Evaluation of the competence of an artificial intelligence-assisted colonoscopy system in clinical practice: A post hoc analysis.

Background: Artificial intelligence-assisted colonoscopy (AIAC) has been proposed and validated in recent years, but the effectiveness of clinic application remains unclear since it was only validated in some clinical trials rather than normal conditions. In addition, previous clinical trials were mostly concerned with colorectal polyp identification, while fewer studies are focusing on adenoma identification and polyps size measurement. In this study, we validated the effectiveness of AIAC in the clinical environment and further investigated its capacity for adenoma identification and polyps size measurement. Methods: The information of 174 continued patients who went for coloscopy in Chongqing Rongchang District People's hospital with detected colon polyps was retrospectively collected, and their coloscopy images were divided into three validation datasets, polyps dataset, polyps/adenomas dataset (all containing narrow band image, NBI images), and polyp size measurement dataset (images with biopsy forceps and polyps) to assess the competence of the artificial intelligence system, and compare its diagnostic ability with endoscopists with different experiences. Results: A total of 174 patients were included, and the sensitivity of the colorectal polyp recognition model was 99.40%, the accuracy of the colorectal adenoma diagnostic model was 93.06%, which was higher than that of endoscopists, and the mean absolute error of the polyp size measurement model was 0.62 mm and the mean relative error was 10.89%, which was lower than that of endoscopists. Conclusion: Artificial intelligence-assisted model demonstrated higher competence compared with endoscopists and stable diagnosis ability in clinical use.

NF-κB p65 and SETDB1 expedite lipopolysaccharide-induced intestinal inflammation in mice by inducing IRF7/NLR-dependent macrophage M1 polarization.

Macrophages exhibit distinct phenotypes that are pro-inflammatory (M1) or anti-inflammatory (M2) in response to inflammation. In this study, we tried to identify the roles and mechanisms of interferon regulatory factor 7 (IRF7) in modulating the phenotypes of macrophages in lipopolysaccharide (LPS)-induced intestinal inflammation. The mouse model of intestinal inflammation was induced by lipopolysaccharide (LPS), and mouse bone marrow-derived macrophages (BMDMs) and mouse intestinal epithelial cells were selected for experimental verification in vitro. Results demonstrated that IRF7 was highly expressed in the mouse model of intestinal inflammation, while IRF7 deficiency repressed macrophage M1 polarization and attenuated intestinal inflammation in mice. p65 and SET domain bifurcated 1 (SETDB1) synergistically promoted histone 3 lysine 4 trimethylation (H3K4me3) methylation to elevate IRF7 expression, which activated the Nod-like receptor (NLR) pathway to induce macrophage M1 polarization. Through this mechanism, IRF7 in BMDMs functioned to accelerate intestinal epithelial cell apoptosis and their release of pro-inflammatory proteins. Furthermore, the promoting effect of p65 and SETDB1 on LPS-induced intestinal inflammation was validated in vivo. To sum up, NF-κB p65 and SETDB1 facilitated IRF7-mediated macrophage M1 polarization, thereby aggravating the LPS-induced intestinal inflammation. Hence, this study highlights the appealing value of these factors as anti-inflammatory targets.