Inflammatory bowel disease (IBD) is a complex condition resulting from environmental, microbial, immunologic, and genetic factors. With the advancement of Mendelian randomization research in IBD, we have gained new insights into the relationship between these factors and IBD. Many animal models of IBD have been developed using different methods, but few studies have attempted to model IBD by combining environmental factors and microbial factors. In this review, we examine how environmental factors and microbial factors affect the development and progression of IBD, and how they interact with each other and with the intestinal microbiota. We also summarize the current methods for creating animal models of IBD and compare their advantages and disadvantages. Based on the latest findings from Mendelian randomization studies on the role of environmental factors in IBD, we discuss which environmental and microbial factors could be used to construct a more realistic and reliable IBD experimental model. We propose that animal models of IBD should consider both environmental and microbial factors to better mimic human IBD pathogenesis and to reveal the underlying mechanisms of IBD at the immune and genetic levels.We highlight the importance of environmental and microbial factors in IBD pathogenesis and offer new perspectives and suggestions for improving experimental animal modeling. Our goal is to create a model that closely resembles the clinical picture of IBD.

Objective:To evaluate modified Lanza score (MLS) of gastric mucosa for predicting the prognosis of geriatric patients with sepsis.Methods:Data of 50 patients with sepsis, who were over 60 years old and underwent gastroscopy for suspected gastrointestinal bleeding in the Department of Geriatric Critical Care Medicine of Guangdong Provincial People's Hospital from January 2019 to April 2022, were retrospectively analyzed. Patients were divided into the death group ( n=32) and the survival group ( n=18) according to their regression within 28 days after gastroscopy. Their gastric mucosa was scored by using MLS system, and the mortality of patients with MLS≥1 was calculated, then the patients were further divided into 2 groups, MLS=0-2 ( n=23, less than 2 regions of lesions ) and MLS=3-5 ( n=27, two or more regions of lesions). The relationship between MLS and acute physiology and chronic health status evaluation (APACHE) Ⅱ score, risk factor of death and mortality in each group were compared. The correlation between MLS and mortality was analyzed. The influence of geriatric sepsis risk factors affecting the prognosis of patients within 28 days were analyzed by using logistic regression. Results:Among the 50 geriatric patients with sepsis, those with gastric mucosal lesions, i.e., MLS ≥1, accounted for 68.00% (34/50), including 84.38% (27/32) patients with MLS≥1 in the death group, which was significantly higher than the 38.89% (7/18) patients with MLS≥1 in the survival group ( χ 2=10.593, P<0.001). Patients with MLS=3-5 had significantly higher APACHE Ⅱ scores (26.09±6.47 VS 18.57±7.66, t=3.527, P=0.001) and higher mortality [85.19% (23/27) VS 39.13% (9/23), χ 2=11.434, P=0.001] compared with MLS=0-2. Correlation analysis showed a significant correlation between MLS and mortality ( r=0.886, P=0.019). Multivariate logistic regression analysis showed that MLS=4-5 was an independent risk factor for death in geriatric patients with sepsis ( OR=17.055, 95% CI: 1.387-209.744, P=0.027). Conclusion:MLS presents high sensitivity in predicting 28-day outcomes for geriatric patients with sepsis. Two or more than 2 regions of gastric mucosal lesions can significantly increase the risk of death in geriatric patients with sepsis.

Gastrointestinal tumors(GT)are characterized by both high malignancy and high mortality and have become the major diseases for prevention in the elderly.GT often present detectable changes, including bleeding and abnormal mucosal morphology.However, many technical difficulties remain in accurately monitoring the tumor itself and related abnormal lesions mentioned above, which are the key factors affecting the early detection rate of gastrointestinal tumors.In recent years, with progresses in artificial intelligence(AI)applications for digestive endoscopy image analysis, biosensors, new biomarkers and other areas, AI holds promise for the detection of bleeding, morphological and structural abnormalities of the mucosa, tumors and other major disorders.Here we review the progress of AI applications in geriatric digestive diseases affecting digestive organs and the mucosa in light of morphology and function, to provide a reference for reducing the incidence of both geriatric emergencies and GT.