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PubMed2026

RNA dysregulation as a determinant of aging and neurodegenerative vulnerability.

In the nervous system, aging causes deterioration of cellular and molecular processes that are associated with declines in cognition, sensory perception, and motor coordination. Aging is also the strongest risk factor for neurodegenerative disease, yet the mechanisms by which aging predisposes neurons to dysfunction remain incompletely understood. While genomic instability, proteostasis decline, mitochondrial dysfunction, and chronic inflammation have dominated prevailing models, recent evidence highlights RNA dysregulation as a central component of age-associated decline. In this review, we summarize recent findings suggesting that aging progressively erodes RNA regulatory fidelity through alterations in RNA-binding protein abundance, localization, biophysical behavior, and RNA interactions. We argue that age-dependent RNA dysregulation represents an important mechanism that converges with genetic risk to drive neuronal vulnerability and neurodegeneration.

RNA dysregulation↗

PubMed2026

Exploring Immersive Virtual Reality as an Approach to Improve School Participation-Related Constructs in Children With ADHD.

BACKGROUND: School participation is frequency and involvement from person-environment transactions, not diagnosis, per the International Classification of Functioning, Disability and Health (ICF) and the family of participation-related constructs (fPRC). In this framework, the environmental and child determinants of school participation (e.g., school routines and peer/teacher context; self-regulation, activity competence and preferences) interact bidirectionally to shape everyday participation. However, many interventions still target isolated impairments, overlooking coordinated changes in capacities and context. Grounded in this contemporary view, this study aimed to investigate the impact of an immersive virtual reality (IVR) intervention on school participation-related constructs in children with ADHD. METHODS: The study included 92 children aged between 7 and 12 years diagnosed with ADHD. Participants were randomly assigned into intervention (n = 46) and control (n = 46) groups. Both groups completed the School Participation Questionnaire (SPQ) and Bruininks-Oseretsky Test of Motor Proficiency Test 2 Brief Form (BOT2-BF) assessment prior to the intervention. The intervention group received an IVR intervention program twice a week for 8 weeks. During this period, the control group did not receive additional therapy. At the end of the 8 weeks, the SPQ was readministered to both groups. RESULTS: Baseline characteristics showed no significant differences in SPQ and BOT2-BF results between groups, confirming homogeneity prior to intervention. Following the intervention, the study group demonstrated significant improvements across all domains of the SPQ (doing, being, symptoms and environment), with large effect sizes for SPQ total score (d = 0.978) and subdomains (d = 0.452-0.910). In contrast, the control group showed no improvements and even declines in subdomains. Post-intervention, between-group comparisons revealed significant differences favouring the study group across all domains (p < 0.001), with large effect sizes (d = 0.878-1.165). CONCLUSIONS: Findings suggest that the IVR program was associated with improvements in teacher-rated environmental and child determinants of school participation (SPQ domains) in children with ADHD.

Humans↗

PubMed2026

Systematic Review of Pharmacologic Treatment for Migraine Prevention in Adults: Report of the AAN Guidelines Subcommittee and the American Headache Society.

BACKGROUND AND OBJECTIVES: This systematic review (SR) provides updated evidence-based conclusions regarding the use of pharmacologic migraine prevention in adults to inform a new joint American Academy of Neurology (AAN) and American Headache Society practice guideline. METHODS: A multidisciplinary panel conducted an SR following the 2017 AAN Clinical Practice Guideline Process Manual. Randomized controlled trials evaluating pharmacologic preventive treatments for adults with episodic or chronic migraine were included. Searches encompassed MEDLINE, Embase, and ClinicalTrials.gov from database inception through June 6, 2024. Studies were screened in duplicate, with dual independent risk-of-bias assessment. Outcomes included change in monthly headache days, ≥50% responder rate, and validated patient-reported quality of life (QOL) measures. Raw mean differences, standardized mean differences, and risk ratios were calculated. A modified Grading of Recommendations Assessment, Development, and Evaluation process was used to classify certainty of evidence. RESULTS: A total of 217 studies met inclusion criteria. For episodic migraine, high-confidence evidence showed that galcanezumab and erenumab are more effective than placebo in reducing headache frequency. Moderate-confidence evidence supported benefit from atogepant, eptinezumab, fremanezumab, propranolol, topiramate, and valproate. Several additional oral agents including amitriptyline, bisoprolol, flunarizine, fluoxetine, levetiracetam, metoprolol, nifedipine, pizotifen, and telmisartan had low-confidence evidence suggesting possible benefit. For chronic migraine, high-confidence evidence supported reductions in headache frequency with fremanezumab, galcanezumab, and onabotulinumtoxinA. Moderate-confidence evidence supported benefit from atogepant, eptinezumab, erenumab, topiramate and valproate. Across both episodic and chronic migraine populations, erenumab, fremanezumab, galcanezumab, eptinezumab, rimegepant, atogepant, topiramate and onabotulinumtoxinA demonstrated improvements in patient-reported QOL outcomes on validated instruments. Evidence comparing active treatments was limited and generally of low or very low confidence, restricting conclusions about comparative effectiveness. DISCUSSION: This SR provides a comprehensive synthesis of evidence on pharmacologic migraine prevention in adults. High- and moderate-confidence findings confirm the efficacy of several established and newer preventive therapies and demonstrate improvements in patient-reported outcomes across multiple validated measures. These conclusions informed the development of evidence-based recommendations, presented in a companion publication, to guide clinicians in selecting preventive medications for adults with episodic and chronic migraine.

Humans↗

PubMed2026

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n = 907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n = 35), colorectal cancer (n = 21), and pancreatic cancer (n = 9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans↗

PubMed2026

Psychological impacts of APOE genotype disclosure among Latinos in New York City: a randomized controlled trial.

INTRODUCTION: Latinos face increased Alzheimer's disease (AD) risk but are underrepresented in studies of APOE genotype disclosure. We evaluated the psychological impacts of APOE disclosure in the Información de la Enfermedad de Alzheimer para Latinos (IDEAL) study, a randomized controlled trial among Latinos in New York City. METHODS: Latino northern Manhattan residents without self-reported AD (mean age 52, 69% women, 49% college graduates) were randomized in the period August 2021 to July 2024 to receive AD risk estimates to age 85 incorporating APOE genotype, family history, and ethnicity (disclosure) or the same factors excluding APOE (non-disclosure). Bilingual genetic counselors delivered risk estimates to both groups, unmasked to randomization. Follow-up surveys were completed 6 weeks, 9 months, and 15 months after risk delivery. Primary outcomes were impact of genetic testing in AD (IGT-AD) and Impact of Event Scale-Revised (IES-R). Secondary outcomes were changes from baseline in depression, anxiety, and perceived AD threat. Analyses used intention-to-treat with multiple imputation. RESULTS: Disclosure (N = 194) and non-disclosure (N = 180) groups did not differ on IGT-AD (mean disclosure-non-disclosure difference [MD] at 6 weeks: -1.5, p = 0.14; 9 months: -1.2, p = 0.35; 15 months: -2.0, p = 0.07), IES-R (MD at 6 weeks: 0.00, p = 0.98; 9 months: 0.01, p = 0.84; 15 months: 0.03, p = 0.64), or change in secondary outcomes. Occurrence of disclosure-related adverse events was similar in the disclosure (N = 2) and non-disclosure (N = 3) groups. DISCUSSION: In this Latino cohort, APOE disclosure did not have clinically significant adverse psychological effects, addressing an important evidence gap. TRIAL REGISTRATION: ClinicalTrials.gov NCT04471779.

Aged↗

PubMed2026

CanDo (Canadian Donor Milk) randomised controlled trial: pasteurised human donor milk supplementation in the well-baby unit - protocol.

INTRODUCTION: Mother's milk is the gold standard for feeding newborns. Despite lactation support while in hospital, supplementation rates remain high in Canadian well-baby units at 35-50%. When supplementation is needed, the choice between formula milk and pasteurised human donor milk (donor milk) remains uncertain with a lack of clinical trials to inform this practice. This study aims to compare the effect of supplementing mother's milk with donor milk versus formula in infants at higher risk for supplementation (infants of diabetic mothers, infants born small for gestational age or with a birth weight less than 2.5 kg and late preterm infants born between 350/7 and 366/7 weeks gestation). METHODS AND ANALYSIS: This is an ongoing, open-label, single-centre, randomised controlled trial conducted at Mount Sinai Hospital, Toronto, Canada. A total of 112 infants (56 per group) will be randomised to receive donor milk or infant formula as a supplement to mother's milk during their initial hospital stay, when supplementation is deemed necessary by the family and/or healthcare team. The primary outcome is exclusive human milk feeding at 4 months of age. Secondary outcomes include any or exclusive human milk feeding at 1, 2 and 3 months; infant growth and health indicators and breastfeeding self-efficacy. Exploratory outcomes encompass infant temperament; parental mental health (assessed using the State-Trait Anxiety Inventory and Edinburgh Postnatal Depression Scale); milk cortisol concentrations; and informal milk sharing comparing donor milk and formula supplementation. Follow-up includes monthly telephone assessments and a virtual or in-person visit at 4 months post partum. Data will be analysed using intention-to-treat principles. ETHICS AND DISSEMINATION: The CanDo trial has received ethics approval from the Mount Sinai Hospital Research Ethics Board and the University of Toronto. Results will be disseminated through peer-reviewed journals, conference presentations and stakeholder engagement with hospital and public health decision-makers. Findings will address a critical evidence gap regarding the use of donor milk supplementation in well-baby units and may inform future clinical practice and policy in newborn feeding. TRIAL REGISTRATION NUMBER: NCT06315127.

Humans↗

PubMed2026

Feasibility and effectiveness of the Bergen 4-Day Treatment for obsessive-compulsive disorder in Australia: A pilot comparison with 3-week inpatient obsessive-compulsive disorder treatment.

OBJECTIVES: Obsessive-compulsive disorder is a debilitating and chronic condition that, when untreated or unresponsive to treatment, imposes a significant health and economic burden on individuals and families. This prospective non-randomised inpatient study compared the acceptability and clinical outcomes of the Bergen 4-Day Treatment programme with those of a standard 3-week specialised treatment programme for obsessive-compulsive disorder in Australia. METHOD: Twenty-five participants diagnosed with obsessive-compulsive disorder were non-randomly assigned to Bergen 4-Day Treatment (n = 12) or a 3-week standard (n = 13) inpatient programme. Independent assessments were completed at pre-treatment, 10 days post treatment and at 3-month follow-up. The Yale-Brown Obsessive-Compulsive Scale was rated to assess obsessive-compulsive disorder severity, while secondary measures of depression, anxiety, obsessive beliefs and wellbeing were self-rated by participants. RESULTS: Baseline characteristics of both groups were comparable, with obsessive-compulsive disorder symptom severity within the moderate to severe range. After treatment, obsessive-compulsive disorder symptoms as well as secondary depression and anxiety symptoms were reduced in both treatment groups. Participants receiving Bergen 4-Day Treatment had significantly lower Yale-Brown Obsessive-Compulsive Scale scores at 10 days (M = 13.46) and 3 months (M = 11.84), compared to standard treatment (M = 19.04 and M = 19.15, respectively). Response (91.9%) and remission (45.8%) rates for the Bergen 4-Day Treatment group were significantly higher at both post-treatment timepoints, compared to the standard treatment group. No dropouts occurred in the Bergen 4-Day Treatment group, and participant satisfaction was high. CONCLUSION: The findings of this pilot open-label study suggest that Bergen 4-Day Treatment shows promise as an acceptable, efficient and effective treatment for obsessive-compulsive disorder, warranting further investigation as a scalable alternative for improving access to specialised obsessive-compulsive disorder treatment in Australia.

Humans↗

PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗

PubMed2026

Whole-Exome Sequencing in a Consanguinity-Enriched South Indian Retinitis Pigmentosa Cohort: Diagnostic Yield and Molecular Spectrum.

PURPOSE: To determine the molecular diagnostic yield, variant spectrum, inheritance architecture, and influence of consanguinity on whole-exome sequencing outcomes in a South Indian retinitis pigmentosa (RP) cohort. DESIGN: Prospective, registry-based cohort study. SUBJECTS: A total of 113 affected participants were enrolled through the Aravind Registry for Inherited Diseases of the Eye, including 109 unrelated probands and 4 affected relatives from already represented families. Primary analyses were restricted to the 109 unrelated probands. METHODS: Whole-exome sequencing was performed using a clinical exome workflow. Variants were interpreted using American College of Medical Genetics and Genomics/Association for Molecular Pathology criteria and cases were categorized as solved, possibly solved, inconclusive, or unsolved using prespecified inheritance-aware rules. MAIN OUTCOME MEASURES: Molecular diagnostic yield, distribution of implicated genes and variant classes, inheritance architecture, and diagnostic yield stratified by consanguinity status. RESULTS: Among the 109 unrelated probands, mean age at testing was 39.3 ± 14.1 years and 58.7% were male. Whole-exome sequencing identified 186 distinct rare variants across 92 inherited retinal disease genes, including 26 pathogenic and 33 likely pathogenic variants. A molecular diagnosis was established in 50 of 109 probands (45.9%), including 42 solved and 8 possibly solved cases; 45 (41.3%) were inconclusive and 14 (12.8%) remained unsolved, including 4 (3.7%) in whom no candidate variant was identified. EYS, USH2A, and ADGRV1 were the most frequently implicated genes. Autosomal recessive (AR) disease predominated (44/50, 88.0%). Consanguineous AR cases were exclusively homozygous (17/17); notably, 68.0% of nonconsanguineous AR cases were also homozygous (P = 0.013). Diagnostic yield was higher in consanguineous probands (51.4% vs. 41.7%), without reaching significance. Recurrent alleles included an established South Asian founder variant (MFSD8 c.1361T>C) and candidate founder alleles in EYS (c.4321C>T) and ADGRV1 (c.14329C>T). CONCLUSIONS: Whole-exome sequencing established a molecular diagnosis in nearly half of this South Indian RP cohort and revealed a predominantly recessive, homozygosity-enriched architecture shaped by consanguinity. These findings define a region-specific variant landscape to support clinical interpretation, genetic counseling, and future trial enrollment in this underrepresented population. FINANCIAL DISCLOSURES: The authors have no proprietary or commercial interest in any materials discussed in this article.

Consanguinity↗

PubMed2026

Toward personalized interventions for preventing depression in primary care: Qualitative and quantitative findings from the e-predictD pilot study.

BACKGROUND: The predictD intervention, delivered by family physicians (FPs), has demonstrated effectiveness and cost-efficiency in preventing depression and anxiety. The e-predictD study aims to design, develop, and evaluate a novel personalized intervention for depression prevention by integrating information and communication technologies (ICTs), risk prediction algorithms, and decision support systems (DSS) for both patients and FPs. OBJECTIVE: To evaluate the satisfaction, usability, and acceptability, of a beta version of the e-predictD intervention in primary care settings. METHODS: The e-predictD intervention follows a biopsychosocial approach, including an initial patient-FP interview, specific FP training, and an app. A β-version was tested in a pilot study without a control group over three months. The app integrates a validated depression risk prediction algorithm, decision algorithms, and a monitoring system supporting the DSS. The DSS generates a personalized prevention plan (PPP) from eight intervention modules: physical exercise, social relationships, problem-solving, communication skills, decision-making, assertiveness, sleep improvement, and cognitive restructuring. Patients and FPs discussed the PPP in a 15-minute baseline interview, selecting modules for implementation over three months. Semi-structured interviews gathered feedback. Assessments included depression (PHQ-9), anxiety (GAD-7), quality of life (SF-12), and major depression risk (predictD algorithm). RESULTS: Six FPs from six Spanish cities enrolled 56 non-depressed patients at moderate-to-high risk of depression; 47 (84%) completed follow-up. The app was used for a median of six days (interquartile range: 1-30). Both FPs and patients expressed satisfaction, leading to incorporated improvements. After three months, significant reductions in major depression risk and anxiety symptoms were observed, alongside improved mental quality of life. However, no significant changes were found in depressive symptoms or physical quality of life. CONCLUSION: This pilot study supports the feasibility and acceptability of the e-predictD β-version, despite lower-than-expected app usability. Health improvements were observed, warranting confirmation in a randomized controlled trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03990792.

Adult↗

PubMed2026

Longitudinal Repeated Protein Measurements in a Multiethnic Cohort Identify Novel Diabetes Biomarkers That Reveal Unique Disease Pathways.

There is up to a fourfold increase in diabetes biomarkers identified with longitudinal repeated versus single time point proteomic measurements. The increase in biomarkers identified with longitudinal repeated measurements is supported by a similar proportion being nominated as causal for type 2 diabetes with Mendelian randomization. Proteins unique to the longitudinal repeated analyses highlighted biological pathways (e.g., posttranslational protein modification and cellular structure and cycle regulation) that were distinct from pathways enriched among the shared proteins (e.g., small-molecule metabolic and catabolic processes). Longitudinal protein measurements identify additional novel disease biomarkers and disparate biological pathways compared with single measurement analyses.

Journal Article↗

PubMed2026

Epithelial regeneration in the gastrointestinal tract.

The gastrointestinal tract possesses a remarkable regenerative capacity to maintain tissue homeostasis against various injuries. However, the intestine and stomach exhibit distinct regenerative strategies. In the intestine, damage to Lgr5-positive (Lgr5+) stem cells induces cellular plasticity and the emergence of transient Revival stem cells (RevSCs), a process critically dependent on YAP/TAZ signaling. Conversely, the stomach utilizes paligenosis, where quiescent p57-positive (p57+) mature chief cells act as reserve stem cells, dedifferentiating to restore damaged tissue. Although the cellular origins differ, both organs appear to share some common regenerative features, including transient activation of pro-proliferative programs such as YAP/TAZ signaling. In contrast, whether Retinoic Acid (RA) signaling also serves as a conserved mechanism for regenerative resolution in the stomach remains to be determined. In this review, we discuss the cellular and molecular mechanisms governing regeneration in these two organs. This comparative analysis provides a framework for future research.

Regeneration↗

PubMed2026

Dynamics and virulence of Enterobacteriaceae reservoirs harboring blaCTX-M group 1 in community wastewater.

UNLABELLED: Extended-spectrum beta-lactamase (ESBL)-producing bacteria are ubiquitous and can cause serious infections. Here, we examined untreated community wastewater influent as a reservoir for blaCTX-M group 1 organisms and their virulence potential. Raw influent samples (n = 268) were collected from four wastewater treatment plants (WWTPs) representing dense urban populations. We observed that blaCTX-M group 1 levels were high at all WWTPs and only ~1-2 log10 lower and not correlated to common human-specific microbiome fecal markers, Lachno3 and HF183, indicating a lack of connection to human fecal inputs. Concentrations of blaCTX-M group 1 genes and markers for presumptive host organisms Escherichia coli and Klebsiella pneumoniae were influenced by travel time and season. Amplicon sequencing revealed high diversity of blaCTX-M group 1-9 genes, with 63% belonging to group 1. Selective culture and 16S rRNA gene sequencing showed blaCTX-M group 1 isolates were 26% E. coli, 26% K. pneumoniae, 40% other Enterobacteriaceae, and 8% Aeromonas. Overall, E. coli averaged 3.6E7 cells/L, with 3% of all E. coli found to contain blaCTX-M group 1. Whole-genome sequencing of blaCTX-M group 1 E. coli from wastewater revealed resistance and virulence gene profiles similar to clinical isolates and distinct from other wastewater ESBL-resistant and non-resistant E. coli. Interpretation of wastewater data needs to consider both the existence of environmental reservoirs that contain potentially pathogenic organisms and the strong influence the dynamics of the conveyance system can have on final concentrations measured at the WWTP. IMPORTANCE: The CTX-M enzyme family is highly abundant in nosocomial, community, and environmental settings and is leading to treatment of infections with carbapenem antibiotics, a last-line therapeutic option. The progressive increase of the clinically relevant blaCTX-M group 1 resistance genes in the human population warrants investigation, particularly to understand the establishment and dynamics of environmental reservoirs. This study utilized molecular and culture methods to gain insight into the possible origin, abundance, and dynamics of blaCTX-M group 1 genes in untreated wastewater influent samples. We found extremely high levels of these genes, with Escherichia coli as a major host organism that closely resembled clinical strains, suggesting they are seeded and propagate in sewer pipe systems. The significance of our research is in developing approaches to monitor antimicrobial resistance reservoirs in community wastewater, which could shed light on global burdens and potential transmission cycles and indicate increasing inputs of clinically relevant strains originating from human populations.

E. coli↗

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

Nurse-Led Home-Based Mobile Health Cardiac Rehabilitation Program for Patients With Chronic Heart Failure: A Randomized Controlled Trial.

This 12-week randomized controlled trial evaluated a nurse-led mHealth intervention for patients with chronic heart failure, conceptually informed by Riegel's middle-range theory of self-care of chronic illness. The program integrated wearable activity tracking with weekly nurse-led behavioral coaching, reflecting the core self-care processes of monitoring, maintenance, and management. Compared with usual care, the intervention significantly improved daily step count, 6-minute walk distance, metabolic equivalents, and left ventricular ejection fraction. Findings highlight the effectiveness of theory-informed, nurse-delivered mHealth strategies in enhancing physical activity and cardiopulmonary function, while underscoring the critical role of advanced practice nurses in home-based chronic disease management.

Aged↗

PubMed2026

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

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

Kinetics↗

PubMed2026

Colorimetric gold nanosensors for monitoring protein aggregation: implications for Alzheimer's disease.

Alzheimer's disease (AD) is the leading cause of dementia worldwide. It remains a major public health challenge due to the lack of early diagnostic tools and effective disease-modifying therapies. Molecularly, AD is characterized by extracellular amyloid-β (Aβ) plaques and intracellular Tau tangles, as well as soluble oligomers that are likely the neurotoxic species. However, the transient and heterogeneous nature of these oligomers makes them difficult to detect using conventional biosensing approaches. Nanomaterial-based colorimetric biosensors have emerged as promising platforms for detecting protein aggregates and discovering aggregation inhibitors. Specifically, the localized surface plasmon resonance properties of metallic nanomaterials can enable rapid, label-free, and visually detectable colorimetric sensing of molecular interactions. These features can be leveraged to monitor protein aggregation processes in real time and achieve high-throughput screening of aggregation inhibitors, which may collectively enable early detection and timely intervention of AD progression. This Review Article presents the design and engineering of gold-nanomaterial-based colorimetric biosensors for monitoring protein aggregation and highlights the current challenges and emerging opportunities for applying these nanosensors to combat AD.

Journal Article↗

PubMed2026

Transcription regulation of cell fate plasticity - from embryonic development to tissue regeneration.

Cell fate plasticity refers to the capacity of cells sharing the same genome to alter, reverse, or reconfigure their identity under physiological, pathological, or experimental conditions. This property underlies embryonic development, cellular reprogramming, and tissue regeneration, but becomes progressively restricted as lineage identity is stabilized. Embryonic development represents an intrinsic process of fate transitions, whereas reprogramming and regeneration reveal how differentiated cells can dedifferentiate or transdifferentiate under specific conditions. Across these contexts, plasticity is governed by multilayered regulatory networks involving transcription factors, epigenetic regulators, cofactors, and the core transcription machinery. Robust regulatory programs stabilize cell identity, whereas stochastic fluctuations in gene expression and chromatin state can prime cells for fate transitions, adding a tunable dimension to plasticity control. In this review, we synthesize recent advances in the regulation of cell fate plasticity across development, reprogramming, and regeneration, highlighting how transcription factors, epigenetic modifications, transcriptional cofactors, and core transcription machinery cooperate to control cell fate decisions and plasticity.

Animals↗