Early prediction of sepsis-induced respiratory tract infection using a biomarker-based machine-learning algorithm.

Early and differential diagnosis of sepsis is essential to avoid unnecessary antibiotic use and further reduce patient morbidity and mortality. Here, we aimed to identify predictors of sepsis and advance a machine-learning strategy to predict sepsis-induced respiratory tract infection (RTI). Patients with sepsis and RTI were selected via retrospective analysis, and essential population characteristics and laboratory parameters were recorded.

Developing a machine learning prediction algorithm for early differentiation of urosepsis from urinary tract infection.

Objectives: Early recognition and timely intervention for urosepsis are key to reducing morbidity and mortality. Blood culture has low sensitivity, and a long turnaround time makes meeting the needs of clinical diagnosis difficult. This study aimed to use biomarkers to build a machine learning model for early prediction of urosepsis.

Four Biomarkers-Based Artificial Neural Network Model for Accurate Early Prediction of Bacteremia with Low-level Procalcitonin.

Objective: Procalcitonin levels above 2.0 ng/mL are associated with a higher risk of severe sepsis. Bacteremia with procalcitonin levels lower than 2.

Genetic variants in class II transactivator are associated with chronic hepatitis B virus infection in the Han Chinese population.

Class II transactivator (CIITA) is a master regulator of MHC gene expression and plays a role in inducing the expression of other immune system genes, including IL-4, IL-10 and Fas ligand, as well as more than 60 other immunologically significant genes. We used CIITA as a candidate gene to analyse whether any single-nucleotide polymorphisms (SNPs) are associated with chronic hepatitis B virus (HBV) infection. In total, 773 patients with chronic HBV infection were enrolled in this hospital-based case-control study.

Meta-analysis of the correlation between the rs17401966 polymorphism in kinesin family member 1B and susceptibility to hepatitis B virus related hepatocellular carcinoma.

Background/aims: The association between the kinesin family member 1B (KIF1B) gene polymorphism and the risk of hepatitis B virus-related hepatocellular carcinoma (HCC) has been investigated in many peer-reviewed studies. However, scholars have failed to replicate these results in validation tests. The purpose of the present study was to explore whether the KIF1B rs17401966 polymorphism was associated with susceptibility to HCC.

Clinical significance of periodic detection of hepatitis B virus YVDD mutation by ultrasensitive real-time amplification refractory mutation system quantitative PCR during lamivudine treatment in patients with chronic hepatitis B.

Monitoring hepatitis B virus (HBV) mutants periodically during nucleoside analogue treatment is of great clinical significance, particularly in persistently HBV DNA-positive patients. However, few studies have investigated the dynamic changes of HBV YMDD (Tyr-Met-Asp-Asp) and YVDD (Tyr-Val-Asp-Asp) populations in chronic hepatitis B (CHB) patients whilst undergoing lamivudine (LMV) treatment. In this study, we sought to investigate the dynamic changes of HBV YMDD and YVDD variants by ultrasensitive real-time amplification refractory mutation system quantitative PCR (RT-ARMS-qPCR) and evaluate its significance for changes in the treatment of CHB patients.

[Studies on the association of single nucleotide polymorphisms of HLA-DP and DQ genes with the outcome of chronic hepatitis B virus infection].

Objective: To investigate the association of single nucleotide polymorphisms in the HLA-DP and DQ genes with the outcome of chronic hepatitis B virus infection.

Methods: Two hundred and four healthy subjects, 255 clearance subjects, 204 asymptomatic HBV carriers (AsC), 136 chronic hepatitis B (CHB), 68 liver cirrhosis (LC) and hepatocellular carcinoma (HCC) were enrolled. Genotypes of rs3077, rs9277535 and rs2647050 were determined by sequence specific primers-PCR (PCR-SSP).

Establishment of real time allele specific locked nucleic acid quantitative PCR for detection of HBV YIDD (ATT) mutation and evaluation of its application.

Background: Long-term use of nucleos(t)ide analogues can increase risk of HBV drug-resistance mutations. The rtM204I (ATT coding for isoleucine) is one of the most important resistance mutation sites. Establishing a simple, rapid, reliable and highly sensitive assay to detect the resistant mutants as early as possible is of great clinical significance.