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PubMed2026

Use of Wearable Sensors in Angelman Syndrome: A Systematic Review.

BACKGROUND: Wearable sensors are a promising method for collecting clinical trial outcome data for people with Angelman syndrome (AS). However, there has yet to be a systematic probe into the ways in which wearable sensors have been successfully used in AS. The current study aims to provide a quantitative summary of wearable sensors used in AS, including contexts of use and psychometric properties, and to present key narrative highlights. METHOD: Literature searches were performed in three electronic databases: APA PsycInfo, PubMed and Web of Science Core Collection. Data items were categorized into four categories: sample characteristics, study methodological details, wearable sensor characteristics and psychometric properties assessed. Sample characteristics included sample size, age, biological sex, race/ethnicity and cognitive/developmental functioning. Study methodological details were subdivided into study design and setting. Wearable sensor characteristics included sensor type, placement site, means of attachment, assessed construct and sensor-related data loss. Psychometric properties assessed included reliability and validity of sensor-derived data. RESULTS: We identified 16 articles through our systematic review. Wearable sensors were used to study sleep (n = 10, 62.5%), language (n = 2, 12.5%), gait (n = 2, 12.5%), caregiver proximity (n = 1, 6.3%), EEG power (n = 1, 6.3%), and arousal (n = 1, 6.3%) in AS through actigraphs, vocalization recorders, inertial sensors, radio-frequency identification watches, wireless EEG caps, and functional near-infrared spectroscopy caps, respectively. Findings from these studies broadly indicate that wearable sensors are feasible, reliable and valid for assessing a range of behaviours relevant to AS. CONCLUSIONS: Wearable sensors are a promising solution to enhance assessments in AS. However, with the small extant literature characterized by small sample sizes and restricted focus on a few relevant features in AS, there remains ample opportunities to explore the use of wearable sensors in people with AS. Additional studies will better inform clinical decision-making and ultimately improve the lives of people with AS and their families.

Humans↗

PubMed2025

CAKL: Commutative algebra k-mer learning of genomics.

Despite the availability of various sequence analysis models, comparative genomic analysis remains a challenge in genomics, genetics, and phylogenetics. Commutative algebra, a fundamental tool in algebraic geometry and number theory, has rarely been used in data and biological sciences. In this study, we introduce commutative algebra k-mer learning (CAKL) as the first-ever nonlinear algebraic framework for analyzing genomic sequences. CAKL bridges between commutative algebra, algebraic topology, combinatorics, and machine learning to establish a new mathematical paradigm for comparative genomic analysis. We evaluate its effectiveness on three tasks-genetic variant identification, phylogenetic tree analysis, and viral genome classification-typically requiring alignment-based, alignment-free, and machine-learning approaches, respectively. Across eleven datasets, CAKL outperforms five state-of-the-art sequence analysis methods, particularly in viral classification, and maintains stable predictive accuracy as dataset size increases, underscoring its scalability and robustness. This work ushers in a new era in commutative algebraic data analysis and learning.

Journal Article↗

PubMed2026

CAKR: commutative algebra k-mer representations for genomics.

Despite the availability of various sequence analysis models, comparative genomic analysis remains a challenge in genomics, genetics, and phylogenetics. Commutative algebra, a fundamental tool in algebraic geometry and number theory, has rarely been used in data and biological sciences. In this study, we introduce commutative algebra k-mer representations as a nonlinear algebraic framework for analyzing genomic sequences. This representation bridges commutative algebra, algebraic topology, combinatorics, and machine learning to establish a mathematical framework for comparative genomic analysis. We evaluate its effectiveness on three tasks including genetic variant classification, phylogenetic tree reconstruction, and viral classification, typically requiring alignment-based, alignment-free, and machine-learning approaches, respectively. In this work, we show that commutative algebra k-mer representations outperform five state-of-the-art sequence analysis methods across twelve primary datasets, with two additional supplementary fragment-placement benchmarks, especially in viral classification, and maintain relatively stable predictive accuracy as dataset size increases, underscoring scalability and robustness.

Genomics↗

PubMed1978

Healthy family functioning: a cross-cultural appraisal.

It is increasingly recognized that rapid cultural, social, economic, and technological changes are imposing increasing stress on family structures, traditional values, and the ability to adapt to new environments in different societies. For the purposes of this paper, "healthy family functioning" is defined in terms of a family unit (however it is conceived in any given culture) effectively coping with cultural, environmental, psychosocial, and socioeconomic stresses throughout the family life cycle. While a review of international literature in the behavioural and biomedical sciences yields little data on comparative studies, there is growing awareness of the need for cooperative international research on family coping mechanisms and determinants of self-reliant communal coping behaviour, as well as more efficient utilization of already available knowledge. After consideration of methodological pitfalls of assessment procedures, there is a presentation of an evolving theory of healthy family functioning with the suggestion that studies of young married couples constitute a particularly promising vehicle for developing needed cooperative cross-cultural research.

Cross-Cultural Comparison↗

PubMed1979

Information system, data bases, and on-line services of the Japan Information Center of Science and Technology (JICST).

The JICST information processing system consists of the data-base production system, authority file management system, bibliographic retrieval system, and printed issue compiling system. The bibliographic retrieval service based on the JICST On-line Information System (JOIS-I) has been available through leased line since 1976 and now also through dial-up line, which covers five data bases: the JICST bibliographic and on-going research information files, CA Condensates, MEDLARS, and TOXLINE files. The on-line output in Japanese kanji is also available. The newly revised JOIS-II system is now being developed.

Forecasting↗

PubMed1979

AVLINE: a search resource for audiovisual instructional materials.

This manuscript describes the historical development and present scope of AVLINE (AudioVisuals-on-LINE), the National Library of Medicine's computer data base of information on nonprint instructional materials in dentistry, medicine, nursing, and allied health. The manuscript outlines the early and present review processes and involvement of dentistry peer reviewers; and provides data describing AVLINE titles by health science discipline and media characteristics for the total data base and the subset of dentistry. The manuscript also includes information on how to access AVLINE and a sample AVLINE citation.

Audiovisual Aids↗

PubMed2026

Neurometabolites and Antipsychotic Response in Psychosis: A Mega-Analysis.

IMPORTANCE: Revealing neurobiological markers of antipsychotic nonresponse in psychosis may aid outcome prediction and inform novel treatment targets. OBJECTIVE: To examine differences in neurometabolites in antipsychotic nonresponsive compared to antipsychotic-responsive psychosis using individual participant data and meta-analysis. DATA SOURCES: Web of Science was searched for studies published between January 1, 1980, and November 1, 2025. Authors of 21 eligible studies identified before August 2024 were invited to contribute individual participant data. STUDY SELECTION: Eighteen studies examining neurometabolites by treatment response in psychosis contributed individual participant data for the mega-analysis. These studies plus a further 5 studies were included in the meta-analyses of standardized mean differences and variability. DATA EXTRACTION AND SYNTHESIS: Individual participant data were analyzed using linear mixed models with study as a random effect. Subgroup analyses examined prospective designs and treatment-resistant samples. Published group means and standard deviations were extracted for meta-analyses. MAIN OUTCOMES AND MEASURES: Group differences in glutamate, glutamate plus glutamine, choline, myo-inositol, N-acetylaspartate, γ-aminobutyric acid, and glutathione in the medial frontal cortex, dorsolateral prefrontal cortex, thalamus, and basal ganglia. RESULTS: The mega-analysis included 1189 participants from 18 studies; of these, 476 were treatment nonresponders (mean [SD] age, 33.0 [12.5] years; 340 male), 427 were treatment responders (mean [SD] age, 30.3 [11.5] years; 299 male), and 286 were healthy control individuals (mean [SD] age, 31.0 [12.5] years; 170 male). Compared with the antipsychotic response group, nonresponders showed elevations in medial frontal glutamate (Glass Δ = 0.21; P = .02), glutamate plus glutamine (Glass Δ = 0.29; P = .002), choline (Glass Δ = 0.22; P = .03), and myo-inositol (Glass Δ = 0.35; P = .001); similar elevations were observed relative to control individuals. Elevated medial frontal glutamate plus glutamine in antipsychotic nonresponders compared with responders was also observed prospectively in first-episode psychosis (Glass Δ = 0.41; P = .002), whereas myo-inositol elevations were greatest in individuals meeting criteria for treatment-resistance (Glass Δ = 0.64; P = .001). The meta-analysis of 23 studies (1844 participants) also showed elevated medial frontal choline and myo-inositol in antipsychotic nonresponse compared with response. CONCLUSIONS AND RELEVANCE: These findings provide evidence of an association between antipsychotic nonresponse in psychosis with elevations in medial frontal glutamate, choline, and myo-inositol. The presence of elevations in these markers supports the continued investigation of glutamate-acting and inflammatory pathway-associated interventions for psychosis and schizophrenia.

Humans↗

PubMed2026

Challenges and future directions in AI-driven biomaterials for microbiome-associated oral infectious diseases: A systematic review.

Oral biofilm-induced antimicrobial resistance is the core pathogenic mechanism of microbiome-associated oral infectious diseases (dental caries, periodontitis, peri-implantitis, and endodontic infection). Traditional therapies and biomaterials are limited by poor biofilm penetration, drug resistance induction, single functionality, and inadequate adaptation to dynamic oral microenvironmental changes (e.g., pH fluctuations, salivary rinsing, masticatory stimulation). Artificial intelligence (AI) has transformed the field by integrating materials science, microbiology, and stomatology data. Via machine learning, deep learning, and multi-physics simulation, AI optimizes biomaterial physicochemical properties, decodes microenvironmental signals, constructs precise sensing-response loops, and supports the full chain of material design, performance prediction, and action simulation, advancing treatment from empirical intervention to precision regulation. This systematic review retrieved literature from PubMed, Embase, and Web of Science (January 2016-January 2026) using keywords across three dimensions: AI, biomaterials, and oral microbiome. Following inclusion/exclusion criteria, 99 articles were included. It elaborates on five core mechanisms of AI-driven oral biomaterials (precise oral microbiome analysis, targeted material design/optimization, performance prediction/simulation, targeted delivery/intervention, effect evaluation/dynamic regulation), analyzes their applications in microbiome-targeted biomaterial research and development (R&D) and clinical practice for the four major oral infectious diseases, addresses technical bottlenecks (insufficient targeting specificity and precision of biomaterials, poor stability and durability in complex oral microenvironments, inadequate biofilm disruption capacity, and clinical translation obstacles), and proposes future directions (multimodal design to enhance targeting specificity, structural and component optimization to improve stability/durability, development of multi-mechanism synergistic biofilm disruption strategies, strengthening translational research for clinical application, and deep integration of AI in the full chain of biomaterial R&D). This work provides comprehensive theoretical and practical support for the R&D, optimization, and clinical translation of AI-driven microbiome-targeted oral biomaterials.

Humans↗

PubMed2026

Clade-dependent antifungal resistance and susceptibility in Candidozyma auris: A global scoping review.

BACKGROUND: Candidozyma auris (formerly Candida auris) is an emerging multidrug-resistant fungal pathogen that has spread globally since its first identification in 2009 and is now classified as a critical-priority pathogen by the World Health Organization. Distinct genetic clades are associated with variations in geographic distribution, antifungal susceptibility, and resistance mechanisms; however, clade-specific evidence remains fragmented. AIMS: To systematically map global evidence on clade diversity, antifungal susceptibility patterns, resistance mechanisms, and clinical implications of C. auris. METHODS: A scoping review was conducted following PRISMA-ScR guidelines. Peer-reviewed primary studies published between 2009 and September 2025 were included if they reported clade attribution and antifungal susceptibility or resistance data. PubMed/MEDLINE, Scopus, and Web of Science were searched. Two reviewers independently screened studies and extracted data using a standardized form. RESULTS: Of 2050 records identified, 105 studies met inclusion criteria, representing 29 countries and diverse study designs. Whole-genome sequencing was the most common typing method. Antifungal susceptibility varied substantially across clades. High fluconazole resistance was consistently reported (MIC 4 to >256μg/mL). Echinocandins generally retained activity, although reduced susceptibility associated with FKS1 mutations was observed. Resistance mechanisms primarily involved mutations in ERG11, FKS1, and efflux-related genes. Studies also reported challenges in healthcare-associated transmission, environmental persistence, and diagnostic misidentification. CONCLUSIONS: C. auris exhibits marked clade-dependent variability in antifungal susceptibility and resistance mechanisms. These findings support the need for clade-informed interpretation of susceptibility data, standardized surveillance, improved diagnostics, and development of novel antifungal therapies.

Antifungal Agents↗

PubMed2026

Effects of blood flow restriction training combined with resistance training on lower-limb strength and sport-specific performance in athletes: a systematic review and meta-analysis.

BACKGROUND: In contemporary sports science, athletes and coaches continuously explore strategies to reduce training load and injury risk while increasing muscular strength and sport-specific performance. This meta-analysis evaluated the effects of blood flow restriction training (BFRT) combined with resistance training (RT) on lower-limb muscle strength and sport-specific performance in athletes. METHODS: Relevant randomized controlled trials (RCTs) were systematically searched across major databases (e.g. PubMed, Web of Science, Cochrane, CNKI, Wanfang Data, and Embase) from inception until November 2024. Two independent reviewers carefully assessed the studies. Data analysis was carried out using RevMan 5.4 software, which included heterogeneity testing, meta-analysis, subgroup analysis, and assessment of publication bias. RESULTS: Ten RCTs (181 athletes; 91 in the BFRT and RT group, 90 in the control group) were included. Outcomes determined BFRT combined with RT yielded notable enhancements in lower-limb muscle strength (SMD = 1.09, 95% CI [0.52, 1.66], p < 0.05) and muscle hypertrophy (MD = 1.09, 95% CI [0.10, 2.09], p < 0.05) compared to control training. However, no significant improvement in sport-specific performance was found (SMD = 0.11, 95% CI [-0.18, 0.40], p = 0.46). Substantial heterogeneity was observed for strength outcomes (I2 = 75%), whereas low heterogeneity was observed for sport-specific performance and hypertrophy outcomes (I2 = 0%). No evidence of significant publication bias was detected. CONCLUSION: BFRT combined with RT appears to provide effective augmentation of lower-limb muscle strength and hypertrophy in athletes compared to RT or conventional training alone. It may be prudent to integrate this approach systematically into training cycles to optimize physiological muscle stimulation and training outcomes, despite not directly improving sport-specific performance.

Humans↗

PubMed1979

Searching the MEDLARS file on NLM and BRS a comparative study.

A comparison of the MEDLARS data base as it is currently available from the National Library of Medicine and Bibliographic Retrieval Services (BRS), Inc., is presented in chart format, and some major capability differences between the two systems are highlighted. The information inlcuded justifies the dual availability of the data base in health sciences libraries. This paper is intended for searchers and others familiar with one or both systems. Administrators considering the acquisition of the BRS system may find the study useful.

MEDLARS↗

PubMed2025

A decentralized future for the open-science databases.

The continuous and reliable open access to curated biological data repositories is indispensable for accelerating rigorous scientific inquiry and fostering reproducible research outcomes. However, the current paradigm, which relies heavily on centralized infrastructure for the storage and distribution of foundational biomedical datasets, inherently introduces significant vulnerabilities. This centralized model is susceptible to single points of failure, including cyberattacks, technical malfunctions, natural disasters, and even political or funding uncertainties. Such disruptions can lead to widespread data unavailability, data loss, integrity compromises, and substantial delays in critical research, ultimately impeding scientific progress. The downstream effect of such interruptions can be the widespread paralysis of diverse research activities, including computational, clinical, molecular, and climate studies. This scenario vividly illustrates the inherent dangers of consolidating essential scientific resources within a single geopolitical or institutional locus. As data generation is accelerating and the global landscape continues to fluctuate, the sustainability of centralized models must be critically re-evaluated. A shift toward federated and decentralized architectures may offer a robust and forward-looking approach to enhancing the resilience of scientific data infrastructures by reducing exposure to governance instability, infrastructural fragility, and funding volatility, while also promoting equity and global accessibility. Inspired by established models such as ELIXIR's federated infrastructure and the policy and funding frameworks developed by CODATA and the Global Biodata Coalition (GBC), emerging Decentralized Science (DeSci) initiatives can contribute to building more resilient, fair, and incentive-aligned data ecosystems. The future of open science depends on integrating these complementary approaches to establish a globally distributed, economically sustainable, and institutionally robust infrastructure that safeguards scientific data as a public good, further ensuring continued accessibility, interoperability, and preservation for generations to come. Here, we examine the structural limitations of centralized repositories, evaluate federated and decentralized models, and propose a hybrid framework for resilient, fair, and sustainable scientific data stewardship.

data accessibility↗

PubMed2026

Neuromodulation for Subjective Tinnitus: A Systematic Review and Meta-Analysis of Randomized Trials.

OBJECTIVE: To evaluate the effectiveness and safety of neuromodulation and bimodal stimulation for chronic subjective tinnitus in randomized controlled trials (RCTs). DATA SOURCES: PubMed/MEDLINE, Web of Science, and EMBASE (January 2015-December 2025) searched per PRISMA 2020. REVIEW METHODS: Adult RCTs (≥ 18 years) with chronic subjective tinnitus (> 3 months) assessing validated outcomes (THI, TFI, TQ) for neuromodulation/bimodal interventions vs. sham/controls. Two-stage screening, Cochrane RoB-2 risk-of-bias assessment. Random-effects meta-analyses (REML) were performed when ≥ 3 comparable trials were available; effects reported as standardized mean differences (SMD) with 95% CIs. Main Outcomes and measures included change in tinnitus severity (THI/TFI/TQ) while secondary outcomes included loudness (VAS/NRS), durability, and adverse events. RESULTS: Twenty-six RCTs (n = 1576) met criteria: tES (11; n = 372), rTMS (8; n = 432), acoustic coordinated reset (1; n = 100), vagus nerve stimulation (2; n = 90), and bimodal stimulation (4; n = 582). Meta-analysis showed a nonsignificant pooled effect for tDCS (SMD -0.36; 95% CI -0.75 to 0.02; I 2 = 51%) and rTMS (SMD -0.15; 95% CI -0.37 to 0.07; I 2 = 0%). Single-trial evidence for coordinated reset showed no advantage over broadband noise. VNS demonstrated modest benefits with safety concerns limited to implanted approaches. Bimodal stimulation yielded consistent, clinically meaningful reductions (often ≥ 10-20 points on THI/TFI), with durability up to 12 months. Adverse events were mild/transient across noninvasive modalities. CONCLUSIONS: Noninvasive neuromodulation appears safe with average benefits; among modalities, bimodal stimulation shows the most consistent and durable clinical improvements. Standardized, adequately powered RCTs with harmonized protocols and long-term follow-up are needed to refine targets and dosing.

Humans↗

PubMed2026

Association between the interleukin 17F rs763780 polymorphism and immune thrombocytopenia risk: A systematic review and meta-analysis.

The literature on the Interleukin 17F (IL-17F) rs763780 polymorphism and its association with immune thrombocytopenia (ITP) risk remains inconsistent and controversial. These uncertainties underscore the urgent need for a meta-analysis to objectively synthesize the heterogeneous findings, mitigate bias, and improve statistical power. This study strictly adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and guidelines. A systematic literature search for original studies was conducted across the CNKI, Wanfang Data, Cochrane Library, Web of Science, and PubMed databases, covering publications up to April 5, 2026. Odds ratios and corresponding 95% confidence intervals were calculated to assess the association. STATA 14.2 software was used to synthesize the pooled estimates. A total of eight case-control studies consisting of 805 ITP cases and 841 controls were included. The summarized statistics suggested the detrimental effect of the A allele in the homozygote and recessive models. In the sensitivity analysis, the results that were initially non-significant in the allele, heterozygote, and dominant models became significant after excluding a single dataset, which was also identified as the source of heterogeneity. Region-stratified analyses revealed statistical significance in the Chinese/Japanese and Egyptian subgroups under specific analytic contrasts. When stratified according to age, the children subgroup showed significant associations in a subset of genetic models, while the adult counterpart demonstrated significance across all models. In conclusion, the pooled estimates of the homozygote and recessive models suggested that the rs763780 polymorphism is associated with ITP risk, but this finding requires further validation through large-scale studies.

Humans↗

PubMed2025

Vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS) syndrome: A comprehensive review of cases across different ethnicities.

OBJECTIVES: Vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS) is an autoinflammatory disease associated with somatic mutations in the UBA1 gene. Although the disease has been described in many different countries, no studies have investigated the origin of patients to determine if the disease is universal across ancestries. The aim of this study is to investigate the distribution of VEXAS syndrome across continents and ethnicities. METHODS: A literature review of all reported cases of VEXAS syndrome was conducted between October 2020 and April 2025 using the term 'VEXAS' with the all-field filter in the Pubmed and Web of Science databases. Epidemiological and clinical data were collected for included patients. If the country of origin was not described, it was assumed to be the same as the country of clinical evaluation. A subgroup analysis was performed for patients whose country of origin or ethnicity was documented by the authors. RESULTS: 674 cases of VEXAS syndrome were collected, with patients described from four continents and 32 countries. Considering the subgroup of patients with documented country of origin, 451 patients were from four continents and 19 countries. Of these, ethnicity was recorded for 372 patients with the presence of Caucasian, Central or East Asian, South Asian, Middle Eastern, Central American and South American ethnicities. CONCLUSION: The results support a broad global distribution of the disease and highlight the importance of investigating the disease regardless of the patient's origin and ethnicity in cases of compatible symptoms.

Humans↗

PubMed2024

Recent advances in environmental antibiotic resistance genes detection and research focus: From genes to ecosystems.

Antibiotic resistance genes (ARGs) persistence and potential harm have become more widely recognized in the environment due to its fast-paced research. However, the bibliometric review on the detection, research hotspot, and development trend of environmental ARGs has not been widely conducted. It is essential to provide a comprehensive overview of the last 30 years of research on environmental ARGs to clarify the changes in the research landscape and ascertain future prospects. This study presents a visualized analysis of data from the Web of Science to enhance our understanding of ARGs. The findings indicate that solid-phase extraction provides a reliable method for extracting ARG. Technological advancements in commercial kits and microfluidics have facilitated the efficacy of ARGs extraction with significantly reducing processing times. PCR and its derivatives, DNA sequencing, and multi-omics technology are the prevalent methodologies for ARGs detection, enabling the expansion of ARG research from individual strains to more intricate microbial communities in the environment. Furthermore, due to the development of combination, hybridization and mass spectrometer technologies, considerable advancements have been achieved in terms of sensitivity and accuracy as well as lowering the cost of ARGs detection. Currently, high-frequency terms such as "Antibiotic Resistance, Antibiotics, and Metagenomics" are the center of attention for study in this area. Prominent topics include the investigation of anthropogenic impacts on environmental resistance, as well as the dynamics of migration, dissemination, and adaptation of environmental ARGs, etc. The research on environmental ARGs has made significant advancements in the fields of "Microbiology" and "Biotechnology Applied Microbiology". Over the past decade, there has been a notable increase in the fields of "Environmental Sciences Ecology" and "Engineering" with a similar growth trend observed in "Water Resources". These three domains are expected to continue driving extensive study within the realm of environmental ARGs.

Drug Resistance, Microbial↗

PubMed2026

The impact of artificial intelligence on critical thinking and clinical reasoning in health professions education: A systematic review and meta-analysis.

BACKGROUND: Critical thinking and clinical reasoning underpin healthcare professionals' ability to navigate uncertainties and deliver safe and effective care. With artificial intelligence (AI) advancement and growing adoption, AI-based educational tools are increasingly used to support these cognitive competencies' development. OBJECTIVE: To synthesize randomised and controlled clinical trials on AI-based educational tools in health professions education and examine their effects on critical thinking and clinical reasoning among health professions students. METHODS: Six electronic databases were searched from January 1, 2014 to July 28, 2025 was reviewed: PubMed, Cochrane Central Register of Controlled Trials, CINAHL, Scopus, Embase and Web of Science. Two independent reviewers performed data extraction and quality assessment using standardized JBI checklists. The GRADE approach was used to assess the certainty of evidence. Studies were pooled via random-effects meta-analyses or narrative syntheses. RESULTS: Fourteen randomised controlled trials and seven controlled clinical trials were included (n = 21). Meta-analyses revealed small to medium effect sizes for the surrogate clinical reasoning outcomes of performance-based assessment scores (SMD 0.68; 95% CI [0.38, 0.98], p-value = 0.00; I2 = 38%) and knowledge test scores (SMD 0.39; 95% CI [0.09, 0.69], p-value = 0.01; I2 = 79%). Critical thinking and clinical reasoning skills and dispositions were narratively synthesized, with majority of included studies favouring AI-based interventions but the evidence had low to very low certainty. CONCLUSION: AI-based educational interventions may improve critical thinking and clinical reasoning among health profession students, but the evidence is very uncertain. This review offers preliminary insights but does not allow identification of optimal interventions or discipline-specific recommendations due to small sample sizes and substantial intervention heterogeneity. Further research is required to draw definitive conclusions. PROTOCOL REGISTRATION: CRD42025634074.

Humans↗

PubMed2026

Effects of Moderate-Frequency Resistance Training on Cardiometabolic Risk Factors in Adults With Overweight or Obesity: A Systematic Review and Meta-Analysis.

BACKGROUND: Resistance training (RT) effectively manages cardiometabolic risk factors in adults, but the specific effects of moderate-frequency RT (2-3 sessions/week) in adults with overweight or obesity are understudied. OBJECTIVE: This study aimed to evaluate moderate-frequency RT's effects on cardiometabolic risk factors in this population and quantify effect sizes. DATA SOURCES: PubMed, Web of Science, EMBASE, and Cochrane Library searched up to July 2025. ELIGIBILITY: English randomized controlled trials (RCTs) comparing RT (≥ 7 weeks) to nonexercise control; nonathletic adults ≥ 18 years with BMI ≥ 25 kg/m2. PARTICIPANTS: 454 participants across 12 RCTs (mean age 58.93 ± 12.87 years; mean BMI 31.2 ± 3.5 kg/m2; ~50% female). RESULTS: RT significantly reduced diastolic blood pressure (MD = -1.53 mmHg; 95% CI: -2.16 to -0.91; p < 0.01), LDL-C (MD = -0.25 mmol/L; 95% CI: -0.41 to -0.08; p < 0.01), and triglycerides (MD = -0.17 mmol/L; 95% CI: -0.30 to -0.04; p = 0.01). No significant effects on systolic blood pressure, mean arterial pressure, waist circumference, glycemic markers, total cholesterol, or HDL-C. Subgroup analyses showed larger LDL-C/triglyceride improvements with concurrent dietary control. CONCLUSION: Moderate-frequency RT inconsistently improves cardiometabolic risk factors, benefiting diastolic blood pressure, LDL-C, and triglycerides but not glycemic or other parameters. Combining with dietary control may enhance benefits, supporting RT as a complementary strategy in multimodal lifestyle interventions. TRIAL REGISTRATION PROSPERO: CRD42022343167.

Humans↗