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PubMed2026

Infant Dietary Patterns and Early Childhood Weight Outcomes: A Secondary Analysis from the Starting Early Program Trial.

BACKGROUND: The Starting Early Program (StEP) promotes healthy nutrition during early life and leads to healthier child weight, but whether dietary patterns contribute to weight or mediate StEP weight outcomes has not been studied. OBJECTIVES: This secondary analysis identified infant dietary patterns in StEP, determined associations between dietary patterns and child weight outcomes, and examined whether dietary patterns mediated the relationship between StEP and child weight. METHODS: Data were from 377 mother-infant dyads in a randomized trial testing the efficacy of StEP. Dietary patterns at 10 months were identified using latent class analysis. Child weights were abstracted from medical records at 12, 24, and 36 months. Associations between infant dietary patterns and weight-for-age z-score (WFAz) and likelihood of being classified as overweight (WFA ≥85th percentile) were assessed using linear and logistic multivariable regression models. Mediation was used to assess intervention effects on WFAz via impacts on infant dietary patterns. RESULTS: Four classes of infant dietary patterns were identified: Breastfed-High variety, Formula fed-High variety, Formula fed-Low variety, and Mixed fed-Low variety. Compared to the Breastfed-High variety class, infants in the Formula fed-Low variety class had higher WFAz and were more likely to be classified as overweight at 24 and 36 months. Participation in StEP increased membership in Breastfed-High variety, which mediated the association between StEP and lower WFAz at 24 months. CONCLUSIONS: Infant dietary patterns were identified, and some were associated with child overweight. StEP was associated with a dietary pattern most consistent with guidelines, which mediated intervention effects on child weight.

Humans↗

PubMed2026

Genetic determinants of gestational diabetes mellitus in thai pregnant women: role of GCKR, CDKAL1, TCF7L2, NEDD1, and CMIP variants.

BACKGROUND: Gestational diabetes mellitus (GDM) has a high global prevalence and arises from complex interactions between genetic predisposition and environmental factors. GDM is associated with metabolic disturbances and chronic low-grade inflammation, both of which contribute to its pathogenesis. This study aimed to investigate the association between GDM and 135 single-nucleotide polymorphisms (SNPs) across 20 genes related to metabolic traits. METHODS: In this case-control study, 152 pregnant women with GDM and 684 pregnant women with normal glucose tolerance (NGT) who underwent antenatal examination at Siriraj Hospital, Bangkok, were enrolled. Clinical data and blood samples were collected from all participants. Genomic DNA was isolated and subjected to whole-genome sequencing using the DNBSEQ-T7RS high-throughput sequencing platform. Genotype analyses were performed using R software, and haplotype analyses were conducted using the online SNPStats software. RESULTS: After adjusting for maternal age and pre-pregnancy body mass index, polymorphisms in TCF7L2 (rs34872471, rs7901695, rs4506565, rs7903146, rs12243326, and rs12255372), NEDD1 (rs10431408, rs11830756, rs249579, rs249585, and rs4762339), CMIP (rs2306115 and rs201681534), CDKAL1 (rs4710942), GCKR (rs2293572 and rs2293571), and GCK (rs5883890) were significantly associated with the risk of GDM. Haplotype analysis demonstrated that the TCF7L2 rs12243326-rs12255372 CA haplotype was associated with a decreased risk of GDM (OR = 0.44, 95% CI: 0.23-0.81), while the NEDD1 rs249579-rs249585-rs4762339 GGT haplotype was associated with an increased risk of GDM (OR = 1.40, 95% CI: 1.08-1.82). CONCLUSIONS: These findings suggest that genetic variations in TCF7L2, NEDD1, CMIP, CDKAL1, GCK, and GCKR contribute to GDM susceptibility in the Thai population.

Humans↗

PubMed2026

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 J mice were orally exposed to characterized PR extract (1.20 or 12.0 g/kg for 5 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-α and IL-1β, 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/IP₃/Ca²⁺/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↗

PubMed2026

Evolution of maize recombination landscape during domestication.

Despite the plethora of knowledge about the benefits of meiotic recombination and numerous theoretical studies examining how recombination rates evolve, there is a general lack of empirical support and consensus across species. To fill this knowledge gap, we characterized the evolution of recombination landscape in maize during its domestication from teosinte and related the observed changes to established theoretical frameworks. Through examining recombination in experimental populations of maize and teosinte and the population genomics approach of identifying historical recombination events using ancestral recombination graph inference to generate saturated maize and teosinte recombination maps, we found that during domestication, maize experienced a 12% increase in its genome-wide recombination rate. Furthermore, maize evolved higher recombination rates on the long arms of chromosomes in regions closer to centromeres, where recombination is generally very low. The repatterning of crossover events came from changes in global crossover positioning rather than alterations in cis-acting chromatin factors. Consequently, we found evidence of selection acting on trans-acting recombination modifiers affecting crossover interference and controlling the interference-dependent class I crossover pathway. We show that CO repatterning was likely beneficial for maize fitness, as significant recombination rate increases were predominantly in gene-rich regions, which harbor domestication-related variation. This work suggests genomic and mechanistic processes leading to the evolution of meiotic recombination landscape in response to directional selection pressure and provides evidence for the evolutionary advantage of recombination.

Zea mays↗

PubMed2026

Integrated bioinformatics analysis reveals cross-talking hub genes and therapeutic agents between sepsis and acute myocardial infarction.

BACKGROUND: Sepsis and acute myocardial infarction (AMI) are two significant diseases that may share overlapping etiological mechanisms. This study aims to systematically identify core genes common to both conditions and to explore their potential as therapeutic targets and drug candidates through an integrative analysis of clinical data and bioinformatics. METHODS: The AMI dataset was obtained from the GEO database, and RNA sequencing data were collected from blood samples of patients with sepsis at our hospital. Common genes were identified using differential expression gene analysis (DEG) and weighted gene co-expression network analysis (WGCNA). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using the MCC/Degree algorithm. Diagnostic value was assessed via receiver operating characteristic curve analysis. Immune infiltration patterns, single-cell sequencing data, and molecular docking simulations were employed to evaluate immune relevance and identify potential therapeutic compounds. RESULTS: A total of 417 genes were identified between sepsis and AMI, with enrichment analysis revealing significant involvement in inflammatory responses. Three hub genes-JAK2, MYD88, and TIMP1-were selected for further investigation. ROC curves confirmed their strong diagnostic performance for both diseases. Immune infiltration analysis showed that these core genes were significantly correlated with the infiltration levels of various immune cell types. Molecular docking indicated that quercetin exhibited stable binding affinity with the proteins encoded by these genes. qPCR validation further confirmed the upregulation of these three genes, supporting the anti-inflammatory effects of quercetin as a potential targeted therapy. CONCLUSION: JAK2, MYD88, and TIMP1 were identified as shared core genes in sepsis and AMI. These genes not only serve as potential diagnostic biomarkers but also offer novel targets for developing common therapeutic strategies for both conditions. Furthermore, quercetin emerges as a promising candidate for targeted treatment.

Humans↗

PubMed2026

Efficacy of pharmacological and microbiota-based therapies in preclinical models of autism spectrum disorder: a systematic review.

BACKGROUND: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition in which pharmacological and microbiota-targeted interventions are emerging as promising therapeutic avenues. Animal models are the main tool to investigate etiology, molecular mechanisms and screening for pharmacological therapies. Methodological differences, outcome measure variability, incomplete reporting, biological confounders, and overgeneralization of the results made evaluating innovative pharmacological agents challenging. These limitations in the field highlight a need for systematic and standardized research to reliably assess and translate pharmacological interventions from ASD animal models to human clinical relevance. SUBJECTS: This systematic review synthesized efficacy evidence for pharmacological and microbiota-based therapies across established ASD animal models. RESULTS: We identified 52 recent (2010-2025) studies that reported key ASD behavioral outcomes after pharmacological or microbiota-focused treatments. Interventions were grouped into therapeutic classes - including oxytocinergic agents, E/I balance therapeutic targets, metabolic drugs, cannabinoids, purine-based interventions and emerging targets - alongside microbiota-directed strategies such as probiotics, prebiotics, and fecal microbiota transplantation. By integrating effect directions and robustness across models, we identified most potential drug candidates, evaluated the efficacy of novel strategies, and recognized critical translational gaps. The reviewed studies demonstrate that ASD-like behavioral deficits in preclinical models can be modulated through interventions targeting diverse biological systems, including neurotransmission, neuroinflammation, metabolism, and the gut-brain axis. CONCLUSIONS: These findings support the multifactorial nature of ASD pathophysiology which arises from a network of interacting systemic processes rather than a single molecular defect. It could explain the limited success of traditionally narrowly targeted interventions and suggest a paradigm shift into a more systemic approach.

Animals↗

PubMed2026

PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.

BACKGROUND: The biology of the estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancers is heterogeneous even when they are categorized by their risk via genomics. Transcriptomic PGR expression reflects endocrine pathway activity and may provide complementary biological information within established GENE70-derived genomic-risk categories. Whether this molecular marker improves the biological interpretation of genomic-risk stratification beyond conventional clinicopathological assessment remains uncertain. OBJECTIVES: The aim of this study was to determine whether transcriptomic PGR expression provides complementary biological and prognostic information within reconstructed GENE70-derived genomic-risk categories and refines the characterization of endocrine-related tumour biology in ER-positive/HER2-negative breast cancer. METHODS: This study analysed publicly available transcriptomic and clinical data from three cohorts: METABRIC (discovery cohort), GSE96058/SCAN-B cohort (validation cohort) and TCGA-BRCA cohort (molecular validation cohort). The GENE70-derived genomic-risk score was reconstructed for each cohort using matched genes. Cox regression, Kaplan-Meier analysis and subgroup comparisons were used to assess relationships between PGR expression, clinicopathologic variables, molecular features and survival outcomes. RESULTS: Across the three independent cohorts, low transcriptomic PGR expression was consistently associated with higher GENE70-derived genomic risk, increased MKI67 expression, reduced ESR1 expression and enrichment of the Luminal B subtype. Survival findings differed between cohorts. In the discovery METABRIC cohort, transcriptomic PGR expression showed heterogeneous associations with survival, particularly within GENE70-derived high-risk subgroups, whereas the external GSE96058/SCAN-B validation cohort demonstrated consistent associations between low PGR expression and poorer overall survival in both the overall ER-positive/HER2-negative population and GENE70-derived high-risk subgroups. CONCLUSION: These findings suggest that transcriptomic PGR provides complementary biological and prognostic information within GENE70-derived genomic-risk categories. However, because treatment response was not evaluated in the present study, the findings should not be interpreted as evidence of predictive or pharmacogenomic utility and prospective studies incorporating treatment-response analyses are required before such applications can be established.

Humans↗

PubMed2026

Antibody-drug conjugates against multidrug-resistant cancers: Biomarker-guided patient selection, payload engineering, linker chemistry, and bystander effects.

Antibody-drug conjugates (ADCs) are one of the most significant advancements in modern cancer therapeutics. Combining the target selectivity of monoclonal antibodies with the cytotoxic potential of payloads, ADCs effectively kill cancer cells and offer hope to patients with even refractory cancer types. Beyond simply increasing the number of therapeutic options available for cancer patients, ADCs have become a powerful frontline agent in overcoming multidrug resistance (MDR). As one of the most challenging obstacles to effective cancer care, MDR is mediated by ATP-binding cassette (ABC) transporter-mediated drug efflux, target-based mutations, and dysregulated apoptosis. The clinical success of ADCs specifically engineered to overcome MDR, including in heterogeneous tumors and cancer cells that exhibit bypass signaling, is well established. This is especially evident with trastuzumab deruxtecan (T-DXd) in HER2-low, HER2-positive, and HER2-mutant cancers; sacituzumab govitecan (SG) in TROP2-expressing triple-negative breast cancer (TNBC) and urothelial carcinoma; and enfortumab vedotin in Nectin-4-positive bladder cancer. By overcoming MDR, ADCs have enabled more effective treatment algorithms across multiple malignancies. Most importantly, the clinical application of ADCs has become inextricably linked to cancer genomics. HER2 testing has evolved from a two-tiered system to a continuous spectrum including HER2-ultralow, HER2-low, HER2-positive, and ERBB2-mutant categories. Each of these categories exhibits different eligibility guidelines for ADC patient selection. As cancer cells continue to evolve and develop resistance to even ADCs through mutations and variants, researchers and clinicians have used pharmacogenomics to predict ADC response and resistance. To define the genomic architecture of ADC-resistant tumor subpopulations, single-cell transcriptomic studies and liquid biopsy approaches are being used to enable real-time examination of the tumor genome during ADC therapy, thereby optimizing treatment and circumventing resistance driven by emerging mutations and variants. This review provides a comprehensive analysis of the molecular structure of ADCs, the pharmacological principles underlying their potent cytotoxic activity against MDR cancer cells, the genomic and transcriptomic biomarkers that guide ADC patient selection, and the emerging resistance mechanisms that will shape the next generation of promising ADC development.

Humans↗

PubMed2026

Ifebemtinib plus garsorasib in previously treated metastatic colorectal cancer with KRASG12C mutation: a multicentre, randomised, phase 1b/2 trial.

BACKGROUND: Ifebemtinib is a potent oral focal adhesion kinase inhibitor. Preclinical evidence supports combining ifebemtinib with the KRASG12C inhibitor garsorasib. This study aimed to evaluate this combination in KRASG12C-mutated solid tumours. METHODS: This multicentre, phase 1b/2 study had a phase 1b component to establish the recommended phase 2 dose and a phase 2 multitumour expansion component. In phase 1b, the safety and tolerability of ifebemtinib combined with garsorasib was assessed using a 3 + 3 design in KRASG12C-mutated solid tumours. No dose-limiting toxic effects were observed, and the recommended phase 2 dose was established as ifebemtinib 100 mg orally once daily plus garsorasib 600 mg orally twice daily. Here, we report the results of the cohort of previously treated KRASG12C-mutated metastatic colorectal cancer from phase 2 expansion. Eligible patients (aged ≥18 years) who had histologically confirmed locally advanced or metastatic colorectal cancer harbouring the KRASG12C mutation, an Eastern Cooperative Oncology Group performance-status score of 0 or 1, and had disease progression after previous irinotecan-based or oxaliplatin-based combination therapy, were recruited from seven of nine participating tertiary hospitals in China. On the basis of the recommended phase 2 dose, phase 2 comprised a single-arm study to evaluate the safety and efficacy of ifebemtinib combined with garsorasib and an open-label, randomised study in which patients were randomly assigned (1:1) to receive ifebemtinib plus garsorasib or garsorasib alone, by use of centralised computer-generated block randomisation with no stratification. Investigators were masked to the block size. The primary efficacy endpoint of phase 2 was investigator-assessed objective response rate (Response Evaluation Criteria in Solid Tumours, version 1.1), assessed in the safety analysis set in the single-arm study and in all randomly assigned patients (intention-to-treat population) in the randomised study. At least six objective responses (safety analysis set) were required in the single-arm study to proceed to the randomised study. This study is registered with ClinicalTrials.gov, NCT06166836 and NCT05379946, and is active but not recruiting. FINDINGS: Between April 7, 2023 and Dec 13, 2024, 51 patients were enrolled in phase 2 (15 in the single-arm study and 36 in the randomised study). In the single-arm study, the median age was 53 years (IQR 39 to 63), nine (60%) patients were female, six (40%) were male, and all were Asian. In the randomised study, the median age was 51 years (IQR 42 to 59) in the combination group and 63 years (IQR 54 to 66) in the monotherapy group, 24 (67%) were female, 12 (33%) were male, and all patients were Asian. In the single-arm part, the confirmed objective response rate was 46·7% (95% CI 21·3 to 73·4). Seven patients had partial responses, triggering progression to the randomised study. In the randomised study, the confirmed objective response rate was 38·9% (95% CI 17·3 to 64·3) with the combination therapy versus 16·7% (95% CI 3·6 to 41·4) with garsorasib alone (between-group difference 22·2%, 95% CI -7·7 to 49·1; one-sided p=0·068). In the single-arm study, grade 3 treatment-related adverse events occurred in four (27%) of 15 patients, and in the randomised study, grade 3 treatment-related adverse events occurred in six (33%) of 18 patients in the combination group and five (28%) of 18 in the garsorasib group. Grade 3 treatment-related adverse events occurring in at least two patients were diarrhoea (six [18%]), proteinuria (two [6%]), and intestinal obstruction (two [6%]) in patients treated with combination therapy (combined), and increased alanine aminotransferase and γ-glutamyltransferase (two [11%] each) in patients treated with garsorasib alone. Serious adverse events occurred in ten (30%) patients in the combination group and in four (22%) patients in the monotherapy group. One patient in the garsorasib monotherapy group died due to the underlying malignancy within 30 days after completing study treatment, which was reported as a serious adverse event. The death was assessed by the investigators as not related to garsorasib. No grade 4 treatment-related adverse events or treatment-related deaths were reported across all cohorts. INTERPRETATION: The combination of ifebemtinib and garsorasib showed promising anticancer activity and manageable safety profile in previously treated patients with KRASG12C-mutated metastatic colorectal cancer. Although the improvement in response rate did not reach statistical significance in the randomised study, these findings support further evaluation of ifebemtinib plus garsorasib in this population. FUNDING: InxMed, InventisBio, National Natural Science Foundation of China, the Jian Bing Ling Yan + X Research and Development Program of Zhejiang Province, and the Zhejiang Province Medical and Health Science and Technology Plan Project.

Humans↗

PubMed2026

Manual, digital, and AI tumour-infiltrating lymphocyte scoring: a secondary analysis of the APHINITY randomised trial.

BACKGROUND: Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context of dual HER2 blockade remains undefined. We evaluated manual, digital, and artificial intelligence (AI)-based sTIL quantification, together with AI-derived spatial metrics, for prognostic and treatment-benefit stratification using tumour samples from the phase 3 APHINITY trial. METHODS: In the APHINITY trial, 4805 patients were randomly assigned to receive chemotherapy plus trastuzumab with pertuzumab or chemotherapy plus trastuzumab with placebo. Median follow-up was 74·1 months (IQR 68·3-75·4). We analysed 4262 haematoxylin and eosin-stained images using manual assessment, an automated digital approach, AI-based lymphocyte quantification (AI percentage lymphocytes), and two AI-derived spatial features (AI-TIL and immune hotspot). Interobserver reproducibility was assessed in 262 randomly chosen tumour samples scored independently by five pathologists. Multivariable Cox models were used to assess associations between TIL levels and invasive disease-free survival (primary outcome in APHINITY), distant recurrence-free interval, and overall survival. The heterogeneity of pertuzumab benefit was evaluated using subgroup analyses, subpopulation treatment effect pattern plot analyses, and nested Cox models with treatment-by-biomarker interaction terms. FINDINGS: Manual scoring showed high interobserver reproducibility (intraclass correlation coefficient 0·84 [95% CI 0·79-0·88]). Concordance between manual and automated methods was modest. AI-based scoring (AI percentage lymphocytes) reclassified 120 (11·6%) of 1035 node-positive tumours from immune-low (by manual scoring) to immune-high; this subgroup of patients showed greater separation of 5-year invasive disease-free survival curves between pertuzumab and placebo groups compared with patients whose tumours were concordantly classified as immune-low by both manual and AI-based approaches. Higher levels of TILs were associated with improved invasive disease-free survival for all sTIL measurement approaches and spatial measurements (hazard ratios [HRs] 0·41-0·93). Pertuzumab was associated with improved invasive disease-free survival at higher sTIL levels across all measurement approaches (HRs 0·36-0·48), but was not associated with higher values of spatial measures. The largest 6-year absolute improvements with pertuzumab were observed in patients with node-positive disease whose tumours scored in the highest level of immune infiltration of manual sTIL scoring (≥70·0%; mean absolute improvement 12·1 percentage points [SD 2·8]). In nested prognostic and predictive models, AI-based immune hotspot scores provided the most consistent additional information when combined with any sTIL measurement (all p<0·010). INTERPRETATION: Standardised manual sTIL scoring was reproducible, and digital and AI-based methods showed consistent prognostic stratification and potential for treatment-benefit stratification despite only modest correlation between platforms. AI spatial metrics provided complementary information beyond sTIL density and could support more scalable immune assessment. Future studies are needed to validate these approaches in independent cohorts and to clarify their clinical utility for stratifying contemporary HER2-directed therapies. FUNDING: None.

Humans↗

PubMed2026

Integrative machine learning and transcriptomic analysis reveals molecular mechanisms underlying low survival rate in larval Chinese Bahaba (Bahaba taipingensis).

Chinese Bahaba (Bahaba taipingensis) is a Class I protected marine fish endemic to China. Low larvae survival during artificial breeding severely hinder population recovery. To investigate the molecular mechanism of high mortality in larval fish, this study performed RNA-seq on liver from naturally deceased (ND) and mass-dead (MD) individuals, combined with least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms to screen for core signature genes. A total of 873 differentially expressed genes (DEGs) were identified, including 112 upregulated and 761 downregulated genes. GO and KEGG enrichment analyses revealed significant enrichment in amino acid metabolism disorders, one‑carbon folate pool impairment, PPAR signaling abnormalities, ECM-receptor interaction, focal adhesion pathway, indicating widespread metabolic suppression accompanied by extracellular matrix remodeling and signaling disturbances in the livers of MD fish. MAD pre-filtering combined with dual machine learning algorithms yielded 18 robust core signature genes, among which SLC38A4, MMP1, FADD, FKBP5, and APOB were consistently identified as high-frequency core genes by both algorithms. SLC38A4 exhibited the highest importance score in the RF model and was significantly downregulated, making it the primary molecule distinguishing ND from MD phenotypes. ROC curve analysis showed that both models achieved an AUC of 1.000 (95% CI lower bound: 0.610), confirming the precise discriminatory ability of the core genes. GSEA further demonstrated significant enrichment of this core gene set in ND samples. This study provides the first systematic elucidation of the molecular mechanisms underlying liver dysfunction in low survival rate B. taipingensis, characterized by amino acid transport impairment, metabolic reprogramming, and structural remodeling, offering theoretical foundations for health assessment, early mortality risk warning, and artificial breeding conservation of this species.

Animals↗

PubMed2026

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence↗

PubMed2026

"Abrazos, no Balazos": Intensity of Risk for Exposure to Violence and Armed Conflict Trajectories for Adolescents and Young Adults in México 2018-2024.

PURPOSE: "Abrazos, no balazos" (Hugs, not gunshots) is the approach to violence used by the Federal Mexican government from 2018 to 2024. This study identifies distinct conceptually useful latent class growth trajectories in the annual intensity of risk for exposure to events and fatalities from violence against civilians and battles for adolescents and young adults (AYAs) in México from 2018 to 2024. METHODS: Data are from the Armed Conflict Location and Event Data project. Latent class growth analyses were conducted with four longitudinal dependent variables assessed in seven sequential years (2018-2024). RESULTS: In most of the Mexican states, AYAs experienced low intensity-flat trajectories (p >.096) in the annual intensity of risk for exposure to events and fatalities from violence against civilians and battles. AYAs who lived in states with extremely, markedly, or moderately elevated 2018 intensities of risk for exposure to violence experienced decreasing trajectories (p =.000). One latent class with a mildly elevated-increasing trajectory (p =.000) in the annual intensity of risk for exposure to violence was identified for each of the four longitudinal dependent variables. DISCUSSION: During the time that the Federal Mexican government used the "Abrazos, no balazos" approach, AYAs in the majority of the states in México had intensity of risk for exposure to violence and armed conflict trajectories that were consistent with the goals of primary and secondary violence prevention. Violence prevention efforts should be augmented in states with unfavorable trajectories.

Humans↗

PubMed2026

Height variation independent of known genetic variants and health in later life: a cohort study.

BACKGROUND: Adult-attained height is associated with later-life health, but it reflects both genetic and nongenetic influences. The health implications of height variation not explained by known common height-associated genetic variants remain unclear. OBJECTIVES: This study aimed to examine associations of residual height (height variation independent of known genetic variants) with multiple disease incidence and all-cause mortality in later life. METHODS: In this cohort study of 407,366 adults of European ancestry (aged 40-70 y) in the United Kingdom Biobank (2006-2010), sex- and age-specific genetically predicted height was estimated from 9863 height-associated variants, adjusted for 30 principal components of ancestry. Residual height was calculated as the difference between observed and genetically predicted height. Plasma proteomics (2054 proteins; Olink Explore) were profiled. Deaths and 49 incident diseases were ascertained through national registries. Multivariable Cox models estimated associations of residual height and related proteins with disease incidence and mortality. RESULTS: Higher residual height [mean (standard deviation, SD), 0.0 (4.8)] was associated with more favorable self-reported preadulthood exposures (e.g., later birth years, no maternal smoking around birth, being breastfed as an infant, no adoption experience, and lower childhood adversity scores) and lower hazard ratios (HRs) of 32 out of 49 diseases (median follow-up = ∼12.5 y). Using participants with residual height within ±0.5 SDs from the mean as reference, those with residual height < -2 SDs had higher adjusted HRs of mortality [1.61; 95% confidence interval (CI): 1.50, 1.72], multimorbidity (1.28; 95% CI: 1.12, 1.46), cardiovascular disease (1.45; 95% CI: 1.32, 1.60), psychiatric/neurological disease (1.38; 95% CI: 1.28, 1.48), and other disease categories (e.g., diabetes, digestive, and musculoskeletal diseases). In contrast, higher genetically predicted height was associated with a higher incidence of 19 diseases, including subtypes of cancer, non-atherosclerotic cardiovascular diseases, and musculoskeletal diseases, as well as higher all-cause mortality. We identified 806 plasma proteins related to inflammation, immune response, and autophagy via tumor necrosis factor, Nuclear factor-kappa B, phosphoinositide-3 kinase/protein kinase B, and Janus kinase/signal transducer and activator of transcription signaling pathways, which were associated with residual height and multiple diseases and mortality. CONCLUSIONS: Higher residual height is associated with lower disease incidence and mortality, with associations that are distinct from those for genetically predicted height.

Humans↗

PubMed2026

Discovery of NAT-6-321056 as a novel modulator of VEGFR2 signaling to suppress tumor angiogenesis.

Vascular endothelial growth factor receptor 2 (VEGFR2) is a master regulator of angiogenesis and cancer progression. However, current VEGFR2 modulators face significant challenges, including off-target toxicity and acquired resistance, underscoring the urgent need for novel therapeutic agents with improved efficacy and safety profiles. Here, we reported that virtual screening of 39,442 natural products from the ZINC natural products-derived library, coupled with molecular docking and molecular dynamics (MD) simulations to evaluate the binding stability of candidate compounds, identified NAT-6-321056 as a highly promising modulator of VEGFR2 signaling. Biological evaluations demonstrated that NAT-6-321056 exerted potent inhibition on the growth of a broad spectrum of cancer cells, including both solid tumors and hematological malignancies. In EA.hy 926 endothelial cells and SK-N-DZ neuroblast cells, the compound significantly suppressed proliferation, migration, and invasion. Microscale thermophoresis (MST) confirmed direct binding of NAT-6-321056 to VEGFR2 with favorable affinity. Kinase profiling against a panel of 33 kinases indicated that NAT-6-321056 exhibited a multi-kinase modulation profile. Mechanistic studies revealed that NAT-6-321056 suppressed the expression of hypoxia-inducible factor 1-alpha (HIF-1α) and was associated with reduced VEGFR2 phosphorylation and attenuation of the downstream ERK/JNK/AKT signaling pathways. Moreover, NAT-6-321056 exhibited robust in vivo anti-angiogenic effects in both the chick chorioallantoic membrane (CAM) assay and transgenic zebrafish vascular fluorescence imaging models. Computational absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction suggested acceptable drug-like properties. Collectively, these findings demonstrated that NAT-6-321056 is a promising modulator of VEGFR2 signaling with potent anti-angiogenic activity and represents a viable candidate for cancer therapy.

Vascular Endothelial Growth Factor Receptor-2↗

PubMed2026

Genomic and One Health insights into Vibrio parahaemolyticus from environmental, seafood and clinical sources.

Vibrio parahaemolyticus is a leading cause of seafood-borne gastroenteritis worldwide, with climate warming facilitating its spread to high-latitude areas. In this study, we analyzed 212 genomes of environmental and seafood-associated isolates collected from seven cities in Zhejiang Province, China (2019-2024), alongside 228 clinical genomes from public databases. The 212 isolates were assigned to 172 sequence types (STs), with ST490 being the most frequent (5/212, 2.36%). Forty-four serotypes were identified, dominated by OL3:KUT (12.68%). High ST and serotype diversity were observed across different sample types and sources, with median pairwise single nucleotide polymorphisms (SNPs) ranging from 57,431 to 58,378, indicating comparable genetic diversity across groups. All isolates carried tlh and T3SS1 but lacked tdh and T3SS2. Resistance rates against ampicillin and cefazolin were 54.72% (116/212) and 44.34% (94/212), respectively, with multidrug resistance (MDR) detected in nine isolates, predominantly from seafood (7/9). A total of 63 distinct antimicrobial resistance genes (ARGs) spanning seven classes were identified. Isolates from aquaculture farms and wet markets exhibited greater resistance category diversity and higher ARG carriage than those from coastal or riverine sites. In contrast, the 228 clinical isolates harbored only 25 ARGs across two classes, with a significantly lower proportion of isolates carrying multiple ARG classes (0.44% vs. 6.13%, P < 0.001). Human isolates formed tighter phylogenetic clusters, although a minority were closely related to environmental/foodborne strains. Overall, our findings demonstrate the genetic diversity and resistance potential of V. parahaemolyticus across environmental, seafood, and clinical sources, highlighting the importance of the One Health approach to comprehensive public health risk assessment.

Vibrio parahaemolyticus↗

PubMed2026

Yoga MAT: A factorial randomized study using the Multiphase Optimization Strategy to develop a multicomponent yoga intervention for people with chronic pain taking medications for opioid use disorder.

BACKGROUND: People taking medications for opioid use disorder (MOUD) commonly experience chronic pain. Yoga interventions show promise for decreasing pain-related disability in other populations. More time spent in yoga practice may improve pain-related outcomes. METHODS: The Multiphase Optimization Strategy (MOST) provided the framework for developing an optimized yoga intervention package. In a 2x2x2x2 factorial experiment, we evaluated four candidate intervention components which, when added to a weekly yoga class, might increase yoga engagement. The primary outcome was minutes per week of yoga practice (classes and other yoga practice) over the 12-week intervention period. We sought to determine which combination of intervention components was associated with the most yoga practice for people with chronic pain taking buprenorphine or methadone as MOUD. RESULTS: We enrolled 192 adults. There was a significant main effect for Component "B" (having two private sessions with a yoga teachers; IRR = 1.10, 90%CI 1.02; 1.18), and a synergistic interaction between Components "B" and "D" (D was financial incentives for attending class; IRR = 1.11, 90%CI 1.02; 1.19). This combination of these two components (without other potential components) was associated with the second highest model-predicted mean minutes of yoga per week (157.1min; 90% CI = 120.1-194.0) which was only 4min less than the combination including all four components. CONCLUSIONS: We identified a combination of intervention components as the optimized intervention. A next step will be to test the effect of this optimized intervention on pain and substance use outcomes in a randomized controlled clinical trial.

Humans↗

PubMed2026

Molecular evaluation of residual disease following neoadjuvant chemotherapy in triple-negative breast cancer CALGB 40603 (Alliance).

BACKGROUNDDespite therapeutic advances in early-stage triple-negative breast cancer (TNBC), residual disease (RD) following neoadjuvant therapy remains a key predictor of a worse prognosis and obstacle to improving patient outcomes.METHODSTo better characterize RD and identify survival-associated features, we performed comprehensive transcriptomic profiling of 340 pretreatment stage II/III TNBCs and 70 matched posttreatment RD samples from the randomized CALGB 40603 (Alliance) phase II clinical trial. To explore preclinical treatment strategies for RD, patient-derived xenograft (PDX) mouse models mimicking RD were treated with antibody-drug conjugates (ADCs).RESULTSOur study shows prognostic genomic features measured pretreatment may differ from prognostic features measured posttreatment from RD specimens. Patients with a genomic PAM50 subtype of basal-like in RD specimens had a poor survival outcome, and their matching pretreatment tumors were characterized by elevated chromosomal amplifications of oncogenic drivers and significantly reduced B and T cell expression features. Paired analyses of basal-like RD and matched pretreatment tumors revealed further lymphocyte depletion in RD, along with lower expression of MHC class I and interferon signaling, indicating an immune-cold RD microenvironment. Treatment of a basal-like and conventional chemotherapy-resistant PDX model, resembling basal-like RD, with sacituzumab govitecan or trastuzumab deruxtecan produced a marked antitumor response.CONCLUSIONRD biology differs from pretreatment tumors, with basal-like subtype RD following neoadjuvant chemotherapy being immune cold and associated with poor survival. Preclinical modeling suggests this high-risk group may benefit from adjuvant ADC therapy.TRIAL REGISTRATIONClinicalTrials.gov NCT00861705.FUNDINGNIH NCI U10CA180821 (Alliance for Clinical Trials in Oncology), NCI U24CA176171 (Alliance for Clinical Trials in Oncology), NCI UG1CA233373 (Alliance for Clinical Trials in Oncology), NCI Breast SPORE program P50-CA058223; Susan G. Komen SAC-160074; Breast Cancer Research Foundation BCRF-23-127; NIH NCI R01-CA229409; UNC LCCC Triple Negative Breast Cancer Center.

Humans↗