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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

A systematic review of sleep hygiene interventions in physically and operationally demanding occupations.

Workers in physically and operationally demanding (POD) occupations (e.g. military personnel, emergency responders, law enforcement) experience disrupted sleep due to irregular schedules and high-stress work environments. Given the importance of sleep for physical and cognitive performance, interventions to improve sleep in POD occupations are crucial yet remain under-researched. To investigate the effectiveness of sleep hygiene interventions in improving sleep quality and quantity outcomes for POD occupations, a systematic review was conducted across five databases (PubMed, CINAHL, SPORTDiscus, PsycINFO, Web of Science) in September 2024. Eligible studies involved workers in POD occupations where a sleep hygiene intervention was compared against a waitlist or passive control. Ten studies were included, eight randomised controlled trials (RCTs) and two non-randomised controlled trials (NRCTs). Narrative synthesis identified Structured Training Programs (n = 7), Phone Assistance Programs (n = 2), and Single Lecture Interventions (n = 1). Evidence certainty ranged from Very Low to Moderate, converging towards Low quality due to imprecision, risk of bias, and indirectness. Structured Training Programs showed moderate improvements in sleep quality and small-to-moderate effects on sleep duration. Phone Assistance Programs had minimal effects, and Single Lecture Interventions had negligible impact. Higher-quality research is urgently needed to assess sleep hygiene interventions in POD occupations.

Humans↗

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

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

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

Ethiopia missed opportunities for vaccination study: Cluster-randomized evaluation of 5-dose measles vaccine vials and a flexible open-vial policy, 2021-2022.

INTRODUCTION: In 2024, an estimated 95,000 people died from measles globally, largely from suboptimal coverage with the measles-containing vaccine (MCV). Health workers may defer vaccinating eligible children to avoid wasting doses from 10-dose MCV vials, which must be discarded six hours after opening. These missed opportunities for vaccination (MOV) reduce coverage and timeliness. Ethiopia, which provides MCV at 9 and 15 months, considered switching to 5-dose vials. METHODS: We conducted a 15-month, randomized controlled trial with a nested cross-sectional design in Ethiopia. Sixty woredas were randomized to: (1) policy-only, instructing health workers to open 10-dose vials for any number of eligible children, with additional stock for increased wastage; (2) 5-dose switch, combining this policy with replacement of 10-dose by 5-dose vials; or (3) control (routine 10-dose practice). Household and health-facility surveys at baseline and endline assessed effects on first-dose (MCV1) and second-dose (MCV2) coverage, MCV1 timeliness, and wastage. Generalized estimating equation models estimated net intervention effects versus control. We also estimated the government cost of a nationwide 5-dose switch. RESULTS: MCV1 coverage was similar between policy-only and control (adjusted risk difference [ARD] = -1%, 95%CI: -17%, 15%), with no significant differences in MCV1 timeliness or MCV2 coverage. In the 5-dose switch group, MCV1 coverage changed little (ARD = 1%, 95%CI: -17%, 18%), but timely MCV1 at 9 months (ARD = 18%, 95%CI: 7%, 28%) and MCV2 coverage (ARD = 17%, 95%CI: 1%, 34%) rose significantly, and wastage fell (ARD = -7%, 95%CI: -14%, -1%). By endline, 29% of 5-dose health workers opened vials ≥10 times monthly (none in control); caregivers in both intervention groups reported 11% fewer measles-related MOVs. A nationwide 5-dose switch was estimated to save 17% in procurement cost per fully vaccinated (two-dose) child. CONCLUSIONS: The combined 5-dose intervention improved MCV1 timeliness and MCV2 coverage and reduced wastage, addressing a key operational barrier and potentially supporting measles elimination in Ethiopia.

Humans↗

PubMed2026

Physical therapy for urinary incontinence in older women: A systematic review.

BACKGROUND: Urinary incontinence is highly prevalent among older women, affecting more than one-third of this population and significantly impairing quality of life, independence, and healthcare utilization. Older women often present with complex needs that may require broader rehabilitation strategies. METHODS: This systematic review evaluated randomized controlled trials of physical therapy interventions for urinary incontinence in older women. PubMed, Embase, and Scopus were searched to October 2025. Eligible studies included women ≥60 years and assessed interventions such as Pelvic floor muscle training (PFMT), bladder training, Yoga, Pilates, general resistance training, electrical stimulation, or multimodal programs. Methodological quality was appraised using the PEDro scale, and random-effects meta-analysis was performed where appropriate. RESULTS: Twenty studies involving 2002 women across 13 countries were included. Eleven trials were rated as good quality and nine as fair. Meta-analysis demonstrated that PFMT significantly reduced urinary incontinence severity compared with usual care (SMD = -1.27, 95% CI: -2.18 to -0.36, p = 0.006). Multimodal programs combining PFMT with mobility, strength, or fall-prevention training also showed significant benefits (SMD = -0.98, 95% CI: -1.60 to -0.36, p = 0.002). Comparative studies indicated that PFMT was similarly effective to Yoga and Pilates, while adjuncts such as general resistance training or tibial nerve stimulation provided additional improvements. CONCLUSION: Physical therapy interventions, particularly PFMT and multimodal programs, are effective in reducing urinary incontinence severity and improving functional outcomes among older women. These findings support prioritizing physical therapy as an important management strategy, with multimodal approaches offering added value for enhancing functional independence and fall prevention.

Humans↗

PubMed2026

Trends in demographic and health survey publications based on a bibliometric analysis.

BACKGROUND: The Demographic and Health Surveys (DHS) Program, launched in 1984, provides high-quality population health data that underpins a vast body of global health research. However, the scale and growth patterns of DHS-based publications remain underexplored, particularly as donor funding uncertainties threaten program sustainability. OBJECTIVE: We examine temporal trends in DHS-based research output from 1984 to 2025, quantifying growth patterns and publication delays to inform understanding of the program's global research expansion. METHODS: A systematic bibliometric review was conducted following PRISMA guidelines across PubMed, Scopus, Web of Science, Dimensions, Wiley, and CINAHL. Eligible peer-reviewed articles using DHS data between 1984 and 2025 were identified. Annual publication counts were analyzed, segmented regression identified growth inflection points, and timeliness was assessed by calculating lag between survey completion and publication. RESULTS: Over 10,000 DHS-based publications were identified. Annual output rose from isolated studies in the 1980s to several hundred annually by the 2010s. Segmentation analysis revealed two rapid growth phases: a 56-publications/year increase from 2004-2012, and a 71-publications/year increase from 2012 to 2024. Despite this growth, median lag from survey completion to publication remained approximately 5 years, with only a modest recent improvement (Kendall's τ =  -0.623, p < 0.001). CONCLUSION: DHS data have fueled exponential growth in global health research over four decades, confirming their vital role in evidence generation. However, persistent publication delays highlight the need to shorten the pathway from data collection to dissemination through strengthened research capacity in low- and middle-income countries. Sustained funding is essential to maintain this critical evidence source.

Bibliometrics↗

PubMed2026

Transcriptomics reveals species-specific adaptive strategies to calorie restriction in two Argopecten scallops with distinct lifespans.

Calorie restriction (CR) is a well-established non-genetic intervention for lifespan extension in multiple model organisms. Seasonal food shortage in cold and temperate seas may mimic CR, inducing in bivalves a response similar to that in vertebrates and thereby prolonging life expectancy. However, the relationship and the mechanism underlying the food availability and lifespan in bivalves remain largely unexplored. Two closely related scallop species the short-lived warm-water Argopecten irradians (lifespan <2 years) and the longer-lived cold-water Argopecten purpuratus (7-10 years) provide an ideal comparative system to investigate species-specific adaptive strategies. In this study, we subjected both species to CR for 30 and 56 days and performed comparative transcriptomic profiling, weighted gene co-expression network analysis (WGCNA), and physiological assays to elucidate their distinct molecular responses. Transcriptomic analysis revealed that A. purpuratus exhibited substantially more DEGs than A. irradians at both time points under CR, with both species showing downregulation of metabolic pathways but to different extents. A. irradians mounted an early nutrient-sensing response at 30 days (IGF1R, PIK3R3, INSR suppression), indicating acute sensitivity to limitation; by contrast, A. purpuratus displayed delayed FoxO activation at 56 days, along with its downstream effectors NFKBIA, CREB3L4, and SMAD4, suggesting a gradual adaptive program may link to its extended lifespan. WGCNA identified three negatively correlated modules in each species, with coral2 being the most prominent in A. irradians and darkolivegreen in A. purpuratus. The former was dominated by ciliary motility genes, whereas the latter featured coordinated repression of oxidative phosphorylation. Additionally, both species exhibited conserved suppression of mTOR/S6K growth signaling and activation of cellular maintenance programs. Collectively, these findings expand the understanding of CR-mediated longevity regulation in bivalves and provide candidate gene resources for future functional studies and breeding programs.

Pectinidae↗

PubMed2026

An Update on Inborn Errors of V(D)J Recombination.

V(D)J recombination is the fundamental process by which developing T and B lymphocytes generate diverse antigen receptors, enabling adaptive immunity. This tightly regulated program operates exclusively in lymphoid precursors during G1 phase and depends on the lymphocyte-specific RAG1-RAG2 recombinase to introduce programmed DNA double-strand breaks at recombination signal sequences, followed by repair through the classical nonhomologous end joining (c-NHEJ) pathway. Disruption of any step in this molecular choreography compromises antigen receptor diversity and underlies a spectrum of inborn errors of immunity (IEIs), ranging from severe combined immunodeficiency (SCID) to immune dysregulation with autoimmunity and granulomatous disease. In this review, we place disorders of V(D)J recombination within the broader framework of T-cell development, detailing the temporal waves of recombinase activity, chromatin accessibility, and DNA damage responses that guide thymocyte differentiation. We discuss pathogenic variants affecting the cleavage phase [RAG1, RAG2, and the recently identified RAG cochaperone NudC domain-containing 3 (NUDCD3)], end processing (ARTEMIS), ligation and repair (LIG4, XLF, XRCC4, PRKDC), and genome surveillance pathways (ATM, MRN complex, RNF168), highlighting genotype-phenotype correlations and mechanisms driving immune deficiency and dysregulation. We briefly review recent diagnostic advances, including newborn screening using T-cell receptor excision circles, repertoire sequencing, and functional assays, alongside current therapeutic strategies. Finally, we outline key unanswered questions and argue that continued integration of clinical observation with molecular discovery is essential to improve outcomes and deepen understanding of adaptive immune development.

Humans↗

PubMed2026

Preregistration nursing student attrition and strategies to improve student retention in university; an umbrella review.

BACKGROUND: Attrition among preregistration nursing students remains a persistent international challenge, contributing to nursing workforce shortages. Although extensive research has examined factors influencing student attrition and retention, the evidence is fragmented across review-level literature, limiting clarity regarding priority and evidence-informed retention strategies. AIM: To synthesize review-level evidence on factors associated with preregistration nursing student attrition and to identify strategies that support student retention in university-based nursing programs. METHODS: An umbrella review was conducted in accordance with the Joanna Briggs Institute methodology. Six electronic databases were systematically searched for peer-reviewed literature reviews published in English between January 2016 and October 2025. Eligible reviews focused on undergraduate preregistration nursing students in face-to-face university programs. Methodological quality was appraised using the JBI critical appraisal checklist. Findings were synthesised using narrative and thematic approaches. RESULTS: Seventeen literature reviews were included. Attrition was consistently described as multifactorial, influenced by academic preparedness, psychosocial wellbeing, socio-demographic factors, and institutional support. Retention strategies reported across reviews were predominantly relational, developmental, and sustained over time, including mentoring, tutoring, academic skills development, psychosocial support, and interventions that foster belonging. Faculty engagement and holistic approaches were repeatedly associated with improved student persistence. However, the evidence base was largely descriptive, with limited experimental evaluation of intervention effectiveness. CONCLUSION: Preregistration nursing student retention is best supported through multifaceted, sustained strategies that begin at admission and extend throughout the curriculum. While current evidence highlights consistent patterns of effective support, further rigorous research is required to evaluate retention interventions and extend evidence to flexible nursing education pathways.

Humans↗

PubMed2026

Sex differences in sleep and alcohol consumption outcomes following a digital insomnia intervention.

BACKGROUND: Poor sleep is a well-established risk factor for heavy drinking, and evidence suggests that sleep could serve as a potential treatment target for reducing alcohol consumption. The relationship between poor sleep and problematic drinking appears to be stronger among females, but no studies to date have assessed sex differences in alcohol consumption following insomnia treatment. Here, we combine the samples from two clinical trials to investigate sex differences in the effects of a digital cognitive behavioral therapy for insomnia (Sleep Healthy Using the Internet; SHUTi) on sleep and alcohol outcomes. METHODS: 184 heavy drinking individuals with insomnia (weekly binge episodes: 4/5 + drinks in one sitting for females/males; AUDIT score >7; ISI score >14) were randomly assigned to either the SHUTi program (n = 102) or an active control program (n = 82). Participants completed self-report assessments at baseline, immediately following the 9-week intervention period, and at 3 and 6-months post-intervention. RESULTS: Linear mixed effects models showed that SHUTi effects over time were stronger among females than males for improved sleep outcomes and reduced frequency of total and heavy drinking days (ps ≤ 0.038). Follow-up comparisons of within-group effect sizes revealed consistently larger reductions in alcohol consumption among SHUTi females (Cohen's d range = 0.92-2.23) than SHUTi males (Cohen's d range = 0.65-1.95). CONCLUSIONS: Findings suggest that SHUTi may be more efficacious in improving sleep and reducing drinking among females with insomnia compared to males. These results could have important implications for sex-specific prevention and treatment efforts for heavy drinking individuals with insomnia.

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

Effectiveness of an AI-based home exercise app for rehabilitation of rotator cuff-related shoulder pain: A randomized controlled trial.

BACKGROUND: Rotator cuff-related shoulder pain contributes to disability and healthcare use. Although therapeutic exercise is first-line treatment, limited supervision and adherence may reduce its effectiveness; digital rehabilitation with real-time feedback may address these limitations. OBJECTIVES: To evaluate the effectiveness of adding a digital rehabilitation program to standard physiotherapy on pain, function, fear-avoidance beliefs, and healthcare utilization. DESIGN: Single-center, assessor-blinded, randomized controlled trial with two parallel groups. METHOD: Forty-six adults (mean age 59 years) with rotator cuff-related shoulder pain were randomized to 12 weeks of conventional physiotherapy or physiotherapy plus an AI-based digital rehabilitation program using computer vision for real-time feedback and performance monitoring. Outcomes were assessed at baseline and at 2, 4, and 12 weeks. Pain intensity (NPRS) was primary outcome; secondary outcomes included upper limb function (QuickDASH), fear-avoidance beliefs (FABQ), and post-intervention healthcare utilization. Analyses followed an intention-to-treat approach. RESULTS: Pain reduction exceeded the MCID (1.3) at 4 and 12 weeks. Between-group differences favoured the intervention at Weeks 2 and 4 (MD -0.7; 95% CI -1.13 to -0.14 and MD -1.01; 95% CI -1.8 to -0.2, respectively). Upper limb function improved more at Week 4 (MD -7.3; 95% CI -12.3 to -2.2). FABQ scores decreased more at Week 12 (MD -7.6; 95% CI -14 to -0.5). Fewer participants in the experimental group required post-intervention healthcare (3 vs 10; p = 0.02). CONCLUSION: Adding AI-based home exercise app to conventional treatment improve pain and may improve function and reduce healthcare utilization in rotator cuff-related shoulder pain.

Humans↗

PubMed2026

Randomized Trial of Intensive Nurse-Led Follow‑Up Versus Standard Care in Inflammatory Bowel Disease.

BACKGROUND:  Nurses play a key role in inflammatory bowel disease (IBD) management. This randomized controlled trial evaluated intensive nurse-led program in patients with IBD starting advanced therapy. METHODS:  Patients were randomized (1:1) to intensive nurse follow‑up (Arm A) or standard care (Arm B). Both arms received baseline nurse education; Arm A additionally had scheduled nurse calls and visits. Primary outcome was reduction in IBD‑Disk score in W12. Secondary outcomes were W52 reduction, robust response (> 20-point improvement), and IBD-Disk remission (score < 40). RESULTS: Overall, 98 patients were randomized (Arm A: n = 50; Arm B: n = 48) with similar baseline characteristics. Mean baseline IBD‑Disk scores were 49.2 ± 20.7 in Arm A and 42.0 ± 19.8 in Arm B (p = 0.07). At W12, both groups improved, with greater IBD-Disk reductions in Arm A (16.1 ± 22.9 vs. 10.1 ± 20.1, p = 0.09). At W52, improvement was greater in Arm A (18.4 ± 20.7 vs 9.4 ± 17.8; p = 0.08). More patients achieved robust response in Arm A (49% vs 21%, p = 0.013) at W12. By W52, IBD-Disk remission was achieved by 22/25 (88%) patients in Arm A vs 18/28 (64%) in Arm B (p = 0.045). CONCLUSIONS:  In this pilot randomized trial, intensive nurse-led follow-up did not significantly improve IBD-Disk at week 12, yet favorable trends of functional outcomes were observed. Intensive nurse‑led follow‑up program may improve quality of life in patients with IBD. These findings support the integration of specialist IBD nurses to improve patient‑centered outcomes.

Humans↗