Electrophilic aromatic substitution at the C5 position of isoxazolines and construction of a new quaternary carbon center were achieved in this paper. This is the first report of carbon-carbon (C-C) bond formation onto isoxazoline without compromising the ring structure. Various aromatics including heteroaromatics gave the desired products in good yields, especially aromatics bearing electron-donating groups.
View Article and Find Full Text PDFObjectives: This study evaluates risk factors for lymph node metastasis (LNM) in T2 colorectal cancer to refine patient selection for endoscopic resection.
Methods: We reviewed records from consecutive patients who had undergone curative surgical resection of T2 colorectal cancer at our institution in Japan between April 2001 and December 2021. Data on conventional clinicopathologic variables were retrieved from the pathology reports at the time of surgery.
Gastrointest Endosc Clin N Am
January 2025
The emerging role of artificial intelligence (AI) in automated endoscopic diagnosis represents a significant advancement in managing inflammatory bowel disease (IBD). AI technologies are increasingly being applied to endoscopic imaging to enhance the diagnosis, prediction of severity, and progression of IBD and dysplasia-associated colitis surveillance. These AI-assisted endoscopy aim to improve diagnostic accuracy, reduce variability of endoscopy imaging interpretations, and assist clinicians in decision-making processes.
View Article and Find Full Text PDFEfficient operating room management is essential and requires precise surgery scheduling. We hypothesized that an estimation formula for the preparation time for anesthesia induction and surgery could be developed by incorporating anesthesia and surgical factors, as well as the 'clinical department,' into the formula. This retrospective observational study analyzed 12,528 scheduled surgical cases.
View Article and Find Full Text PDFClin Gastroenterol Hepatol
July 2024
Background: In the management of ulcerative colitis (UC), histological remission is increasingly recognized as the ultimate goal. The absence of neutrophil infiltration is crucial for assessing remission. This study aimed to develop an artificial intelligence (AI) system capable of accurately quantifying and localizing neutrophils in UC biopsy specimens to facilitate histological assessment.
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