Intestinal fibrosis, a severe complication of Crohn’s disease (CD), is characterized by excessive extracellular matrix (ECM) deposition and induces intestinal strictures, but there are no effective antifibrosis drugs available for clinical application. We performed single-cell RNA sequencing (scRNA-Seq) of fibrotic and nonfibrotic ileal tissues from patients with CD with intestinal obstruction. Analysis revealed mesenchymal stromal cells (MSCs) as the major producers of ECM and the increased infiltration of its subset FAP ⁺ fibroblasts in fibrotic sites, which was confirmed by immunofluorescence and flow cytometry. Single-cell transcriptomic profiling of chronic dextran sulfate sodium salt murine colitis model revealed that CD81 ⁺ Pi16 ^– fibroblasts exhibited transcriptomic and functional similarities to human FAP ⁺ fibroblasts. Consistently, FAP ⁺ fibroblasts were identified as the key subtype with the highest level of ECM production in fibrotic intestines. Furthermore, specific knockout or pharmacological inhibition of TWIST1, which was highly expressed by FAP ⁺ fibroblasts, could significantly ameliorate fibrosis in mice. In addition, TWIST1 expression was induced by CXCL9 ⁺ macrophages enriched in fibrotic tissues via IL-1β and TGF-β signal. These findings suggest the inhibition of TWIST1 as a promising strategy for CD fibrosis treatment.

Background: A number of recent observational studies have indicated a correlation between the constitution of gut microbiota and the incidence of pancreatitis. Notwithstanding, observational studies are unreliable for inferring causality because of their susceptibility to confounding, bias, and reverse causality, the causal relationship between specific gut microbiota and pancreatitis is still unclear. Therefore, our study aimed to investigate the causal relationship between gut microbiota and four types of pancreatitis.Methods: An investigative undertaking encompassing a genome-wide association study (GWAS) comprising 18,340 participants was undertaken with the aim of discerning genetic instrumental variables that exhibit associations with gut microbiota, The aggregated statistical data pertaining to acute pancreatitis (AP), alcohol-induced AP (AAP), chronic pancreatitis (CP), and alcohol-induced CP (ACP) were acquired from the FinnGen Consortium. The two-sample bidirectional Mendelian randomization (MR) approach was utilized. Utilizing the Inverse-Variance Weighted (IVW) technique as the cornerstone of our primary analysis. The Bonferroni analysis was used to correct for multiple testing, In addition, a number of sensitivity analysis methodologies, comprising the MR-Egger intercept test, the Cochran’s Q test, MR polymorphism residual and outlier (MR-PRESSO) test, and the leave-one-out test, were performed to evaluate the robustness of our findings.Results: A total of 28 intestinal microflora were ascertained to exhibit significant associations with diverse outcomes of pancreatitis. Among them, Class Melainabacteria (OR = 1.801, 95% CI: 1.288–2.519, p = 0.008) has a strong causality with ACP after the Bonferroni-corrected test, in order to assess potential reverse causation effects, we used four types of pancreatitis as the exposure variable and scrutinized its impact on gut microbiota as the outcome variable, this analysis revealed associations between pancreatitis and 30 distinct types of gut microflora. The implementation of Cochran’s Q test revealed a lack of substantial heterogeneity among the various single nucleotide polymorphisms (SNP).Conclusion: Our first systematic Mendelian randomization analysis provides evidence that multiple gut microbiota taxa may be causally associated with four types of pancreatitis disease. This discovery may contribute significant biomarkers conducive to the preliminary, non-invasive identification of Pancreatitis. Additionally, it could present viable targets for potential therapeutic interventions in the disease’s treatment.

Although the oral administration of Bifidobacterium longum (B. longum) relieves the signs of irritable bowel syndrome (IBS) in clinical settings, the mechanisms underlying its effects are unclear. In this study, we evaluated the precise effects of B. longum on IBS via regulation of Paneth cell function. We confirmed the beneficial effects of B. longum on defecation habits and visceral hypersensitivity in WAS rats. Further analysis revealed that B. longum enhanced mucosal repair, promoted lysozyme production, and ameliorated dysbiosis of the microbiota in WAS rats. These processes are closely correlated with Paneth cell functions. In vitro, we incubated primary cultured enteroids with B. longum and found that B. longum promoted the proliferation of these organoids; this may be attributed to the upregulation of the stem niche factors WNT3A and TGF-β, which are secreted by Paneth cells. Based on our findings, we propose that B. longum relieves IBS by restoring the antimicrobial activity and stem niche maintenance function of Paneth cells.

Background: Endoscopic ultrasonography (EUS) is recommended as the best tool for evaluating gastric subepithelial lesions (SELs); nonetheless, it has difficulty distinguishing gastrointestinal stromal tumors (GISTs) from leiomyomas and schwannomas. GISTs have malignant potential, whereas leiomyomas and schwannomas are considered benign.Purpose: This study aimed to establish a combined radiomic model based on EUS images for distinguishing GISTs from leiomyomas and schwannomas in the stomach.Methods: EUS images of pathologically confirmed GISTs, leiomyomas, and schwannomas were collected from five centers. Gastric SELs were divided into training and testing datasets based on random split‐sample method (7:3). Radiomic features were extracted from the tumor and muscularis propria regions. Principal component analysis, least absolute shrinkage, and selection operator were used for feature selection. Support vector machine was used to construct radiomic models. Two radiomic models were built: the conventional radiomic model included tumor features alone, whereas the combined radiomic model incorporated features from the tumor and muscularis propria regions.Results: A total of 3933 EUS images from 485 cases were included. For the differential diagnosis of GISTs from leiomyomas and schwannomas, the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve were 74.5%, 72.2%, 78.7%, and 0.754, respectively, for the EUS experts; 76.8%, 74.4%, 81.0%, and 0.830, respectively, for the conventional radiomic model; and 90.9%, 91.0%, 90.6%, and 0.953, respectively, for the combined radiomic model. For gastric SELs <20 mm, the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve of the combined radiomic model were 91.4%, 91.6%, 91.1%, and 0.960, respectively.Conclusions: We developed and validated a combined radiomic model to distinguish gastric GISTs from leiomyomas and schwannomas. The combined radiomic model showed better diagnostic performance than the conventional radiomic model and could assist EUS experts in non‐invasively diagnosing gastric SELs, particularly gastric SELs <20 mm.

Background and Objectives: A majority of pancreatic malignancies are unresectable at the time of presentation and require EUS–guided fine-needle aspiration or fine-needle biopsy (EUS-FNA/FNB) for diagnosis. With the advent of precision therapy, there is an increasing need to use EUS-FNA/FNB sample for genetic analysis. Next-generation sequencing (NGS) is a preferred technology to detect genetic mutations with high sensitivity in small specimens. We performed a meta-analysis to evaluate the adequacy of EUS-FNA/FNB for NGS in pancreatic malignancies. Methods: PubMed, Embase, Cochrane Library, and Web of Science were searched from database inception to November 11, 2023. The primary outcome was the proportion of sufficient sample acquired by EUS-FNA/FNB in pancreatic malignancies for NGS. Secondary outcomes were the proportion of sufficient sample for NGS in pancreatic ductal adenocarcinoma (PDAC) and the detection rates of mutations in KRAS, TP53, CDKN2A, and SMAD4 and actionable mutations in PDAC. The pooled proportions were calculated using a random-effects model. Potential sources of heterogeneity were investigated with subgroup analyses and meta-regression. Results: Twenty studies with 881 samples were included. The pooled adequacy of EUS-FNA/FNB sample for NGS was 89.9% (95% CI, 80.8%–96.7%) in pancreatic malignancies and 92.0% (95% CI, 81.3%–98.8%) in PDAC. Screening sample suitability before NGS testing was associated with lower adequacy in subgroup analysis (79.7% vs. 98.4%, P = 0.001). The pooled prevalences of mutations in KRAS, TP53, CDKN2A, and SMAD4 in PDAC were 87.4% (95% CI, 83.2%–91.2%), 62.6% (95% CI, 53.2%–71.7%), 20.6% (95% CI, 11.9%–30.8%), and 19.4% (95% CI, 11.2%–29.1%), respectively. The pooled prevalence of potentially actionable mutations in PDAC was 14.5% (95% CI, 8.2%–22.0%). Conclusions: In the majority of cases, EUS-FNA/FNB can acquire adequate sample for NGS and identify tumor-specific mutations in patients with pancreatic malignancies. Strict pre-analysis screening criteria may negatively impact the sample adequacy and the success rate for NGS.