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PubMed2026

Efficacy of an Adhesive Hydrocolloid Bandage on Wound Healing: Findings of a 28-Day, Single-Centre, Randomised, Controlled Study.

This single-centre, randomised, controlled study assessed the wound healing efficacy of adhesive bandages in eligible healthy adults (N = 36) aged 25-55 with Fitzpatrick skin types II and III using a model of laser-induced wounds. Here, we report data for wounds that were randomised to treatment with either a hydrocolloid bandage for multi-day use (BAND-AID Adhesive Bandage Hydroseal), standard of care (SoC) (BAND-AID Adhesive Bandage Tru-Stay Sheer) or an uncovered control. Primary endpoints included the time to complete healing and a composite wound healing score. Hydrocolloid bandage-treated wounds healed twice as fast as the uncovered control or SoC-treated wounds. Median time (days) to complete healing was significantly faster for the hydrocolloid bandage-treated wounds (6.9) versus SoC (11.9) and uncovered control (11.8). Hydrocolloid bandage-treated wounds had significantly better composite wound healing scores versus SoC and versus uncovered control over 2 weeks. At Day 28, cosmesis was better with hydrocolloid bandage treatment (0.3) versus SoC (0.6) and uncovered control (2.1) (change from baseline in a composite scar score; higher score = worse outcome). Multi-day wound occlusion with a hydrocolloid bandage promoted faster healing and improved cosmesis compared with daily SoC dressings or uncovered control.

Humans↗

PubMed2026

No association between alcohol consumption and hip osteoarthritis: a diverse national analysis of 87,585 adults from the "All of Us" research program.

INTRODUCTION: Hip osteoarthritis (OA) is estimated to affect 62.6 million individuals by 2050. A probable link exists between alcohol use and hip OA. However, the results are inconsistent, and the relationship between alcohol and hip OA remains speculative. To address these gaps, this study aimed to utilize the diverse, nationally representative All of Us Research Program dataset to explore the association between alcohol consumption and hip OA. METHODS: This retrospective case-control study utilized data from the All of Us Research Program Controlled Tier Dataset v8. 17,517 hip OA cases and 70,068 controls were identified. A 1:4 case-to-control matching ratio was applied based on age and sex. Alcohol use frequency was categorized into five levels: Never, Monthly or Less, Two to Four Times per Month, Two to Three Times per Week, and Four or More Times per Week. Multivariable logistic regression models evaluated the association between alcohol use frequency and hip OA after adjusting for demographic and clinical variables. RESULTS: Multivariable analysis found that alcohol use frequency was not significantly associated with hip OA. Compared to never users, participants with low (OR 0.98, 95% CI 0.93-1.04, P = 0.583), moderate (OR 0.99-1.01, all P > 0.05), and high (OR 1.02, 95% CI 0.95-1.09, P = 0.599) levels of alcohol consumption had no statistically significant differences in odds of hip OA. Female sex, Asian race, diabetes, hypertension, hyperlipidemia, and nicotine dependence increased the odds of hip OA. CONCLUSION: Any level of alcohol consumption was not significantly associated with the odds of hip OA. This study adds valuable insight to the current body of conflicting evidence. Further prospective studies appear warranted to shed light on the long-term effects of different alcoholic beverages on different joints. Key Points • This study found no significant association between any degree of alcohol consumption and the odds of developing hip osteoarthritis. • Utilizing data from 87,585 adults in the NIH "All of Us" Research Program, this is the first study to analyze this relationship in a large, nationally representative population. • The research provides clarity to previously conflicting literature by demonstrating that alcohol lacks a clear harmful or protective effect on the clinical course of the disease. • The analysis highlights that independent risk factors such as Asian race, nicotine dependence, and components of metabolic syndrome increase the odds of hip osteoarthritis.

Humans↗

PubMed2026

Lower urinary tract evaluation in children with cerebral palsy: A crossectional study.

INTRODUCTION: Cerebral palsy (CP) is a chronic, non-progressive motor disorder affecting voluntary movement and posture. Lower urinary tract (LUT) dysfunction is highly prevalent in children with CP. This study aims to evaluate LUT function in children with CP. MATERIAL AND METHODS: This cross-sectional study was conducted at a tertiary care hospital. Patients aged 5-18 years with established CP diagnosis were included. Evaluation included clinical history, physical examination, urinary ultrasonography with post-void residual (PVR) measurement, and urodynamic studies when indicated. Patients were categorized into three groups; group-1 (LUT dysfunction), group-2 (symptomatic), and group-3 (asymptomatic) for analysis. RESULTS: The study included 97 children with CP (41 girls, 56 boys; median age 8 years). Of the patients, 61.8% were ambulatory (GMFCS I-III) and 38.2% were non-ambulatory (GMFCS IV-V). At least one LUT symptom was detected in 75.3% of patients. Incontinence was the most common symptom at 69.1%. Incontinence prevalence was significantly higher in non-ambulatory patients (81.1% vs 61.7%, p = 0.044). Invasive urodynamics was performed in 19 patients, and LUT dysfunction was diagnosed in 89.5% of them (19.3% of the entire population). Prematurity rate was significantly higher in patients with LUT dysfunction (94.1% vs 64.8%, p = 0.017). Binary logistic regression analysis identified elevated PVR as the strongest independent risk factor for LUT dysfunction (OR = 108, p < 0.001). Abnormal urinary frequency (OR = 14.9, p = 0.022) and quadriplegia (OR = 10.3, p = 0.016) were other independent risk factors. ROC analysis determined the optimal cut-off value for PVR as 19 mL (sensitivity 58.82%, specificity 94.92%). In the intergroup analysis, multinomial logistic regression identified elevated PVR as the strongest predictor (Group-1 vs Group-2: OR = 101; Group-1 vs Group-3: OR = 24, both p < 0.003). Lower gestational age was also an independent risk factor in both comparisons (OR = 1.25-1.26, p < 0.020). DISCUSSION: This study demonstrates LUT dysfunction affects 19.3% of children with CP, strongly correlating with motor impairment severity. Elevated PVR emerged as the strongest independent predictor (OR = 108), offering a practical non-invasive screening tool. Our proposed urodynamic criteria achieved 94.7% diagnostic yield, enabling selective evaluation. Limitations include single-center design and cross-sectional methodology without longitudinal follow-up. These findings support integrating systematic urological assessment into standard CP care for early intervention. CONCLUSION: LUT dysfunction prevalence is high in children with CP, and symptom frequency increases with higher GMFCS levels. Elevated PVR is the strongest predictor, with a clinically applicable cut-off value of 19 mL. Particularly in quadriplegic, non-ambulatory, and premature patients, close follow-up and urodynamic evaluation when necessary should be performed with a multidisciplinary approach.

Humans↗

PubMed2026

Long-term efficacy of cognitive behavioural therapy for insomnia (CBT-I) on depressive symptoms: A systematic review and meta-analysis of randomised controlled trials.

Depressive symptoms are common in individuals with persistent insomnia. Previous meta-analyses of randomised controlled trials (RCTs) showed that cognitive behavioural therapy for insomnia (CBT-I) can reduce depressive symptoms at post-treatment. However, the long-term maintenance of these improvements has never been systematically examined. To fill-in this gap, we conducted a systematic review and meta-analysis of the long-term (≥3 months) effects of CBT-I on depressive symptoms. The review was registered in PROSPERO (CRD420251146061). Only RCTs in adults with insomnia were considered. Pubmed, Scopus, Psycinfo, CINAHL, and Medline were searched up to 12 September 2025 with no predefined time constraints. From 5359 records initially retrieved, we included 53 articles reporting on 13,608 individuals. After outliers removal, random effects meta-analysis showed that CBT-I was superior to control conditions in reducing depressive symptoms at 3 [k = 29, d = -.35, [95% CI: -.49 to -.21], p < .001], 6 [k = 29, d = -.32, [95% CI: -.59 to -.05], p = .018], and 12 [k = 10, d = -.25, [95% CI: -.39 to -.12], p < .001] months follow-ups. Results demonstrate that the effects of CBT-I on depressive symptoms are sustained throughout the year following treatment, although effects may decline over time.

Humans↗

PubMed2026

Synchronicity of parent-child sleep and potential mechanisms: A systematic review and meta-analysis.

Existing evidence indicates that parent and child circadian rhythms are associated, but studies have mainly examined factors affecting child sleep health. This systematic review addressed two questions: a) is there a synchronous relationship between parent and offspring sleep? and b) what are the potential mechanisms? PubMed, Embase, PsychINFO, and Scopus were searched from inception to April 2025. Forty-six studies comprising over 100000 parent-child dyads across 16 countries were included. Results showed small-to-moderate parent-child synchronicity in sleep duration (r = 0.18, 95% CI [0.14, 0.23]), sleep efficiency (r = 0.30, 95% CI [0.19, 0.41]), bedtime (r = 0.34, 95% CI [0.20, 0.46]), and wake up time (r = 0.48, 95% CI [0.24, 0.66]), with stronger effects observed in mother-child dyads. Synchronicity in sleep continuity was moderate, whereas associations in sleep satisfaction were small and non-significant. Mechanisms included genetic and hormonal factors, bedtime routines, shared environments, and attachment. These findings are consistent with family systems theory's premise that sleep is a relational phenomenon. Observed synchronicity in sleep timing may partly reflect shared external constraints like work and school schedules. Most studies were cross-sectional, limiting causal or directional conclusions. Future research should adopt standardized methodologies and longitudinal designs to clarify mechanistic pathways.

Humans↗

PubMed2026

Pcgf5 controls the exit from totipotency in mouse embryonic stem cells.

Mouse embryonic stem cell (ESC) cultures contain a rare subpopulation of two-cell-like cells (2CLCs) that transiently reactivate a two-cell embryo-like transcriptional program characteristic of zygotic genome activation (ZGA), including the endogenous retrovirus MERVL and Zscan4, and thereby regain a totipotent-like state. Polycomb repressive complex 1 (PRC1)-mediated H2AK119ub1 has been implicated in restraining entry into the 2C-like state through Pcgf6, yet the factors governing exit from this state and loss of totipotency remain poorly defined. Here, we show that among the six Pcgf paralogs, Pcgf5, which is most prominently upregulated in 2CLCs and forms an MERVL-driven chimeric transcript (Pcgf5MT2C_Mm) during ZGA in 2-cell embryos, controls exit from the 2C-like state in mouse ESCs. Using a reporter ESC line carrying MERVL-tdTomato and Zscan4c-EGFP (MtZG), we manipulated Pcgf5 dosage bidirectionally. Doxycycline (Dox)-inducible overexpression (OE) of Pcgf5 reduced the double-positive (DP) 2C-like population. Conversely, CRISPR-mediated knockout (KO) of Pcgf5 by targeting a common exon shared by all Pcgf5 variants (hereafter, total Pcgf5) increased the DP population. Time-lapse imaging directly confirmed that these changes reflected genuine differences in duration of the 2C-like state: OE shortened, whereas KO prolonged, the time cells spent in this state. These findings reveal that a Polycomb group factor controls not only entry into but also exit from the 2C-like state.

Animals↗

PubMed2026

Healing from within: A randomized controlled trial of a novel expressive writing intervention among trans and gender expansive adults.

Transgender and gender expansive (TGE) populations in the United States experience high rates of mental health disparities. High rates of depressive and anxiety symptoms have been linked to a host of stigma-related stressors and exacerbated by decreased access to competent and affirming formalized health care supports, particularly in the face of legislation aiming to curb access. As a result, intervention strategies that can be made widely available, accessed at no cost, and address these stressors to improve mental health and well-being are needed. This study presents findings from a self-administered online mental health intervention, titled Reflections to (re)Claim an Affirmed Identity to Improve Mental Health (RECLAIM), which used an expressive writing approach to address internalized anti-TGE stigma to reduce depressive and anxiety symptoms and improve perceived community connectedness. In this randomized controlled trial, 115 TGE community adults were assigned to one of three study conditions: two RECLAIM interventions and one expressive writing active control group. Analysis of between-group effects found that all three groups experienced similar levels of improvement in mental health over time, while within-group effects of time by condition demonstrated some notable differences in the overall trajectory of treatment or control effects. Overall, results of this randomized controlled trial provide preliminary empirical support for the efficacy of RECLAIM in reducing depressive and anxiety symptoms and internalized anti-TGE stigma and improving community connectedness. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Humans↗

PubMed2026

Integrative analysis of transcriptome and DNA methylome dynamics during caudal fin regeneration in silver pomfret (Pampus argenteus).

Caudal fin regeneration in teleost fish is a complex, multi-stage process involving coordinated molecular and cellular changes. While the role of epigenetic regulation particularly DNA methylation has been studied in model freshwater species such as zebrafish, its contribution to regeneration in marine teleosts remains largely unexplored. In this study, we integrated transcriptomic and DNA methylomic data to characterize the temporal dynamics of gene expression and methylation during caudal fin regeneration in the silver pomfret (Pampus argenteus). Using RNA-sequencing and reduced representation bisulfite sequencing (RRBS) at three biologically critical time points 1, 3, and 7 days post-amputation (dpa), we characterized the spatiotemporal molecular landscape of caudal fin regeneration. These time points capture the key transitional phases of wound healing and inflammation (1 dpa), blastema formation and progenitor proliferation (3 dpa), and regenerative outgrowth with tissue remodeling (7 dpa), enabling robust detection of the major molecular programs underlying epimorphic regeneration. Concurrently, CG-methylome analysis identified thousands of dynamically changing differentially methylated regions (DMRs). A strong global inverse correlation was observed between promoter methylation and gene expression. Integrative analysis pinpointed key regeneration genes (fgf20a, msxb, sox9b) whose expression was associated with dynamic methylation changes in their promoters or gene bodies. We conclude that DNA methylation is a dynamic and key regulatory layer that acts in concert with transcriptional reprogramming to coordinate tissue regeneration, providing new insights into the epigenetic mechanisms underlying complex regenerative processes in teleosts.

Animals↗

PubMed2026

A genome-wide coverage-based pipeline for the identification of host-derived candidate DNA biomarkers from cell-free blood.

We have created a new data-analysis pipeline for the discovery of host-specific candidate DNA biomarkers derived from sequencing data of cell-free blood. Unlike approaches that rely on specific molecular or genetic signatures, our method leverages the coverage distribution of cell-free DNA sequences mapped to a reference genome, applying statistical analyses to identify informative short genomic regions for biomarker discovery. The pipeline is applicable to diverse diseases and can be used to analyze cell-free DNA sequences from plasma or serum to identify candidate biomarkers that are characteristic of disease states in mammals. Core functionalities were developed in Java and integrated with open-source software tools for the preprocessing of raw sequencing data, complemented by Python scripts for the machine-learning analysis and statistical validation. The pipeline is designed for HPC use and users can access the pipeline through a Galaxy workflow, which offers a user-friendly web interface for input selection prior to execution and analysis progress monitoring. Performance tests, carried out using duplicate sets of COVID-19 samples and controls, showed linear scalability of execution time with an increasing dataset size, as well as a substantial reduction in execution time through parallelized computation, whereby each HPC node is used to process the data of one chromosome. Further statistical tests confirmed the quality of the pipeline's results by showing that the set of identified candidate biomarkers remained stable across varying dataset sizes.

Biomarkers↗

PubMed2026

Elucidating the evolution of meat quality, water distribution, microstructure, and protein structure during sous-vide and micro-pressure cooking.

This study investigated the evolution of eating quality (colour, texture and volatile flavour compounds), water status, microstructure and protein structure of pork meat under different cooking methods. The methods analysed included traditional cooking (TC: 10, 20, 30 and 40 min, 100 °C), sous-vide cooking (SV: 1, 2, 3 and 4 h, 60 °C) and micro-pressure cooking (MC: 10, 20, 30 and 40 min, 120 °C). Across the three cooking processes, as cooking time increased, cooking loss, lightness, yellowness, P23, β-sheet, random coil and surface hydrophobicity of the meat samples increased. By contrast, redness, P22, hydrogen proton density, esters content, α-helix, β-turn and sulfhydryl group content decreased. Moreover, the Warner-Bratzler shear force (WBSF), adhesiveness, hardness, springiness, gumminess, chewiness, alcohols, aldehydes, ketones and fluorescence intensity of the meat samples, initially increased and then decreased as cooking progressed. SV resulted in higher water-holding capacity (WHC), improved redness and increased alcohol and ester levels, whereas MC produced softer meat and greater water mobility. Furthermore, MC enhanced the degree of microstructural damage and protein structural unfolding in the meat. MC requires less time to achieve textures and flavours similar to those obtained using the TC and SV methods. Thus, MC is an efficient cooking method for the catering industry to obtain desired meat quality rapidly.

Cooking↗

PubMed2026

Pesticide occurrence, transformation, and transport from wastewater treatment plants into stream networks with diverse land uses.

Neonicotinoid insecticides and strobilurin fungicides are detected in many environmental compartments and have been associated with negative environmental and human health implications. Wastewater treatment plants (WWTPs) are often hotspots for introducing such contaminants into the environment. Therefore, the occurrence of strobilurin fungicides, neonicotinoids, and their metabolites at two WWTPs with varying land uses and population sizes was investigated. Polar organic chemical integrative samplers were deployed in WWTP influent and effluent and placed upstream and downstream of the effluent mixing zone for 2 weeks in April and July 2022. Biosolids were also collected at each time point. Neonicotinoids were detected with the highest frequency (68%), followed by strobilurin fungicides (49%) and neonicotinoid metabolites (31%). Time-weighted average concentrations for influent/effluent ranged from 85.2 ± 87.8 to 409.4 ± 74.5 ng/L. Pesticide concentrations, specifically the metabolites, typically increased from influent to effluent, resulting in effluent having higher pesticide loads than influent. Pesticide concentrations varied between the upstream and downstream monitoring locations by analyte, with WWTP samples in the highly developed region having significantly higher concentrations of pesticides and less variation by monitoring period. Chronic ecotoxicity benchmarks for freshwater invertebrates for imidacloprid were surpassed in treated effluent at both WWTPs in July and in the downstream monitoring location in the heavily developed area. Findings support the need for further exploration of pesticide contributions from WWTPs to river systems, specifically related to metabolite contributions to downstream streams and their effects on aquatic environments.

Water Pollutants, Chemical↗

PubMed2026

Mitigating pH-induced instability in deruxtecan-based ADCs: an onboard-mixing icIEF approach for robust charge heterogeneity characterization.

Accurate charge variant analysis of antibody-drug conjugates (ADCs) is essential for understanding product heterogeneity and ensuring quality control. However, Deruxtecan (DXd)-based ADCs present a unique analytical challenge due to the intrinsic instability of the payload, where the lactone ring readily undergoes hydrolysis under alkaline conditions, resulting in time-dependent shifts in charge distribution during imaged capillary isoelectric focusing (icIEF). In this study, we describe the development of an onboard-mixing icIEF method designed to minimize pH-induced degradation during sample preparation. By separating ADC samples from carrier ampholytes (CAs) prior to injection and enabling real-time mixing within the instrument, this approach effectively suppresses premature lactone ring opening and stabilizes charge variant profiles. Comparative studies between conventional premixing and onboard-mixing approach demonstrated that the latter significantly enhances reproducibility, particularly for acidic variants that are highly sensitive to structural conversion. Comprehensive method validation confirmed excellent precision, linearity, and sensitivity, with consistent performance across run-to-run and intra-day analyses. The results underscore the importance of controlling microenvironmental pH exposure in the analysis of chemically instable ADCs. The proposed onboard-mixing strategy provides a robust and efficient solution for icIEF-based characterization, reducing analytical artifacts while simplifying method development. This approach is broadly applicable to ADCs and other biotherapeutics containing pH-sensitive functional groups.

Hydrogen-Ion Concentration↗

PubMed2026

Genome-wide association study of estimated glomerular filtration rate using repeated measurements in the Taiwan Biobank.

BACKGROUND: Chronic kidney disease (CKD) is a major global public health issue, with genetic factors playing a significant role in kidney function. Although genome-wide association studies (GWAS) have identified numerous loci associated with estimated glomerular filtration rate (eGFR), most studies relied on a single time-point measurement, which limits the capacity to account for within-individual measurement variability. METHODS: We performed a repeated-measurement GWAS in the prospective Taiwan Biobank (Taiwanese ancestry; n = 25,004) using two repeated creatinine-based eGFR measurements. Repeated eGFR values were analyzed using a linear mixed-effects model with a subject-specific random intercept and time-varying covariates, providing a more precise estimate of eGFR level. Identified loci underwent functional annotation (expression quantitative trait locus, deleteriousness prediction, and epigenetic markers) and were compared with results from a single-measurement GWAS. RESULTS: Six loci associated with eGFR were identified, including four previously reported regions (1q22, 4q21.1, 11p14.1, and 17q21.2) and two additional loci (6p21.32 and 15q24.2). Functional annotation implicated several candidate genes-such as MUC1/EFNA1, SHROOM3, HLA-DQB1, MPPED2, NRG4, and PGAP3/FBXL20-in the regulation of kidney function. CONCLUSION: Incorporating repeated eGFR measurements into GWAS may improve phenotypic precision for identifying genetic associations with kidney function. This study identified eGFR-associated loci and biologically plausible candidate genes in a Taiwanese population, which require further replication and functional validation.

Chronic kidney disease↗

PubMed2026

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans↗

PubMed2026

Multimodal intervention benefits: Responder analysis of J-MINT PRIME Kanagawa trial.

INTRODUCTION: The J-MINT PRIME Kanagawa trial was an 18-month multimodal intervention (incorporating exercise, nutrition, and metabolic management) for dementia prevention. Because the primary analysis showed no significant benefits, we performed an exploratory responder analysis to identify responsive subpopulations. METHODS: We analyzed the Full Analysis Set comprising 188 participants. Classification and regression tree (CART) analysis, applied to the intervention arm, identified baseline predictors of cognitive improvement. These rules were then applied to the entire cohort to evaluate treatment effects on the Mini-Mental State Examination (MMSE) using fully adjusted mixed-effects models for repeated measures (MMRM). RESULTS: CART identified a "Target Group" (N = 108) characterized by baseline profiles such as an MMSE score < 28 or specific metabolic ranges (e.g., LDL-C < 135 mg/dL). Within this target group, the intervention significantly preserved MMSE trajectories compared with the control group (group × time interaction, P = 0.022). In contrast, the Non-Target Group (N = 80), consisting of high-functioning individuals (MMSE ≥ 28), exhibited no significant group × time interaction. DISCUSSION: Multimodal interventions may effectively preserve global cognition in older adults with sub-threshold cognitive decline. Careful targeting of appropriate populations, while considering potential longitudinal measurement artifacts (e.g., practice effects), is essential. These findings provide a hypothesis-generating framework that warrants external validation in future prevention trials.

Humans↗

PubMed2026

Evidence of genome-wide relaxed selection on mildly deleterious mutations in an ancient subterranean catfish.

About one hundred subterranean catfish species have been described, resulting from repeated colonization of cave environments by multiple surface lineages. Most cave-dwelling species are found in the Americas, in particular in South America, but a few species also live in Central and North America. Despite the availability of high-quality genome assemblies for two cave species, the Mexican blind catfish Prietella phreatophila and the Colombian blind catfish Trichomycterus rosablanca, genomic approaches to investigate genetic changes associated with subterranean life or to estimate cave colonization times remain largely unexplored. To fill this gap, we additionally sequenced the genomes of four blind and depigmented subterranean catfishes from Peru (three Trichomycterus and one Astroblepus), as well as the genomes of four close surface relatives. We first extracted a large set of light-related genes, such as phototransduction and crystallin genes, and found contrasting decays of these sequences in different cave species, from 1% of pseudogenes in T. rosablanca to 48% in P. phreatophila. Two independent molecular dating methods gave congruent ages, indicating that these catfishes colonized subterranean habitats at different times, ranging from Early Pliocene to Late Pleistocene, supporting the hypothesis that surface catfishes repeatedly and rapidly adapted to subterranean habitats. The oldest cave species, P. phreatophila, appears to have been thriving in the dark for over 3.5 million years. Moreover, a genome-wide analysis of protein-coding genes suggests weaker purifying selection on mildly deleterious mutations in this cavefish than in other catfish lineages, likely reflecting a long-term small effective population size.

cavefishes↗

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

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗