Biomedical subjects

Yu Zhang

Publications and source records attributed to Yu Zhang.

At least 19 recordsLinked to original sources

PubMed2026

A wild soybean MADS-box gene GsAGL62 improves seed weight by enhancing cytokinin signaling and cell proliferation.

Soybean seed weight is a key yield determinant, but the transcriptional mechanisms connecting hormone signaling to seed growth are poorly understood. Here, we identify GsAGL62, a wild soybean MADS-box transcription factor located within a previously mapped hundred-seed weight (HSW) locus and a domestication-associated selective sweep. Functional analyses show that overexpression of GsAGL62 in cultivated soybean significantly increases HSW, whereas ethyl methanesulfonate (EMS)-induced gmagl62 mutants reduce it. Integrated transcriptomic and metabolomic analyses reveal that GsAGL62 enhances cytokinin accumulation and signaling cytokinin-associated responses, accompanied by increased expression of genes involved in cell proliferation. Mechanistically, GsAGL62 directly binds to the promoter of the conserved growth inhibitor GmATPK2 and represses its transcription. Consistently, independent EMS-induced gmatpk2 mutants exhibit increased seed weight, supporting GmATPK2 as a downstream negative regulator of seed growth. Population genetic analyses further reveal strong differentiation of GsAGL62 promoter haplotypes during soybean domestication and improvement. These haplotypes show differential promoter activities and are associated with distinct agronomic performance, suggesting that cis-regulatory variation at GsAGL62 contributes to its selection during soybean improvement. Collectively, our findings establish a regulatory module linking GsAGL62 to cytokinin-associated responses, cell proliferation, and seed growth, and highlight GsAGL62 as a potential target for soybean yield improvement.

Cell proliferation↗

PubMed2026

Occurrence of antibiotic-resistant E. coli and antibiotic resistance genes from culturable bacteria in drinking water sources along the Upper Mahaweli River, Sri Lanka.

Antibiotic-resistant Escherichia coli (AR-E. coli) and antibiotic resistance genes (ARGs) in aquatic environments pose a serious threat to public health. However, their presence in river water in South Asian countries is not well established. The present study investigated AR-E. coli and ARGs from culturable bacteria in drinking water sources from 14 drinking water treatment plants situated along the Upper Mahaweli River, a tropical central hill-country river system in Sri Lanka. A total of 167 E. coli isolates were tested against ten antibiotics using the Kirby-Bauer method, and genomic DNA from culturable bacteria in 45 water samples were screened for 11 ARGs using PCR. Overall, 60.48% E. coli isolates exhibited resistance to at least one antibiotic and multidrug resistance was detected in 27.54%. Highest resistance was for amoxicillin (47.31%), tetracycline (26.95%), and co-trimoxazole (24.55%) and four antibiotics showed seasonal variation. ARGs, dominated by blaTEM (80.0%), tetA (66.67%), and tetM and qnrS (62.22%) were detected in 42.42% PCR assays (n = 210). Multiple antibiotic resistance index varied from 0.00 to 0.80, with 44.91% exceeding the 0.2 threshold value, and the antibiotic resistance index varied from 0.00 to 0.32, with eight above the threshold (≥ 0.2). Hierarchical cluster analysis grouped majority of drinking water sources into the intermediate category while few were categorized under low (Kotagala and Thalawakelle-Galkanda) and high (Haragama, Paradeka, and Nawalapitiya), reflecting the variability of anthropogenic interference. Results highlight the risk associated with AR-E. coli and ARGs from culturable bacteria in one of Sri Lanka's key drinking water sources. Proactive interventions ensuring long-term safety of drinking water sources are urgently needed to safeguard public health.

Sri Lanka↗

PubMed2026

Survival prediction for clear cell renal cell carcinoma based on deep multimodal synergistic survival network.

Objective.To propose a deep multimodal synergistic survival analysis framework (Deep Multimodal Synergistic Survival Network, DMSSN) to achieve accurate prognostic analysis for clear cell renal cell carcinoma (ccRCC).Methods.This study (DMSSN) utilized matched multimodal data from the Cancer Genome Atlas-KIRC database, including CT imaging data, whole slide images, copy number variation (CNV) features, and clinical data. Deep Canonical Correlation Analysis was employed to map heterogeneous modalities into a shared latent space. Contrastive learning was introduced to enhance semantic consistency across multimodal features, and a gating network was utilized for the adaptive fusion of multimodal information to achieve precise survival risk prediction for patients.Results.Experimental results demonstrated that DMSSN achieved a Concordance Index (C-index) of 0.8153 ± 0.0994, with a Log-rank testp-value of 1.6553×10-11. DMSSN exhibited significant performance advantages over traditional statistical methods like Log-rank-Cox (0.7055 ± 0.0670) and machine learning methods such as Random Survival Forest (RSF) (0.6836 ± 0.1048). Furthermore, in comparison with similar deep learning approaches, DMSSN outperformed late fusion strategies (0.7493 ± 0.1211) and discrete-time survival models such as DeepHit (0.7655 ± 0.1041) and Nnet-surv (0.7694 ± 0.0635). Notably, DMSSN still achieved the best predictive performance when compared to the classic deep survival model DeepSurv (0.7919 ± 0.0978) and advanced state-of-the-art multimodal fusion frameworks like Context-Aware Transformer (0.7735 ± 0.0818) and Multimodal Co-Attention Transformer (0.8102 ± 0.0972). Ablation studies showed that removing any single modality led to a decline in performance, with the largest numerical decrease occurring after removing CT imaging features (C-index decreased to 0.7327), validating the complementarity of multimodal data and the pivotal role of radiomic features in prognostic assessment. Module ablation experiments further confirmed the effectiveness of the core components.Conclusion:By effectively integrating imaging, pathology, genomic, and clinical features, the DMSSN framework demonstrates superior performance and robustness in the survival prediction of ccRCC.

Carcinoma, Renal Cell↗

PubMed2026

Comprehensive Identification of WDR Gene Family in Panax ginseng: PgWDR Gene Expression Analysis with Ginsenosides Biosynthesis Under MeJA.

Panax ginseng (Panax ginseng C.A. Mey.) produces pharmacologically valuable ginsenosides. WD40-repeat (WDR) proteins act as versatile regulators of plant specialized metabolism, yet their biological roles under methyl jasmonate (MeJA) elicitation remain largely uncharacterized in ginseng. In this study, we identified 29 PgWDR family members at the whole-genome level, and systematically analyzed their phylogeny, gene structure, cis-acting promoter elements, as well as organ- and development-dependent expression patterns. Six candidate genes potentially associated with ginsenoside biosynthesis were screened through integrating gene-metabolite correlation analysis and gene co-expression analysis. Under MeJA treatment, three of these candidates showed statistically significant expression responses, while the other three exhibited variable expression fluctuations with no statistical significance. PgWDR24 displayed a positive correlation with key ginsenoside biosynthetic enzyme genes, and a negative correlation with protopanaxadiol-type ginsenoside accumulation. Combined with its predicted nuclear localization, we hypothesize that PgWDR24 participates in the negative modulation of protopanaxadiol-type ginsenoside accumulation, although further genetic functional validation is still required. This work provides valuable candidate genes for deciphering ginsenoside regulatory networks and offers support for molecular-assisted breeding of high-quality ginseng.

Panax ginseng C. A. Mey.↗

PubMed2026

JP1 peptide modulates oxidative stress and autophagy via Keap1-Nrf2-ARE in ALS model mice.

BACKGROUND: The simultaneous modulation of oxidative stress and autophagy represents a potential therapeutic strategy for amyotrophic lateral sclerosis (ALS), yet agents capable of coordinately regulating both processes remain scarce. The Keap1‑Nrf2‑ARE pathway serves as a critical hub linking redox homeostasis and autophagic regulation, making it an attractive target for ALS intervention. JWA is a stress‑responsive protein involved in cellular protection against oxidative injury, and its neuroprotective effects have been shown to depend on activation of the MEK/ERK‑Nrf2 axis. JP1 is a functional oligopeptide derived from the JWA protein that has been engineered to cross the blood-brain barrier and specifically target integrin αVβ3. Based on the link between JWA and Nrf2 signaling, we hypothesized that JP1 activates the Keap1‑Nrf2‑ARE pathway to coordinate antioxidant defense and autophagic clearance. Here, we evaluated this hypothesis in the SOD1‑G93A mouse model, a well‑established transgenic model of familial ALS, and elucidated the underlying mechanisms. METHODS: We evaluated the efficacy of JP1 in the SOD1-G93A mice model using behavioral phenotyping and survival analysis. The coordinated mechanism was investigated in spinal cord tissues by profiling the Keap1-Nrf2-ARE pathway and oxidative stress, quantifying autophagic flux (by Western blotting and transmission electron microscopy) and neuronal apoptosis, and evaluating histology (by Nissl staining and immunofluorescence). Integrated transcriptomic and proteomic analyses further elucidated the global molecular landscape underlying the therapeutic effects of JP1. RESULTS: JP1 treatment ameliorated motor deficits and extended survival in SOD1-G93A mice without adversely affecting liver or kidney function. JP1 crossed the blood-brain barrier, targeted motor neurons expressing integrin αVβ3, and activated the ERK pathway. This promoted Keap1/Cul3 degradation and Nrf2 nuclear translocation, thereby activating the Keap1-Nrf2-ARE pathway to alleviate oxidative stress. Concurrently, JP1 restored autophagic flux, increased autophagic activity, attenuated motor neuron injury, suppressed neuronal apoptosis, and preserved neuronal structural integrity. The Nrf2 inhibitor ML385 reversed the protective effects of JP1 on survival, motor function, autophagy, oxidative stress, and neuronal apoptosis, which confirms that JP1 acts via the Nrf2 pathway. CONCLUSIONS: JP1 acts as a promising coordinator of antioxidant and autophagic processes by targeting the Keap1-Nrf2-ARE pathway, thus highlighting its therapeutic potential for ALS.

Animals↗

PubMed2026

Screening of Fermentative Strains for Reducing the Allergenicity of a Whey Protein-Soy Protein System and Genomic Characterization of the Selected Strain.

Dual-protein systems combining whey protein isolate (WPI) and soy protein isolate (SPI) offer complementary nutritional benefits but are limited by the presence of major allergens. Lactic acid bacteria (LAB) fermentation provides a promising strategy to mitigate this limitation. In this study, Lacticaseibacillus paracasei JM053, selected from 13 LAB strains based on phenotypic screening, significantly reduced the in vitro allergenicity of the dual-protein system, increasing the IgE-binding inhibition rate to 48.75%. Whole-genome sequencing and characterization of JM053 revealed a comprehensive proteolytic system, including the proline-specific peptidase genes pepX and pepQ, which may contribute to the degradation of allergenic peptide sequences. Combined with in silico bioinformatic analysis, potential cleavage sites within the linear epitopes of the dual-protein system were predicted based on the substrate specificity of the identified proteases, offering a testable hypothesis for the strain's mechanism of action. In addition, in vitro safety assessment and genomic analysis supported the safety potential, stress tolerance, and probiotic characteristics of JM053. Collectively, this study provides a valuable candidate strain for the development of hypoallergenic dual-protein products and offers preliminary genomic insights into LAB-mediated allergenicity reduction.

Lacticaseibacillus paracasei↗

PubMed2026

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↗

PubMed2026

Inhibitory mechanism of anthocyanin B-ring substituents on advanced glycation end-product formation through bovine serum albumin binding: Insights from multispectral, molecular docking and proteomics approaches.

This study demonstrated that the inhibitory effect of anthocyanins on AGEs formation is highly dependent on the substitution pattern of the B-ring. Among the four anthocyanins, delphinidin-3-O-glucoside (D3G) exhibited the most potent antiglycation activity across BSA-fructose, MGO, and GO models with half-maximal inhibitory concentration (IC50) of 30.77, 200.29 and 269.97 μM. This superior performance was attributed to the presence of three hydroxyl groups on the B-ring, which facilitates a high-affinity, spontaneous binding interaction with BSA primarily through hydrophobic forces and hydrogen bonding. Spectroscopic and computational analyses revealed that D3G effectively stabilizes the protein scaffold, specifically recovering α-helix content and shielding critical subdomains (IB, IIA, and IIIA). Proteomics data are consistent with a protective binding mechanism, suggesting that D3G reduces the accessibility of key lysine and arginine residues to glycation-induced modifications. These findings provide a structural basis for developing D3G-rich extracts as targeted, structure-based functional ingredients to mitigate glycation-associated food quality degradation and related health issues.

Anthocyanins↗

PubMed2026

Positional grammar of transcription factor binding partitions developmental and stress-response regulation in plants.

Understanding how transcription factor binding site (TFBS) position influences gene regulation remains a fundamental challenge in plants. Here, we integrate conserved multiDAP TFBS maps for 244 transcription factors (TFs) with single-nucleus chromatin accessibility, cell type-resolved gene expression, and hormone-response datasets across Brassicaceae species to determine how TFBS position relates to regulatory function. Although conserved TFBSs are enriched near transcription start sites (TSSs), TSS-proximal accessibility poorly predicts cell type-specific expression. Instead, cell type-specific expression correlates best with conserved TFBSs embedded in cell type-restricted chromatin, with TF family-specific distributions across distal promoters and introns. In contrast, TSS-proximal TFBSs in broadly accessible chromatin are associated with rapid transcriptional responses to abiotic and biotic stress hormones. Coding sequence TFBSs mark a distinct regulatory context in which the same DNA sequence encodes both amino acid sequence and TF motifs, including evidence that CDS-localized ABR1 binding may contribute to repression during hormone response. Finally, distal upstream regions contain conserved multi-family TF clusters with enhancer-like features overlapping rare cell type-specific accessible chromatin and enriched near genes controlling embryonic, meristematic, and hormone-dependent developmental patterning. Together, these results support a positional grammar in which TFBS position and chromatin context jointly partition developmental, stress-responsive, and repressive regulatory output in plants.

Transcription Factors↗

PubMed2026

Novel bacterial hosts and mobile genetic structure of tet(X) variants in tetracycline-contaminated aquatic environment uncovered by culture and long-read metagenomics.

Clinically important tigecycline (3rd-generation tetracycline) resistance tet(X) variants were inferred to have evolutionarily originated from environmental bacteria, and have been recognized among environment, human and animals. However, genetic basis for environmental proliferation and dissemination of tet(X) variants remains ambiguous. This study profiled tet(X) variants at gene, contig, isolate, and community levels in environmental community subjected to long-term stepwise increasing oxytetracycline (1st-generation tetracycline) or tigecycline pressure using long-term microcosm experiments, quantitative PCR, bacterial isolation, whole-genome sequencing, and Nanopore-based long-read metagenomics. We confirmed that both oxytetracycline and tigecycline enriched the abundance of tetracycline resistance genes especially oxytetracycline-enriched tet(X3). Unexpectedly diverse bacterial hosts and genetic structure of tet(X)-positive mobile elements in the environment microbiome were identified using bacterial isolation and long-read Nanopore metagenomics. Pseudomonas defluvii was first reported to carry tet(X3) in the chromosome, forming IS26-tet(X3)-res-ISCR2 circular intermediate to transfer between different DNA molecules. Database mining revealed similar mobile segments have prevailed among animal-derived Acinetobacter species. Unlike the widely reported ISCR2-mediated transfer of tet(X6), we identified a novel mobile multidrug transposon TnAs3 where tet(X6) and class 1 integron co-transferred as its passenger region. Mobile tet(X2)-ere(D)-aadS-erm(F)-blaOXA-347 segment was annotated in Runella, and co-occurrences of tet(X2) and ere(D), aadS, blaOXA-347 were also found in Flavobacterium, Arsenicibacter, Chryseobacterium and Pedobacter. Overall, tetracycline-contaminated aquatic microbiome harboured diverse mobile tet(X)-positive segments which have not yet been acquired by clinical pathogens, and thus served as the genetic pool of tet(X) variants together with indigenous bacterial hosts, especially the newly reported Pseudomonas defluvii. Reducing pollution of older-generation tetracyclines would be a proactive way to mitigate environmental evolution and possible clinical effects of tet(X) variants.

Metagenomics↗

PubMed2026

Machine Learning-Based Identification of Survival-Associated CpG Biomarkers in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an exceptionally aggressive cancer with a 5-year survival rate of less than 10%, driven by late-stage diagnosis, limited treatment options, and a lack of reliable biomarkers for early detection and prognosis. In this study, we integrated DNA methylation data from TCGA and ICGC cohorts, categorizing samples based on survival time, and identified 688 differentially methylated CpG sites, along with 224 CpG biomarkers significantly associated with patient survival through statistical and machine learning-based analyses. We developed a random forest model to predict patient survival, achieving 85.2% accuracy for short-survival patients and 70.0% for long-survival patients in the validation set. External dataset validation further confirmed the model's robustness and accuracy. De novo motif analysis of genomic regions surrounding the 224 CpG biomarkers identified TWIST1 and FOXA2 as key transcriptional regulators enriched in survival-associated CpG sites, linking their activity to patient survival outcomes. Collectively, our findings highlight valuable epigenetic biomarkers and provide a predictive model to assess PDAC risk levels post-surgery, offering the potential for improved patient stratification and personalized therapeutic strategies.

DNA methylation↗

PubMed2026

Comparative Genomics Reveals Convergent Evolution Between Avivorous Bats (Ia io and Nyctalus aviator).

Investigating the genetic basis of dietary specialization can provide insights into the evolution of niche breadth. In this study, we employed comparative genomics to investigate the adaptive mechanisms enabling two bat species (Nyctalus aviator and Ia io) to shift from insectivory to seasonal bird consumption (avivorous bats). Our findings revealed adaptation related to immune response and lipid metabolism in avivorous bat species. Avivorous bats exhibit strong positive selection and convergent evolution in immune-related genes, which are under heightened selective pressure compared to those of non-avivorous bats. These species also display significantly fewer endogenous retroviral elements. These findings emphasized the significance of immune-driven adaptive evolution in avivory. Additionally, our results showed that the dietary evolution of avivorous bats is accompanied by convergent evolution associated with the lipid metabolism. Notably, CEPT1, the upstream gene required for the activation of the PPAR pathway, underwent positive selection and convergence, which may have affected lipid metabolism. These adaptations may enable avivorous bat species to face the challenge of immune response and nutrition during dietary niche expansion. These findings not only provide comprehensive insights into the adaptive evolution driving the unique diet of avivorous bats but also offered novel perspectives on the molecular mechanisms underlying ecological niche evolution in a dietary context.

Animals↗

PubMed2026

Research on multi-trait genome association study method based on Shannon information entropy.

BACKGROUND: Genetic analysis of complex traits is crucial for elucidating disease mechanisms and biological inheritance processes. However, traditional Genome-wide Association Study (GWAS) for single trait often fail to capture the synergistic effects of genetic loci on multiple traits. METHODS: This study proposes a method for analyzing the association between multiple traits and gene regions based on Shannon information entropy. Innovatively, Shannon information entropy is introduced to integrate gene region information as genetic entropy, thereby constructing an Inverse Shannon Entropy-Multi-Trait Association Analysis of Gene Region genetic model (InvSE-MTAGR). Furthermore, a partial regression test is applied to the model to establish the Inverse Partial Shannon Entropy-Multi-Trait Association Analysis of Gene Region method (InvPSE-MTAGR). When performing multi-trait analysis with InvSE-MTAGR, the method achieved statistical significance by accumulating minor effects, thereby enhancing the ability to identify pleiotropic gene regions. RESULTS: The simulation results showed that the proposed multi-trait gene region association analysis method performed well in terms of both Type I error rate control and statistical power. Leveraging tomato and sorghum datasets for validation, the proposed multi-trait gene region association analysis method based on Shannon information entropy accurately pinpointed most of the gene regions harboring candidate genes. CONCLUSION: The study reveals the advantage of multi-trait method in integrating weak-effect pleiotropic signals and capturing the correlation among traits, which provides an efficient theoretical tool for dynamic analysis of complex multi-trait genetic networks and multi-target collaborative breeding of crops.

Genome-Wide Association Study↗

PubMed2026

Oxidative Stress Associated LncRNAs as Potential Biomarkers for Prognosis and Immune Responses in Lung Squamous Cell Carcinoma Patients.

Long-chain non-coding RNA (lncRNA) significantly influences lung squamous cell carcinoma's (LUSC) prognostic value and immune infiltration. This study aimed to demonstrate how oxidative stress-related lncRNAs impact lung squamous cell carcinoma (SCC). The Cancer Genome Atlas (TCGA) dataset gathered transcriptome information and related clinical data for LUSC. To build a prognostic model, 10 prognostic-related genes were identified using a series of bioinformatics analyses that compared the OS gene's aberrant expression in tumor and healthy tissues, as well as its association with malignancy. Subjects were stratified into high- and low-risk groups based on the median risk score derived from the 10-gene signature. While the mathematical risk model demonstrated limited independent predictive performance in the validation cohort (AUC ~ 0.5), functional and immunological evaluations revealed significant differences in the tumor microenvironment (TME) across risk strata. Specifically, high-risk patients exhibited distinct immune infiltration profiles and altered immunological scores relative to their low-risk counterparts. Therefore, rather than serving as a direct clinical prediction tool, this oxidative stress-related lncRNA signature provides valuable biological insights into the immune landscape of LUSC and highlights potential therapeutic targets for further mechanistic investigation.

Humans↗

PubMed2026

MYC-bound enhancer RNAs in cis regulate gene transcription and tumorigenesis.

Emerging evidence suggests that MYC binds RNAs, but its functional consequences remain unclear. Here, we integrate multiomics data and reveal that MYC broadly binds enhancer RNAs (eRNAs), which exhibit high cancer- and tissue-specific expression in cancer cell lines and patient tumors. Moreover, we developed a computational pipeline to identify potential cis-regulatory MYC-eRNA target genes, with most predicted eRNA-target pairs supported by RNA polymerase II-mediated chromatin interaction data. Among these, we functionally characterized MERG1 as an oncogenic eRNA that promotes breast cancer tumorigenesis. Mechanistically, MERG1 interacts with MYC to enhance its occupancy at the GREB1 promoter, driving chromatin remodeling and epigenetic activation. This process specifically amplifies GREB1 expression and promotes tumor progression. Last, nanoparticle-mediated delivery of antisense oligonucleotides targeting MERG1 suppresses MYC-mediated breast cancer growth. These results advance our understanding of the enhancer-driven regulation of gene expression and tumorigenesis and provide insights into the regulatory landscape of MYC in cancer.

Humans↗

PubMed2026

Intervention components, training dose, and adherence in exercise-based prevention of hamstring strain injury in football: a systematic review and meta-analysis.

OBJECTIVE: To quantify associations between exercise-based prevention programmes and hamstring strain injury (HSI) risk in football participants, and whether training dose and adherence modify effects. METHODS: Six databases were searched to 1 October 2025. Randomised and cluster-randomised trials comparing HSI prevention programmes with usual practice or warm-up in football participants were included. Random-effects meta-analysis pooled risk ratios (RRs); subgroup analyses and meta-regression assessed effect modification. RESULTS: Fifteen trials (n = 7,465) were analysed. Programmes reduced HSI risk (RR = 0.51, 95% CI 0.36-0.71), with I²=57% and a prediction interval crossing the null (0.18-1.40). Based on a control event rate of 7.8%, absolute risk reduction was 3.8% (38 fewer HSIs per 1000 participants; 95% CI 23-50 fewer). Effects were stronger for shorter interventions (1-6 months; RR = 0.43) than longer interventions (7-10 months; RR = 0.77; P for interaction=0.04), and for elite/semi-professional players (RR = 0.38) than amateur players (RR = 0.77; P for interaction = 0.02). Training frequency and weekly volume did not modify effects, whereas adherence did. High adherence (≥75%) was associated with lower HSI risk (RR = 0.36, 95% CI 0.28-0.48), whereas low adherence (<75%) showed no clear benefit (RR = 0.92, 95% CI 0.68-1.23; P for interaction <0.00001). Each 10% increase in adherence corresponded to an RR multiplier of 0.83 (approximately 17% lower RR). Certainty of evidence was low. CONCLUSION: Exercise-based programmes reduce HSI risk in football when implementation supports sustained adherence. Effects may be stronger in shorter interventions and elite populations, but evidence remains insufficient to differentiate programme types or components.

Humans↗

PubMed2026

Deep learning and statistical methods identify novel asthma risk variants in Europeans.

BACKGROUND: Asthma is a common heritable respiratory disorder with a complex genetic basis. Although large-scale genome-wide association studies have identified many risk loci, the full spectrum of its polygenic architecture remains to be defined. OBJECTIVE: We refined the genetic landscape of asthma in individuals of European ancestry and improve polygenic risk prediction through statistical and deep learning-based methods. METHODS: We conducted the largest genome-wide association study meta-analysis of asthma in individuals of European ancestry, combining data from the Global Biobank Meta-analysis Initiative (121,940 cases, 1,254,131 controls) and the Million Veteran Program (36,823 cases, 398,278 controls). To enhance discovery, we applied pleiotropy-informed multitrait analysis and conditional false discovery rate approaches, each incorporating eosinophil counts as a secondary trait. In parallel, we used a Transformer-based deep learning framework to further prioritize variants and improve polygenic risk prediction. RESULTS: The meta-analysis identified 69 independent genome-wide significant loci (P < 5 × 10-8) not previously reported in asthma. Multitrait analysis of genome-wide association studies, conditional false discovery rate, and deep learning approaches uncovered additional candidate loci. Functional annotation and expression quantitative trait locus mapping implicated novel genes in immune regulation, airway remodeling, and metabolic processes. Polygenic risk score models derived from deep learning-prioritized variants outperformed those based on conventional genome-wide association study and standard statistical approaches. CONCLUSIONS: Our study yields a comprehensive map of asthma-associated loci in European ancestry populations, improves genetic risk prediction, and informs future mechanistic studies.

Humans↗

PubMed2026

Dexamethasone as an adjuvant to continuous erector spinae plane block for postoperative analgesia after video-assisted thoracoscopic surgery for pulmonary nodule surgery: a randomized controlled trial.

BACKGROUND: While dexamethasone is proven to enhance single-shot erector spinae plane block (ESPB), its role as an adjuvant in continuous ESPB catheters is unclear. This randomised controlled trial evaluated whether adding dexamethasone to ropivacaine improves analgesia after video-assisted thoracoscopic surgery (VATS). METHODS: 85 patients undergoing VATS with continuous ESPB were randomised to receive postoperative infusion of either 0.2% ropivacaine(C-ESPB group) or ropivacaine with 10 mg dexamethasone(D + C-ESPB group). The primary outcome was resting pain visual analog scale (VAS)at 12 h postoperatively, while secondary outcomes included QoR-15 scores, tramadol consumption, time to first analgesic requirement, postoperative adverse events, 3-month incidence of chronic pain, catheter-related complications, pain intensity at other times, and hospital stay. RESULTS: The D + C-ESPB group had significantly lower resting pain at 12 h [2.56 (1.03) vs 3.24 (1.21), mean difference -0.680, p = 0.006]; and lower coughing pain at 12 h [4.60 (1.48) vs 5.69 (1.35), mean difference 1.086, p < 0.001], with analgesic superiority sustained through 72 h. Quality of Recovery-15 scores were higher at 12 h [124.70 (12.48) vs 117.26 (12.24); mean difference -7.436, p = 0.007] and 48 h [141.60 (5.51) vs 138.98 (6.64); mean difference -2.628, p = 0.050]; Total tramadol consumption over 72 h was markedly reduce [0 (0,100) vs 100 (75,100), z = -3.807, p < 0.001], and hospital stay was shorter [Mean (SD) 6.09 (1.34) d vs 6.93 (1.55)d, p < 0.001]. The intervention did not, however, alter the 3-month incidence of chronic postsurgical pain (31% vs 34%, p = 0.756). CONCLUSION: Dexamethasone significantly enhances the analgesic efficacy of continuous ESPB, improving early pain control, recovery quality, and opioid-sparing after VATS, but does not reduce the incidence of chronic persistent surgical pain.

Humans↗