Interpretable prediction of 30-day mortality in patients with acute pancreatitis based on machine learning and SHAP.

Background: Severe acute pancreatitis (SAP) can be fatal if left unrecognized and untreated. The purpose was to develop a machine learning (ML) model for predicting the 30-day all-cause mortality risk in SAP patients and to explain the most important predictors.

Methods: This research utilized six ML methods, including logistic regression (LR), k-nearest neighbors(KNN), support vector machines (SVM), naive Bayes (NB), random forests(RF), and extreme gradient boosting(XGBoost), to construct six predictive models for SAP.

Identification of Copper Homeostasis-Related Gene Signature for Predicting Prognosis in Patients with Epithelial Ovarian Cancer.

Objectives: This research aims to establish a copper homeostasis-related gene signature for predicting the prognosis of epithelial ovarian cancer and to investigate its underlying mechanisms.

Methods: We mainly constructed the copper homeostasis-related gene signature by LASSO regression analysis. Then multiple methods were used to evaluate the independent predictive ability of the model and explored the mechanisms.

Endoplasmic reticulum stress promotes hepatocellular carcinoma by modulating immunity: a study based on artificial neural networks and single-cell sequencing.

Introduction: Hepatocellular carcinoma (HCC) is characterized by the complex pathogenesis, limited therapeutic methods, and poor prognosis. Endoplasmic reticulum stress (ERS) plays an important role in the development of HCC, therefore, we still need further study of molecular mechanism of HCC and ERS for early diagnosis and promising treatment targets.

Method: The GEO datasets (GSE25097, GSE62232, and GSE65372) were integrated to identify differentially expressed genes related to HCC (ERSRGs).

Assessment of phylogenetic relationships and genetic diversity of Sagittaria trifolia using phenotypic traits and SNP markers.

The aquatic perennial herb Sagittaria trifolia L. commonly known as arrowhead, has been utilized in China both as a culinary vegetable and in traditional medicines. Characterizing the phylogenetic relationships and genetic diversity of arrowheads is crucial for improved management, conservation, and efficient utilization of the germplasm resources associated with this species.

Elabela, a Novel Peptide, Exerts Neuroprotective Effects Against Ischemic Stroke Through the APJ/miR-124-3p/CTDSP1/AKT Pathway.

Elabela (ELA), which is the second endogenous peptide ligand of the apelin receptor (APJ) to be discovered, has been widely studied for potential use as a therapeutic peptide. However, its role in ischemic stroke (IS), which is a leading cause of disability and death worldwide and has limited therapeutic options, is uncertain. The aim of the present study was to investigate the beneficial effects of ELA on neuron survival after ischemia and the underlying molecular mechanisms.

Protective properties of extracellular vesicles in sepsis models: a systematic review and meta-analysis of preclinical studies.

Background: Multiple preclinical studies have reported a beneficial effect of extracellular vesicles (EVs), especially mesenchymal stem cells derived EVs (MSC-EVs), in the treatment of sepsis. However, the therapeutic effect of EVs is still not universally recognized. Therefore, we conducted this meta-analysis by summarizing data from all published studies that met certain criteria to systematically review the association between EVs treatment and mortality in animal models of sepsis.

Peptide hormone ELABELA promotes rat bone marrow-derived mesenchymal stem cell proliferation and migration by manipulating the cell cycle through the PI3K/AKT pathway under the hypoxia and ischemia microenvironment.

Background: Mesenchymal stem cells (MSCs) are emerging as a potential candidate for stem cell transplantation to repair myocardial tissue in myocardial infarctions (MI). However, there are some pivotal limitations such as poor survival and low migration capacity of MSCs in hypoxic and ischemic microenvironments of MI. Our previous work verified that ELABELA (also abbreviated as ELA), a peptide hormone, could play a role as a growth factor and prolong the life span of rat bone marrow-derived mesenchymal stem cells (RAT BM-MSCs) under hypoxic and ischemic conditions.