Clinical characteristics and prediction model of re-positive nucleic acid tests among Omicron infections by machine learning: a real-world study of 35,488 cases.

Background: During the Omicron BA.2 variant outbreak in Shanghai, China, from April to May 2022, PCR nucleic acid test re-positivity (TR) occurred frequently, yet the risk factors and predictive models for TR remain unclear. This study aims to identify the factors influencing Omicron TR and to develop machine learning models to predict TR risk.

Relationship of body mass index and kidney outcomes in patients with primary glomerulonephritis: A systematic review and meta-analysis.

Background: Primary glomerulonephritis, is a major contributor to the development of chronic kidney disease and end-stage renal disease. Previous studies on the relationship between overweight/obesity with primary glomerulonephritis in the chronic kidney disease was inconsistent. This study aimed to systematically review and meta-analyze the relationship between body mass index and adverse kidney outcomes in patients with primary glomerulonephritis.

Impact of body mass index on adverse kidney events in diabetes mellitus patients: A systematic-review and meta-analysis.

Background: The incidence of chronic kidney disease among patients with diabetes mellitus (DM) remains a global concern. Long-term obesity is known to possibly influence the development of type 2 diabetes mellitus. However, no previous meta-analysis has assessed the effects of body mass index (BMI) on adverse kidney events in patients with DM.

Deep evolutionary fusion neural network: a new prediction standard for infectious disease incidence rates.

Background: Previously, many methods have been used to predict the incidence trends of infectious diseases. There are numerous methods for predicting the incidence trends of infectious diseases, and they have exhibited varying degrees of success. However, there are a lack of prediction benchmarks that integrate linear and nonlinear methods and effectively use internet data.

Discovery of potential biomarkers for lung cancer classification based on human proteome microarrays using Stochastic Gradient Boosting approach.

Purpose: Early identification of lung cancer (LC) will considerably facilitate the intervention and prevention of LC. The human proteome micro-arrays approach can be used as a "liquid biopsy" to diagnose LC to complement conventional diagnosis, which needs advanced bioinformatics methods such as feature selection (FS) and refined machine learning models.

Methods: A two-stage FS methodology by infusing Pearson's Correlation (PC) with a univariate filter (SBF) or recursive feature elimination (RFE) was used to reduce the redundancy of the original dataset.

E-DU: Deep neural network for multimodal medical image segmentation based on semantic gap compensation.

Background: U-Net includes encoder, decoder and skip connection structures. It has become the benchmark network in medical image segmentation. However, the direct fusion of low-level and high-level convolution features with semantic gaps by traditional skip connections may lead to problems such as fuzzy generated feature maps and target region segmentation errors.

Integrating Internet multisource big data to predict the occurrence and development of COVID-19 cryptic transmission.

With the recent prevalence of COVID-19, cryptic transmission is worthy of attention and research. Early perception of the occurrence and development risk of cryptic transmission is an important part of controlling the spread of COVID-19. Previous relevant studies have limited data sources, and no effective analysis has been carried out on the occurrence and development of cryptic transmission.

Propranolol induces hemangioma endothelial cell apoptosis via a p53‑BAX mediated pathway.

The use of propranolol for the treatment of infantile hemangioma (IH) has been widely investigated in recent years. However, the underlying therapeutic mechanism of propranolol for the treatment of IH remains poorly understood. The aim of the present study was to investigate the expression of proteins regulated by cellular tumor antigen p53 (p53) in associated apoptosis pathways in IH endothelial cells (HemECs) treated with propranolol.

A 30-InDel Assay for Genetic Variation and Population Structure Analysis of Chinese Tujia Group.

In the present study, thirty autosomal insertion and deletion polymorphic loci were simultaneously amplified and genotyped in a multiplex system, and their allelic frequencies as well as several forensic parameters were obtained in a sample of 236 unrelated healthy Tujia individuals. All the loci were in Hardy-Weinberg equilibrium after applying a Bonferroni correction and all pair-wise loci showed no significant linkage disequilibrium. These loci were observed to be relatively informative and discriminating, quite efficient for forensic applications.

[Effects of NGF and estrogens on human hair follicle in vitro].

Objective: To observe the effects of NGF, estrogens and minoxidil on the growth of human hair follicle in vitro.

Methods: In a model of human hair follicle in vitro, the follicle was separately treated with the NGF, estrogens and minoxidil. The growth of the hair follicle was measured in length with an eyepiece micrometer.