Gastroenterology

BackgroundEndoscopic resection is the standard treatment for rectal neuroendocrine tumors (r-NETs) [&le;]10 mm, yet the optimal technique remains controversial. Modified endoscopic mucosal resection (m-EMR) has emerged as a potential alternative compared to endoscopic submucosal dissection (ESD), but existing evidence is largely retrospective and the results of recent randomized controlled trials (RCTs) are inconclusive. AimsTo compare the efficacy and safety of m-EMR versus ESD for r-NETs [&le;]10 mm. MethodsWe systematically searched CENTRAL, PubMed, Embase, and WanFang from January 1st, 1970 to December 23, 2025 for RCTs comparing m-EMR with ESD in r-NETs [&le;]10 mm. The GRADE framework assessed evidence certainty, while trial sequential analysis (TSA) controlled random errors and evaluated conclusion validity. ResultsSix RCTs involving 440 patients were analyzed. No significant difference between m-EMR and ESD was found in histologic complete resection (RR = 1.00, 95% CI 0.97-1.03; I2 = 0%), en bloc resection rates (P = 0.75) and procedure-related complications (P = 0.94). And m-EMR was associated with a significantly shorter procedure time (P<0.00001) and lower hospitalization cost (P<0.00001). The evidence was of moderate certainty; TSA confirmed its reliability, and both cumulative and sensitivity analyses supported the robustness. ConclusionsModerate-certainty evidence indicates m-EMR achieves oncologic outcomes comparable to ESD while offering clear advantages in procedural efficiency and cost for r-NETs [&le;]10 mm, supporting m-EMR possibly as a preferred endoscopic strategy in clinical practice.

PurposeHirschsprung-associated enterocolitis remains a major postoperative complication of Hirschsprungs disease (HD), and impaired epithelial barrier integrity has been proposed as a contributing factor. In this study, we investigated whether 12-hydroxyheptadecatrienoic acid (12-HHT), an endogenous leukotriene B4 receptor 2 (BLT-2) agonist, enhances the epithelial barrier and exerts anti-inflammatory effects in patient-derived colonic organoids. MethodsNormoganglionic specimens from rectal/rectosigmoid HD at pull-through (HD-N; n = 8) and transverse colon specimens from anorectal malformation (ARM) at colostomy closure (n = 10) were used to generate colonic organoids. Epithelia were isolated using ethylenediaminetetraacetic acid and subsequently embedded in Matrigel. Baseline expression of TJP1, TJP2, F11R (encoding junctional adhesion molecule-A), JAM2, CLDN1, CLDN3, CLDN4) and LTB4R2 (encoding BLT-2) was assessed by qPCR and immunoblotting. Organoids were then treated with 12-HHT (0.4, 2, or 10 M) for 7 days, followed by qPCR. Additional experiments assessed cytokine expression (IL1B, IL6) and TJPs after 24 h with tumor necrosis factor- (TNF-, 100 ng/mL) plus phosphate buffered saline or 12-HHT. Barrier function was evaluated using FITC-dextran influx assays. ResultsHD-N and ARM organoids exhibited similar growth efficiencies. Baseline expression for F11R, JAM2, CLDN1, CLDN3, CLDN4, and LTB4R2 was significantly lower in HD-N than in ARM. TJPs were upregulated by 12-HHT at 2 and 10 M in both groups, with stronger effects in ARM. In HD-N organoids, 10 M 12-HHT suppressed TNF--induced IL1B and IL6 elevation mitigated tight junction proteins (TJPs) downregulation more effectively than 2 M. 12-HHT attenuated TNF--induced FITC-dextran influx in HD-N organoids. Conclusion12-HHT may exert anti-inflammatory effects by integrating TJPs of HD-N.

Introduction Vonoprazan, a new oral potassium-competitive acid blocker (PCAB), has shown promise in terms of superior acid suppression when compared to Proton pump inhibitors (PPIs). We evaluated the efficacy of PCABs versus PPIs in preventing rebleeding in high-risk peptic ulcer patients after endoscopic hemostasis. Methods Following the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) guidelines, we conducted a comprehensive search for relevant studies across Medline, Embase, Web of Science, Cochrane Central Register of Controlled Trials and ClinicalTrials.gov, from inception till March 25, 2025. The primary outcome of interest was peptic ulcer rebleeding rate. Pooled risk ratios (RR) and mean difference (MD) with the corresponding 95% confidence intervals (CIs) were calculated. Results Three studies with 54,410 patients receiving endoscopic hemostasis for peptic ulcer bleeding were included in our analysis. The mean age of included participants was 71 years. There was no significant difference in rebleeding rates between patients receiving PPIs and PCABs (RR 0.827; 95 % CI: 0.5 to 1.3). We observed a significant reduction in length of hospital stay in the PCAB group when compared to the PPI group (MD: -0.44, 95% CI: -0.72 to -0.17), but no significant difference in all-cause mortality between both groups (RR: 0.90, 95% CI: 0.79 to 1.04). Conclusions Our study demonstrates comparable efficacy of PPIs and PCABs in preventing rebleeding in patients with high-risk peptic ulcers after successful endoscopic hemostasis. However, there was a significant reduction in hospital length of stay favoring PCABs. Keywords: Vonoprazan, Proton Pump inhibitors, peptic ulcer bleeding, Endoscopy

BackgroundCurrent British Society of Gastroenterology (BSG) guidelines misclassify metachronous lesion risk after polypectomy in approximately 40% of patients. Building on evidence that immune exclusion drives progression of adenomas to colorectal cancer, this study examined immune profiles in screen-detected adenomas as a predictive biomarker for metachronous lesion risk. MethodsPatients undergoing polypectomy within the Scottish Bowel Screening Programme, with surveillance colonoscopy between 6 months and 6 years were included. Chromogenic immunohistochemistry (IHC; n=2642), 6-plex multiplex immunofluorescence (mIF; n=334), and spatially resolved 6000-plex single cell transcriptomics (n=7) were applied to adenoma microarrays. Cell density and location were measured using QuPath. Hierarchical then K-means clustering was used to define immune cell density-based clusters, which were compared to future lesion events using Kaplan-Meier curves and the log rank test. ResultsAfter adjustment for age, sex, site, size and dysplasia, adenoma CD3+ T cell density was significantly associated with future colorectal neoplasia (HR 1.43, 95% CI 1.19-1.71, p<0.001). Using mIF three immune cell density clusters were identified; 1) high T cell density, low macrophage density, 2) low T cell density, low macrophage density, and 3) high T cell, macrophage and SMA density, with significant differences in future lesion risk (Cluster 1: 22%, Cluster 2: 41%, Cluster 3: 36%, p=0.032). Bulk RNAseq and spatial transcriptomic analysis revealed significant variation in T cell and macrophage co-location and gene expression profiles between clusters. ConclusionAdenoma immune contexture emerges as a determinant of future metachronous lesion risk, offering a novel biomarker to refine surveillance and reduce disease burden. SummaryWhat is already known on this topic: O_LIPost-polypectomy surveillance is currently recommended to patients with high-risk pathological features to detect metachronous lesions and cancer. However current guidelines misclassify risk in a proportion of patients, leading to unnecessary surveillance for some, whilst falsely reassuring others. C_LI What this study adds: O_LIAnalysis of this large post-polypectomy surveillance cohort reveals that adaptive immune responses within removed index adenomas predicts low risk of metachronous lesions, while an immune excluded phenotype signals higher risk, independent of pathological characteristics, and patient risk factors. C_LI How this study might affect research, practice or policy: O_LIDefining immune cell spatial distributions and interactions that drive future adenoma and cancer risk will enable more precise risk stratification for surveillance, informing surveillance guidelines and shaping targeted colorectal cancer prevention strategies. C_LI

BackgroundGestational exposures may contribute to the newborns lifetime risk of inflammatory bowel disease (IBD). While gestational influences are associated with IBD onset, the causality and confounding of such exposures are difficult to ascertain. The neonatal metabolome provides a metabolic snapshot of gestational influences. ObjectiveWe tested the neonatal metabolomes ability to predict future IBD, to assess whether gestational exposures are reflected in early molecular precursors of the disease. MethodsWe profiled dried blood spots from 520 newborns who later developed IBD and matched controls using high-resolution untargeted mass spectrometry metabolomics (1,350 QC-passing metabolites). Genotyping was available for 1,009 of these individuals. PERMANOVA confirmed assay sensitivity to gestational exposures, gradient boosting was used for prediction. ResultsThe neonatal metabolome significantly captured maternal smoking, birth weight, and gestational age (p < 0.001), but explained minimal variance in IBD status (R2 = 0.09%, p = 0.390) and showed no predictive power for IBD (AUC = 0.51, 95% CI 0.50-0.52, p = 0.585). Stratifying by disease subtype and age of onset did not improve performance. In contrast, genetic risk scores were modestly predictive (CD: AUC = 0.64, p < 5.11x10-14; UC: AUC = 0.63, p < 7.65x10-{superscript 1}{superscript 2}), but uncorrelated with neonatal metabolomic profiles (CD: p = 0.650; UC: p = 0.970), suggesting a later-age effect. ConclusionsUsing a large, comprehensively profiled cohort, we demonstrate that neonatal metabolomic profiles sensitively capture gestational signatures, but not the overall future IBD risk. Our findings suggest that most IBD risk accumulates later in life, beyond gestational molecular imprints.

Background and AimsCholedocholithiasis (CDL) is a common condition that can lead to serious complications, requiring effective risk stratification for timely intervention. While current guidelines use clinical predictors, imaging, and laboratory markers for risk assessment, the role of glutamate dehydrogenase (GLDH) in CDL remains poorly understood. This study aims to evaluate its potential as a clinical biomarker for identifying patients with CDL. MethodsThis single-center cohort study identified 23,103 patients who presented to the emergency department of the University Medical Center Hamburg-Eppendorf and underwent routine abdominal laboratory testing between May 2021 and December 2023. Patients were classified into CDL and other diagnoses. To assess the predictive value of age, sex and laboratory markers for CDL, we developed a random forest machine learning model, conducted a backward stepwise logistic regression and performed receiver operating characteristic (ROC) analysis. Results152 patients were diagnosed with CDL and 22,951 with other diagnoses. In the random forest machine learning model, GLDH emerged as the most significant feature for predicting CDL. ROC analysis revealed that GLDH had the highest area under the curve of 0.93 among laboratory markers. At the upper limit of normal, GLDH demonstrated the best sensitivity (92%) compared to aspartate aminotransferase (AST), alanine aminotransferase (ALT) and bilirubin. High GLDH levels exceeding 150 U/L demonstrate the highest specificity (99%) for CDL, outperforming AST, ALT and bilirubin. ConclusionGLDH outperforms AST, ALT and bilirubin as a screening and predictive marker for CDL, supporting its inclusion in clinical guidelines for risk stratification.

Background and aimsPopulation screening for liver disease in high-risk groups is recommended. Community diagnosis of liver disease is a challenge due to the asymptomatic nature of disease until very advanced stages. Moreover, regional variation in testing availability can result in people with clinically significant liver disease being missed. Machine learning (ML) has been proposed as a method to reduce diagnostic error and automate screening. We present a novel machine learning derived algorithm (ID LIVER-ML) designed to predict the risk of clinically significant liver disease in a high-risk community population to identify those needing further investigations or specialist referral. MethodsUsing data from 2039 patients recruited to two UK cohorts, we created a parsimonious model using investigations that would be available in primary care using liver stiffness measurement as reference standard. The performance of ID LIVER-ML was compared against FIB-4 score in a second unseen hold out cohort (n=327). ResultsID LIVER-ML performed well at identifying patients at risk of clinically significant liver fibrosis (sensitivity 0.90, Specificity 0.43, PPV 0.54, NPV 0.86, AUC 0.83) and outperformed conventional risk scoring systems (FIB-4: AUC 0.65; NAFLD Fibrosis Score: AUC 0.66; APRI: AUC 0.53; BARD: AUC 0.58). ConclusionMachine learning derived algorithms can help screen high risk populations in a community setting for liver fibrosis. ClinicalTrials.gov ID: NCT04666402 Impact and ImplicationsThe prevalence of steatotic liver disease is rising globally and is an increasingly significant challenge for healthcare systems. Existing risk stratification scores are not validated in a real-world cohort where patients have risk factors for multiple aetiologies of liver disease. Our work shows that a machine learning model can predict the risk of clinically significant liver disease using routine primary care data, better than existing non-invasive risk stratification tools in a real-world cohort. This highlights a potential role for machine learning in the automation of fibrosis risk assessment in primary care. Highlights- Machine learning derived algorithms can predict the risk of clinically significant liver disease in an at risk community population with a mixed aetiology of liver diseases. - The performance of the ML algorithm (ID LIVER-ML) is not affected by metabolic, alcohol, or mixed aetiologies. - ID LIVER-ML outperforms traditional risk stratification scoring systems such as FIB-4 and NAFLD fibrosis scores. - Compared to the FIB-4 score, the use of Machine Learning can reduce the need for secondary care investigations by 59%.

Background and AimsAvoidance of symptom-related situations is common in chronic gastrointestinal (GI) conditions, contributing to greater symptom severity, psychological distress, and reduced quality of life. However, no validated measure exists to comprehensively assess GI-specific avoidance. We developed and validated the GI-specific Avoidance Scale (GIAS), a self-report instrument measuring behavioral and cognitive avoidance specific to GI symptoms. MethodsFollowing literature review and multidisciplinary input, an initial pool of 58 items was generated and refined through expert and patient ratings, yielding 37 items. A sample of 102 adults (mean age 40.8 years) with medically diagnosed GI conditions completed the GIAS and validated measures of avoidance, psychological flexibility, illness shame, GI symptoms, distress, and quality of life. Exploratory factor analysis was used to determine factor structure. Internal consistency, convergent validity, incremental validity, and mediation analyses were conducted. ResultsFactor analysis supported a 20-item, three-factor solution: General Avoidance, Food Avoidance, and Intimacy/Body Exposure Avoidance. Internal consistency was excellent for the total scale ( = .94) and good-to-excellent for subscales ( = .82-.94). GIAS scores correlated positively with illness shame, GI symptoms, and distress, and negatively with psychological flexibility, self-compassion, and quality of life. GIAS showed incremental validity over a general illness avoidance measure (IBAS) in predicting GI symptoms and anxiety. Moreover, mediation models suggested that GI-specific avoidance partially mediates bidirectional associations between GI symptoms and psychological distress. ConclusionsThe GIAS is a novel, psychometrically robust, and multidimensional self-report questionnaire of GI-specific avoidance. It holds potential for clinical assessment, treatment planning, and evaluation of intervention mechanisms in GI populations.

BackgroundComprehensive data on the prevalence of Helicobacter pylori infection and its associated risk factors among patients with gastrointestinal symptoms remain limited. Generating this evidence would help inform clinical management and improve antibiotic stewardship. H. pylori infection affects a substantial proportion of the global population, with prevalence varying widely across regions. In Uganda, previous studies have documented the presence of H. pylori infection. However, data specific to symptomatic patients are scarce. This study therefore aimed to determine the prevalence of H. pylori infection and associated factors among patients with gastrointestinal symptoms attending Mulago National Referral Hospital in Kampala, Uganda. MethodsA cross-sectional study was conducted among 353 patients with gastrointestinal symptoms attending Mulago Hospital. Data on socio-demographic characteristics, lifestyle and dietary habits, and medical history were collected using a semi-structured questionnaire. H. pylori infection status was determined using stool antigen tests. Proportions were used to determine the prevalence of H. pylori, and associated factors analyzed using STATA version 14 software by performing bivariate and multivariate analyses. ResultsAmong the 353 participants, majority were between 16 and 25 years old (69%), female (58%), and residing in peri-urban areas (74%). The prevalence of H. pylori infection in this population was 308 (87.3%). Multivariate analysis showed that H. pylori infection was significantly associated with having more than five income dependents (aPRR = 1.104, 95% CI: 1.025-1.189, p = 0.008), a history of previous H. pylori treatment (aPRR = 3.459, 95% CI: 2.138-5.595, p < 0.001), and a family history of H. pylori infection or gastrointestinal ulcers (aPRR = 1.135, 95% CI: 1.055-1.221, p = 0.001). ConclusionThis study demonstrated a high prevalence of Helicobacter pylori infection among patients presenting with gastrointestinal symptoms, with nearly nine out of ten individuals testing positive. The high burden observed suggests that routine screening for H. pylori, or carefully guided empirical treatment, may be clinically justified in symptomatic patients. These findings underscore the need for integrated clinical and public health strategies to improve diagnosis, treatment, and prevention of H. pylori infection in this setting.

Background and AimMASLD affects 30-38% of Indian adults, yet the contribution of genetic risk variants to disease susceptibility and fibrosis progression remains poorly characterised. We investigated the association of 12 candidate SNPs with MASLD susceptibility and fibrosis severity in North Indian patients, benchmarking allele frequencies against IndiGenomes and global populations. MethodsSixty-nine MASLD patients (75.4% male; median BMI 29.8 kg/m{superscript 2}) from a tertiary care liver clinic in New Delhi were genotyped for 12 SNPs using Illumina custom BeadChip array and Sanger sequencing. Patients were stratified by liver stiffness measurement (LSM): significant fibrosis ([&ge;]8 kPa, n=38) versus no significant fibrosis (<8 kPa, n=31). Allele frequencies were compared with IndiGenomes ([~]1,020 Indian individuals) and 1000 Genomes populations. ResultsPNPLA3 rs738409 G allele was the strongest within-cohort predictor of significant fibrosis (allelic OR 2.89, 95% CI 1.35-6.19, P=0.006; dominant model OR 3.94, P=0.008), with carriers demonstrating higher LSM (median 15.6 vs. 7.5 kPa, P=0.005). SAMM50 rs3761472 (OR 2.12, P=0.065) and FTO rs9939609 (OR 2.08, P=0.089) showed non-significant trends. In the population-level comparison, APOC3 rs2854116 T allele was the only variant significantly enriched after Bonferroni correction (64.0% vs. 47.9%; OR 1.93, 95% CI 1.35-2.77, P<0.001), followed by PNPLA3 (33.3% vs. 24.1%, OR 1.57, P=0.019) and SAMM50 (31.2% vs. 22.6%, OR 1.55, P=0.028). Notably, APOC3 showed no association with fibrosis (OR 0.96, P=1.000), suggesting a role in susceptibility rather than progression. All SNPs were in Hardy-Weinberg equilibrium. ConclusionsThis study reveals a dissociation between genetic determinants of MASLD susceptibility and fibrosis progression in North Indian patients. APOC3 rs2854116 predisposes to MASLD at the population level, while PNPLA3 rs738409 drives fibrosis severity within established disease, underscoring the need for ancestry-specific genetic risk stratification. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/26347059v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@187f189org.highwire.dtl.DTLVardef@25d3borg.highwire.dtl.DTLVardef@13704e9org.highwire.dtl.DTLVardef@1238cce_HPS_FORMAT_FIGEXP M_FIG C_FIG

This study aimed to evaluate the prognostic value of quantitative analysis of {superscript 1}F-FDG positron emission tomography (PET)/computed tomography (CT) metabolic parameters in patients with pancreatic ductal adenocarcinoma (PDAC) after neoadjuvant chemotherapy (NACT). A retrospective analysis was conducted on the clinical and imaging data of 44 patients with pathologically confirmed PDAC who received NACT. All patients completed standard chemotherapy regimens and underwent {superscript 1}F-FDG PET/CT examinations within 2 weeks before and after chemotherapy. Multiple metabolic parameters of lesions were extracted, their percentage changes were calculated, and the optimal cut-off values for each parameter were determined. Kaplan-Meier survival analysis and Cox proportional hazards regression analysis were applied to explore the prognostic value of the metabolic parameters, and the prognostic stratification performance of PET Response Criteria in Solid Tumors (PERCIST) 1.0 was compared with that of Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. PERCIST 1.0 demonstrated significantly superior prognostic stratification compared with RECIST 1.1. A peak standardized uptake value corrected for lean body mass (SULpeak2) > 3.07 and a percentage change in SULpeak between pre- and post-treatment scans ({Delta}SULpeak%) [&le;] 37.66% were identified as independent risk factors for poor prognosis. Furthermore, SUL-related parameters exhibited markedly better predictive efficacy than traditional metabolic parameters such as the standardized uptake value and metabolic tumor volume. Quantitative analysis of {superscript 1}F-FDG PET/CT metabolic parameters can effectively predict prognosis in PDAC after NACT, and PERCIST 1.0 is a more optimal criterion for efficacy and prognostic assessment. A post-NACT SULpeak > 3.07 and {Delta}SULpeak% [&le;] 37.66% were core independent indicators for predicting poor prognosis in these patients.

ObjectivesTo characterize ultra-processed food (UPF) circulating metabolic signatures associated with Crohns disease (CD) and to localize key metabolic mediators linking UPF intake to CD risk. DesignProspective cohort study. SettingTwo large multi-center cohorts (UK Biobank [UKB] and Whitehall II [WHII] study) across the UK and an Eastern multi-center cohort ONE-IBD Study from China. ParticipantsUK Biobank discovery cohort (n=10,229) for signature derivation, internal validation cohort (n=91,306), external validation cohort Whitehall-II (n=7,893), and three additional cohorts (two Western and ONE-IBD) for validation of key metabolic drivers. Main outcome measuresPrimary outcomes were UPF-related circulating metabolic signatures and their associations with CD risk; secondary outcomes included evidence supporting causal roles of candidate metabolites and genetic pathways assessed by Mendelian randomization, colocalization, and gene-environment analysis. ResultsA UPF metabolic signature of 73 metabolites was constructed and validated across cohorts (Spearman {rho}: 0.20-0.25). More pronounced UPF metabolic signature was associated with increased CD risk (HRper SD=2.65, 95% CI 1.57-4.48). WGCNA revealed a cluster enriched in fatty acids. Within this cluster, docosahexaenoic acid (DHA) emerged as the strongest, which mediated 17.1% of the UPF-CD association. External validation in ONE-IBD supported DHA as the strongest associated metabolite with UPF and CD. Mendelian randomization supported a causal protective effect of DHA on CD (OR=0.72, 95% CI 0.61- 0.83; P<0.001), with colocalization implicating rs174546 in the FADS1 gene. ConclusionThe adverse effects of UPF on CD risk may be driven by a relative deficiency of protective metabolites such as DHA, apart from additive harm to metabolic depletion. This reframes UPF-related risk and highlighting potential targets for precision nutrition in CD prevention.

ObjectiveAs cannabis use has increased in the United States, so has cannabinoid hyperemesis syndrome (CHS), a disorder characterized by severe nausea, vomiting, and abdominal pain among heavy cannabis users. We previously showed that CHS symptoms are associated with several behavioral and psychological characteristics linked to psychosocial impairment. We examined links between CHS symptoms and suicidal thoughts, behaviors, and proximal suicide risk factors. MethodsWe used data from the National Firearms, Alcohol, Cannabis, and Suicide survey, a nationally representative survey of 7,034 US adults. Items assessed symptoms of CHS and suicidal thoughts and behaviors. Comparisons focused on: those with daily cannabis use and CHS symptoms (n = 191), those with daily cannabis use without CHS symptoms (n = 882), those with past year cannabis use but not daily use (n = 1288), and those without past year cannabis use (n = 4673). ResultsThose with CHS symptoms reported the highest prevalence of suicidal thoughts and behaviors with most lifetime rates being significantly higher than those with daily cannabis use without CHS symptoms. Those with CHS symptoms also reported higher mean-levels of thoughts and feelings associated with suicide (i.e., perceived burdensomeness, thwarted belongingness, defeat, entrapment) than all the other groups. ConclusionsThose with CHS symptoms reported especially high rates of suicidal thoughts, behaviors, and attempts even when compared to others with daily cannabis use. People with CHS symptoms appear to be at high risk of suicide, possibly related to distress from their gastrointestinal symptoms and psychiatric, substance use, and medical comorbidities.

Background Short-chain fatty acids (SCFAs) are widely used as functional readouts of gut microbial activity in vivo. The growing adoption of decentralised study designs and self-collection protocols has amplified the need for reliable room-temperature storage and shipment strategies. However, SCFAs volatility and the persistence of post-collection microbial metabolism raise concerns regarding pre-analytical stability and the interpretability of measured concentrations. Methods We assessed the temporal stability of fatty acids (FAs) across intestinal and systemic matrices under room-temperature storage. Untreated stool was compared with two nucleic acid stabilisation devices (eNAT and OMNIgene-GUT), while whole blood, plasma and dried blood spots (DBS) were evaluated as minimally invasive systemic sampling strategies. Profiles were quantified using complementary GC-MS and LC-MS/MS workflows. Results Untreated stool showed fermentation-driven increases in major SCFAs, whereas immediate freezing preserved baseline profiles. eNAT maintained faecal FA stability for up to 21 days, while OMNIgene-GUT exhibited baseline and time-dependent alterations. In systemic matrices, plasma and whole blood showed upward drift, whereas DBS declined initially before stabilising after approximately 14 days. Conclusions FA measurements are highly matrix- and device-dependent. Our findings provide practical guidance for the selection of sampling strategies in microbiome-associated FA studies and emphasise the need for controlled pre-analytical conditions in decentralised microbiome studies.

Accurate polyp segmentation from colonoscopy images is critical for colorectal cancer prevention, yet the generalization of deep learning models under domain shift remains insufficiently explored. We propose Boundary-Explicit Guided Attention U-Net (BEGA-UNet), a boundary-aware segmentation architecture that introduces explicit edge modeling as a structural inductive bias to enhance both segmentation accuracy and cross-domain robustness. The framework integrates three components: an Edge-Guided Module (EGM) with learnable Sobel-initialized operators to capture boundary cues, a Dual-Path Attention (DPA) module that processes channel and spatial attention in parallel, and a Multi-Scale Feature Aggregation (MSFA) module to encode contextual information across multiple receptive fields. Evaluated on the combined Kvasir-SEG and CVC-ClinicDB benchmarks, BEGA-UNet achieves 88.53% Dice and 82.51% IoU, outperforming representative convolutional and transformer-based baselines. More importantly, cross-dataset evaluation demonstrates strong robustness under domain shift, with BEGA-UNet retaining 83.2% of its in-distribution performance-substantially higher than U-Net (64.5%), Attention U-Net (47.5%), and TransUNet (53.1%). In a zero-shot setting on an entirely unseen dataset, the model further maintains 72.6% performance retention. Comprehensive ablation studies indicate that explicit boundary modeling plays a central role in improving generalization, while multi-scale context aggregation further stabilizes performance across domains. Feature distribution analyses support this observation by showing that edge-oriented representations exhibit markedly reduced cross-domain variability compared to appearance-driven features. Overall, BEGA-UNet provides an effective and interpretable solution for robust polyp segmentation, demonstrating that explicit boundary modeling serves as a critical inductive bias for ensuring reliability under clinical domain shifts.

PurposePortal hypertension, a major complication of chronic liver disease, leads to significant morbidity and mortality. While portal vein diameter measured on imaging has long been proposed as a non-invasive marker of portal hypertension, normative CT-based reference values and population-level associations remain incompletely characterized. Here, we aim to define contemporary reference values for portal vein diameter on clinically obtained CT and evaluate its associations with demographic, clinical, and imaging factors, as well as its diagnostic performance for portal hypertension. MethodsWe conducted a retrospective analysis of 20,225 clinically obtained CT scans at a single academic medical center. The main portal vein was automatically segmented using Total Segmentator, and maximum diameter extracted using the Vascular Modeling Toolkit. Associations with demographic and imaging factors were evaluated using linear mixed-effects models; prevalent liver disease and portal hypertension using logistic regression; risk of incident ascites and esophageal varices among participants with liver disease using Cox regression; and invasive hepatic venous pressures using correlation analysis and linear regression. ResultsThe mean portal vein diameter was 12.4 mm (95% CI, 12.37-12.45). Larger diameter was independently associated with male sex (+1.4 mm), higher BMI (+0.11 mm/kg/m2), greater height (+0.04 mm/cm), and older age (+0.05 mm/10 years) (all p <0.001), and was substantially larger on contrast-enhanced abdomen/pelvis CT (+2.4 mm, p <0.001). Each 1-mm increase in portal vein diameter was associated with higher odds of prevalent liver disease (OR 1.06; 95% CI, 1.04-1.08) and portal hypertension (OR 1.18; 95% CI, 1.12-1.28). Among individuals with liver disease, greater diameter predicted higher risk of incident esophageal varices (baseline diameter HR 1.50; 95% CI, 1.14-2.08) and ascites (HR per mm increase in diameter 1.06; 95% CI, 1.003-1.12). However, portal vein diameter demonstrated weak to no association with invasively measured hepatic venous pressures. ConclusionIn this large, EHR-linked imaging cohort, the mean portal vein diameter on CT was 12.4 mm and varied with demographic and imaging factors. Larger diameter was associated with liver disease, portal hypertension, and subsequent development of varices and ascites, supporting use of portal vein diameter as a pragmatic screening or enrichment tool within multimodal clinical frameworks. Key ResultsO_LIMean portal vein diameter on routine clinical CT was 12.4 mm (95% CI, 12.37-12.45) and varied with sex, height, BMI, exam type, contrast use, and clinical setting. C_LIO_LIEach 1-mm increase in portal vein diameter was associated with higher odds of prevalent liver disease (OR 1.06) and portal hypertension (OR 1.18). C_LIO_LIAmong individuals with liver disease, larger portal vein diameter predicted higher risk of incident esophageal varices and ascites, independent of demographic and imaging factors. C_LI

Amatoxin-induced acute liver failure complicates misidentified foraged mushroom ingestion worldwide; abrupt multisystem collapse punctuates apparent improvement. Our prospective single-arm clinical trial investigated proactive toxicokinetic-based management to preserve elimination capacity: sustained enhanced hydration to maintain renal clearance; fasting plus octreotide to suppress meal-driven enterohepatic circulation; and intravenous silibinin to inhibit OATP1B3-mediated hepatic uptake, enabling safe passage and elimination of gallbladder-confined amatoxin-laden bile. Safety population (N=99) transplant-free recovery (TFR): 88.0% (87 recoveries, 6 transplants, 6 deaths). Protocol-adherent Efficacy population (n=86) TFR: 98.8% (85 recoveries, 1 transplant, 0 deaths). Multivariable analysis identified uninterrupted hydration as strongest TFR predictor (P<0.001), followed by earlier silibinin initiation (P=0.003); octreotide shortened INR recovery by 11 hours (P=0.033). These findings support a toxin elimination model in which preserved renal clearance and biliary sequestration are central recovery determinants. The kinetic balance between renal clearance and hepatic uptake governs both recovery and collapse.

BackgroundCannabinoid hyperemesis syndrome (CHS) is characterized by episodes of severe nausea, vomiting, and abdominal pain among those with heavy cannabis use. We estimated differences between those reporting CHS symptoms and other daily and less frequent cannabis users on drug use, psychiatric problems, other health problems, antisocial behavior, and personality. MethodsThe National Firearms, Alcohol, Cannabis, and Suicide survey was administered to 7034 US adults in 2025. Survey items assessed substance use, common psychiatric symptoms, personality traits, and symptoms of CHS. ResultsThose with CHS symptoms reported the highest rates and greatest variety of drug use compared to others who used cannabis. Those with CHS symptoms reported higher rates of other drug use than those who used cannabis daily without CHS symptoms across a variety of drug classes, including opioids, hallucinogens, and sedatives, higher rates of drug overdoses, and greater use of all drug classes than those with less-than-daily cannabis use. Those with CHS symptoms also reported more depression, anxiety, sleep problems, chronic pain, antisocial behavior, intimate partner violence, and disinhibited personality traits than those who used daily (mean d = 0.58) and less frequently (mean d = 0.69) and those with no cannabis use in the past 12 months (mean d = 0.99). ConclusionsThose with CHS symptoms exhibit a variety of psychological and behavioral problems including higher rates of other drug use, psychiatric symptoms, antisocial behavior, and dysfunctional personality traits. Results highlight the importance of understanding and addressing the broader psychosocial challenges faced by people experiencing CHS symptoms. Highlights O_LICHS symptoms are linked to greater polysubstance use and overdose risk C_LIO_LICHS symptoms are associated with depression, anxiety, sleep, and pain problems C_LIO_LICHS tied to antisocial behavior and intimate partner violence C_LIO_LICHS shows disinhibited personality traits and low well-being C_LIO_LINational survey identifies high-risk psychosocial CHS profile C_LI

Background and ObjectiveThe dysbiosis of human gut microbiome has been increasingly seen to have a relation in the development of autoimmune diseases, with specific microbial signatures having causative association with specific conditions. Inflammatory bowel disease (IBD) is one such autoimmune ailment. This paper proposes a predictive tool that can identify the IBD status of an individual based on the composition of the gut microbiome using machine learning and AI agents driven techniques. The technology can strengthen the suspicion of a potential IBD diagnosis a patient may have based on their gut microbiome profile. MethodsThe tool processes patient gut metagenome using integrated Kneaddata and MetaPhlAn to generate taxonomic profiles. These are fed into an XGBoost classifier to predict IBD or healthy status. Dysbiotic taxa are identified via Z-score and fold change. CrewAI delivers personalized probiotic recommendations based on diagnosis and dysbiosis. ResultsThe tuned XGBoost model achieved 86.6% accuracy. On validation using single ulcerative colitis sample, the tool correctly predicted IBD status but misclassified it as Crohns disease(possibly due to overlapping microbial signatures), identifying Faecalibacterium and Flavonifractor as dysbiotic taxa.The probiotic recommended was Faecalibacterium prausnitzii, backed with reasoning basedon scientific literature. ConclusionsDespite limited validation sample size, the high accuracy, correct IBD detection, dysbiosis analysis and elaborate probiotic recommendation suggest promising potential; further validation needed

BackgroundHistologic descriptors such as lymphovascular invasion (LVI), visceral pleural invasion (VPI), spread through air spaces (STAS), and grading system have each been associated with adverse outcomes in lung adenocarcinoma (LUAD). However, with the exception of VPI, these features are not formally incorporated into the TNM staging system. We evaluated the prognostic value and incremental contribution of these histologic descriptors within the framework of the 9th edition TNM staging system. MethodsIn total, 1,745 individuals diagnosed with stage I-III invasive non-mucinous lung adenocarcinoma (NM-LUAD) were included in this study, comprising 1139 French-Canadian patients who underwent surgical resection at IUCPQ-Universite Laval (discovery cohort) and 606 patients from the National Cancer Center Hospital in Tokyo, Japan (validation cohort). The objective of this study was to assess the prognostic contribution of histologic descriptors, including STAS, and LVI, as complements to conventional 9th edition TNM staging. ResultsGrade 3 tumors, LVI, and STAS were identified in 880 (50.4%), 809 (46.4%), and 775 (44.4%) of 1745 cases, respectively. Histologic grade and LVI demonstrated the strongest associations, particularly in early-stage disease, while STAS exhibited a stage-dependent effect, being more impactful in stages II-III. VPI showed less consistent prognostic value. Incorporating these histologic descriptors into TNM staging improved prognostic model performance, with the largest gains driven by histologic grade and LVI, while STAS provided additional, complementary prognostic refinement. ConclusionThese findings demonstrate that key histologic descriptors--including grading system, LVI, and STAS--represent robust and reproducible prognostic parameters. Importantly, these descriptors provide complementary, stage-dependent information that may enhance risk stratification and inform refinement of future TNM staging frameworks, including the forthcoming 10th edition.