suicide is the 10th leading cause of death in US adults. Standard once-daily repetitive transcranial magnetic stimulation (rTMS) can reduce suicidal ideation. Yet, antidepressant and anti-suicidal effects often take several weeks to emerge, while rapid improvement is often required. Accelerated TMS has been proposed as a strategy to hasten therapeutic response. A recent FDA-regulated multicenter trial evaluated accelerated intermittent theta burst Deep TMS with the H1-coil versus standard high-frequency Deep TMS in MDD. Both groups demonstrated high remission and response rates for depression, with the accelerated protocol showing non-inferiority and a shorter time to remission. The goal of this exploratory secondary analysis was to evaluate the impact of these two H-coil TMS dosing paradigms on suicidal ideation. The Scale for Suicide Ideation (SSI), as well as suicidality items of HDRS, MADRS and CUDOS were collected and analyzed. On all scales, both accelerated and standard Deep TMS protocols were associated with meaningful reductions in suicidality. The accelerated protocol achieved a faster onset of improvement. Comparison between the timeline of improvement in suicidality and in overall depressive symptoms found a trend for faster improvement in suicidality, especially with the accelerated protocol. These findings highlight the importance of treatment frequency in determining time to clinical benefit and support the use of scalable accelerated protocols for patients requiring more rapid symptom relief.

Humans

Building phenotypic character matrices for phylogenetic inference: exploration of 35&#x2009;years of practice.

Recent methodological development in phylogenetic inference has focused predominantly on molecular data. However, renewed interest in other data types, particularly morphological data, has followed from the increased recognition of the power of total evidence and tip-dating approaches, including fossil data, for inference of time-scaled trees and rates of evolution. However, attention has largely focused on the improvement of models of morphological evolution and other analytical tools with much less discussion about data acquisition itself. Here we review past and current practice for describing and collecting morphological data for phylogenetic inference. We present a systematic review of 164 phylogenetic analyses conducted over the last 35&#x2009;years and focused on a diverse group of extinct arthropods: trilobites. Trends in increasing matrix size, data type, and coding strategy are evident. Where present, polymorphic characters have been predominantly derived from discretized continuous characters, although increasingly practitioners are utilizing alternative approaches for the treatment of quantitative characters. Not surprisingly, traditional indices that describe character consistency are highly correlated with matrix size but show surprising variation at different taxonomic scales. More recent attempts to describe data quality using information theory imply that characters can have high information content even if data are missing for many tips, providing support against the exclusion of characters because of missing data. In consideration of this, as well as advances in the study of developmental biology and variational complexity, we identify several avenues for increasing the quality and quantity of morphological data going forward.

Phylogeny

Relationship Between Number of Acute Pancreatitis Episodes and Risk of New-onset Diabetes in the U.S.: A Real-world Data Analysis.

INTRODUCTION: Acute pancreatitis (AP) is a common inflammatory disorder that is associated with increased risk for diabetes mellitus (DM). It remains unclear whether recurrent acute pancreatitis (RAP) is associated with further increased risk of incident DM. This study aims to investigate the association between RAP and incident DM using real-world data. METHODS: We conducted a retrospective cohort study using the MerativeTM MarketScan&#xae; claims database (2016-2023), identifying patients with AP and no prior history of DM at baseline. The primary exposure of interest, RAP, was defined as one or more episodes of AP occurring &#x2265;90 days after the index AP diagnosis, whereas one episode of AP referred to a single episode of AP (SAP) with no subsequent recurrence within 90 days following the index event. A multivariable stratified Cox proportional hazards regression models were used to determine the association between RAP and incident DM, identified using ICD-10 codes. RESULTS: In total, 16,184 individuals with AP (mean [SD] age: 45.8 [12.3]) contributed 40,712 person-years of follow-up, during which 1,477 incident cases of DM were documented. Individuals with RAP had an increased risk of incident DM compared with those with a SAP(adjusted HR, 1.92; 95% CI, 1.61-2.29). The risk increased significantly with the frequency of RAP. In comparing the modifying effect of patient demographics and comorbidities, a stronger association between RAP and incident DM was observed in females (adjusted HR, 2.44; 95% CI, 1.87-3.19) than in males (adjusted HR, 1.64; 95% CI, 1.30-2.07; Pinteraction=0.03). Also, stronger associations were observed among younger patients (18-46&#xa0;y) (adjusted HR=2.56; 95% CI, 1.97-3.31) and among non-tobacco abuse (adjusted HR=2.19; 95% CI, 1.81-2.65), with significant interactions for all comparisons (Pinteraction<0.05. CONCLUSIONS: In this real-world study, RAP was associated with an increased risk of incident DM. Our findings highlight an opportunity for glycemic monitoring and proactive management of patients with RAP to mitigate their risk of developing DM.

AP

Identification Matters: How Data Sharing Affects Pupil Honesty and Engagement in Universal School Well-Being Assessments.

PURPOSE: Universal well-being assessments in schools may support early identification of pupils needing mental health support. However, little is known about how privacy and confidentiality concerns influence pupils' acceptability of assessments and willingness to engage authentically. This study examined how hypothetical identification, where responses are linked to pupils and shared with key stakeholders, affects pupils' anticipated honesty and engagement, and whether known help-seeking barriers predict negative responses. METHODS: Cross-sectional data were collected from 12,377 primary (ages 8-10) and secondary pupils (ages 11-17) across 55 schools in England. Pupils reported whether their responses would change if identifiable and shared with school staff, parents/guardians, or external professionals. Responses indicating reduced honesty or likelihood of disengagement were coded as negative. Predictors were examined using mixed-effects logistic regression models, including demographics, school connectedness, and mental well-being. RESULTS: Identification and data sharing influenced pupils' anticipated engagement, particularly in secondary schools. Identification by school staff elicited the highest proportion of negative responses in both phases, whereas external professionals elicited the fewest. Most primary pupils reported they would respond authentically, while a larger proportion of secondary pupils indicated they would respond less honestly or disengage when responses were identifiable and shared. Across primary and secondary samples, low well-being, low school connectedness, and being female were associated with greater likelihood of negative response. DISCUSSION: Pupils' anticipated engagement with well-being assessments is shaped by who accesses their data, with marked developmental differences. Strengthening trust, privacy, and connectedness, and supporting pupils' autonomy, may improve the acceptability and response accuracy.

Humans