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PubMed2026

Integrated transcriptomic and metabolomic analysis of fluoride tolerance-related pathways and differentially expressed genes in silkworm strain XSKD.

XueSong KD (XSKD) silkworm strain exhibits prominent fluoride tolerance, yet the underlying molecular mechanisms of fluoride tolerance remains unclear. In the present study, fourth-instar pre-molting XSKD silkworms were used as experimental materials for integrated transcriptomic and untargeted metabolomic analyses. In total, 572 differentially expressed genes and 90 differential metabolites were screened. GO enrichment and KEGG enrichment based on the hypergeometric distribution model revealed that 13-Hydroxy-9Z,11E-octadecadienoic acid (13-(S)-HODE) acts as the core differential metabolite, which is significantly enriched in the linoleic acid metabolism pathway. Within this pathway, LOC101737302 and CYP338A1 display opposite expression trends and show correlations with pathway metabolites. Based on multi-omics data, this study preliminarily characterizes the lipid metabolic response under fluoride stress, providing omics dataset support for further in-depth exploration of the molecular mechanism of fluoride tolerance in silkworms.

Animals↗

PubMed2026

Integrated salivary proteomic and metabolomic analyses reveal molecular characterization and novel biomarker panels of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.

Humans↗

PubMed2026

Pelvic lymph node dissection in prostate cancer: current evidence, controversies, and future directions.

BACKGROUND: Pelvic lymph node dissection (PLND) remains controversial in the management of prostate cancer. Although it provides the most accurate pathological staging, its therapeutic value beyond staging has long been debated due to conflicting evidence and concerns regarding procedure-related morbidity. OBJECTIVE: To critically evaluate the contemporary role of PLND, particularly extended pelvic lymph node dissection (ePLND), in prostate cancer management in the context of modern imaging, risk stratification tools, and evolving oncologic endpoints. EVIDENCE ACQUISITION: A narrative review of recent literature was conducted, focusing on high-level evidence including randomized trials, observational studies, and contemporary guideline recommendations addressing the indications, extent, oncologic outcomes, and complications of PLND. EVIDENCE SYNTHESIS: Recent randomized and observational studies suggest that ePLND improves nodal staging accuracy and may be associated with modest improvements in metastasis-free survival (MFS) in selected patients with intermediate- and high-risk prostate cancer, although the absolute benefit remains limited and causality is not definitively established. Advances in molecular imaging, particularly prostate-specific membrane antigen (PSMA) PET/CT, together with multiparametric MRI, validated nomograms, and emerging genomic classifiers, now allow more precise identification of patients most likely to benefit from ePLND. The integration of these tools supports a more individualized surgical strategy, including image-guided and sentinel lymph node approaches designed to maximize staging accuracy while minimizing unnecessary dissection. CONCLUSIONS: In the contemporary PSMA imaging era, ePLND continues to play an important role in nodal staging and may contribute to improved oncologic outcomes in carefully selected patients.

Humans↗

PubMed2026

A chromosomal gtrB homolog and dam differentially contribute to dry-heat and high hydrostatic pressure resistance in Salmonella enterica.

Salmonella enterica can persist in low-moisture foods and shows enhanced dry-heat resistance under low water activity, posing significant food safety challenges. However, the genetic basis of extreme dry-heat resistance and its relationship with other processing stresses remain unclear. In this study, twelve S. enterica strains were screened for dry-heat treatment at 60 °C and 80 °C, with S. Infantis CICC21649 identified as the most resistant strain. Comparative genomics and transcriptional analysis identified candidate genes related to envelope integrity and regulation, including gtrB and dam. Deletion of the chromosomal gtrB homolog reduced dry-heat resistance, producing an additional 0.91-log10 reduction relative to the parent strain at 80 °C. Deletion of dam caused broader stress sensitivity, reducing resistance to both dry heat and high hydrostatic pressure, with the stronger phenotype observed under high hydrostatic pressure. Proteomic analysis of the chromosomal gtrB homolog mutant revealed broad alterations in envelope-associated proteins, transport functions, oxidative stress pathways, and central metabolism under dry-heat stress. These findings indicate that the chromosomal gtrB homolog is an important contributor to extreme dry-heat resistance, whereas dam contributes to resistance against both dry-heat and high hydrostatic pressure, likely through a broader regulatory role in stress adaptation. These results reveal distinct structural and regulatory layers underlying stress adaptation in S. enterica and provide practical guidance for low-moisture food processing by highlighting the need to account for strain-dependent and stress-specific resistance during process validation.

Hydrostatic Pressure↗

PubMed2026

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

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

Humans↗

PubMed2026

A 20-Y Analysis of Motorcycle Trauma After Helmet Law Repeal.

INTRODUCTION: After Arkansas repealed its universal motorcycle helmet law in 1997, helmet use decreased and motorcycle-related injuries and fatalities increased. Long-term clinical and population-level impacts of this policy change remain incompletely characterized. This study integrates statewide crash and fatality data with trauma center data to evaluate trends in helmet use, injury severity, and mortality at scene and hospitalization. METHODS: We retrospectively reviewed motorcycle-related admissions and emergency department deaths at the state's only adult level I trauma center from 2004 to 2023 across three periods: 2004-2006, 2013-2015, and 2021-2023. Demographics, helmet use, injury severity, and outcomes were assessed. Logistic regression evaluated associations between helmet use, severe head injury (Abbreviated Injury Scale ≥3), and inhospital mortality. Fatality data were obtained from the National Highway Traffic Safety Administration, and crash-level data (2015-2023) were obtained from the State Department of Transportation. RESULTS: Among 1104 trauma admissions, annual admissions nearly tripled over time, with nonhelmeted riders representing 64%-72%. Helmet use was independently associated with lower odds of severe head injury (odds ratio 0.48, P < 0.001). Nonhelmeted riders had higher on-scene fatality risk (relative risk 1.21). Severe head injuries increased and were strong predictors of inhospital mortality. Population-adjusted motorcycle fatality rates rose from 2.34 to 3.18 per 100,000 residents by 2021-2023. CONCLUSIONS: Motorcycle fatalities and severe head injuries increased during the postrepeal period and were associated with helmet nonuse and severe head trauma. Clinical and statewide data show consistent associations among helmet nonuse, severe head injury, and prehospital and in-hospital mortality, highlighting helmet use as a target for injury prevention policy.

Acute brain injury↗

PubMed2026

Comparative profiling of microbial community structure, enzyme potential, metabolic features, and volatile composition in craft and Jiafan Huangjiu processes.

Craft Huangjiu and Jiafan Huangjiu represent two distinct industrial Huangjiu product outcomes with contrasting volatile profiles. This study compared craft Huangjiu (L70) and Jiafan Huangjiu (L79) to characterize their physicochemical, microbial, gene-level functional, metabolic, and volatile features. Because L70 involved mid-fermentation addition of finished Huangjiu, this comparison was not intended to isolate the sole effect of fermentation interruption versus continued fermentation. L79 showed more extensive carbon and nitrogen utilization, with lower residual substrates and higher ethanol and acetic acid contents than L70, whereas L70 retained a less complete fermentation state. At the volatile level, GC-MS and volatile metabolomics consistently showed an ester-enriched profile in L79 and a more alcohol-dominant profile in L70. FlavorDB-based putative annotation and threshold-based OAV analysis further indicated distinct database-assigned descriptor distributions and potential odor-active compounds, with more OAV > 1 ester-related compounds in L79. Metagenomic analysis showed that L70 was dominated by Lactobacillus acetotolerans, whereas L79 contained higher relative abundances of Saccharomyces cerevisiae, Aspergillus oryzae, Aspergillus flavus, and Fructilactobacillus fructivorans. Metagenomic functional annotation showed higher representation of hydrolysis-related CAZy genes and ester-related enzyme annotations in L79. KEGG-based pathway mapping further indicated greater gene-level potential for ethanol-, acetate-, and acetyl-CoA-related metabolism in L79. Accordingly, the L70 profile should be interpreted as the integrated final-product outcome of process intervention, exogenous input, and subsequent fermentation. The findings provide a comparative basis for future flavor regulation and process optimization in Huangjiu and other fermented alcoholic beverages.

Volatile Organic Compounds↗

PubMed2026

Integrated widely targeted metabolomics and GC-IMS reveal dynamic flavor, nutritional, functional, and metabolic profiles in macadamia kernels during processing.

Different processing stages influence the color, flavor, and antioxidant activities of macadamia kernels. However, the biochemical mechanisms that occur during processing are not well known. This study integrated widely targeted metabolomics (UPLC-MS/MS) with GC-IMS to systematically characterize non-volatile and volatile compounds in macadamia kernels across key three sample groups: fresh kernels (FMN), low-temperature-dried kernels (DMN), and roasted kernels (BMN). A total of 622 non-volatile metabolites and 52 volatile compounds were identified. Low-temperature drying promoted the accumulation of phenolic acids and flavonoids, enhancing antioxidant capacity. Roasting degraded heat-sensitive nutrients but generated flavor compounds via Maillard reaction and lipid oxidation, shifting aroma from green to nutty notes. Nutritional assessment confirmed that roasting significantly reduced antioxidant activities and bile acid binding capacity. Pearson correlation analysis verified the key metabolite-antioxidant relationships. These findings provide critical insights into metabolic dynamics during nut processing and establish a scientific basis for optimizing thermal processing strategies.

Metabolomics↗

PubMed2026

Microplastic contamination in South Asian commercially important seafood: A comprehensive assessment of occurrence, source, and human health risk.

Seafood is a cornerstone of global food security and human nutrition, serving as the primary source of animal protein for more than one-fourth of the global population, with South Asia representing one of the world's fastest-growing seafood-consuming regions. However, escalating microplastic (MP) pollution in marine ecosystems poses an emerging threat to seafood safety and human health, yet a comprehensive regional assessment of MP contamination in South Asian seafood remains lacking. This study presents the first region-wide systematic synthesis of the literature on MP contamination in commercially important seafood across South Asia, integrating occurrence patterns, human exposure assessment, polymer-specific hazard evaluation, and bibliometric analysis to address this critical knowledge gap. The meta-analysis estimated an average microplastic exposure of 145 particles/person/day through seafood consumption in South Asia, with fish contributing the highest intake (121 particles/person/day). The detected polymers were classified into PHI hazard levels I-IV, with polyvinyl chloride (PVC), polyurethane (PU), and polyacrylamide (PAM) representing the highest hazard categories. The mean pollution load index (PLI) was 7.71 (Category I), with crustaceans exhibiting the highest contamination (PLI = 10.07). Polypropylene was the predominant polymer, whereas fragments and blue particles were the most frequently reported microplastic characteristics. These findings provide the first regional baseline for assessing microplastic contamination, polymer-associated hazards, and human exposure through seafood consumption in South Asia, underscoring the need for standardized monitoring and targeted mitigation strategies to safeguard seafood safety and public health.

Animals↗

PubMed2026

From fear to empowerment: the impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.

PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.

Humans↗

PubMed2026

BIOCARD framework: integrating fecal bile acids, lipids, and metabolites to assess response to a cardiovascular health intervention.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality, particularly in under-resourced populations. Although nutritional interventions are important for CVD prevention, their outcomes are commonly evaluated using conventional clinical and behavioral indicators, which may not fully capture early molecular responses. In this study, we developed the BIOCARD framework, an exploratory fecal multi-omics platform integrating bile acids, lipids, and metabolites to evaluate intervention outcomes related to cardiovascular health. Fecal samples were collected from caregiver-child participants enrolled in a 10-week randomized controlled trial comparing a multicomponent garden-based intervention (SHA) with an education-only control group (MSP). Fecal polar metabolites, lipids, and bile acids were analyzed by UHPLC-HRMS-based approaches and integrated with conventional health indicators. Traditional clinical indicators in the present study showed limited sensitivity for detecting intervention-related differences. In contrast, fecal multi-omics analyzes revealed intervention-associated differences in metabolites, lipids, and bile acids, with children showing more apparent molecular variation than parents. Network analysis further revealed associations between selected molecular features and cardiovascular-related indicators, including blood pressure, body fat, skin carotenoids, and Healthy Eating Index scores. Together, these findings suggest that the BIOCARD framework may serve as an exploratory molecular approach to complement traditional outcome measures and improve the evaluation of nutritional interventions for cardiovascular health.

Humans↗

PubMed2026

Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integrating global proteomics, acetylomics, and succinylomics to dissect the molecular dynamics during platelet storage. METHODS: We performed quantification of global proteomics, acetylome and succinylome based on TMT-labeled LC-MS/MS analysis, combined with antibody-affinity enrichment and purification. Dynamic molecular changes and functional transformation of platelet were also characterized under proper conditions stored for 1, 3, 5, 7 days, respectively. RESULTS: We systematically characterized 3,609 proteins, 1,308 acetylation sites, and 1,947 succinylation sites across multiple storage time points (D1, D3, D5, D7). We distinct temporal patterns of post-translational modifications, with succinylation showing more extensive coverage than acetylation in platelets. Pathway enrichment analysis revealed extensive metabolic reprogramming involving complement activation, energy metabolism, and cellular detoxification processes. The identification of specific motif patterns provided mechanistic insights into the functional specificity of these modifications. Random forest machine learning identified 20 core regulatory proteins representing critical nodes in PSL development. Furthermore, we employed real - time quantitative polymerase chain reaction (RT - QPCR) to measure the expression levels of key genes related to platelet function and PTM - associated pathways. CONCLUSION: By mapping the interplay between proteomic abundance shifts and PTM dynamics, this study provides a multidimensional understanding of PSL, establishing a foundational framework for optimizing storage protocols and enhancing transfusion safety.

Blood Platelets↗

PubMed2026

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metabolism axis in this comorbidity remains unclear. We explored its underlying mechanisms and evaluated the therapeutic potential of gentiopicroside. METHODS: Integrated multi-omics analyses combining transcriptomics, single-cell RNA sequencing, Mendelian randomization, machine learning, molecular docking, and in vitro functional assays were performed to identify shared molecular pathways and therapeutic targets across PCOS, hypertension, NAFLD, and T2DM. RESULTS: SLC11A2 was consistently dysregulated in PCOS transcriptomic datasets, and associated with iron metabolism, inflammatory response and oxidative stress pathways. Genetic analyses validated RAS-related regulation in hypertension susceptibility and revealed shared genetic architecture between PCOS and cardiometabolic traits. Network and single-cell analyses characterized SLC11A2-associated molecular patterns in disease-relevant cell types; machine learning identified disease-classifying molecular signatures. Gentiopicroside alleviated inflammatory and oxidative stress phenotypes, including reduced IL-6 expression and reactive oxygen species accumulation. CONCLUSION: This study defines an RAS-SLC11A2 molecular framework linking iron metabolism dysregulation to PCOS-related cardiometabolic risk, elucidating the mechanisms connecting ovarian dysfunction, inflammation, oxidative stress and hypertension, and supports gentiopicroside as a promising therapeutic candidate.

Humans↗

PubMed2026

Genomic determinants underlying biogenic amine detoxification phenotypes in food-associated lactic acid bacteria: Mechanism, evolutionary origin, and relevance to fermented food safety.

Biogenic amines (BAs) are toxic metabolites that accumulate in fermented foods and pose significant food safety concerns. Although several lactic acid bacteria (LAB) have previously been reported to exhibit strain-specific BA-degrading phenotypes, the genetic determinants underlying these activities have remained largely uncharacterized. Here, we analyzed 8251 LAB genomes to validate BA-degrading phenotypes. We predicted five BA-associated genes, including two direct biogenic amine-degrading genes (BADGs), mco and patA, and three polyamine-modifying genes (PMGs), speG, paiA, and bltD. Among BADGs, mco was broadly distributed across LAB and strongly enriched across food-associated niches. patA, organized within a conserved potD-glnB-potABC-patA cassette, is a putative, functionally distinct BADG in LAB, revealing a nitrogen-responsive polyamine uptake-catabolism module. Phylogenomics, phylogenetic reconciliation, and synteny analysis established that all five genes entered the LAB through episodic horizontal gene transfer followed by lineage-specific fixation. GC compositional bias and mobile genetic element association further corroborated the horizontal origin of the two BADGs. Structural analysis confirmed the conservation of catalytic core residues of BADGs across LAB, indicating strong purifying selection. Phenotype-to-genotype correlation with experimentally reported LAB suggested mco as a reliable genomic predictor of degrading phenotype. Integration of degradation and biosynthetic profiles predicted multiple LAB species capable of both synthesizing and degrading BA, along with 1823 genomes with degradation potential but lacking detectable BA biosynthesis genes. This study provides the first large-scale genome framework linking BA-degrading phenotypes with their genetic determinants in LAB and offers a rational basis for selecting BA-detoxifying strains for fermented food applications.

Biogenic Amines↗

PubMed2026

Understanding Suicide through Coroners' Narratives: implications for primary care from a mixed‑methods study of 157 Coroners' reports.

Suicide is a major public health concern, and general practice is often a recent point of contact before death. While mental illness is well recognised, the broader social and contextual factors influencing suicide risk remain under-reported in primary care and epidemiological research Aim To describe the demographic, clinical, and psychosocial characteristics of individuals who died by suicide, integrating coronial quantitative data with qualitative narrative accounts to identify implications for primary/ secondary care and public health. Design and setting Explanatory sequential mixed‑methods study of 157 consecutive deaths by suicide recorded by coroners (2018-19) across five English local authorities. Method Demographic, clinical, and social data were extracted from coroners' records and summarised descriptively. Narrative case summaries were coded and analysed thematically to identify contextual, relational, and service factors preceding death. Results Of 157 individuals: 79% were male; 65% lived in the most deprived IMD quintile; 85% had a diagnosed mental health condition; 62% had a long‑term physical illness; 41% had a previous suicide attempt. About half consulted a GP in the preceding three months; mental health featured in about half of those consultations. Common stressors were relationship breakdown (37.2%), housing instability (22.1%), and work pressures (18.2%). Seven interlinked themes were identified: Mental health; Alcohol/Substance use, Physical health; Social connectedness; Life course trauma, Socioeconomic and Structural Vulnerability; Healthcare access. Service transitions were key vulnerability points Conclusion Coroners' records offer important insights into the complex circumstances preceding suicide and highlight opportunities for GPs to recognise intersectional complexity and support integrated, cross-sector suicide prevention approaches.

General Practice↗

PubMed2026

Effects of Cognitive Behavioral Couple Therapy With Integrated Mindfulness on Mindful Attention, Depressive Symptoms, and Dyadic Adjustment in Low-Income Couples: A Pilot Randomized Clinical Trial.

Psychosocial distress can exacerbate marital conflict, maladjustment, and mental health vulnerability. This pilot randomized clinical trial examined cognitive-behavioral couple therapy (CBCT) integrated with mindfulness in low-income Brazilian couples (per-capita household income up to one minimum wage). Thirty-four participants (17 heterosexual couples) were randomized (independent computer-generated sequence) to an experimental (n = 16) or waitlist control group (n = 18). We assessed dyadic adjustment, mindful attention, marital social skills, and depressive symptoms (R-DAS, MAAS, IHSC, BDI-II) at baseline, post-treatment, and 3-month follow-up. The intervention was eight 80-min conjoint sessions plus daily home exercises. Time × group effects favored the experimental group for dyadic adjustment, mindful attention, and depressive symptoms (all p < 0.001, = 0.20-0.37), but not marital social skills (p = 0.14). Because two outcomes differed at baseline, effects were confirmed with baseline- and dependence-adjusted sensitivity analyses. These findings provide preliminary evidence that CBCT with mindfulness may benefit disadvantaged couples.

Adult↗

PubMed2026

Multi-omics panorama of glaucoma: Pathogenesis, biomarkers, and novel therapeutic strategies.

Glaucoma is a group of irreversible, blinding eye diseases characterized by progressive loss of retinal ganglion cells, leading to gradual visual field defects that severely impact patients' quality of life. Its complex pathophysiological mechanisms remain incompletely understood, limiting the development of early diagnostic and effective therapeutic strategies. Advances in omics technologies have provided new insights into elucidating the pathophysiology of glaucoma. We summarize specific alterations in genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiomics associated with glaucoma. We emphasize the systematic analysis of disease mechanisms, identification of clinically applicable biomarkers, and discovery of novel therapeutic targets through the integration of these data. This approach paves new pathways for glaucoma subtype diagnosis and personalized treatment, while also outlining future research directions and challenges.

Humans↗

PubMed2026

Integrated metabolomic, transcriptomic, and proteomic analyses reveal changes in the non-volatile metabolite profile of LED light-withered oolong tea.

LED light withering is a crucial method for overcoming weather limitations and enhancing the quality of oolong tea. To elucidate the underlying molecular mechanisms, this study simulated solar spectra using multiwavelength LED light and compared the resulting metabolic, transcriptomic, and proteomic profiles during the enzymatic-catalysis process (ECP) in oolong tea processing. Results indicated that LED light withering altered gene expression and protein regulation of secondary metabolism, particularly in the flavonoid biosynthesis pathway. These shifts encompassed key quality-related compounds, including flavonoids (quercetin-3-O-rhamnoside, dihydroquercetin), amino acids (L-asparagine, L-histidine), guanosine 5'-monophosphate (GMP), and carbohydrates. Furthermore, LED light withering accelerated tea leaf water loss, influenced gene expression involved in photosynthetic cellular components (chloroplasts, thylakoids), increased ascorbate peroxidase regulation under stress, and subsequently modulated energy metabolism and signal transduction in tea leaves. This study offers molecular theoretical framework for the controlled light-withering of oolong tea under bad weather and the associated improvements in its quality.

Camellia sinensis↗