Introduction

Aims & Methods

Results

SVT was identified in 3.7% of patients diagnosed with acute pancreatitis (73 out of 1,969), with the splenic vein being the most commonly involved segment (69.9%). Compared to patients without SVT (n = 1,896), patients with thrombosis were more frequently male (61.6% vs. 49.0%, p = 0.030) and significantly younger (58.8 ± 14.9 years vs. 63.7 ± 16.6 years, p = 0.001). Among the 73 patients with SVT, 58.9% developed signs of PHT, including splenomegaly (16.4%), collateral circulation (39.7%), and esophageal varices (17.8%), while 8.2% developed ascites and 4.1% experienced variceal bleeding as manifestations of portal hypertension decompensation, during a median follow-up of 4.9 months (range: 0.2–68.8 months). Active smoking was significantly more common in SVT patients than in the control group (24.7% vs. 8.2%, p = 0.001). Subgroup analysis was performed on 45 patients with available follow-up CT scans. Recanalization occurred in 10 out of 45 patients (22.2%). Among the 35 non-recanalized patients, 68.5% developed PHT, and 7 (29.1%) experienced decompensation (2 with variceal bleeding and 5 with ascites). Complete thrombosis, irrespective of splanchnic site, was the only significant predictor of non-recanalization (7.7% in the recanalized group vs. 42.1% in the non-recanalized group, p = 0.006). Anticoagulation showed a trend toward association with recanalization (27.8% in the anticoagulated group vs. 0.0% in the non-anticoagulated group, p = 0.08), although it did not impact overall survival. Two deaths occurred in patients with severe AP and absence of recanalization of SVT.

Conclusion

Introduction

Artificial intelligence (AI) is increasingly integrated into medical decision-making and education, particularly through large language models such as ChatGPT. In gastroenterology, where clinical reasoning relies heavily on imaging, biological interpretation, and complex decision processes, the effective implementation of AI tools remains poorly documented in real-world settings.

Aims & Methods

This study aimed to compare how gastroenterologists and physicians from other specialties perceive the usefulness and practical applications of AI in gastroenterology, with a focus on diagnostic, therapeutic, and educational support.
A cross-sectional survey was distributed to physicians practicing in various hospital settings in March 2025. Participants were grouped as gastroenterologists or non-gastroenterologists. The questionnaire assessed demographics, clinical exposure to digestive diseases, prior AI usage, and perceived utility of AI in gastroenterology. Statistical comparisons were conducted using the Chi-squared test, with significance set at p<0.05.

Results

Gastroenterologists were significantly more likely to have used AI for gastroenterology-specific clinical questions (64% vs. 41% among other physicians). While 96% of all respondents acknowledged the potential usefulness of AI in gastroenterology, gastroenterologists expressed greater caution: 60% described AI as useful but with limitations, 36% viewed it as a promising tool, and 4% saw no particular benefit. Similar distributions were observed among other physicians (56%, 42%, and 2%, respectively), with no statistically significant difference in overall perception (p = 0.77).
However, the perceived domains of utility differed significantly between the groups (p = 0.047). Gastroenterologists most often highlighted the role of AI in continuing medical education (24.5%), diagnostic support (20.8%), and public education (15.1%). In contrast, other physicians emphasized diagnostic assistance (21.9%), pedagogical support (23.5%), and notably, therapeutic decision-making (13.8%), which was less frequently cited by gastroenterologists (7.5%).

Conclusion

Gastroenterologists—although more experienced with AI in their field—tend to adopt a more cautious and targeted perspective on its clinical integration. They see it as a complementary tool for interpretation and professional development, rather than a primary decision-making assistant. Meanwhile, non-specialist physicians show a slightly broader enthusiasm, seeing AI as helpful both in clinical decisions and educational support. While both groups recognize the potential of AI in gastroenterology, its successful implementation will require tailoring to the specific expectations, workflows, and trust levels of each medical discipline.

Introduction

Current therapeutic strategies for inflammatory bowel disease (IBD) remain limited, with clinical efficacy often falling short of expectations. Post-translational modifications play a pivotal role in IBD pathogenesis. This study aims to elucidate the functional significance of ubiquitination in IBD development and progression.

Aims & Methods

By analyzing colon RNA sequencing (RNA-seq) data from healthy and dextran sulfate sodium (DSS)-induced colitis mice, combined with RNA-seq datasets from healthy individuals and ulcerative colitis (UC) patients, we identified differential RNA expression levels of ATDC between healthy and inflammatory groups. Single-cell RNA sequencing (scRNA-seq) analysis further pinpointed the primary cell types exhibiting ATDC expression discrepancies. These findings were validated through immunohistochemistry, immunofluorescence, and western blot. Co-immunoprecipitation (Co-IP) assays and molecular docking simulations were employed to confirm and model the interaction between ATDC and PRMT5 in vitro. The role of ATDC in IBD pathogenesis was investigated using an ATDC-knockout (ATDC-KO) murine DSS model, with flow cytometry analyses delineating its impact on immune status.

Results

RNA-seq analysis revealed elevated ATDC mRNA levels in DSS-treated mice and UC patient intestinal tissues. scRNA-seq data indicated ATDC upregulation predominantly in the intestinal epithelial cells of UC patients. Protein-level upregulation of ATDC was further confirmed in both DSS mice and UC patient specimens. Lipopolysaccharide stimulation increased ATDC expression in Caco2 cells. Overexpression of ATDC in Caco2 cells, coupled with mass spectrometry, identified ATDC-PRMT5 binding, which was corroborated by Co-IP assays and molecular docking simulations. ATDC overexpression downregulated PRMT5 protein (but not mRNA) levels. In DSS models, PRMT5 expression was reduced compared to healthy controls; however, ATDC-KO mice exhibited PRMT5 upregulation and exacerbated colitis severity. Flow cytometry demonstrated an elevated Th17 cell proportion in ATDC-KO DSS mice relative to wild-type counterparts.

Conclusion

This study is the first to demonstrate the protective role of ATDC in colitis. ATDC attenuates colonic inflammation by promoting the degradation of PRMT5, thereby suppressing Th17 cell-mediated immune responses. Enhancing ATDC activity may represent a novel therapeutic strategy for mitigating colitis progression.

References

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Introduction

Endoscopic scores are crucial for assessing Crohn's disease (CD) severity, guiding therapy, and monitoring progression. The Simplified Endoscopic Score for Crohn's Disease (SES-CD) is widely used for this purpose [1]. Accurate scoring is vital for patient care. Recently, artificial intelligence has demonstrated potential in medical image interpretation [2]. This study aims to evaluate ChatGPT's effectiveness in rating the SES-CD.

Aims & Methods

This retrospective study evaluated ChatGPT's accuracy in assessing CD endoscopic activity using the SES-CD. One representative still image was selected for each bowel segment, and stricture degrees were provided separately if present. ChatGPT scored the SES-CD based on these images. The IBD expert's ratings were validated by calculating the intra-class correlation coefficient (ICC) with clinical trial central readers. The ICC between the IBD expert and ChatGPT scores was calculated to determine ChatGPT's reliability in SES-CD scoring.

Results

Nine (mean age 32.0 ± 11.8 years, 77.8% male) were included, with 45 bowel segments. Three (33.4%), 5 (55.6%), and 1 (11.1%) had nonstricturing nonpenetrating, structuring, and penetrating disease, respectively. Four (44.4%) had ileal disease and 5 (55.6%) had ileocolonic disease. Five (55.6%) had previous IBD surgery.
The SES-CD scores of the participants, rated by IBD expert in the hospital, revealed the following mean and standard deviation for each segment of the bowel: 6.9 ± 2.3 in the ileum, 1.3 ± 2.6 in the right colon, 1.6 ± 2.4 in the transverse colon, 1.3 ± 2.6 in the left colon, and 1.3 ± 2.6 in the rectum. The total SES-CD score was 12.4 ± 10.9. The score reliability of the institute IBD expert was tested compared to the clinical trial central reader and an intraclass correlation coefficient was calculated and found to be 0.96 (95% CI, 0.84-0.99) which is considered extremely correlated.
The mean and standard deviation of ChatGPT score in each segment were: 6.4 ± 2.4 in the ileum, 2.4 ± 3.8 in the right colon, 0.9 ± 2.7 in the transverse colon, 0.3 ± 1.0 in the left colon, 0.6 ± 1.3 in the rectum, with total SES-CD score of 10.6 ± 6.8. The calculated ICC between the expert and ChatGPT obtained SES-CD scores was 0.80 (95% IC, 0.64- 0.89) which is considered highly correlated.

Conclusion

Despite being based on only one photo per segment, ChatGPT demonstrated satisfactory performance in estimating endoscopic activity in CD. The differences between the IBD expert obtained scores and ChatGPT scores were acceptable, suggesting that artificial intelligence has the potential to be a useful tool in clinical and research settings, providing an accurate estimation of disease severity based on limited visual data.

References

1- Daperno M, D'Haens G, Van Assche G, et al. Development and validation of a new, simplified endoscopic activity score for Crohn's disease: the SES-CD. Gastrointest Endosc. 2004;60(4):505-512.
2- Levartovsky A, Albshesh A, Grinman A, et al. Enhancing diagnostics: ChatGPT-4 performance in ulcerative colitis endoscopic assessment. Endosc Int Open. 2025;13:a25420943. Published 2025 Mar 14.