The effects of L-arginine (L-Arg), the physiological NO precureor and NO synthetase inhibitor NG-nitro-L-arginine (L-NNA) on endogenous endothelin (ET) secretion and renal function were observed in a model of glycerol-induced acute renal failure (ARF) in rat. It was found that endogenous ET secretion was significantly increased, while serum NO was markedly decreased in ARF rats. The administration of L-NNA to the ARF rats induced significant increases in plasma ET and positive immunoreactive particles of ET in renal tubular epithelial cells(EP cells), and the impairment of renal function was exaggerated. L-Arg might effectively decrease the level of plasma ET and the positive immunoreactive particles of ET in renal tubular EP cells, suggesting the improvement of the renal function. It is suggested that the ability of NO in improving renal function may relatedto the inhibition of endogenous ET secretion in glycerol-induced ARF rats.

Objective:To discuss the composition and connotation of practical training objectives for nurses specialized in intravenous therapy, and provide guidance and reference for standardizing the practical training of nurses specialized in intravenous therapy.Methods:In this phenomenological analysis in qualitative research, 13 intravenous treatment and nursing experts from Shandong, Zhejiang, Sichuan, and Shaanxi provinces were selected from May to July 2021 for semi-structured interviews. Colaizzi's 7-step method and Nvivo 12.0 were used to organize data and analyze and refine themes.Results:Three themes and 12 subthemes were extracted for the practical training of intravenous therapy nurses, including knowledge objectives, ability objectives, and well-rounded objectives.Conclusions:Attention should be paid to the setting of clinical professional knowledge, skills and comprehensive quality goals for nurses specialized in intravenous therapy, so as to improve the pertinence and timeliness of training, promote the quality of training and the professional development of specialized training for intravenous therapy.

Background::Pulmonary embolism (PE) is a severe and acute cardiovascular syndrome with high mortality among patients with autoimmune inflammatory rheumatic diseases (AIIRDs). Accurate prediction and timely intervention play a pivotal role in enhancing survival rates. However, there is a notable scarcity of practical early prediction and risk assessment systems of PE in patients with AIIRD.Methods::In the training cohort, 60 AIIRD with PE cases and 180 age-, gender-, and disease-matched AIIRD non-PE cases were identified from 7254 AIIRD cases in Tongji Hospital from 2014 to 2022. Univariable logistic regression (LR) and least absolute shrinkage and selection operator (LASSO) were used to select the clinical features for further training with machine learning (ML) methods, including random forest (RF), support vector machines (SVM), neural network (NN), logistic regression (LR), gradient boosted decision tree (GBDT), classification and regression trees (CART), and C5.0 models. The performances of these models were subsequently validated using a multicenter validation cohort.Results::In the training cohort, 24 and 13 clinical features were selected by univariable LR and LASSO strategies, respectively. The five ML models (RF, SVM, NN, LR, and GBDT) showed promising performances, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.962-1.000 in the training cohort and 0.969-0.999 in the validation cohort. CART and C5.0 models achieved AUCs of 0.850 and 0.932, respectively, in the training cohort. Using D-dimer as a pre-screening index, the refined C5.0 model achieved an AUC exceeding 0.948 in the training cohort and an AUC above 0.925 in the validation cohort. These results markedly outperformed the use of D-dimer levels alone.Conclusion::ML-based models are proven to be precise for predicting the onset of PE in patients with AIIRD exhibiting clinical suspicion of PE.Trial Registration::Chictr.org.cn: ChiCTR2200059599.