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PubMed2026

Functional and Nutritional Potential of Chickpea Protein Hydrolysates: A Systematic Review and Plant-protein Network Analysis.

Chickpea is a protein-rich legume increasingly explored as a substrate for functional plant-based ingredients. Chickpea protein hydrolysates (CPHs) and chickpea-derived peptides (CPs), obtained through enzymatic hydrolysis or simulated gastrointestinal digestion, may provide technological and biological properties while supporting the valorization of chickpea fractions and by-products. This review integrates a network analysis of title-abstract terms from 5,728 unique Scopus and PubMed records on plant protein hydrolysates with a systematic review of 72 studies focused on CPH production, peptide characterization, bioactivity, and translational gaps. The evidence indicates that CPHs and CPs show promising antioxidant, antihypertensive, antidiabetic, anti-inflammatory, lipid-lowering, immunomodulatory, antimicrobial, and anticancer-related activities, mainly supported by biochemical assays, cell models, and animal studies. However, heterogeneous hydrolysis protocols, incomplete peptide characterization, inconsistent bioactivity methods, limited scale-up evidence, and the absence of human intervention trials restrict translation. Future studies should prioritize standardized protocols, mechanistic validation, bioavailability, sensory and regulatory assessment, food-matrix validation, and clinical trials.

Cicer↗

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

Insights into the fate and dynamics of antibiotic resistance in multidrug-resistant Bacillus cereus during in vitro simulated gastrointestinal digestion.

Bacillus cereus, an important pathogen responsible for causing foodborne diseases worldwide, releases pore-forming enterotoxins, which target host epithelial cells, leading to osmotic lysis and ultimately manifesting as diarrheal syndrome. Moreover, some B. cereus strains carry antimicrobial resistance genes that confer multidrug resistance against a spectrum of antibiotics. Characterizing the survival traits of multidrug-resistant (MDR) B. cereus strains in the intestinal microenvironment is essential for developing targeted strategies to effectively manage diarrheal foodborne diseases caused by this pathogen. This study used whole-genome sequencing (WGS) to evaluate the pre- and post-digestion toxigenic potential, antimicrobial resistance profiles, and genetic diversity of MDR B. cereus strains isolated from food samples in Guangdong Province, China. The four B. cereus isolates investigated in this study exhibited a genetic diversity, as determined by multilocus sequence typing analysis of WGS data. All four isolates produced the diarrheal toxins Hbl, Nhe, and CytK to varying levels, indicative of their potential to cause outbreaks of foodborne diseases. Each of the four isolates exhibited resistance to more than three classes of antibiotics, fulfilling the criterion for multidrug resistance. At an initial concentration of 9 log colony-forming units (CFU)/mL, the intestinal concentration of these four isolates crossed the threshold required to induce widespread diarrhea in the general population. Under rice slurry protection, all tested isolates maintained intestinal concentration beyond the threshold when the initial concentration was increased to ≥8 log CFU/mL. Moreover, the upregulations of genes associated with acid tolerance, bile tolerance and stress response were observed in the surviving MDR B. cereus isolates. Digestion markedly altered the antibiotic resistance profiles of the MDR B. cereus isolates. In the absence of a food matrix, the MDR isolates lost their resistance to imipenem, meropenem, amoxicillin-clavulanic acid, and trimethoprim-sulfamethoxazole post-digestion and was influenced by the initial concentration of the strains. In the presence of food matrix rice slurry, the effects of digestion on the antibiotic resistance of MDR B. cereus isolates can be mitigated, enabling them to maintain their antibiotic resistance to the greatest extent. Most remarkably, after digestion, the isolates Bce055 and Bce166 exhibited newly emergent resistance to cefotetan and trimethoprim-sulfamethoxazole, respectively. Our findings clarify the fate of MDR B. cereus isolates in the gastrointestinal tract and inform the development of prevention and control strategies for foodborne diseases caused by this pathogen.

Drug Resistance, Multiple, Bacterial↗

PubMed2026

Implicit and explicit statistical learning in reading: Evidence from a randomized controlled-learning study and computational modeling.

A key challenge in reading acquisition is understanding how learners extract the complex probabilistic mappings between print, meaning, and sound. Statistical learning (SL) theory offers a mechanistic account of how such mappings are acquired, whether implicitly through exposure or explicitly through instruction. We conducted a randomized controlled-learning study in Chinese, a writing system characterized by multiple sub-lexical regularities linking orthography, semantics, and phonology. Ninety-five 2nd-3rd graders with or at risk for dyslexia were randomly assigned to one of three groups: an implicit-SL training group exposed to repeated lexical and sublexical orthography-semantics-phonology associations, an explicit-SL training group receiving the same input plus explicit instruction on the sublexical print-sound mapping, and a no-SL control group. Both SL groups outperformed controls on the characters they were trained on, as well as on untrained characters that required generalization. However, only the explicit group demonstrated abstraction of print-sound mapping to novel items. Neural network simulations further revealed distinct mechanisms supporting implicit and explicit SL, consistent with a dual-system account of reading acquisition. Together, these findings (1) clarify how implicit and explicit learning distinctly support the discovery of statistical structure in written language and (2) underscore the implicit-explicit dual learning mechanism underlying reading acquisition.

Humans↗

PubMed2026

Assessment of the role and effectiveness of nurse-led multimodal intervention in the rehabilitation of dysphagia in patients with brain tumors.

BACKGROUND: Dysphagia is a common complication in patients with brain tumors, which has a profound adverse impact on patients' health status and quality of life. However, there is a relative lack of research on the rehabilitation of dysphagia in brain tumor patients, especially regarding the role and effectiveness of nurse-led multimodal interventions in the rehabilitation of dysphagia in brain tumor patients, which lacks systematic assessment and in-depth discussion. AIM: This study aimed to evaluate the role and effectiveness of a nurse-led multimodal intervention in improving swallowing function and quality of life in brain tumor patients with dysphagia. METHODS: In this study, a randomized controlled trial (RCT) design was used to select 120 dysphagia patients among brain tumor patients admitted to our hospital during the period of January 2024 to May 2024 as the study subjects, and they were stratified and randomly divided into an intervention group (n = 60) and a control group (n = 60). While the control group received conventional nursing care and treatment protocols, the intervention group received a nurse-led multimodal intervention program, including personalized swallowing training, nutritional support, psychological care, and a family-participatory rehabilitation program, which was developed and dynamically adjusted by nurses, rehabilitation therapists, and dietitians. Differences in data before and after the intervention were analyzed using the paired t-test or Wilcoxon signed-rank test, and between-group comparisons were made using the independent samples t-test or Mann-Whitney U test. RESULTS: Both the intervention and control groups showed improvement in swallowing function among the patients. The Kubota drinking test score, Saito's swallowing function grading, and the quality of life scores for patients in the intervention group showed a significant enhancement compared to those in the control group (P < 0.05), indicating that the intervention was more effective than the control. When compared within groups, all scores in both the intervention and control groups improved gradually with the time of intervention (P < 0.05). The improvement was significantly higher in the intervention group than in the control group. CONCLUSION: This study demonstrates that a nurse-led multimodal intervention is significantly effective in improving swallowing function and quality of life in patients with brain tumors. The intervention provides comprehensive rehabilitation support for patients through multidisciplinary collaboration and personalized care and has certain clinical promotion value.

Humans↗

PubMed2026

Toxicological effects of propyl 4-hydroxybenzoate on gallstone pathogenesis: An integrated mendelian randomization, network toxicology, and experimental study.

BACKGROUND: Gallstone disease is a prevalent digestive disorder with substantial global socioeconomic burden. Propyl 4-hydroxybenzoate (PP), a widely used paraben preservative, exhibits potential metabolic and hepatic toxicity, yet its role in gallstone pathogenesis remains unclear. This study aimed to explore the causal association between PP exposure and gallstone formation and the underlying mechanism. METHODS: Two-sample Mendelian randomization (MR) was performed using genome-wide association study (GWAS) data. Network toxicology, molecular docking, and molecular dynamics simulation were applied to screen for core targets. In vivo experiments, transcriptome sequencing, Western blot (WB), and ELISA were conducted for mechanistic validation. RESULTS: MR confirmed a causal link between circulating PP levels and an elevated risk of gallstones (P < 0.05), with AKT1 identified as the key target. In mice, PP aggravated gallstone formation by activating the AKT1-NF-κB-CXCL1 pathway, enhancing hepatic inflammation and neutrophil extracellular traps (NETs) formation; these effects were reversed by AKT inhibition. CONCLUSION: PP promotes gallstone formation via the AKT1-NF-κB-CXCL1-NETs axis. Our findings highlight PP as an environmental risk factor for gallstones, providing novel insights into their prevention and targeted therapy.

Animals↗

PubMed2026

Effectiveness of Topical Huzhang Sanhuang with Standard Nursing for Chemotherapy-Induced Phlebitis: Randomized Controlled Study.

Chemotherapy-induced phlebitis (CIP) is a common complication of peripheral intravenous chemotherapy that can cause pain, local inflammation, treatment interruption, and diminished quality of life. This randomized controlled trial evaluated the efficacy and safety of the topical Huzhang Sanhuang (HZSH) formula, combined with standard nursing care, in managing CIP. Ninety-four hospitalized patients with CIP (grade I or higher) were randomly assigned in a 1:1 ratio to receive either topical HZSH formula plus standard nursing care (experimental group, n = 47) or 50% magnesium sulfate wet dressing plus standard nursing care (control group, n = 47) for 14 days. Prespecified outcomes included phlebitis grade, visual analog scale (VAS) pain score, high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), symptom resolution time, and safety indicators. By Day 14, patients in the experimental group demonstrated significantly greater improvement in phlebitis severity than those in the control group (risk ratio for grade ≥ II, 0.42; 95% confidence interval, 0.20-0.87; P = 0.012). The experimental group also showed significantly larger reductions in VAS pain scores, hs-CRP levels, and IL-6 concentrations (all P < 0.01). Kaplan-Meier analysis further demonstrated faster resolution of multiple local symptoms in the experimental group. Treatment adherence was high in both groups, and no serious adverse events or major safety concerns were observed. These findings indicate that the topical HZSH formula, combined with standard nursing care, is a safe and effective integrative nursing intervention that accelerates clinical recovery, alleviates local symptoms, and reduces the inflammatory burden in patients with chemotherapy-induced phlebitis.

Humans↗

PubMed2026

Structural and tissue-specific organisation of endocrine Fgf19 and Fgf21 signalling in rainbow trout.

Endocrine fibroblast growth factors (FGF19 subfamily) play a key role in regulating metabolic homeostasis in vertebrates. However, their functional diversification in salmonids remains poorly understood. In this study, we conducted an integrative characterisation of Fgf19 and Fgf21 signalling in rainbow trout (Oncorhynchus mykiss) by combining phylogenetic, structural and expression analyses. Phylogenetic analyses revealed the conservation of single fgf19 and fgf21 genes, despite the extensive expansion of receptors post-Ss4R (salmonid-specific fourth-round whole genome duplication). Structural modelling and molecular dynamics simulations demonstrated the stable interactions of both ligands to multiple Fgfr isoforms, with receptor-specific energetic profiles and conserved core interaction residues. Tissue expression profiling revealed clear differences from mammalian models, such as predominant hepatic fgf19 expression and the absence of hepatic fgf21 under basal conditions. In addition, there were complex and tissue-dependent distributions of fgfr and klotho transcripts. These findings support a receptor-driven diversification model of endocrine Fgf signalling in salmonids, suggesting enhanced endocrine plasticity associated with the retention of receptors following post-genomic duplication. Taken together, our findings provide new insights into the structural and regulatory organisation of endocrine Fgf signalling, as well as its potential role in metabolic regulation in rainbow trout.

Animals↗

PubMed2026

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation↗

PubMed2026

An automated geometric modeling framework in GATE for the design and optimization of high-sensitivity converging-beam SPECT collimators.

Objective.The trade-off between detection sensitivity and spatial resolution is a fundamental challenge in designing organ-dedicated Single-photon emission computed tomography (SPECT) collimators. While converging-hole geometries offer a solution, their optimization is often hindered by the lack of flexible computational tools capable of modeling large-scale, non-parallel hole arrays. This study aims to develop an automated geometric modeling framework to facilitate the design and evaluation of complex converging- and diverging-hole collimators within standard Monte Carlo environments.Approach.We developed a specialized modeling framework by implementing custom C++ classes and a vector-based alignment algorithm within GATE. This platform enables automated, orientation-consistent construction of large-scale converging arrays not natively supported by standard implementations. A high-sensitivity pure cone-beam collimator (CBC) was designed using this framework. The evaluation used hot-rod, disc, and Jaszczak phantoms for physical characterization, while XCAT and dedicated brain models were employed for clinical tasks, including cardiac, brain perfusion, and DaTscan SPECT simulations.Main results.The CBC achieved a nearly fourfold sensitivity increase compared to a conventional low-energy high-resolution parallel-hole collimator at a 20 cm radius of rotation, while maintaining comparable spatial resolution. Despite a 52.3% field of view reduction, the CBC yielded a 2.2-fold noise reduction (CV: 11.7% vs 25.9%) and mitigated partial volume effects via geometric magnification. XCAT and brain phantom simulations confirmed enhanced anatomical definition and contrast recovery in cardiac, perfusion, and DaTscan tasks.Significance.This work provides an efficient computational tool for rapid design space exploration of advanced collimator geometries. The results demonstrate that the proposed CBC design offers a significant sensitivity advantage, making it highly suitable for high-performance, small-volume clinical applications such as brain and cardiac molecular imaging.

Tomography, Emission-Computed, Single-Photon↗

PubMed2026

Discovery and characterization of multifunctional bioactive peptides from Alaska Pollock (Gadus chalcogrammus) milt: hybrid in silico, in vitro, and proteomic approaches.

The growing demand for multifunctional bioactive peptides has sparked interest in underutilized marine by-products as sustainable bioresources. This study explored Alaska Pollock (Gadus chalcogrammus) milt protein as a novel source of peptides with anti-inflammatory, anti-hypertensive, and anti-diabetic effects. Protein composition was analyzed via LC-MS, followed by in silico digestion and bioactivity prediction. Molecular docking identified peptides targeting DPP-IV, α-glucosidase, ACE, GLP-1 receptor, COX-2, MuRF1, and the 20S proteasome. Among the candidates, a promising peptide (CLPPH) was synthesized and validated in vitro, demonstrating inhibitory effects on nitric oxide production, DPP-IV, ACE, and α-glucosidase. These results highlight CLPPH's potential as a multifunctional bioactive peptide and support the valorization of Alaska Pollock milt as a sustainable source for functional foods and nutraceutical applications.

Animals↗

PubMed2026

Nurse-led attribution remodeling training based on the Neuman systems model to enhance resilience, adaptive coping, and attributional style in women newly diagnosed with breast cancer: A randomized controlled trial.

BACKGROUND: Psychological interventions for patients with breast cancer often overlook the critical role of maladaptive attributional style in shaping their adjustment. Therefore, the need for theory-driven, scalable interventions that target cognitive restructuring, particularly during the vulnerable post-diagnosis period, is clear. OBJECTIVE: To evaluate the effectiveness of a nurse-led attribution remodeling training intervention grounded in the Neuman systems model for improving resilience, adaptive coping, and attributional style among women newly diagnosed with breast cancer. DESIGN: A randomized controlled trial. SETTING: A tertiary general hospital. PARTICIPANTS: A total of 130 eligible women newly diagnosed with breast cancer were recruited between March and November 2024. METHODS: A two-arm parallel-group randomized controlled trial was conducted. Participants were randomly assigned to receive either attribution remodeling training plus routine nursing (n = 65) or routine nursing only (n = 65). The nurse-led attribution remodeling training intervention, delivered via a blended model of in-person sessions and continued support through the WeChat mobile platform, was designed to systematically reshape maladaptive attributions into more adaptive ones. Resilience (primary indicator), coping strategy (i.e., confrontation, avoidance, resignation), and attributional style (secondary indicators) were assessed at baseline and at 1, 3, and 6 months post-baseline. A linear mixed model was used to analyze the effects of group, time, and group-by-time interactions. Effect sizes (Cohen's D) were calculated based on the means and standard deviations. RESULTS: At the 6-month follow-up, the intervention group had better outcomes than the control group in terms of resilience (mean difference: 1.49, 95% confidence interval: 0.37, 2.61), confrontation coping (3.35 [2.33, 4.37]), and adaptive attributional style (4.16 [3.87, 4.45]). Avoidance coping showed a small increase (0.82 [0.22, 1.42]), whereas resignation coping decreased (-1.66 [-2.49, -0.83]). Group effects and group-by-time interactions were statistically significant for all outcomes. Effect sizes at 6 months ranged from small for resilience (D = 0.28) and avoidance coping (D = 0.26) to moderate for confrontation coping (D = 0.60) and resignation coping reduction (D = -0.51), and large for attributional style (D = 0.94). CONCLUSIONS: Attribution remodeling training is a promising and effective theory-based intervention that can enhance psychological adaptation in women newly diagnosed with breast cancer. By strengthening key defense mechanisms, as conceptualized by the Neuman systems model, the program is effective, scalable, and nurse-deliverable for psycho-oncology care, bridging a critical gap in supportive cancer care and empowering nurses as primary psychological support providers. REGISTRATION: ChiCTR2000031827, registered prospectively on April 11, 2020, www.Chictr.or.cn.

Humans↗

PubMed2026

Family-Wise Error Rate Control in Clinical Trials With Overlapping Populations.

We consider clinical trials with multiple, overlapping patient populations that test multiple treatment policies specifically tailored to these populations. Such designs may lead to multiplicity issues, as false statements will affect several populations. For type I error control, often the family-wise error rate (FWER) is controlled, which is the probability to reject at least one true null hypothesis. If the joint distribution of the test statistics is known, the FWER level can be exhausted by determining critical values or adjusted-levels. The adjustment is typically done under the common ANOVA assumptions. However, the performed tests are then only valid under the rather strong assumption of homogeneous null effects, that is, when the null hypothesis applies to all subpopulations and their intersections. We show that under cancelling null effects, when heterogeneous effects cancel out in some or all subpopulations, this procedure does not provide FWER control. We also suggest different alternatives and compare them in terms of FWER control and their power.

Humans↗

PubMed2026

Modelling the effects of biological intervention in a dynamical gene network.

Cellular response to environmental and internal signals can be modeled by dynamical gene regulatory networks (GRN). In the literature, three main classes of gene network models can be distinguished: (1) non-quantitative (or data-based) models which do not describe the probability distribution of gene expressions; (2) quantitative models which fully describe the probability distribution of all genes co-expression; and (3) mechanistic models which allow for a causal interpretation of gene interactions. We propose two rigorous frameworks to model gene alteration in a dynamical GRN, depending on whether the network model is quantitative or mechanistic. We explain how these models can be used for design of experiment, or, if additional alteration data are available, for validation purposes or to improve the parameter estimation of the original model. We apply these methods to the Gaussian graphical model, which is quantitative but non-mechanistic, and to mechanistic models of Bayesian networks and penalized linear regression.

Gene Regulatory Networks↗

PubMed2026

Penalized Cumulative Probability Model for a Continuous Outcome Subject to Detection Limits.

Mixed-type outcome data occur when the outcome variable's distribution is a mixture of both continuous and discrete ordinal variables. Such mixed-type outcomes are common in biomedical, psychological, and the health sciences, particularly for variables having either a detection or quantitation limit. When interest lies in identifying a combination of genomic features associated with a mixed-type outcome, any method used would require a variable selection strategy for high-dimensional data. Unfortunately, few variable selection methods exist for modeling a mixed-type outcome when the covariate space is high dimensional. This study develops a high-dimensional penalized cumulative probability model (CPM), to allow for the identification of genomic features associated with mixed-type outcome of interest. We demonstrated how such model may be estimated using the iterative penalization procedure-the generalized monotone incremental forward stagewise (GMIFS) algorithm. The Model-X knockoffs procedure was combined with the estimation algorithm to control the false discovery rates (FDR) when performing variable selection. Through extensive simulation studies, our penalized CPM was shown to outperform alternative methods in terms of controlled variable selection performance by achieving high statistical power with the FDR being controlled at the target level. We demonstrate the utility of our method by applying it to predict estimated glomeruli filtration rate (eGFR) in kidney transplant recipients at 24 months post-transplant using baseline gene expression data as predictors. Our CPM model identified five genes associated with this mixed-type outcome which have important links to renal disease, which may provide prognostic guidance for kidney transplantation recipients.

Models, Statistical↗

PubMed2026

A Standardized Nursing-Led Protocol Integrated Pain, Sleep, Medication Adherence, and Symptom Management in Postherpetic Neuralgia.

Postherpetic neuralgia (PHN) is a persistent neuropathic pain condition after herpes zoster that frequently coexists with sleep disturbance, medication-related problems, and fluctuating symptoms. This study evaluated whether a standardized nursing-led protocol could improve multidimensional short-term outcomes beyond usual care. In this prospective, parallel-group randomized controlled trial, 128 adults with PHN were allocated 1:1 to usual care or usual care plus an eight-week protocol integrating structured pain assessment, sleep monitoring, medication-adherence support, and rule-based digital symptom monitoring. The primary outcome was the between-group difference in change in Numeric Rating Scale (NRS) pain score from baseline to Week 8. Secondary outcomes included Pittsburgh Sleep Quality Index (PSQI), MMAS-8 medication adherence, symptom burden, pain-related nocturnal awakenings, breakthrough pain, rescue analgesic use, adverse events, rule-based alerts, and nursing satisfaction. Week-8 data were available for 116 participants (57 usual care; 59 protocol). Mean NRS scores decreased from 7.19 ± 1.08 to 4.82 ± 1.53 in the usual-care group and from 7.28 ± 1.05 to 3.24 ± 1.28 in the protocol group. An NRS reduction of at least 2 points occurred in 49.1% and 76.3% of participants, respectively. The protocol group also showed larger improvements in PSQI, MMAS-8, symptom burden, and nocturnal awakenings, with fewer breakthrough-pain episodes and less rescue-analgesic use. These findings support further evaluation of the standardized nursing-led protocol in preregistered multicenter trials with intention-to-treat analyses and longer follow-up.

Humans↗

PubMed2026

Social Isolation and Loneliness Among Older Asian Immigrants Through the Lens of Sense of Coherence: Systematic Review of Qualitative Studies.

AIM: To explore the meaning older Asian immigrants attribute to social isolation and loneliness, their management strategies, utilisation of resources and impact on health. DESIGN: Systematic review of qualitative studies. DATA SOURCES: AgeLine, CINAHL, MEDLINE, ProQuest, PsycINFO, Scopus, and Web of Science databases were searched in September 2024. METHODS: Inclusion criteria: participants were Asian immigrants to Western countries aged 65 and over, community-living and experiencing social isolation and loneliness. Antonovsky's Sense of Coherence was used to frame the thematic analysis. RESULTS: Ten papers were included and analysed deductively using elements of the sense of coherence framework: • Comprehensibility: Social isolation and loneliness are viewed as multifaceted, influenced by cultural and environmental dislocation, language barriers, intergenerational conflicts, deteriorating health and mobility, and socioeconomic challenges. • Manageability: included engaging in culture-specific community programs, family and ethnic community support and living within ethnic enclaves mitigated isolation and loneliness. • Meaningfulness: Strong family ties, active community involvement, spirituality, volunteerism, and cultural practices fostered resilience. However, accepting the changing values of their new world, living independently, and carving their own niche provided meaning to their transformed reality. CONCLUSION: Older Asian immigrants experience social isolation and loneliness through a cultural lens, shaped by migration experiences, language barriers, and shifting family dynamics. Cultural roots, family ties, spirituality, community, acceptance, and independence enhance sense of coherence. Recognising the dynamic interplay between cultural identity, resilience, and adaptation is key to understanding their lived experience. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: This review informs culturally sensitive interventions, guiding healthcare, community services, and policy to support social participation, mitigate loneliness through ethno-specific activities, and improve the quality of life for aging immigrant populations in Western countries. REPORTING METHOD: The review was undertaken and reported using the PRISMA guidelines. PATIENT OR PUBLIC INVOLVEMENT: None. PROTOCOL REGISTRATION: PROSPERO (CRD42023425752).

Humans↗

PubMed2026

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation↗