Development and validation of a nomogram to predict risk of septic cardiomyopathy in the intensive care unit.

The aim of this study was to develop a simple but effective nomogram to predict risk of septic cardiomyopathy (SCM) in the intensive care unit (ICU). We analyzed data from patients who were first admitted to the ICU for sepsis between 2008 and 2019 in the MIMIC-IV database, with no history of heart disease, and divided them into a training cohort and an internal validation cohort at a 7:3 ratio. SCM is defined as sepsis diagnosed in the absence of other cardiac diseases, with echocardiographic evidence of left (or right) ventricular systolic or diastolic dysfunction and a left ventricular ejection fraction (LVEF) of less than 50%. Variables were selected from the training cohort using the Least Absolute Shrinkage and Selection Operator (LASSO) regression to develop an early predictive model for septic cardiomyopathy. A nomogram was constructed using logistic regression analysis and its receiver operating characteristic (ROC) and calibration were evaluated in two cohorts. A total of 1562 patients participated in this study, with 1094 in the training cohort and 468 in the internal validation cohort. SCM occurred in 13.4% (147 individuals) in the training cohort, 16.0% (75 individuals) in the internal validation cohort. After adjusting for various confounding factors, we constructed a nomogram that includes SAPS II, Troponin T, CK-MB index, white blood cell count, and presence of atrial fibrillation. The area under the curve (AUC) for the training cohort was 0.804 (95% CI 0.764-0.844), and the Hosmer-Lemeshow test showed good calibration of the nomogram (P = 0.288). Our nomogram also exhibited good discriminative ability and calibration in the internal validation cohort. Our nomogram demonstrated good potential in identifying patients at increased risk of SCM in the ICU.

MicroRNA-21: A Critical Pathogenic Factor of Diabetic Nephropathy.

Diabetic nephropathy (DN), one of the most common and intractable microvascular complications of diabetes, is the main cause of terminal renal disease globally. MicroRNA-21 (miR-21) is a kind of miRNA early identified in human circulation and tissues. Mounting studies have demonstrated that miR-21 plays an important role in the development and progression of DN. This collaborative review aimed to present a first attempt to capture the current evidence on the relationship between miR-21 and DN. After a systematic search, 29 relevant studies were included for comprehensively and thoroughly reviewing. All these eligible studies reported that miR-21 was up-regulated in DN, whether in serum or renal tissues of human or animal models. MiR-21 exhibited its pathogenic roles in DN by forming a complex network with targeted genes (e.g. MMP-9, Smad7, TIMP3, Cdk6, FOXO1, IMP3, and MMP2) and the signaling cascades (e.g. Akt/TORC1 signaling axis, TGF-ß/NF-κB signaling pathways, TGF-ß/SMAD pathway, CADM1/STAT3 signaling, and AGE-RAGE regulatory cascade), which resulted in epithelial-to-mesenchymal transition, extracellular matrix deposition, cytoskeletal remodeling, inflammation, and fibrosis. This review highlights that miR-21 is a pivotal pathogenic factor in the development of DN. It may serve as an attractive potential diagnostic, prognostic, and predictive biomarker for DN in clinical practice after further confirmation of the clinicopathological features and molecular mechanisms of miR-21-mediated DN.

[Setup a model for study the interfere between chemokine and immunocyte].

OBJECTIVE: To investigated the effect of chemoattractant of rhTNF-alpha on TB-LCL. Set up a model for study the interaction between cytokine and B cells. METHOD: PTC were transfected with Epstein Barr virus, to get tonsil B lymphoblastic cell line(TB-LCL). RESULT: It was found rhTNF-alpha can chemotactic TB-LCL, in a dose-dependent manner and this chemotactic effect can be blocked by the neutralizing antibody E6 against TNF. CONCLUSION: This is an useful model in study the interfere between chemokine and immunocyte.