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BackgroundIschemia reperfusion (I/R) play an imperative role in the expansion of cardiovascular disease. Sinomenine (SM) has been exhibited to possess antioxidant, anticancer, anti-inflammatory, antiviral and anticarcinogenic properties. The aim of the study was scrutinized the cardioprotective effect of SM against I/R injury in rat.MethodsRat were randomly divided into normal control (NC), I/R control and I/R + SM (5, 10 and 20 mg/kg), respectively. Ventricular arrhythmias, body weight and heart weight were estimated. Antioxidant, inflammatory cytokines, inflammatory mediators and plasmin system indicator were accessed.ResultsPre-treated SM group rats exhibited the reduction in the duration and incidence of ventricular fibrillation, ventricular ectopic beat (VEB) and ventricular tachycardia along with suppression of arrhythmia score during the ischemia (30 and 120 min). SM treated rats significantly (P < 0.001) altered the level of antioxidant parameters. SM treatment significantly (P < 0.001) repressed the level of creatine kinase MB (CK-MB), creatine kinase (CK) and troponin I (Tnl). SM treated rats significantly (P < 0.001) repressed the tissue factor (TF), thromboxane B2 (TXB2), plasminogen activator inhibitor 1 (PAI-1) and plasma fibrinogen (Fbg) and inflammatory cytokines and inflammatory mediators.ConclusionOur result clearly indicated that SM plays anti-arrhythmia effect in I/R injury in the rats via alteration of oxidative stress and inflammatory reaction.  相似文献   
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《Cancer cell》2022,40(11):1392-1406.e7
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BackgroundSurgical resection is recommended for patients with resectable acinar cell carcinoma (ACC). The aim of this study was to investigate the clinical characteristics and surgical outcomes of resectable ACC in comparison to pancreatic ductal adenocarcinoma (PDAC).MethodA retrospective analysis was performed on all patients who consecutively underwent radical resection with pathologically confirmed ACC and PDAC from December 2011 to December 2018. Clinicopathologic characteristics and follow-up information were analyzed. A 1:3 propensity score matching (PSM) method was used to minimize the bias between ACC and PDAC.ResultsA total of 26 patients with ACC and 1351 with PDAC were included. Compared to PDAC, ACC tended to be larger (4.5 vs. 3.0 cm; p < 0.001) and more frequently located in the pancreatic body/tail (61.5% vs. 36.6%, p = 0.009), with lower total bilirubin levels, lower neutrophil lymphocyte ratio (NLR) levels and lower carbohydrate antigen 19-9 (CA19-9) levels and carcinoembryonic antigen (CEA) levels. There was no difference in postoperative morbidities in patients with ACC and PDAC. The median OS and RFS were longer in ACC when compared to PDAC (OS: 43.5 mo vs. 19.0 mo, p = 0.004; RFS: 24.5 mo vs. 11.6 mo, p = 0.023). After the 1:3 PSM, ACC remained to be a better histological type for OS (p = 0.024), but had comparable RFS with PDAC (p = 0.164).ConclusionPatients with ACC after radical resection had better OS than that with PDAC. However, ACC is also an aggressive tumor with a similar trend of RFS with PDAC after the matching, necessitating the multidisciplinary treatment for resectable ACC disease.  相似文献   
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Transfusion-associated graft-versus-host disease (TA-GVHD) is a rare life-threatening complication of blood transfusion caused by donor T cells that escape rejection by the recipient immune system. These donor T cells drive recipient tissue damage in response to host antigens. On the other hand, GVHD occurring after allogeneic hematopoietic cell transplantation (HCT-GVHD) is also caused by donor T cells, but its pathophysiology is more complex and differs due to the effects of tissue damage caused by pre?HCT conditioning and profound immunosuppression. Both TA-GVHD and HCT-GVHD can be fatal; however, mortality is higher with TA-GVHD due to the paucity of treatment options. Here, we compare and summarize the presentation, diagnosis, pathophysiology, prevention, and treatment of TA-GVHD and HCT-GVHD.  相似文献   
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BackgroundDissection of lymph nodes at the roots of the inferior mesenteric artery (IMAN) should be offered only to selected patients at a major risk of developing IMAN involvement. The aim of this study is to present the first artificial intelligence (AI) models to predict IMAN metastasis risk in the left colon and rectal cancer patients.MethodsA total of 2891 patients with descending colon including splenic flexure, sigmoid colon and rectal cancer undergoing major primary surgery and IMAN dissection were included as a study cohort, which was then split into a training set (67%) and a testing set (33%). Feature selection was conducted using the least absolute shrinkage and selection operator (LASSO) regression model. Seven AI algorithms, namely Support Vector Machine (SVM), Logistic Regression (LR), Extreme Gradient Boosting (XGB), Light Gradient Boosting (LGB), Decision Tree Classifier (DTC), Random Forest (RF) classifier, and Multilayer Perceptron (MLP), as well as traditional multivariate LR model were employed to construct predictive models. The optimal hyperparameters were determined with 5 fold cross-validation. The predictive performance of models and the expert surgeon was assessed and compared in the testing set independently.ResultsThe IMAN involvement incidence was 4.6%. The optimal set of features selected by LASSO included 10 characteristics: neoadjuvant treatment, age, synchronous liver metastasis, synchronous lung metastasis, signet ring adenocarcinoma, neural invasion, lymphovascular invasion, CA199, endoscopic obstruction, T stage evaluated by MRI. The most accurate model derived from MLP showed excellent prediction power with area under the receiver operating characteristic curve (AUROC) of 0.873 and produced 81.0% recognition sensitivity and 82.5% specificity in the testing set independently. In contrast, the judgment of IMAN metastasis by expert surgeon yield rather imprecise and unreliable results with a significantly lower AUROC of 0.509. Additionally, the proposed MLP had the highest net benefits and the largest reduction of unnecessary IMAN dissection without the cost of additional involved IMAN missed.ConclusionMLP model was able to maintain its prediction accuracy in the testing set better than other models and expert surgeons. Our MLP model could be used to help identify IMA nodal metastasis and to select candidates for individual IMAN dissection.  相似文献   
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