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Nanopore-based epigenomic profiling reveals the absence of widespread CpG methylation in the African swine fever virus genome.

DNA methylation is a critical epigenetic mechanism implicated in regulating replication and transcription in DNA viruses. However, the epigenetic landscape of African swine fever virus (ASFV), a large double-stranded DNA virus infecting pigs, remains controversial. Here, we systematically profiled the DNA methylome of the first ASFV strain isolated in Hong Kong (HK_NT_202103) using Oxford Nanopore Technologies (ONT) R10.4.1 sequencing. We employed a paired design: native whole-genome sequencing (WGS) against a methylation-free whole-genome amplification (WGA) control. Using conservative thresholds, we found no evidence of 5-methylcytosine (5mC), especially typical CpG methylation, across the viral genome. Importantly, clear CpG methylation signals were successfully detected in the host genome from WGS data, confirming the functionality of the workflow to detect 5mC at CG sites. While widespread 5mC seems absent, a small number of putative N6-methyladenine (6mA) loci were identified. A specific 6mA candidate exhibited raw ionic current disruptions and gene-level intersection with another ASFV isolate (CAS19-01/2019), although it lacked single-base consensus across different methylation callers or between the two isolates. Although our biological findings are restricted to a single isolate under specific experimental conditions, this study introduces a novel, highly rigorous ONT framework for viral epigenomics research. Furthermore, the absence of ASFV CpG methylation indicates that host CpG-depletion remains a viable strategy for viral metagenomic enrichment. Ultimately, our work offers a critical methodological baseline for ASFV surveillance and highlights the necessity of targeted experimental validation for rare viral modifications.

African Swine Fever Virus

Fungal drivers of mycotoxin contamination in wheat: Early warning and plasma-based control.

Mycotoxin contamination in wheat is a major food safety concern; however, quantitative evidence linking fungal community signals, mycotoxin exceedance risk, and wheat quality traits in naturally contaminated wheat remains limited. In this study, wheat samples were collected from mycotoxin-prone monitoring sites under unusually rainy conditions in 2022 to explore early-warning indicators and post-harvest mitigation strategies. According to the National Food Safety Standard of China GB 2761-2017, aflatoxin B1 (AFB1), deoxynivalenol (DON), and zearalenone (ZEN) exceeded the maximum limits in 52.24, 47.76, and 23.88% of samples, respectively; 38.81% exceeded the reference EU threshold for T-2 toxin, and 46.27% showed co-contamination with at least two mycotoxins above their respective thresholds. Although Alternaria, Cladosporium, and Epicoccum dominated the fungal community, Fusarium abundance was significantly associated with DON contamination and Fusarium-damaged kernels (FDKs). Mediation analysis identified DON as a significant mediator linking Fusarium abundance to FDKs, accounting for 68.41% of the total effect. In addition, Fusarium abundance above 3.70% showed strong predictive performance for DON exceedance, with an area under the curve of 0.906, indicating its potential as an early-warning indicator. Culture-based assays confirmed the toxigenic potential of Aspergillus and Fusarium isolates under simulated temperature and moisture conditions. After optimization using a toxin-spiked wheat flour model, dielectric barrier discharge cold plasma degraded AFB1, DON, and ZEN by 29.30-35.68%, disrupted the morphology of toxigenic fungi, and did not significantly affect wheat quality. This study provides practical insights into mycotoxin risk warning and post-harvest mitigation in wheat.

Triticum

Longitudinal Prediction of Retinal Sensitivity Based on Disease Progression Quantified From Optical Coherence Tomography in Geographic Atrophy.

PURPOSE: The purpose of this study was to analyze the association between disease progression of geographic atrophy (GA) from optical coherence tomography (OCT) with retinal sensitivity (RS) in microperimetry (MP) over a 2-year follow-up period. METHODS: This is a longitudinal analysis of the OAKS Phase-III clinical trial. Both study and fellow eyes with GA that underwent imaging with the Spectralis OCT and consecutive MP examination were eligible. Pointwise quantification of ellipsoid zone (EZ) thickness, EZ and retinal pigment epithelium (RPE) loss from OCT volumes was correlated with localized RS. A longitudinal predictive model using a Markov Chain framework was implemented to predict RS change over time based on OCT biomarkers. The modeling of morphological and functional progression was based on the fellow-eye cohort. RESULTS: A total of 39,681 MP points from 406 patients were analyzed. In the fellow eye cohort, baseline (BSL) EZ thickness was positively associated with RS (0.3 decibel [dB]/&#xb5;m, P < 0.001). Decrease in EZ thickness between visits during follow-up was significantly associated with decrease in RS (0.1 dB / 1&#xa0;&#xb5;m change). RS was significantly lower in MP points within EZ loss during follow-up compared with MP points within the retina with measurable EZ (P < 0.001). The largest functional decline was observed within RPE loss, also associated with the highest probability of absolute scotoma (P < 0.001). Morphological progression to EZ and RPE loss was influenced by EZ thickness and the morphology of adjacent MP points (P < 0.001). CONCLUSIONS: Two exploratory endpoints were developed, namely quantification of EZ thickness and loss, and localized RS within high-risk OCT areas. RS decline during follow-up is associated with automatically quantified disease progression in OCT.

Humans

Obstructive sleep apnea and long-term risk of site-specific cancers: A population-based cohort study.

BACKGROUND: Obstructive sleep apnea is common, but its long-term association with site-specific cancers remains unclear. In this study, we examined 15-year risks of site-specific cancers in people with obstructive sleep apnea compared with the general population and to people with overweight or obesity. METHODS: We conducted a nationwide population-based cohort study using Danish registries, 1995-2021. People diagnosed with obstructive sleep apnea were compared with the general population and to people with overweight or obesity. Adjusted (weighted) 15-year risks, risk differences, and risk ratios (RRs) were estimated using the Aalen-Johansen estimator. Confounding was addressed using standardized morbidity ratio weighting. RESULTS: The study included 114,264 people with obstructive sleep apnea, 115,497 members of the general population, and 113,034 with overweight or obesity. After weighting, the distributions of sex (74% male), age (median 53 years), and comorbidities were comparable across the three cohorts. Obstructive sleep apnea was associated with an increased risk of cancers of the brain (adjusted 15-year risk: 5.78 vs. 3.61 per 1,000 persons; aRR 1.60 [95% CI 1.43-1.78]) and spinal cord (1.65 vs. 1.17 per 1,000 persons; aRR 1.41 [95% CI 1.16-1.72]) compared with the general population. Associations persisted when the obstructive sleep apnea cohort was compared with those with overweight or obesity. No associations were observed for other site-specific cancers. CONCLUSION: Obstructive sleep apnea was associated with an increased risk of brain and spinal cord cancers. These findings highlight the importance of effective prevention of obstructive sleep apnea and the need for further research on treatment.

Cohort Study

Development of a cell-based nanoluciferase reporter system for high-throughput screening of HBV cccDNA inhibitors.

Hepatitis B virus (HBV) persistence is sustained by the viral covalently closed circular DNA (cccDNA) minichromosome, which remains a major barrier to curative antiviral therapies. The lack of reliable quantitative cccDNA detection methods and surrogate markers has hindered efforts to target cccDNA in antiviral high-throughput screening (HTS). Here, we established a novel inducible cccDNA-dependent nanoluciferase (NLuc) reporter cell line, designated HepBLE12, by inserting an in-frame 11-amino acid split-NLuc HiBiT tag into the precore (pC) coding region of an HBV transgene. The resulting 1.3-kDa HiBiT tag on pC serves as the detection module of the split NLuc system, generating quantitative luminescence upon high-affinity complementation with the cognate 18-kDa LgBiT subunit in cell lysates. Notably, the HiBiT assay enables direct detection of intracellular HiBiT-pC protein rather than secreted HBeAg, providing a reporter signal more closely linked to cccDNA activity. HepBLE12&#x202f;cells exhibited inducible and robust viral DNA replication, and the cccDNA-dependent HiBiT signal was validated under diverse experimental conditions that modulate cccDNA formation or transcription. We further miniaturized the assay to a 384-well format and optimized key parameters following standard HTS assay development practices. The assay was successfully automated and demonstrated excellent performance in a multi-day variability study and a pilot screen, with signal-to-background (S/B)&#x202f;&#x2248;&#x202f;9, coefficient of variance (CV)&#x202f;<&#x202f;10%, and average Z-factor value of 0.74, exceeding canonical HTS quality benchmarks. Together, the HepBLE12 cell-based HTS platform provides a robust and practical tool for identifying inhibitors targeting HBV cccDNA.

Hepatitis B virus

Revealing potential biomarkers and metabolic mechanisms of ovarian aging in hens during late laying period based on machine learning and metabolomics.

Ovarian function decline during the late laying period represents a major bottleneck for the economic efficiency of the global poultry industry. However, the underlying metabolic mechanisms and reliable early-warning biomarkers for ovarian aging remain poorly understood. In this study, we performed the first untargeted LC-MS/MS metabolomics analysis of ovarian tissues from Taihe silky fowls at peak laying (30&#xa0;weeks) and late laying (50&#xa0;weeks) stages, and employed an ensemble machine learning strategy integrating LASSO, random forest, and support vector machine (SVM) algorithms to identify high-confidence core biomarkers of ovarian aging. Gene expression analysis was further conducted to validate the potential molecular mechanisms. Our results showed that the metabolic profiles of ovarian tissues differed significantly between the two groups. A total of 6 core biomarkers were identified, 4 of which were long-chain acylcarnitines. Mechanistic analysis revealed that downregulation of key genes in the carnitine shuttle system led to impaired mitochondrial fatty acid &#x3b2;-oxidation, which in turn triggered excessive oxidative stress and compromised ovarian endocrine function. In conclusion, this study identifies long-chain acylcarnitines as potential metabolic biomarkers for ovarian aging in Taihe silky fowls. These findings provide novel insights into the metabolic basis of poultry ovarian aging and lay a theoretical foundation for the precise regulation of reproductive performance in indigenous poultry breeds.

Animals

Construction of precision clinical-proteomics risk model based on machine learning for predicting heart failure in type II diabetes mellitus.

BACKGROUND AND AIMS: Heart failure (HF) is a severe complication in type 2 diabetes mellitus (T2DM), but current risk stratification scores have limited predictive accuracy. We aimed to develop novel prediction tools integrating clinical variables with proteomics to improve risk stratification of hospitalization for HF in T2DM. METHODS AND RESULTS: In this study, we included 2111 UK Biobank participants with T2DM but no prior HF, and profiled 2920 proteins to predict 10-year incident HF hospitalization. Participants were randomly divided into training (70%), tuning (10%), and validation (20%) sets.Three prediction models were developed: a Clinical model based on demographic characteristics, comorbidities, medication use, and laboratory indices; a Protein model based on 40 proteins selected by the Light Gradient Boosting Machine (LGBM); and the Clinical OMics and Protein ASSessment for Heart Failure (COMPASS-HF) model, which integrated both clinical variables and the LGBM-selected proteins. Models were evaluated for area under the curve (AUC), sensitivity, and specificity. During follow-up, 168 participants (7.96%) developed incident HF. The COMPASS-HF model showed better discrimination than the Clinical model, with an AUC of 0.897 (95% CI: 0.850-0.945) versus 0.790 (95% CI: 0.723-0.856). It also demonstrated higher sensitivity (0.882; 95% CI: 0.725-0.967) and consistent performance in subgroups. COMPASS-HF effectively stratified risk of hospitalization for HF, with cumulative incidence rates of 31.9% in the high-risk group and 1.2% in the low-risk group. CONCLUSIONS: By combining clinical and proteomic variables, we developed a high-performance HF prediction model for T2DM, enabling precise risk stratification and informing early intervention strategies.

Humans

Cost-effectiveness analysis of omeprazole for preventing esophageal stricture in patients with Zargar grade 2b and 3a corrosive esophageal injuries: A trial-based economic evaluation.

BACKGROUND: Corrosive esophageal injury frequently results in esophageal stricture requiring repeated endoscopic dilatation and substantial healthcare expenditure. This study evaluated the cost-effectiveness of omeprazole plus standard treatment compared with standard treatment alone for preventing esophageal stricture in adult patients with Zargar grade 2b and 3a corrosive esophageal injuries. METHODS: A trial-based economic evaluation was conducted alongside a randomized controlled trial from the healthcare provider and patient perspectives. Twenty patients were randomized to receive either standard treatment alone (n&#x2005;=&#x2005;10) or standard treatment plus omeprazole (n&#x2005;=&#x2005;10). Direct medical costs were analyzed using the incremental cost-effectiveness ratio. Deterministic one-way sensitivity analysis and probabilistic sensitivity analysis using Monte Carlo simulation were performed. RESULTS: The incidence of corrosive esophageal stricture was 20% (2/10) in the omeprazole group and 70% (7/10) in the standard treatment group (relative risk, 0.29; 95% confidence interval, 0.08-1.05; Fisher's exact test, P&#x2005;=&#x2005;.070). Omeprazole plus standard treatment reduced healthcare costs by THB 4642.30 per patient from the provider perspective and THB 5476.60 per patient from the patient perspective. The intervention remained the dominant strategy across all deterministic sensitivity analyses. Probabilistic sensitivity analysis demonstrated that 68.3% and 78.8% of simulations favored omeprazole from the provider and patient perspectives, respectively. CONCLUSION: Omeprazole plus standard treatment may represent a cost-effective strategy for adult patients with Zargar grade 2b and 3a corrosive esophageal injuries. However, these findings should be considered preliminary and require confirmation in larger multicenter randomized controlled trials.

Humans

Adolescents' Growing Sensitivity to Psychosocial Stressors: Evidence From Two Decades of Health Behaviour in School-aged Children (HBSC) Data in the Nordic Countries.

PURPOSE: We tested a perception-based explanation for rising psychosomatic complaints among adolescents in the Nordic countries. Specifically, we examined whether adolescents have become more sensitive to psychosocial stressors, reflected in stronger associations between stressors and psychosomatic complaints in 2022 than in 2002. METHODS: Data were drawn from the 2002 to 2022 waves of the Health Behaviour in School-aged Children survey among 15-year-olds in five Nordic countries (N = 7,263 in 2002 and 6,739 in 2022). Psychosomatic complaints were examined in relation to stressors in the following three domains: interpersonal relationships, school-related strain, and body- and activity-related factors. Moderated regression analyses tested whether associations between stressors and complaints differed between survey years. Sex and perceived family finances were included as covariates. RESULTS: Four of five psychosocial stressors showed stronger associations with psychosomatic complaints in 2022 than in 2002. Perceived poor family finances, although less prevalent in 2022, were more strongly related to complaints. Girls consistently reported higher levels of psychosomatic complaints, and the association between school pressure and complaints was stronger among girls. DISCUSSION: Although several psychosocial stressors declined in prevalence, their associations with psychosomatic complaints strengthened over time. These findings suggest that rising complaints may reflect changes in how psychosocial stressors are linked to adolescents' psychosomatic symptoms, rather than increases in exposure to those stressors. This shift highlights the importance of considering how adolescents interpret and respond to everyday stress when addressing population trends in mental health.

Humans

Proteomics-based analysis of the defense mechanisms of disease-resistant grass carp against Aeromonas veronii.

Sustainable aquaculture of grass carp (Ctenopharyngodon idella, GC) is consistently threatened by bacterial diseases, particularly those caused by Aeromonas veronii. A disease-resistant grass carp (DR-GC) has been developed by backcrossing female gynogenetic GC with normal male GC, exhibiting improved resistance. However, the systemic molecular mechanisms of DR-GC defending against Aeromonas veronii infection remain largely unexplored. Here, a label-free quantitative proteomics approach was employed to systematically compare proteomic profiles across five tissues (intestine, liver, muscle, skin, and kidney) in DR-GC and GC under healthy and infected conditions. The intestine was identified as the central defense tissue, exhibiting the highest number of differentially abundant proteins (DAPs). In DR-GC, A0A3N0YEK7 (small ribosomal subunit protein eS28), A0A3N0YGT8 (ATP synthase-coupling factor 6) and A0A3N0YNS7 (apolipoprotein A-I) were significantly upregulated in intestine, while D5KZW6 (GCHV-induced protein), A0A3N0Z0A1 and Q8JH84 (hemoglobin subunit alpha) were significantly dysregulated across multiple tissues, which playing the critical roles in defense mechanisms at the protein level. Furthermore, cytochrome P450-associated pathways, cytosolic DNA-sensing and RIG-I-like receptor signaling pathways were identified as crucial coordinators mediating immune and metabolic responses. This study provides the first comprehensive proteomic view of multi-tissue defense mechanisms in DR-GC, and identifies key DAPs and pathways for subsequent functional validation.

Animals

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans

Identification of molecular subtypes in clear cell renal cell carcinoma based on chromatin regulators and tumor immune microenvironment profiling.

In the histological classification of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC) accounts for the highest proportion and is the most common subtype. Despite advances in management, it continues to be associated with considerable incidence and mortality. Although surgery and systemic therapies are available, their efficacy is constrained by pronounced intratumoral heterogeneity and treatment resistance. Identifying robust biomarkers and clarifying the underlying biological mechanisms are therefore essential to improving diagnosis, risk stratification and therapeutic decision-making. In this work, we identified two ccRCC molecular subtypes displaying divergent chromatin regulator (CR) profiles and different clinical prognoses. Using the genes differentially expressed between these subgroups, we constructed a CR-related score (CRS) that effectively stratified patients according to survival. More analysis concluded that the low expression of CR was more linked with the immune-activated tumors, which encompassed the immune pathway enrichment, as well as the elevation of numerous immune cell subtypes. Moreover, elevated CRS was associated with improved immunotherapy responsiveness. Drug-sensitivity analyses nominated several candidate agents, and SMARCD3 knockdown in 786-O cells inhibited proliferation and migration and reduced sensitivity to masitinib. Collectively, these findings support the prognostic and therapeutic relevance of CR-related states in ccRCC and provide a framework for future experimental validation of chromatin-regulated tumor-immune interactions.

Humans

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

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7&#xa0;&#xd7;&#xa0;108&#xa0;CFU/mL and a low detection limit of 1.66&#xa0;CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19%&#xa0;&#x223c;&#xa0;104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer

Effectiveness of a Web-Based Educational eHealth Platform on Women's Health Literacy About Phthalate Exposure: Randomized Controlled Trial.

BACKGROUND: Phthalates are environmental endocrine-disrupting chemicals widely used in plastics, cosmetics, food packaging, and personal care products. Women may experience frequent exposure through everyday consumer and household products. Improving phthalate-related health literacy may support informed exposure-reduction decisions; however, conventional health education provides limited opportunities for repeated, interactive, and individually tailored learning. OBJECTIVE: This randomized controlled trial evaluated the effectiveness of an eHealth educational intervention (Phthalates Free) in improving women's overall and domain-specific phthalate-related health literacy and examined the association between platform engagement and health literacy outcomes. METHODS: A double-blind randomized controlled trial was conducted in the outpatient department of a regional teaching hospital in Taipei, Taiwan. A total of 114 women were randomly assigned to an intervention group (n=58) receiving a 6-month eHealth platform-based education program and a control group (n=56) receiving conventional paper-based education. Assessments were conducted at baseline (T0), 3 months (T1), and 6 months (T2). The Phthalate Health Literacy Scale (10 items; &#x3b1;=.90, content validity index=0.93) measured overall and domain-specific literacy (health care, disease prevention, and health promotion). Longitudinal outcomes were analyzed using generalized estimating equations based on all available observations according to participants' original randomized assignments, with adjustment for waist circumference and pregnancy history. Analysis of covariance (ANCOVA) was used to compare 6-month outcomes after adjustment for baseline scores. Platform engagement and perceived usability were assessed using back-end analytics and the System Usability Scale (SUS). RESULTS: At 6 months, the intervention group showed a significantly greater increase in total health literacy than the control group (+9.93 points, Wald &#x3c7;&#xb2;1=17.74; P<.001). Domain analyses revealed significant improvements in health care (+1.52; P=.001), disease prevention (+1.32; P=.001), and health promotion (+1.12; P=.001) domains. ANCOVA confirmed the between-group difference at T2 after adjusting for baseline scores (F1,109=11.43; P=.001; adjusted mean difference=7.15, 95% CI 2.96-11.34). Engagement analysis showed that high-engagement users (n=10) scored significantly higher in overall health literacy (t55=-3.00; P=.004) and all domains than general users. The SUS results (mean 84.7, SD 5.2; n=46, 79.3%) indicated high perceived usability. CONCLUSIONS: The Phthalates Free eHealth educational intervention significantly improved women's overall and domain-specific health literacy over 6 months. Higher platform engagement was associated with better health literacy outcomes. The intervention may serve as a practical adjunct to nurse-led education in outpatient and community settings by providing accessible, continuous, and evidence-based guidance on reducing phthalate exposure.

Humans

Outcomes of Response-Based Watch-and-Wait and Surgical Management After Total Neoadjuvant Therapy for Rectal Cancer: A Systematic Review and Meta-analysis.

BackgroundTotal neoadjuvant therapy (TNT) increases clinical complete response rates in locally advanced rectal cancer (RC), allowing response-based management strategies such as watch-and-wait (WW) as an alternative to total mesorectal excision (TME). Outcomes associated with WW after TNT remain incompletely defined. This study aimed to compare oncologic and organ-preservation outcomes between WW and surgical management following TNT.MethodsA systematic search was conducted in PubMed, Scopus, and Cochrane Central up to April 2025. Observational studies comparing WW and TME following TNT were included. Pooled odds ratios (ORs), hazard ratios (HRs), and 95% confidence intervals (CIs) were calculated using a random-effects model. Heterogeneity was assessed with I2 statistics. Secondary outcomes included tumor regrowth, salvage surgery, and permanent stoma. Risk of bias was evaluated using ROBINS-I.ResultsSix studies comprising 793 patients were analyzed. WW showed no significant difference compared with TME regarding local recurrence (OR 1.36, 95% CI 0.07-26.17; I2 = 80%), distant metastases (OR 0.62, 95% CI 0.29-1.33; I2 = 49%), 5-year disease-free survival (HR 0.97, 95% CI 0.71-1.31; I2 = 51.7%), or overall survival (HR 1.03, 95% CI 0.81-1.30; I2 = 27.9%). Permanent stoma rates were lower with WW (OR 0.12, 95% CI 0.01-1.23; I2 = 71%), becoming significant after sensitivity analysis (OR 0.04, 95% CI 0.01-0.19).ConclusionWW after TNT offers oncologic outcomes comparable to TME, with high organ preservation and reduced surgical morbidity in highly selected patients.

Humans

Comparative analyses of olfactory receptor repertoires in Schizothorax fish based on the chromosome-level genomes: Implications for regulatory roles of dietary differentiation and ploidy variation.

The olfactory receptor (OR) genes constitute the molecular basis of fish olfaction, mediating survival behaviors and environmental adaptation while coevolving with habitat-driven evolution. Schizothorax, a cyprinid genus endemic to the Qinghai-Tibetan Plateau, exhibits remarkable dietary divergence and ploidy variation in response to plateau environmental changes, which presumably facilitates the adaptive evolution of OR genes. However, the evolutionary patterns of OR genes associated with trophic divergence and ploidy variation in this genus remain unclear. In this study, three species were selected: the herbivorous diploid S. macropogon, the carnivorous diploid S. lantsangensis, and the herbivorous tetraploid S. curvilabiatus. S. macropogon possessed 142 OR genes (92.25% functional), primarily located on chromosomes 14 and 24, with the fewest sequence clusters. Such compact gene repertoire and highly overlapping chromosomal clusters indicated specialization for a herbivorous olfactory niche. S. lantsangensis contained 127 OR genes (93.70% functional), concentrated on chromosomes 4 and 5, with fewer sequence clusters and a scattered distribution, reflecting evolution of OR genes under carnivorous feeding habits. The herbivorous tetraploid S. curvilabiatus exhibited striking features: 316 OR genes (94.30% functional), the most subfamilies, unique &#x3b5; and &#x3ba; OR subfamilies, and species-specific motifs. These characteristics revealed that ploidy, rather than herbivory, dominated OR gene evolution. In conclusion, dietary differentiation and ploidy variation together drove olfactory adaptive evolution in Schizothorax, providing new insights into vertebrate OR gene ecological adaptation.

Animals

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans