Establishment and Verification of an Artificial Intelligence Prediction Model for Children With Sepsis.

BACKGROUND: Early identification of high-risk groups of children with sepsis is beneficial to reduce sepsis mortality. This article used artificial intelligence (AI) technology to predict the risk of death effectively and quickly in children with sepsis in the pediatric intensive care unit (PICU). STUDY DESIGN: This retrospective observational study was conducted in the PICUs of the First Affiliated Hospital of Sun Yat-sen University from December 2016 to June 2019 and Shenzhen Children's Hospital from January 2019 to July 2020. The children were divided into a death group and a survival group. Different machine language (ML) models were used to predict the risk of death in children with sepsis. RESULTS: A total of 671 children with sepsis were enrolled. The accuracy (ACC) of the artificial neural network model was better than that of support vector machine, logical regression analysis, Bayesian, K nearest neighbor method and decision tree models, with a training set ACC of 0.99 and a test set ACC of 0.96. CONCLUSIONS: The AI model can be used to predict the risk of death due to sepsis in children in the PICU, and the artificial neural network model is better than other AI models in predicting mortality risk.

Cellulose nanofiber/MXene (Ti3C2Tx)/liquid metal film as a highly performance and flexible electrode material for supercapacitors.

In recent times, there has been significant interest in the utilization of cellulose nanofiber (CNF) films as the foundation for supercapacitors due to their three-dimensional structure, flexibility and eco-friendliness. An ultrasonic and vacuum filtration method was used to prepare a hybrid film consisting of MXene (Ti3C2Tx), CNF and liquid metal (LM). The combination of CNF and LM with MXene produces a porous structure with higher electrical conductivity, which facilitates the transportation of ions and electrons within the composition and confers the material with heightened electrochemical properties. The CNF/MXene/LM electrode has a significant area capacitance of 871.3 mF cm-2 at a current density of 5 mA cm-2. The hybrid film demonstrates excellent stability, maintaining a high conductivity of 546.4 S∙cm-1 and retaining 96.9 % capacitance after 2000 cycles at a current density of 10 mA cm-2. By utilizing the thin film as an electrode, a high-performance quasi-solid supercapacitor was fabricated, with a remarkably thin thickness of only 0.319 mm. Supercapacitors show exceptional electrical properties, including a surface-specific capacitance of 188.2 mF cm-2 at a current density of 5 mA cm-2. This study indicates that flexible electrodes made from cellulose nanofiber have extensive potential in the realm of supercapacitors.

Predicting Severity in Hypertriglyceridemia-Induced Acute Pancreatitis: The Role of Neutrophils, Calcium, and Apolipoproteins.

BACKGROUND Hypertriglyceridemia-induced acute pancreatitis (HTG-AP), representing 10% of all acute pancreatitis cases, is characterized by younger onset age and more severe progression, often leading to higher ICU admission rates. This condition poses a significant challenge due to its rapid progression and the potential for severe complications, including multiple organ failure. HTG-AP is distinct from other forms of pancreatitis, such as those caused by cholelithiasis or alcohol, in terms of clinical presentation and outcomes. It's essential to identify early markers that can predict the severity of HTG-AP to improve patient management and outcomes. MATERIAL AND METHODS This study divided 127 HTG-AP patients into mild acute pancreatitis (MAP, n=71) and moderate-to-severe acute pancreatitis (MSAP/SAP, n=56) groups. Blood biological indicators within the first 24 hours of admission were analyzed. Risk factors for HTG-AP progression were determined using binary logistic regression and ROC curves. RESULTS Elevated levels of HCT, NLR, TBI, DBI, AST, Cre, and AMS were noted in the MSAP/SAP group, with lower levels of LYM, Na⁺, Ca²âº, ApoA, and ApoB compared to the MAP group (p<0.05). NEUT%, Ca²âº, ApoA, and ApoB were significantly linked with HTG-AP severity. Their combined ROC analysis yielded an area of 0.81, with a sensitivity of 61.8% and specificity of 90%. CONCLUSIONS NEUT%, Ca²âº, ApoA, and ApoB are significant risk factors for progressing to MSAP/SAP in HTG-AP. Their combined assessment provides a reliable predictive measure for early intervention in patients at risk of severe progression.