BACKGROUND/OBJECTIVES: Increased mass of adipose tissue in obese persons is caused by excessive adipogenesis, which is elaborately controlled by an array of transcription factors. Inhibition of adipogenesis by diverse plant-derived substances has been explored. The aim of the current study was to examine the effects of the aqueous methanol extract of laver (Porphyra yezoensis) on adipogenesis and apoptosis in 3T3-L1 adipocytes and to investigate the mechanism underlying the effect of the laver extract. MATERIALS/METHODS: 3T3-L1 cells were treated with various concentrations of laver extract in differentiation medium. Lipid accumulation, expression of adipogenic proteins, including CCAAT enhancer-binding protein alpha, peroxisome proliferator-activated receptor gamma, fatty acid binding protein 4, and fatty acid synthase, cell viability, apoptosis, and the total content and the ratio of reduced to oxidized forms of glutathione (GSH/GSSG) were analyzed. RESULTS: Treatment with laver extract resulted in a significant decrease in lipid accumulation in 3T3-L1 adipocytes, which showed correlation with a reduction in expression of adipogenic proteins. Treatment with laver extract also resulted in a decrease in the viability of preadipocytes and an increase in the apoptosis of mature adipocytes. Treatment with laver extract led to exacerbated depletion of cellular glutathione and abolished the transient increase in GSH/GSSG ratio during adipogenesis in 3T3-L1 adipocytes. CONCLUSION: Results of our study demonstrated that treatment with the laver extract caused inhibition of adipogenesis, a decrease in proliferation of preadipocytes, and an increase in the apoptosis of mature adipocytes. It appears that these effects were caused by increasing oxidative stress, as demonstrated by the depletion and oxidation of the cellular glutathione pool in the extract-treated adipocytes. Our results suggest that a prooxidant role of laver extract is associated with its antiadipogenic and proapoptotic effects.
3T3-L1 Cells ; Adipocytes* ; Adipogenesis* ; Adipose Tissue ; Apoptosis* ; Carrier Proteins ; Cell Survival ; Glutathione ; Humans ; Methanol* ; Oxidative Stress ; PPAR gamma ; Transcription Factors

Bleeding frorn the duodenal varix is an unusual event. Upper gastrointestinal endoscopy is the diagnostic procedure of choice in diagnosing duodenal varices. If performed during active bleeding, it can differentiate between esophageal and duodenal varices as the source, which has important therapeutic implications. A thorough examination of the duodenum for varices is important in an upper gastrointestinal hemorrhage. Treatment modalites for bleeding duodenal varices are sclerotherapy, varix suture ligation, portocaval shunt, and duodenal resection. Although endoscopic sclerotherapy has lirnited success in controlling active duodenal varix as initial treatment, endoscopic injection sclerotherapy is a useful first-line therapeutic measure in the treatment of bleeding duodenal varices. In this study we present a case of a ruptured duodenal varix, which was defected by an endoscopy, in a 61-year-old male. An endoscopic examination showed small and nonbleeding esophageal varices and a prominant ulcerated varix was identified in the 2nd portion of the duodenum. Endoscopic sclerotherapy was performed by injecting ethanolamine oleate into the varix. Our report demonstrate that endoscopic sclerotherapy can be efficient even in the presence of acute bleeding and that it can provide a definitive method of curing of a bleeding duodenal varix.
Duodenum ; Endoscopy ; Endoscopy, Gastrointestinal ; Esophageal and Gastric Varices ; Ethanolamine ; Gastrointestinal Hemorrhage ; Hemorrhage* ; Humans ; Ligation ; Male ; Middle Aged ; Oleic Acid ; Sclerotherapy* ; Sutures ; Ulcer ; Varicose Veins*

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.