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An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5​ concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution

Impact of Integrated Continuous Team Midwifery Care on Breastfeeding Success within the Iranian Health System: A Randomized Controlled Trial.

INTRODUCTION: Supporting women during the perinatal period helps build confidence, strengthens early bonding between mother and baby, and encourages successful breastfeeding. Continuous midwifery care models are one of the ways that support women in this periods. OBJECTIVE: This study aimed to evaluate the effect of integrated continuous team midwifery care (ICTMC) in enhancing breastfeeding success in the Iranian health system. METHODS: In this randomized controlled trial, 200 low-risk primiparous women with a gestational age of less than 12 weeks were recruited from public health centers. Participants were randomly assigned to either the intervention group, which received continuous midwifery care throughout pregnancy, childbirth, and postnatal follow-up, or the control group, which received routine care. The primary outcomes were early skin-to-skin contact and breastfeeding success at the time of discharge and at 4-6 weeks postpartum. Data were analyzed using Stata, employing descriptive statistics, Chi-square, independent t-test, Phi/Cramer's V, and Cohen's d. The p < 0.05 is significant. Data were analyzed with SPSS 26. RESULTS: ICTMC groups were significantly more likely to initiate skin-to-skin contactearly skin-to-skin contact immediately after birth (92% vs. 74%, p < 0.001) and achieve successful breastfeeding at the discharge time (88% vs. 70%, p = 0.002) compared to the control group. At 6 weeks postpartum, breastfeeding success remained higher in the intervention group (82% vs. 65%, p = 0.004). CONCLUSION: Women with ICTMC, effectively support skin-to-skin contactearly mother-infant bonding and enhance breastfeeding success among low-risk primiparous women. Integrating this model into routine maternal care may improve perinatal outcomes.

Humans

Integrating genomic distance analyses in the description of a new family, genus, and species of sponge-associated antipatharians (black corals).

Antipatharians (black corals) are among the least studied coral groups, with much of their diversity still undescribed. Here, we present an integrative morphological, phylogenomic and genomic distance study of deep-sea antipatharians sampled in high seas areas of the North Pacific Ocean and from New Zealand's Exclusive Economic Zone. These corals grow on hexactinellid sponges - a unique characteristic in the order Antipatharia. Using a dataset of ultra-conserved elements and exons, combined with morphological analyses, we reconstruct phylogenomic relationships and formally describe a new family (Eidikopathidae fam. nov.), a new genus (Eidikopathesgen. nov.), and two new species (E. korallispongiasp. nov., E. zealandkoralliasp. nov.). Morphologically, the new family is distinguished by a corallum consisting of a network of loose branches that fuse with the sponge skeletal framework. Phylogenomic analyses recovered consistent topologies with strong nodal support, corroborating the distinct evolutionary placement of this sponge-associated lineage. Pairwise genomic distances estimated using the Tamura-Nei model were concordant with patristic genomic distances, identifying Pteridopathidae as the genetically closest family to Eidikopathidae fam. nov., followed by Myriopathidae and Stylopathidae, which were recovered as sister families in the phylogeny. This pattern shows that genomic distance complements, rather than simply mirrors, tree topology by quantifying accumulated sequence divergence among lineages. Together, these results provide the first genomic distance framework for Antipatharia, offering a baseline for future systematic, evolutionary, and biodiversity studies on this fundamental shallow, mesophotic and deep-sea coral group.

Animals

Omics in hereditary optic neuropathies: A systematic review of clinical studies with an integrated point of view.

Hereditary optic neuropathies are characterized by bilateral visual loss due to the degeneration of retinal ganglion cells, resulting in optic nerve degeneration and atrophy. Although the genetic origin of the main isolated and syndromic hereditary optic neuropathies has been characterized, the clinical phenotypes exhibit significant and poorly understood variability in both penetrance and expressivity. Additionally, the genetic and environmental factors that influence the onset of these optic neuropathies remain poorly understood, with limited biomarkers to predict disease progression or as readouts for therapeutic trials. Data-driven omics strategies allow deep phenotyping to improve our understanding of pathophysiological mechanisms and to search for new biomarkers and therapeutic targets. We explore whether the omics strategies applied to patients with hereditary optic neuropathies have provided such new insights. MEDLINE, Web of Science and EMBASE databases were screened for studies with terms relating to hereditary optic neuropathies, transcriptomics, epigenomics, proteomics, metabolomics and lipidomics in clinical studies exploring patients' samples. Out of 1244 references identified, 22 articles were included after double-masked data curation. These articles focused only on the 3 main forms of hereditary optic neuropathies, namely, OPA1-related dominant optic atrophy (n&#x202f;=&#x202f;4), Leber hereditary optic neuropathy (n&#x202f;=&#x202f;13), and Wolfram syndrome (n&#x202f;=&#x202f;5). While the methodological designs and results of these studies were highly heterogeneous, they revealed molecular alterations that we have attempted to discuss at the integrated multi-omics level. This data integration highlighted several common pathophysiological mechanisms such as energetic impairment, endoplasmic reticulum stress, proteotoxic and oxidative stresses, lipid remodeling and altered amino acid and purine metabolisms, while suggesting potential new biomarkers and therapeutic targets. These findings underscore the potential of integrated multi-omics approaches to deepen our understanding of the phenotypic complexity of hereditary optic neuropathies and to support the development of innovative diagnostic and therapeutic strategies.

Humans

Comprehensive analysis of mRNA-microRNA-lncRNA expression profiles in post-traumatic elbow heterotopic ossification using RNA sequencing and experimental validation.

BACKGROUND: This study aimed to profile the molecular signatures of post-traumatic elbow heterotopic ossification (HO) to identify key regulators and potential therapeutic targets. METHODS: Total RNA from post-traumatic elbow HO tissues (n=4) and normal bone tissues (n=6) was subjected to high-throughput sequencing to identify differentially expressed mRNAs (DEGs), microRNAs (DEMs), and lncRNAs (DELs). Bioinformatics analyses included Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein-protein interaction network construction, and transcription factor (TF)-microRNA-mRNA network analysis. The expression trends of four most upregulated and four most downregulated DEGs were validated by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). RESULTS: We identified 2,138 DEGs, 40 DEMs, and 905 DELs. DEGs were significantly enriched in biological process "bone mineralization," cellular component "plasma membrane," molecular function "integrin binding," and pathways including PI3K-Akt, NF-&#x3ba;B, JAK-STAT, and TNF signaling pathways. Hub genes with high connectivity included MMP9, IL6, MMP3, CTSK, and BGLAP. Integrated network analysis highlighted the transcription factor JUN and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b). The qRT-PCR results confirmed the expression trends of selected DEGs. CONCLUSIONS: This study, for the first time, profiled the differentially expressed mRNAs, microRNAs, and lncRNAs in post-traumatic elbow HO using high-throughput RNA sequencing. These findings provide valuable insights into the molecular mechanisms of HO following elbow trauma. The identified hub genes (MMP9, IL6, MMP3, CTSK, and BGLAP), key TF (JUN), and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b) may serve as potential therapeutic targets for preventing and treating post-traumatic elbow HO.

Humans

Phytolacca acinosa Roxb. induces intestinal toxicity through the histamine-MLCK-tight junction axis: Integrated evidence from proteomics, metabolomics, intestinal organoids and epithelial barrier validation.

Phytolacca acinosa Roxb. (PR) is a saponin-rich medicinal plant associated with gastrointestinal toxicity, but the mechanisms underlying PR-induced intestinal barrier injury remain unclear. In this study, raw PR extract was analytically characterized by UPLC-ZenoTOF-MS/MS, confirming triterpenoid saponins as the predominant constituents. C57BL/6&#x202f;J mice were orally exposed to characterized PR extract (1.20 or 12.0&#x202f;g/kg for 5&#x202f;h), and Caco-2 cells and mouse intestinal organoids were used to assess epithelial toxicity and barrier disruption. Histopathology, ELISA, FITC-dextran permeability assays, immunofluorescence, CCK-8, LDH release, western blotting, DIA-based proteomics and untargeted metabolomics were integrated to define toxicological mechanisms. PR induced dose-dependent intestinal inflammation and barrier dysfunction, with the ileum as the most sensitive target. PR increased serum DAO and D-lactate and intestinal TNF-&#x3b1; and IL-1&#x3b2;, disrupted organoid morphology, enhanced epithelial permeability, and reduced ZO-1 expression. Proteomics revealed changes in inflammatory, lipid-metabolic, cytoskeletal and tight-junction pathways, including upregulation of MLCK3 and phospholipase-related proteins and downregulation of ZO-1 and ZO-2. Metabolomics identified histidine metabolism disturbance and histamine accumulation. Integrated multi-omics and pharmacological validation indicated that histamine activated the PLC/IP&#x2083;/Ca&#xb2;&#x207a;/CaM/MLCK cascade, promoting MLC phosphorylation, tight-junction disassembly and epithelial leakiness. MLCK inhibition partially restored ZO-1/ZO-2 expression and attenuated PR-induced epithelial injury. These findings identify the histamine-MLCK-tight junction axis as a key mechanism of PR-induced intestinal toxicity and support hazard identification of saponin-rich PR exposure.

Animals

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence

Integrated physiological and transcriptomic analyses reveal coordinated gill responses to heat stress in pikeperch (Sander lucioperca).

Climate change-driven warming of aquatic environments has made thermal stress an increasingly important factor influencing fish physiological homeostasis. Given their central roles in respiration and osmoregulation, gills are particularly responsive to variations in ambient temperature. Histological examination, physiological measurements, and transcriptome profiling were integrated to investigate the mechanisms associated with heat stress-induced gill injury in pikeperch (Sander lucioperca). Histological analysis revealed that exposure to 29&#xa0;&#xb0;C directly caused structural damage to the gills of pikeperch. Oxidative status was evaluated by measuring malondialdehyde (MDA) levels and the activities of antioxidant enzymes, including superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). MDA accumulation was significantly enhanced under heat stress, while antioxidant enzyme activities (SOD, POD, and CAT) displayed a transient increase followed by a subsequent decline. Transcriptome profiling showed marked enrichment of the protein processing in endoplasmic reticulum pathway after heat stress, suggesting activation of endoplasmic reticulum (ER) stress in pikeperch gills. With increasing stress duration, the unfolded protein response (UPR) appeared unable to re-establish ER homeostasis, shifting ire1 and atf6 toward a pro-apoptotic state. Protein-protein interaction (PPI) analysis further highlighted hub genes potentially involved in heat stress-induced ER stress and apoptosis. TUNEL staining and western blotting collectively confirmed that heat stress triggered apoptosis in pikeperch gill tissue. Overall, this study provides new insights into the physiological and molecular responses of pikeperch gills to heat stress and enhances our understanding of thermal stress adaptation in cold-water aquaculture species under climate change.

Animals

The effects of mindfulness-based cognitive therapy in the psychological and physical health of cancer patients: A systematic review and meta-analysis.

PURPOSE: No prior systematic review has specifically evaluated the efficacy of mindfulness-based cognitive therapy (MBCT) in improving both psychological and physical outcomes among cancer populations. This study aims to assess MBCT's effects on cancer patients' mental and physical health. METHOD: Following PRISMA guidelines and with PROSPERO registration (CRD42023453581), we systematically searched PubMed, Cochrane CENTRAL, Embase, and Web of Science for randomized controlled trials (RCTs) were searched up to June 2026. Eligible trials enrolled adults (&#x2265; 18&#xa0;years) with any cancer type/stage, compared MBCT delivered per standard manual against non-MBCT controls, and reported at least one validated measure of distress, depression, or anxiety; secondary outcomes included fatigue, quality of life, and mindfulness skills. Two reviewers independently selected studies, extracted data, and assessed risk of bias using the Cochrane tool; random-effects meta-analyses were performed in Stata 16. RESULTS: 11 RCTs comprising 1122 participants (mean age 54.8&#xa0;years; 91% female) were included. MBCT produced large, significant reductions in psychological distress (SMD&#xa0;=&#xa0;-0.81, 95% CI-1.27 to-0.40), depression (SMD&#xa0;=&#xa0;-0.95, 95% CI -1.40 to-0.49), and anxiety (SMD&#xa0;=&#xa0;-0.86, 95% CI -1.22 to-0.51). It also markedly decreased fatigue (SMD&#xa0;=&#xa0;-0.83, 95% CI-1.10 to-0.56), improved quality of life (SMD&#xa0;=&#xa0;0.56, 95% CI 0.22-0.88), and enhanced mindfulness skills (SMD&#xa0;=&#xa0;0.76, 95% CI 0.59-0.92). CONCLUSIONS: This meta-analysis is the first to exclusively synthesize RCT evidence of standardized MBCT in cancer care, demonstrating significant dual benefits for emotional and physical well-being while providing strong support for integrating MBCT into comprehensive oncology rehabilitation.

Humans

Virtual, Augmented, and Mixed Reality Technologies in Neurosurgical Training: Enhancing Skills and Surgical Outcomes: A Systematic Review.

OBJECTIVE: To systematically review the role of virtual reality (VR), augmented reality (AR), and mixed reality (MR) in neurosurgical education and training. DESIGN: Systematic review conducted in accordance with the PRISMA guidelines. SETTING: A comprehensive search was performed across PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar for English-language studies published between 1 January 2020 and 30 April 2026. PARTICIPANTS: Studies involving neurosurgeons, fellows, residents, and medical students (maximum sample size: n = 48) were included. RESULTS: Of 7,204 initially identified studies, 25 met the inclusion criteria. VR was primarily used for surgical simulation (100% of VR studies) and anatomical education (62.5%). AR demonstrated broader applications, including preoperative planning (40%) and intraoperative support (30%). MR was evenly distributed across simulation, planning, and intraoperative support (40% each). The most frequently improved outcomes were training effectiveness (52%) and technical proficiency (44%). Methodological quality scores, assessed using the Modified Medical Education Research Study Quality Instrument (MMERSQI), ranged from 39.5 to 84.5, indicating varied rigor. CONCLUSION: VR, AR, and MR technologies show potential to enhance surgical precision, technical skills, and educational outcomes in neurosurgical training. However, standardization of methodologies and cost-effective solutions remain essential. Future research should focus on long-term clinical impact and integration of AI-driven training models.

Virtual Reality

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans

Integrated single-cell and bulk transcriptomic analysis identifies a novel senescent fibroblast subtype associated with poor prognosis in acral melanoma.

BACKGROUND: Acral melanoma (AM) exhibits significant intratumoral heterogeneity, but its tumor microenvironment (TME) and immune regulation remain unclear. This study aims to dissect TME heterogeneity and establish a prognostic model based on key cell subpopulations. METHODS: We collected AM single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Unsupervised clustering, CellChat, and Scissor analysis were performed to characterize cellular heterogeneity, cell-cell communication, and prognosis-related cell subpopulations. Kaplan-Meier analysis was used to assess the prognostic value of key genes, which were further validated by multiplex immunohistochemistry (mIHC). RESULTS: In AM, Mel_C2, C7, and C9 with high SEMA6A and KIT expression were strongly linked to poor prognosis. We further identified a senescent fibroblast subpopulation (sCAF_CDKN2A) characterized by high fibroblast senescence signature (FSS) scores. Integrating Scissor analysis of fibroblast subtypes with bulk prognostic data, we identified COL3A1, VCAN, and KIT as prognosis-associated genes upregulated in poor-outcome-related fibroblast subsets. Cell-cell communication analysis revealed that sCAF_CDKN2A engages in an immunosuppressive network, interacting with regulatory T cells (Tregs) via MIF signaling and receiving signals from exhausted CD8+ T cells through PPIA-BSG interactions. Using transcription factor expression patterns from these fibroblast subtypes, we constructed a prognostic model that effectively stratified patients into distinct risk groups with significant differences in overall survival (OS). mIHC confirmed significantly higher protein levels of SEMA6A and COL3A1 in tumor tissues compared to matched normal tissues. CONCLUSIONS: We established a novel prognostic model for AM and identified sCAF_CDKN2A as an immunosuppressive senescent fibroblast subpopulation driving poor prognosis.

Acral melanoma

Single-cell transcriptome revealed the aberrant keratinocytes activation in antigen presentation in atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD), a common chronic inflammatory skin disease, has been extensively studied using single-cell genomics. However, keratinocytes, as key effector cells in AD, have underlying mechanisms remain incompletely understood and require further investigation. METHODS: We integrated single-cell transcriptomic data from skin tissues of healthy controls, chronic active AD patients, spontaneously healed AD (SHAD) patients, and an ovalbumin-induced AD mouse model. The study particularly emphasized the gene expression and cellular dynamics of keratinocytes across the different groups, as well as their interactions with immune cells. RESULTS: Compared to healthy controls, we observed significant changes in the keratinocyte transcriptome, cellular state, and keratinocyte-immune cell ligand-receptor interactions in AD skin, particularly the marked activation of genes involved in antigen processing and presentation. Interestingly, such gene activation was not observed in keratinocytes from the ovalbumin-induced AD mouse model, despite its phenotype closely resembling human AD. Furthermore, in SHAD, we identified a recovery of both the ligand-receptor interaction patterns and antigen processing and presentation genes, accompanied by a notable shift in the transcriptome. This involved a significant downregulation of genes related to cytoplasmic transcription and oxidative phosphorylation. Notably, this pattern was not observed in the self-healing mouse model following the removal of ovalbumin stimulation. CONCLUSION: Our results suggest that the persistent activation of antigen processing and presentation pathways in keratinocytes may be a key driver of chronic inflammation in AD. Therefore, redirecting anti-allergic therapeutic strategies from solely targeting immune cells to targeting of keratinocyte-mediated antigen presentation may offer a more effective approach. Furthermore, we raise concerns about the use of ovalbumin-induced mouse models to recapitulate human chronic AD, as the underlying mechanisms may differ significantly.

Dermatitis, Atopic

Climate and soil shape Daqu wheat quality and seed microbiome via rhizosphere taxa and microbial assembly.

The grain quality and seed microbiome of Daqu wheat are fundamental determinants of Daqu fermentation performance; however, the mechanisms by which cultivation environments influence these traits via rhizosphere microbial communities remain unclear. Bacterial and fungal communities across the bulk soil-rhizosphere-seed continuum of three wheat cultivars grown in four ecoregions were characterized using absolute quantitative amplicon sequencing. The rhizosphere microbiome was treated as a central intermediary, while the response variables were seed microbial diversity and grain-quality traits, including starch content, protein content, and grain hardness. Twelve physicochemical properties of soil and 11 climatic factors were integrated into a multidimensional association framework. Environmental conditions exerted stronger influences on both seed quality traits and microbial diversity than cultivar identity. Distinct regional signatures were also evident in rhizosphere microbiomes, with environmental gradients explaining community variation more effectively than geographic distance. Bacterial communities exhibited greater sensitivity to environmental fluctuations than fungi. Mantel analyses identified available nitrogen, precipitation, and atmospheric pressure as significant drivers of core rhizosphere taxa (P&#xa0;<&#xa0;0.05). iCAMP revealed that stochastic processes predominantly governed rhizosphere bacterial assembly, whereas stochastic and deterministic mechanisms jointly shaped fungal assembly. Partial least squares path modeling further uncovered a rhizosphere-mediated environment-seed cascade, wherein sunlight intensity and duration, atmospheric pressure, and soil nitrogen directly or indirectly affected seed wet gluten content, grain hardness, and seed microbial diversity through their influences on rhizosphere microbiota. Rhizosphere bacterial diversity was negatively associated with seed bacterial diversity (path coefficient&#xa0;=&#xa0;-0.118, P&#xa0;<&#xa0;0.05), indicating that rhizosphere communities may shape seed endophytic bacterial assemblages via environmental filtering and competitive interactions. Collectively, these findings elucidate how environments shape the quality and seed microbiomes of Daqu wheat, providing scientific guidance for optimal site selection and the standardized production of high-quality brewing wheat for industrial Baijiu.

Triticum

Integrated assessment of biocontrol potential and genome analysis of endophytic Bacillus velezensis MGL-B1 against mango stem-end rot.

Mango stem-end rot is a globally significant postharvest disease that severely threatens the mango industry, primarily caused by Botryosphaeria dothidea. However, information on biocontrol agents targeting this pathogen in mango remains limited. In this study, we isolated and identified a strain of Bacillus velezensis MGL-B1 from mango leaf tissues for the first time, which exhibited broad-spectrum antifungal activity. Both in vitro and in vivo assays demonstrated that MGL-B1 effectively inhibited the growth of B. dothidea, with an in vivo biocontrol efficacy reaching 83.72&#xa0;&#xb1;&#xa0;5.10%, comparable to that of the commonly used chemical fungicide thiabendazole. Further mechanistic analysis revealed that MGL-B1 acts by directly disrupting the integrity of the pathogen's mycelial cell membrane. In addition, its released volatile organic compounds (VOCs) also displayed significant antifungal activity, with components such as 2-nonanone, 2-nonanol, and phenylethyl alcohol being confirmed to exert antifungal effects in in vitro fumigation assays. qPCR analysis showed that MGL-B1 treatment significantly upregulated the transcriptional levels of genes involved in plant-pathogen interaction, phenylpropanoid biosynthesis, and antioxidant defense pathways in mango fruits, with upregulation folds of 16.32, 37.19, and 75.93, respectively; meanwhile, the expression of browning-related genes such as polyphenol oxidase (PPO) was markedly suppressed. Whole-genome sequencing further revealed 14 biosynthetic gene clusters for antimicrobial compounds, including five unknown gene clusters. Collectively, B. velezensis MGL-B1 represents a promising biocandidate strain with multiple antifungal mechanisms and excellent control efficacy, providing a valuable resource for green and sustainable management of mango diseases.

Mangifera

Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.

BACKGROUND: Immunotherapy resistance in lung adenocarcinoma (LUAD) remains a critical clinical challenge, and the mechanisms underlying resistance-associated intratumoral heterogeneity are poorly characterized. METHODS: We performed single-cell RNA sequencing of LUAD patients receiving neoadjuvant immunotherapy (responders vs. non-responders), integrating inferCNV, GSVA, and differential expression analyses. Cluster-specific genes were validated across seven independent cohorts (TCGA-LUAD, GSE13213, GSE26939, GSE29016, GSE30219, GSE31210, GSE42127). A multi-algorithm machine learning framework was used to construct a prognostic model, and the immune microenvironment was characterized using TCIA scoring, seven infiltration algorithms, and ESTIMATE. ARNTL2 function was assessed by CCK-8 and Transwell assays in A549 and H1299 cells. RESULTS: Non-responders showed significant enrichment of epithelial cells, depletion of cytotoxic T/NK cells, and elevated copy number variation burden versus responders (p < 0.0001). A resistance-enriched malignant subcluster (Cluster 2) exhibited hyperproliferative and metabolic reprogramming signatures with upregulated KRT17, S100A2, and CST6, which showed tumor-specific overexpression, adverse prognostic value, and genomic amplification across cohorts. CoxBoost combined with survivalSVM achieved optimal predictive performance (C-index = 0.686), yielding robust risk stratification (HR: 2.54-10.51, all p < 0.05). Low-risk patients showed greater immune infiltration and higher TCIA immunophenoscores. ARNTL2 was an independent prognostic factor (HR: 2.07-4.64) strongly correlated with risk score (r = 0.69), and its knockdown suppressed proliferation and invasion in both LUAD cell lines (all p < 0.05). CONCLUSION: This study identifies a resistance-associated malignant subcluster in LUAD, constructs a validated CoxBoost + survivalSVM prognostic model with robust immune stratification, and establishes ARNTL2 as a core oncogenic driver and therapeutic target.

ARNTL2

Dengue and chikungunya vaccines past, present and future: implications for travelers.

PURPOSE OF REVIEW: Novel vaccines for dengue and chikungunya viruses offer new prevention options against two globally important arboviral diseases. This review summarizes recent developments in vaccine licensure, implementation, real-world experience and research priorities, with emphasis on implications for both endemic populations and travelers. RECENT FINDINGS: Of the three live-attenuated dengue vaccines licensed to date, TAK-003 is authorized in >40 countries and Butantan-DV in Brazil, while manufacturing of CYD-TDV is discontinued. Long-term and postmarketing data continue to refine understanding of serotype-specific protection, waning immunity, and rare adverse events.For chikungunya, two single-dose vaccines are licensed-a live-attenuated vaccine (VLA1553) and virus-like particle vaccine (PXVX0317). Uptake is guided by emerging safety and effectiveness data, with each platform offering potential advantages in different settings.Further data on long-term protection, safety, effectiveness, use in vulnerable populations and integration into outbreak management and immunization systems is anticipated. SUMMARY: Dengue and chikungunya vaccines are increasingly being used in immunization programs and pretravel consultations. Further real-world data are needed-particularly for seronegative dengue vaccine recipients and older, immunocompromised or medically at-risk adults. Research priorities include developing single-dose, nonlive dengue vaccines suitable for high-risk groups, understanding long-term chikungunya vaccine performance, and exploring broader flaviviral or pan-arboviral platforms.

Humans

Prioritizing Parkinson's disease risk-associated mitochondrial candidate genes via multi-omics integrative analysis.

BACKGROUND: Mitochondrial dysfunction has been implicated in Parkinson's disease (PD), but the genetically regulated mitochondrial genes associated with PD risk remain incompletely defined. METHODS: We conducted a summary-data-based genetic epidemiology study integrating summary-based Mendelian randomization (SMR), Heterogeneity in dependent instruments (HEIDI) filtering, and Bayesian colocalization to prioritize mitochondrial-related molecular features associated with PD risk. Mitochondrial-related genes were defined using MitoCarta3.0. Genetically predicted gene expression and plasma protein abundance were evaluated using expression quantitative trait loci (eQTL) data from eQTLGen and GTEx v8, and protein quantitative trait loci (pQTL) data was assessed using International Parkinson's Disease Genomics Consortium (IPDGC) as the discovery genome-wide association study (GWAS) and FinnGen as the replication dataset. Prespecified QTL analyses were interpreted using FDR correction, HEIDI filtering, and colocalization support. DNA methylation QTL analysis, mitochondrial phenotype MR, and single-nucleus RNA-seq analysis were performed as complementary analyses. RESULTS: In the primary eQTL analysis, higher genetically predicted TTC19 expression was associated with lower PD risk (OR = 0.80, 95% CI: 0.74-0.87, PPH4&#x202f;= 0.80), whereas higher MALSU1 expression was associated with increased PD risk (OR = 2.21, 95% CI: 1.59-3.06, PPH4&#x202f;= 0.96). Both associations survived FDR correction, passed HEIDI filtering, and showed colocalization support. GTEx whole-blood data supported the direction of the TTC19 association. No mitochondrial protein reached significance after FDR correction and colocalization filtering in the primary pQTL analysis. Complementary methylation analysis highlighted cg06270993 as an exploratory regulatory signal for MALSU1. CONCLUSIONS: This MR-colocalization study prioritizes TTC19 and MALSU1 as genetically supported mitochondrial-related candidate genes associated with PD risk. Further validation is required to define their functional roles in PD pathogenesis.

Humans