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Introduction: Endoscopic submucosal dissection (ESD) has been popular worldwide to treat laterally spreading tumors and large polyps. Post-ESD coagulation syndrome (PECS) is more common than the two major ESD-related complications, perforation, and bleeding. The aim of this study was to assess the prevalence of PECS, identify the risk factors for PECS, and create a risk prediction model for PECS. Methods: Retrospective cross-sectional study analyzed a total of 986 patients who underwent colorectal ESD. Logistic regression models were used to assess risk factors with PECS. Each risk factor was scored, and the 3-step risk stratification index of prediction model was assessed. Results: The prevalence of PECS was 21.4% (95% confidence interval [CI] = 18.9–24.1%). The risk factors of PECS in the multivariate logistic regression were tumor size (+1 cm: odds ratio [OR], 1.29; 95% CI, 1.16–7.09), cecal lesion (OR, 1.96; 95% CI, 1.09–1.53), procedure time (+30 min: OR, 1.19; 95% CI, 1.02–1.39), and ESD with snaring (OR, 0.64; 95% CI, 0.43–0.95). Applying a simplified weighted scoring system based on adjusted OR increments of 1, the risk of PECS was 12.3% (95% CI, 0.3–16.0%) for the low-risk group (score ≤4) and was 36.0% (95% CI = 29.4–43.2%) for the high-risk group (score ≥8). Overall discrimination (C-statistic = 0.629; 95% CI = 0.585–0.672) and calibration (p = 0.993) of the model were moderate to good. Conclusion: PECS occurs frequently, and the prediction model can be helpful for effective treatment and prevention of PECS. [ABSTRACT FROM AUTHOR]

Epacs (exchange proteins directly activated by cyclic AMP [cAMP]) act as downstream effectors of cAMP and play important roles in energy balance and glucose homeostasis. While global deletion of Epac1 in mice leads to heightened leptin sensitivity in the hypothalamus and partial protection against high-fat diet (HFD)-induced obesity, the physiological functions of Epac1 in white adipose tissue (WAT) has not been explored. Here, we report that adipose tissue-specific Epac1 knockout (AEKO) mice are more prone to HFD-induced obesity, with increased food intake, reduced energy expenditure, and impaired glucose tolerance. Despite the fact that AEKO mice on HFD display increased body weight, these mice have decreased circulating leptin levels compared to their wild-type littermates. In vivo and in vitro analyses further reveal that suppression of Epac1 in WAT decreases leptin mRNA expression and secretion by inhibiting cAMP response element binding (CREB) protein and AKT phosphorylation, respectively. Taken together, our results demonstrate that Epac1 plays an important role in regulating energy balance and glucose homeostasis by promoting leptin expression and secretion in WAT.

Simple Summary: We developed an attention-based whole slide image (WSI)-level classification deep learning model employing surgically and endoscopically resected specimens to predict LNM in T1 CRC. Our AI model with H&E-stained WSIs and without annotations showed good performance power with the validation of an independent cohort in a single center. The area under the curve of our model was 0.781–0.824, higher than that of previous artificial intelligence (AI) studies with only WSIs. Our AI model, which showed the highest sensitivity (92.9%), reduced unnecessary additional surgery by 14.2% more than using the current JSCCR guidelines (68.3% vs. 82.5%). This revealed the feasibility of using an AI model with only H&E-stained WSIs to predict LNM in T1 CRC. According to the current guidelines, additional surgery is performed for endoscopically resected specimens of early colorectal cancer (CRC) with a high risk of lymph node metastasis (LNM). However, the rate of LNM is 2.1–25.0% in cases treated endoscopically followed by surgery, indicating a high rate of unnecessary surgeries. Therefore, this study aimed to develop an artificial intelligence (AI) model using H&E-stained whole slide images (WSIs) without handcrafted features employing surgically and endoscopically resected specimens to predict LNM in T1 CRC. To validate with an independent cohort, we developed a model with four versions comprising various combinations of training and test sets using H&E-stained WSIs from endoscopically (400 patients) and surgically resected specimens (881 patients): Version 1, Train and Test: surgical specimens; Version 2, Train and Test: endoscopic and surgically resected specimens; Version 3, Train: endoscopic and surgical specimens and Test: surgical specimens; Version 4, Train: endoscopic and surgical specimens and Test: endoscopic specimens. The area under the curve (AUC) of the receiver operating characteristic curve was used to determine the accuracy of the AI model for predicting LNM with a 5-fold cross-validation in the training set. Our AI model with H&E-stained WSIs and without annotations showed good performance power with the validation of an independent cohort in a single center. The AUC of our model was 0.758–0.830 in the training set and 0.781–0.824 in the test set, higher than that of previous AI studies with only WSI. Moreover, the AI model with Version 4, which showed the highest sensitivity (92.9%), reduced unnecessary additional surgery by 14.2% more than using the current guidelines (68.3% vs. 82.5%). This revealed the feasibility of using an AI model with only H&E-stained WSIs to predict LNM in T1 CRC. [ABSTRACT FROM AUTHOR]

Background/Aims: We investigated the clinical practice patterns of post-polypectomy colonoscopic surveillance among Korean endoscopists. Methods: In a web-based survey conducted between September and November 2021, participants were asked about their preferred surveillance intervals and the patient age at which surveillance was discontinued. Adherence to the recent guidelines of the U.S. Multi-Society Task Force on Colorectal Cancer (USMSTF) was also analyzed. Results: In total, 196 endoscopists completed the survey. The most preferred first surveillance intervals were: a 5-year interval after the removal of 1-2 tubular adenomas < 10 mm; a 3-year interval after the removal of 3-10 tubular adenomas < 10 mm, adenomas = 10 mm, tubulovillous or villous adenomas, = 20 hyperplastic polyps < 10 mm, 1-4 sessile serrated lesions (SSLs) < 10 mm, hyperplastic polyps or SSLs = 10 mm, and traditional serrated adenomas; and a 1-year interval after the removal of adenomas with highgrade dysplasia, >10 adenomas, 5-10 SSLs, and SSLs with dysplasia. In piecemeal resections of large polyps (> 20 mm), surveillance colonoscopy was mostly preferred after 1 year for adenomas and 6 months for SSLs. The mean USMSTF guideline adherence rate was 30.7%. The largest proportion of respondents (40.8%-55.1%) discontinued the surveillance at the patient age of 80-84 years. Conclusions: A significant discrepancy was observed between the preferred post-polypectomy surveillance intervals and recent international guidelines. Individualized measures are required to increase adherence to the guidelines. [ABSTRACT FROM AUTHOR]