Gastric cancer (GC) is one of the most common clinical malignant tumors worldwide, with high morbidity and mortality. Presently, the overall response rate to immunotherapy is low, and current methods for predicting the prognosis of GC are not optimal. Therefore, novel biomarkers with accuracy, efficiency, stability, performance ratio, and wide clinical application are needed.
View Article and Find Full Text PDFBackground: GC is a highly heterogeneous tumor with different responses to immunotherapy, and the positive response depends on the unique interaction between the tumor and the tumor microenvironment (TME). However, the currently available methods for prognostic prediction are not satisfactory. Therefore, this study aims to construct a novel model that integrates relevant gene sets to predict the clinical efficacy of immunotherapy and the prognosis of GC patients based on machine learning.
View Article and Find Full Text PDFObjective: To test the hypothesis that Neutrophil gelatinase-associated lipocalin (NGAL) is an early biomarker for acute kidney injury (AKI) in patients after cardiac surgery.
Methods: 33 cases undergoing cardiac surgery were divided into AKI group and Non-AKI group according to the AKI criteria. The concentration of urine NGAL at different time points were measured.
Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi
December 2007