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PubMed2026

User Engagement and Feature Preferences in an AI-Powered mHealth Intervention for Diabetes Prevention: Secondary Analysis of a Randomized Controlled Trial.

BACKGROUND: Prediabetes is highly prevalent and increasing globally, yet lifestyle interventions remain underused. AI-driven mobile health (mHealth) tools can help scale diabetes prevention efforts, but the key factors driving their success are not well understood. OBJECTIVE: This post hoc secondary analysis of a randomized controlled trial (RCT) aimed to characterize the most valued features and the role of user engagement in outcomes of a fully automated mHealth intervention for diabetes prevention. METHODS: Data from 151 participants with prediabetes and overweight or obesity who were assigned to an AI-based diabetes prevention program (Sweetch) in a parent RCT (NCT05056376) were analyzed. Engagement (defined as the total number of days the app was used) was categorized into tertiles (low, medium, and high). Baseline characteristics were compared across engagement groups using ANOVA, Kruskal-Wallis, and chi-square tests, and regression models assessed the association between engagement and achievement of diabetes risk reduction outcomes (≥5% weight loss, ≥4% weight loss with ≥150 min/week of physical activity, or ≥0.2 percentage point reduction in hemoglobin A1c [HbA1c] at 12 months). Perceived usefulness of intervention features was surveyed at 12 months. RESULTS: Median engagement was 98 (IQR 34-232) days. Older age (P<.001) and lower baseline BMI (P=.04) were significantly associated with higher engagement. Compared with low engagement, high engagement was associated with greater odds of achieving the composite diabetes risk reduction outcome (odds ratio [OR] 2.59, 95% CI 1.11-6.01; P=.03), ≥5% weight loss (OR 3.31, 95% CI 1.16-9.42; P=.03), and ≥0.2 percentage point reduction in HbA1c (OR 3.57, 95% CI 1.19-10.75; P=.02). Participants most frequently rated weight tracking, physical activity tracking, and the digital body weight scale as the features that were most helpful for achieving their health goals. CONCLUSIONS: Higher engagement with an AI-driven intervention requiring no human intervention was associated with improved diabetes risk reduction. Contrary to concerns about lower digital literacy, older adults engaged with the intervention more than younger adults. Features related to weight and physical activity tracking were most valued by patients in the program. TRIAL REGISTRATION: ClinicalTrials.gov NCT05056376; https://clinicaltrials.gov/study/NCT05056376.

Humans↗

PubMed2026

Effects of exercise on aerobic capacity in people with prehypertension or hypertension: a systematic review and meta-analysis of randomized controlled trials.

This study aimed to quantify the effects of exercise on aerobic capacity in people with prehypertension or hypertension and to identify exercise prescription parameters that optimize improvements. A comprehensive search was conducted in PubMed, Web of Science, Embase, Cochrane Library, and Scopus from inception to 24 October 2025. Data were pooled using standardized mean differences (SMDs) with 95% confidence intervals (CI). Fifteen studies met the inclusion criteria. Exercise significantly improved aerobic capacity in people with prehypertension or hypertension (SMD = 0.88; 95% CI: 0.61-1.15; P  < 0.00001), with multicomponent training demonstrating superior efficacy. Exploratory subgroup analyses suggest that longer programs (≥12 weeks), lower frequency (<3 sessions/week), 60-min sessions or longer, total weekly exercise less than 180 min, and professional supervision may be associated with better outcomes.

Humans↗

PubMed2026

The Effect of Game-Based Virtual Reality Rehabilitation and Its Impact on Upper Extremity Function After Arthroscopic Rotator Cuff Repair: A Randomized Controlled Trial.

BACKGROUND: Arthroscopic rotator cuff repair (ARCR) often results in prolonged recovery and limited shoulder function. Conventional physical therapy rehabilitation programs require sustained patient engagement; however, adherence is frequently low. Game-based virtual reality (VR) offers an interactive and engaging environment that may enhance rehabilitation outcomes. OBJECTIVE: To evaluate the effect of a game-based VR program on the function of the upper limb in patients following ARCR. METHODS: A randomized controlled trial was conducted with patients who underwent ARCR. Participants were randomized into two groups: game-based VR or conventional rehabilitation. Outcomes were evaluated using the Disabilities of the Arm, Shoulder and Hand score, pain severity by the Numerical Pain Rating Scale, range of motion measures, and muscle strength testing. Assessments were performed at baseline and at 6 weeks and 12 weeks post surgery. RESULTS: Results have shown significant within-group improvements in pain, function, range of motion, and isometric muscle strength across all time points (P < 0.05). Between-group analysis revealed greater improvements in pain, function, flexion range, and abduction and external rotation strength in the experimental group at both time points (P < 0.05). Abduction range improved significantly only at 12 weeks (P = 0.02), whereas external rotation range showed no significant difference between groups at either time point (P > 0.05). CONCLUSION: The findings indicate that integrating game-based VR rehabilitation provides additional benefits over conventional therapy in improving pain and upper extremity function following ARCR. These findings support the use of VR as an effective alternative to the conventional rehabilitation for postoperative rehabilitation.

Humans↗

PubMed2026

Leading with Innovation: Maternal Health Transformation in New York City Health + Hospitals.

New York City's (NYC) maternal health crisis drew close attention in the late 2010s, driven by alarming data: Approximately 30 women died annually during childbirth in NYC, Black non-Hispanic women were 12 times more likely to die than white women, and more than 3,000 women experienced life-threatening birth complications each year. In response, NYC committed $12.8 million in July 2018 to reduce maternal mortality and eliminate racial disparities.NYC Health + Hospitals (H+H)-the nation's largest public health system, serving 1.1 million patients annually with roughly 15,000 births per year-became the primary vehicle for this initiative. With 80 percent of the system's deliveries covered by Medicaid and a patient population that is 51.2 percent Hispanic and 27.1 percent Black, H+H is uniquely positioned to lead the fight against maternal health inequity.Three flagship programs anchor H+H's response to the city's maternal mortality rate. The OB Simulation Program, launched in 2012 and expanded in 2018, was the first in the nation to use mannequins of color to train thousands of providers in obstetric emergencies. The Maternal Home Program, piloted at H+H's Kings County Hospital in 2019 and scaled system-wide by 2021, has served more than 10,341 patients, generating more than 33,000 referrals for social, behavioral health, and community resources. The Cardio-Obstetrics Program located at Kings County Hospital targets cardiovascular disease-the leading cause of maternal death among Black women-through screening, education, and community outreach. These programs are a health equity imperative, made more urgent by impending federal Medicaid cuts resulting from the H.R.1 One Big Beautiful Bill Act (passed on July 4, 2025).

Humans↗

PubMed2026

Regional and statewide hysterectomy-corrected endometrial cancer incidence and five-year relative survival in Texas.

BACKGROUND: Rising endometrial cancer (EC) incidence nationwide, particularly among Hispanic women, and high prevalence of risk factors such as obesity and comorbidities in Texas, motivated us to estimate EC incidence rates (IRs) and survival by age (<50 years/ early-onset, ≥50 years/late-onset), race-ethnicity (Non-Hispanic-White [NHW], -Black [NHB], Hispanic), histology (endometrioid, non-endometrioid), and area-based socioeconomic (SES) factors across Texas Health Service Regions (HSRs). STUDY DESIGN: Between 2000 and 2019, a total of 42,571 women (20-79 years) with EC were reported from Texas within the Surveillance, Epidemiology, and End Results Program. IRs and 5-year relative survival were calculated using SEER*Stat. IRs were corrected for hysterectomy using Behavioral Risk Factor Surveillance System data. RESULTS: Statewide EC IRs rose from 38.5 (2000-2009) to 44.5 (2010-2019), with the highest increase in the Upper-South (42.6 to 53.8). Across HSRs, Upper-South consistently had higher IRs among women < 50 (13.9) and ≥ 50 years (112.7). Among those < 50 years, Hispanics had the highest IRs (12.4), predominantly endometrioid tumors, whereas in women ≥ 50 years, NHB had the highest IRs (119.2) with a large proportion of non-endometrioid tumors. IRs were higher in areas with lower poverty, and higher education, income, and urbanization. Associations with unemployment were mixed. Worse survival outcomes were observed among NHBs, non-endometrioid, advanced-stage, and lower SES. Central Texas had more favorable survival outcomes compared to other HSR. CONCLUSION: EC IRs and survival rates in Texas largely mirror national trends, with regional differences likely reflecting sociodemographic and histologic distributions.

Humans↗

PubMed2026

Effect of walking training on blood glucose control and metabolic health in patients with type 2 diabetes: A systematic review and meta-analysis.

OBJECTIVE: To systematically evaluate the improvement effect of walking training on blood glucose control and metabolic health indicators in type 2 diabetes patients, and to explore the effect of different intervention program characteristics on the efficacy through subgroup analysis. METHOD: The system searched PubMed, Web of Science, EMBASE, Cochrane Library, and EBSCO databases, with a search period from the establishment of the database to March 15, 2026. Include a randomized controlled trial with the main intervention measures of walking behavior, with an intervention period of ≥8 weeks. Two researchers independently conducted literature screening, data extraction, and bias risk assessment. Meta-analysis was conducted using RevMan 5.4 software, with mean difference (MD) and its 95% confidence interval (CI) as effect measures for continuous variables. Select fixed effects model or random effects model for combined analysis based on heterogeneity size, and conduct subgroup analysis according to intervention program characteristics. RESULTS: Totally 5 randomized controlled trials were included, including 483 patients with type 2 diabetes (241 cases in the intervention group and 242 cases in the control group). Participants had a mean age of 54.2 ± 6.5 years, BMI of 29.1 ± 3.2 kg/m2, and 48.5% were male. The meta-analysis results showed that walking training significantly reduced glycated hemoglobin levels, with a combined effect of -0.48% (95% CI: -0.60 to -0.36, P < 0.00001), There is moderate heterogeneity among the studies (I2 = 67%). Subgroup analysis showed that the "walking + other interventions" subgroup (combined effect size -0.58%, 95% CI: -0.96 to -0.20) and the "clear step target" subgroup (combined effect size -0.52%, 95% CI: -0.65 to -0.39) had larger effect sizes and lower heterogeneity within the subgroups. The bias risk assessment shows that the overall quality of the included research methodology is good. CONCLUSION: Walking training can significantly improve the blood glucose control in patients with type 2 diabetes. Combined with diet or behavioral intervention, setting clear goals for the number of steps may achieve better results. Walking training can be used as an effective auxiliary treatment for the management of type 2 diabetes in clinical promotion. Due to limitations in the number and quality of studies included, the above conclusions still require more high-quality research to validate.

Humans↗

PubMed2026

Maternal obesity in rats results in male-specific increases in genome-wide DNA methylation in postnatal offspring liver.

Male-specific peripubertal DNA demethylation in the liver has been reported in mice. Here, we investigated whether it also occurs in rats, the influence of maternal obesity and whether DNA demethylation changes contribute to observed sex-specific effects of maternal obesity in offspring. Female rats were fed a high-fat, high-sugar 'cafeteria' (Caf) diet before mating with standard chow-fed males. The offspring liver methylome and transcriptome were examined. Body weight was higher in Caf-fed dams prior to mating, during gestation and at parturition. Male and female offspring from Caf-fed dams had lower birth weights but higher adult weights and adiposity than offspring from chow-fed dams. A comparison of DNA methylation in 3-week-old weaner males versus female siblings from chow-fed dams did not reveal the male-specific DNA demethylation that was previously reported in mice. However, strong maternal diet effects in male weaner offspring methylation were observed. A comparison of female weaners from chow- versus Caf-fed dams showed a range of differences, with 39% of differentially methylated regions (DMRs) having higher methylation in Caf offspring and 61% of DMRs having higher methylation in chow offspring. In stark contrast, 99% of maternal-diet-induced DMRs in male weaner offspring had higher methylation in offspring from Caf-fed dams. This suggests that maternal obesity induces widespread hypermethylation in the male offspring liver at weaning. However, a comparison with RNA sequencing data revealed limited transcriptional changes at this developmental stage or in adult offspring. While these data highlight how environmentally sensitive DNA methylation is in the male rodent perinatal period, these methylation changes may not be a major contributor to sex differences in developmentally programmed liver disease.

Animals↗

PubMed2026

Cancer statistics for Asian American, Native Hawaiian, and Pacific Islander people, 2026.

BACKGROUND: Cancer statistics for Asian American and Native Hawaiian and Pacific Islander (NHPI) people are usually aggregated, masking substantial variation within this heterogeneous population. Herein, the American Cancer Society reports cancer incidence and survival for 8 Asian American and 3 NHPI ethnic groups. METHODS: The authors used population-based cancer registry data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program, for Asian American and NHPI ethnic groups from 2000 through 2022. RESULTS: During 2018-2022, overall cancer incidence ranged from 218.3 per 100,000 Kampuchean people to 474.5 per 100,000 Native Hawaiian people, which was 1.5 times higher than the rate for the aggregated Asian American and NHPI population (307.3 per 100,000). High incidence among Native Hawaiian people is largely driven by the highest rates of female breast, colorectal, and prostate cancers, whereas infection-related cancers were highest among Asian American ethnic groups. For example, liver and stomach cancer incidence is highest among Vietnamese (22.2 per 100,000) and Korean people (17.8 per 100,000), respectively, both of which were nearly twice that in Native Hawaiian people (12.9 and 9.6 per 100,000, respectively). Native Hawaiian and Samoan women are twice and 3 times as likely, respectively, to be diagnosed with uterine corpus cancer as aggregated Asian American and NHPI women or White women. Five-year relative survival ranges from 42% in Laotians to 74% in Asian Indians/Pakistanis, with largest differences for colorectal (43% in Laotians to 72% in Asian Indians/Pakistanis) and prostate (63% in Kampucheans to 97% in Japanese) cancers. CONCLUSIONS: Wide variation in cancer risk within the Asian American and NHPI population highlights the critical need for disaggregated data to effectively target cancer prevention and control interventions.

Adolescent↗

PubMed2026

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of Ψ sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine↗

PubMed2026

Glucocorticoids and placental 11βHSD2 - A systematic review of human studies and animal models.

CONTEXT: Elevated prenatal glucocorticoid (GC) exposure is linked to adverse offspring outcomes. The placental enzyme 11β-hydroxysteroid-dehydrogenase-type-2 (11βHSD2) protects the fetus by converting maternal derived cortisol to inactive cortisone. Although in vitro studies suggest GC mediated upregulation of 11βHSD2, in vivo evidence remains inconclusive. METHODS: PubMed, Embase, and PsycInfo were searched in October 2024 for human and mammalian animal studies on endogenous or exogenous GCs during pregnancy and associations with placental 11βHSD2 (mRNA, protein, activity, gene methylation). Narrative synthesis was conducted due to heterogeneity precluding meta-analysis. RESULTS: Eighteen studies (eight human, ten animal populations) met inclusion criteria. Exogenous GC exposure was associated with modifications in placental 11βHSD2 expression in animal models, with effects varying by substance, timing, and species. Dexamethasone trended towards increased expression in rodents, whereas betamethasone increased expression in non-human primates but not rodents. Human studies on endogenous GCs showed inconsistent associations with 11βHSD2 changes. In asthmatic pregnancies, moderate inhaled GC-use maintained enzyme activity compared to untreated patients. No convincing sex-specific trend emerged. CONCLUSIONS: GC exposure alters placental 11βHSD2 in a substance- and species-specific way; translational relevance remains limited based on current literature. Future studies should employ technological advances and include GC-sensitive biomarkers to clarify mechanisms of maternal-fetal stress transmission.

Female↗

PubMed2026

Pembrolizumab-Chemotherapy Versus Pembrolizumab in Head and Neck Squamous Cell Carcinoma: A PD-L1 CPS-Stratified Analysis of Updated KEYNOTE-048 Data.

Based on KEYNOTE-048, pembrolizumab monotherapy and pembrolizumab-chemotherapy are established category 1 first-line treatments for recurrent/metastatic head and neck squamous cell carcinoma (HNSCC) with programmed death ligand-1 (PD-L1) combined positive score (CPS) ≥ 1. We compared their efficacy using updated trial data. We analyzed 4-year progression-free survival on next-line therapy (PFS2) and 5-year overall survival (OS) data from KEYNOTE-048 by reconstructing time-to-event data using KMSubtraction. Efficacy was compared in CPS 1-19 and CPS ≥ 20 subgroups using Kaplan-Meier estimates, Cox models, restricted mean survival time (RMST), and landmark analyses. Among 499 patients with CPS ≥ 1, 240 (48.1%) had CPS 1-19 and 259 (51.9%) had CPS ≥ 20. In the CPS 1-19 subgroup, pembrolizumab-chemotherapy showed numerically longer median PFS2 (10.1 vs. 8.0 months; hazard ratio [HR]: 0.81; 95% confidence interval [CI]: 0.62-1.06) and OS (12.8 vs. 10.8 months; HR: 0.87; 95% CI: 0.67-1.15) versus monotherapy, without statistical significance. For CPS ≥ 20 patients, efficacy was comparable between regimens, with similar median PFS2 (11.3 vs. 11.7 months; HR: 0.95) and OS (14.7 vs. 14.9 months; HR: 0.96). RMST and landmark analyses showed an early PFS2 benefit and a trend toward OS benefit with pembrolizumab-chemotherapy in CPS 1-19, with comparable outcomes in CPS ≥ 20. Pembrolizumab-chemotherapy showed a trend toward improved outcomes in the CPS 1-19 subgroup, with comparable efficacy in the CPS ≥ 20 subgroup, supporting a refined first-line strategy: monotherapy for CPS ≥ 20 to minimize toxicity, and combination therapy for CPS 1-19 to potentially enhance disease control.

Humans↗

PubMed2026

Reinforcement learning-based dynamic ensemble for missense variant effect prediction and tiered prioritization of VUS.

BACKGROUND: Accurate classification of missense variants remains a challenging task despite major advances in genomics. Numerous computational models have been developed to assist in variant classification, but often require repeated integration and benchmarking efforts. Ensemble methods have been proposed to overcome the limitations of single predictors, but mostly rely on fixed, predefined weights that constrain their ability to capture interactions among predictive signals. METHODS: We present GenixRL, a dynamic ensemble framework that reformulates model fusion as a reinforcement learning optimization problem. GenixRL uses a Q-learning agent to learn a policy that dynamically weights the probabilistic outputs of complementary predictors, including BayesDel (addAF and noAF), ClinPred, and MetaRNN. Replacing static weighting with policy learning allows GenixRL to adaptively identify optimal weightings and substantially improve classification accuracy. RESULTS: In benchmark evaluation against 25 state-of-the-art predictors, GenixRL achieved an AUROC of 0.9644 on an independent ClinVar dataset. On saturation genome editing assays for BRCA1 and BRCA2, GenixRL achieved the best performance and ranked highest on 14 of 17 clinically significant genes in a zero-shot evaluation. Applied to uncertain and conflicting ClinVar variants, GenixRL enabled tiered, evidence-based prioritization of hundreds of thousands of variants as likely pathogenic or pathogenic with high confidence, supported by orthogonal population evidence from gnomAD. CONCLUSION: GenixRL advances pathogenicity prediction for missense variants and provides an adaptive ensemble that sorts variants of uncertain significance into tiered candidates for expert curation and functional validation.

Mutation, Missense↗

PubMed2026

Effects of cinnamon supplementation combined with exercise training on anthropometric indices and reproductive hormones in overweight and obese women.

BACKGROUND: The prevalence of obesity and increased fat in the chest and abdomen in women and hormonal changes, can affect female fertility. The present study aims to investigate the effect of exercise training combined with cinnamon supplementation on chest and abdominal circumference, as well as sex hormones, in overweight and obese women. METHODS: Twenty-six inactive overweight and obese women were randomly allocated to an exercise (E; n = 13) and exercise plus cinnamon supplementation (E+S; n = 13) group. Both groups completed a 4-week exercise program three times weekly, while the E+S group additionally received cinnamon supplementation three times weekly. Chest and abdominal circumferences and serum concentrations of estradiol, progesterone, follicle-stimulating hormone (FSH), and luteinizing hormone (LH) were assessed before and after the intervention. RESULTS: Significant pre-to-post reductions in chest and abdominal circumference were observed in both groups (all p ≤ 0.005). Estradiol, progesterone, and FSH concentrations increased, whereas LH concentrations decreased significantly in both groups (all p ≤ 0.005). However, between-group comparisons revealed a significant difference only for chest circumference (p = 0.003), with no significant group differences in abdominal circumference or any reproductive hormone concentration (all p > 0.05). CONCLUSION: Both groups showed favorable changes in anthropometric and reproductive hormone measures following the 4-week study period. However, the significant between-group difference was limited to chest circumference, providing no clear evidence that cinnamon supplementation conferred additional benefits for abdominal circumference or reproductive hormone profiles beyond those observed with exercise. These findings highlight the potential relevance of exercise-based interventions while warranting confirmation in larger, adequately powered trials.

Humans↗

PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

Mixed Methods Research on Family Caregiving for Stroke Survivors: A Methodological Systematic Review.

AIM: To examine how mixed methods research has been applied in studies of family caregiving for stroke survivors, focusing on key methodological components (rationale, design types, integration strategies, and use of joint displays). DESIGN: Methodological systematic review. METHODS: A systematic search of five databases yielded 17 studies. The extraction focused on mixed methods features (rationale, design, integration, joint displays), and quality was appraised using the Mixed Methods Appraisal Tool. DATA SOURCES: PubMed, CINAHL, Scopus, Web of Science, and PsycINFO were searched for relevant studies published from 2010 to 2025. RESULTS: The included studies addressed topics such as caregiver burden, coping, resilience, and intervention outcomes. Convergent and explanatory sequential designs predominated. Complementarity was the most frequent rationale for mixing methods. Integration occurred mainly through merging, with fewer instances of connecting or building. Three studies included joint displays to integrate the results. CONCLUSION: Mixed methods research is increasingly applied in family caregiving. To advance the field, researchers should strengthen integration during analysis and results and improve transparency in reporting key design features. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Strengthening methodological rigour in mixed methods studies on stroke caregiving will improve the evidence base for nursing practice. Intentional and meaningful integration of qualitative and quantitative evidence can better inform effective interventions and support programs, ultimately enhancing care for stroke survivors and their families. IMPACT: This review evaluates how mixed methods research is applied in family caregiving studies. It identifies significant methodological gaps, including unclear reporting of design and limited use of advanced integration techniques. The recommendations provide practical guidance for researchers to improve reporting and integration, yielding richer evidence to inform interventions and policies that support family caregivers. REPORTING METHOD: The review followed the PRISMA 2021 guidelines for transparent reporting of systematic reviews. PATIENT OR PUBLIC CONTRIBUTION: No patient or public involvement.

Humans↗

PubMed2026

Exploring Implementation of Cantonese Radio Broadcasting as a Mental Health Promotion Initiative for Linguistically Isolated Immigrants.

Digital-first public health efforts often miss linguistically isolated immigrant communities because of structural barriers and stigma. Ethnic legacy media can reach these groups, but keeping programs funded and operational over the long term is frequently difficult. This Practice Note examines a Cantonese-language radio health program in "Los Angeles County" that ran 128 live broadcasts across a full 12-year Chinese zodiac cycle. Instead of a top-down clinical model, the show endured by acting as an informal community navigation hub. We examine two recurring administrative frictions: anonymous off-air calls about urgent economic needs (e.g., hotel job referrals) and on-air audience corrections of mispronounced medical terms. We argue these interactions should be seen not as disruptions but as measurable indicators of structural trust that sustain programs. We offer practical guidance for recruiting undergraduates to expand reach via ethnic print newspapers, using peer-recovery milestones to amplify impact. The note concludes with a pragmatic blueprint for health educators to manage professional boundaries, preserve commercial-clinical separation, and uphold cultural safety in isolated communities.

Chinese American health↗

PubMed2026

A contextual activity score (CAS) for inferring ADAR-associated transcriptional activity across RNA-seq, single-cell, and spatial transcriptomics.

BACKGROUND AND OBJECTIVE: Adenosine-to-inosine RNA editing, catalyzed by Adenosine Deaminases Acting on RNA (ADARs), is a widespread modification involved in neural function, immune regulation, and cancer. The Alu Editing Index (AEI) is the standard metric to estimate ADAR activity but requires raw sequencing reads and is poorly suited for single-cell and spatial transcriptomic data. This study aimed to develop an alternative framework for inferring ADAR-associated transcriptional activity from gene expression data across diverse transcriptomic technologies. METHODS: We developed the Contextual Activity Score (CAS), a framework based on transcriptional signatures from ADAR perturbation experiments. Context-specific signatures were generated for human neurons, mouse neurons, and cancer models to infer ADAR1 and ADAR2 activity. CAS was computed from normalized gene expression matrices using regulon-based enrichment analysis. Performance was evaluated by comparing with the Alu Editing Index across bulk RNA sequencing datasets, simulated sequencing depths, and library preparation protocols. RESULTS: CAS showed strong concordance with the Alu Editing Index across multiple datasets, while remaining robust to reduced sequencing depth and different library protocols. Unlike the Alu Editing Index, CAS can be applied to single-cell and spatial transcriptomic data and enables the independent assessment of ADAR2 activity. In cancer and neuronal contexts, CAS captured biologically meaningful variations in ADAR-associated transcriptional activity at sample, cell-type, and spatial levels. CONCLUSION: CAS provides a scalable approach applicable across multiple RNA-seq protocols for estimating ADAR-associated transcriptional activity using gene expression data. This method, implemented in an open-source R package for broad adoption, expands the ability to study ADAR-associated transcriptional activity across transcriptomic modalities where direct editing quantification is challenging, such as single-cell and spatial transcriptomics.

Adenosine Deaminase↗

PubMed2026

Effects of digital health-based exercise interventions on older adults with sarcopenia: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Sarcopenia, the progressive loss of muscle mass and function, impairs independence in older adults. Digital health exercise interventions are scalable solutions for older adults with sarcopenia. This systematic review and meta-analysis aimed to synthesize the evidence on their efficacy in populations with clinically diagnosed sarcopenia and identify influential intervention characteristics associated with treatment outcomes. METHODS: We systematically searched PubMed, EMBASE, Web of Science, Cochrane Library, CINAHL, CNKI, and Wanfang on May 20, 2026, with no date restrictions. We included randomized controlled trials involving adults aged ≥60 with sarcopenia receiving digital exercise interventions. Two reviewers independently screened studies, extracted data, and assessed risk of bias; analyses were performed using R and Review Manager. RESULTS: Fourteen trials (n = 927) were included. Digital interventions showed potential improvements in muscle mass (MD = 0.25, 95%CI:0.03-0.46, 95% PI:-0.36 to 0.85), muscle strength (MD = 2.14, 95% CI:1.18-3.11, P < 0.001), balance ability (SMD = 0.31, 95% CI:0.12-0.51, P = 0.001), walking performance (SMD = 0.55, 95% CI:0.21-0.89, 95% PI:-0.70 to 1.79), and physical function (SMD = 0.89, 95% CI:0.08-1.71, 95% PI:-2.33 to 4.12), but not quality of life (SMD = 0.08, 95% CI:-0.19 to 0.35, P = 0.53). Exploratory subgroup analyses suggested that factors such as supervision, program duration, and measurement tools may influence outcomes; however, formal tests for subgroup differences were generally non-significant, and consistent patterns across all metrics were not observed. CONCLUSION: Digital exercise interventions show potential for managing sarcopenia in older adults, though the very low to moderate certainty of evidence indicates that true effects may differ substantially from observed estimates. This review explores potential roles of intervention design, supervision, and multimodal delivery. Future research should adopt rigorous designs and longer follow-up to validate results and enhance clinical application. TRIAL REGISTRATION: PROSPERO CRD420251135174.

Humans↗