Ulinastatin treatment mitigates glycocalyx degradation and associated with lower postoperative delirium risk in patients undergoing cardiac surgery: a multicentre observational study.

Background: Ulinastatin (UTI), recognized for its anti-inflammatory properties, holds promise for patients undergoing cardiac surgery. This study aimed to investigate the relationship between intraoperative UTI administration and the incidence of delirium following cardiac surgery.

Methods: A retrospective analysis was performed on a retrospective cohort of 6,522 adult cardiac surgery patients to evaluate the relationship between UTI treatment and the incident of postoperative delirium (POD) in patients ongoing cardiac surgery.

scSMD: a deep learning method for accurate clustering of single cells based on auto-encoder.

Background: Single-cell RNA sequencing (scRNA-seq) has transformed biological research by offering new insights into cellular heterogeneity, developmental processes, and disease mechanisms. As scRNA-seq technology advances, its role in modern biology has become increasingly vital. This study explores the application of deep learning to single-cell data clustering, with a particular focus on managing sparse, high-dimensional data.

Construction of a rodent neural network-skeletal muscle assembloid that simulate the postnatal development of spinal cord motor neuronal network.

Neuromuscular diseases usually manifest as abnormalities involving motor neurons, neuromuscular junctions, and skeletal muscle (SkM) in postnatal stage. Present in vitro models of neuromuscular interactions require a long time and lack neuroglia involvement. Our study aimed to construct rodent bioengineered spinal cord neural network-skeletal muscle (NN-SkM) assembloids to elucidate the interactions between spinal cord neural stem cells (SC-NSCs) and SkM cells and their biological effects on the development and maturation of postnatal spinal cord motor neural circuits.

Multi-modal framework for battery state of health evaluation using open-source electric vehicle data.

Accurate, practical, and robust evaluation of the battery state of health is crucial to the efficient and reliable operation of electric vehicles. However, the limited availability of large-scale, high-quality field data hinders the development of the battery management system for state of health estimation, lifetime prediction, and fault detection in various applications. In this work, to gain insights into underlying factors limiting battery management system performance in real-world vehicles, we analyze the operational data of 300 diverse electric vehicles over three years to understand the disparities between field data and laboratory battery test data and their effect on state of health estimation.

2-dodecyl-6-methoxycyclohexa-2,5-diene-1,4-dione protects against MPP-induced neurotoxicity by ameliorating oxidative stress, apoptosis and autophagy in SH-SY5Y cells.

2-dodecyl-6-methoxycyclohexa-2,5-diene-1,4-dione (DMDD) is a cyclohexanedione compound extracted from the roots of Averrhoa carambola L. Several studies have documented its beneficial effects on diabetes, Alzheimer's disease, and cancer. However, its potential neuroprotective effects on Parkinson's disease (PD) have not yet been explored.