Risk factors for cefmetazole-non-susceptible bacteremia in acute cholangitis.

INTRODUCTION: Cefmetazole (CMZ), an antibiotic with limited international distribution, is recommended by the Tokyo Guidelines 2018 (TG18) for non-severe cases of acute cholangitis (AC). However, the risk factors for CMZ-non-susceptible (CMZ-NS) bacteremia in AC remain unclear. Here, we aimed to investigate the risk factors for CMZ-NS bacteremia and evaluate mortality in patients with AC. METHODS: This single-center, retrospective, observational study included all patients diagnosed with definite bacteremic AC, based on TG18, from April 2019 to March 2023. Risk factors for CMZ-NS bacteremia were analyzed by univariate, and age- and sex-adjusted, logistic regression analyses. Mortality was compared by cause of obstruction, CMZ-susceptible/CMZ-NS bacteremia, and initial treatment. RESULTS: In total, 165 patients were enrolled. CMZ-NS bacteremia was diagnosed in 46 (27.9 %) patients. Histories of diabetes mellitus, hepato-biliary-pancreatic cancer, malignant biliary obstruction, and endoscopic sphincterotomy were identified as significant factors associated with the risk of CMZ-NS bacteremia. Thirteen patients died within 30 days of hospital admission. The mortality of patients with AC and malignant biliary obstruction was statistically higher than that of patients with bile duct stones. No patients with AC and bile duct stones died in the group with CMZ-NS bacteremia and inappropriate initial antibiotics. CONCLUSIONS: In AC, a history of diabetes mellitus, hepato-biliary-pancreatic cancer, malignant biliary obstruction, and endoscopic sphincterotomy are associated with an increased risk of CMZ-NS bacteremia. Therefore, the choice of empiric therapy for AC should be based on the etiology and patient background, rather than on the severity.

Artificial intelligence-based diagnosis of upper gastrointestinal subepithelial lesions on endoscopic ultrasonography images.

BACKGROUND: Endoscopic ultrasonography (EUS) is useful for the differential diagnosis of subepithelial lesions (SELs); however, not all of them are easy to distinguish. Gastrointestinal stromal tumors (GISTs) are the commonest SELs, are considered potentially malignant, and differentiating them from benign SELs is important. Artificial intelligence (AI) using deep learning has developed remarkably in the medical field. This study aimed to investigate the efficacy of an AI system for classifying SELs on EUS images. METHODS: EUS images of pathologically confirmed upper gastrointestinal SELs (GIST, leiomyoma, schwannoma, neuroendocrine tumor [NET], and ectopic pancreas) were collected from 12 hospitals. These images were divided into development and test datasets in the ratio of 4:1 using random sampling; the development dataset was divided into training and validation datasets. The same test dataset was diagnosed by two experts and two non-experts. RESULTS: A total of 16,110 images were collected from 631 cases for the development and test datasets. The accuracy of the AI system for the five-category classification (GIST, leiomyoma, schwannoma, NET, and ectopic pancreas) was 86.1%, which was significantly higher than that of all endoscopists. The sensitivity, specificity, and accuracy of the AI system for differentiating GISTs from non-GISTs were 98.8%, 67.6%, and 89.3%, respectively. Its sensitivity and accuracy were significantly higher than those of all the endoscopists. CONCLUSION: The AI system, classifying SELs, showed higher diagnostic performance than that of the experts and may assist in improving the diagnosis of SELs in clinical practice.

TNF-α-induced Inhibition of Protein Myristoylation Via Binding Between NMT1 and Sorbs2 in Osteoblasts.

BACKGROUND/AIM: Bone resolution due to tumor invasion often occurs on the surface of the jaw and is important for clinical prognosis. Although cytokines, such as TNF-α are known to impair osteoblasts, the underlying mechanism remains unclear. Protein myristoylation, a post-translational modification, plays an important role in the development of immune responses and cancerization of cells. A clear understanding of the mechanisms underlying this involvement will provide insights into molecular-targeted therapies. N-myristoyltransferase1 (NMT1), a specific enzyme involved in myristoylation, is expressed in cancer cells and in other normal cells, suggesting that changes in myristoylation may result from the regulation of NMT1 in cancer cells. MATERIALS AND METHODS: Using newly emerging state-of-the-art techniques such as the Click-it assay, RNA interference, mass spectrometry, immunoprecipitation, immunocytochemistry, and western blotting, the expression of myristoylated proteins and the role of TNF-α stimulation on NMT1 and Sorbs2 binding were evaluated in a murine osteoblastic cell line (MC3T3-E1). RESULTS: The expression of myristoylated proteins was detected; however, TNF-α stimulation resulted in their inhibition in MC3T3-E1 cells. The expression of NMT1 also increased. Immunoprecipitation and mass spectrometry identified Sorbs2 as a novel binding protein of NMT1, which upon TNF-α stimulation, inhibited myristoylation. CONCLUSION: The binding between NMT1 and Sorbs2 can regulate myristoylation, and NMT1 can be considered as a potential target molecule for tumor invasion.