A bibliometric and visual analysis of Parkinson's disease sleep disorders: articles from 2008 to 2023.

Objective: Sleep disorder is a common non-motor symptom (NMS) of Parkinson's disease. However, the global research focus on Parkinson's sleep-related disorders (PDSDs) and future trends remains unclear. Currently, there is no bibliometric analysis of PDSDs.

A bibliometric analysis of international publication trends in brain atrophy research (2008-2023).

Background: Brain atrophy is a type of neurological and psychiatric disorder characterized by a decrease in brain tissue volume and weight for various reasons and can have a serious impact on the quality of life of patients. Although there are many studies on brain atrophy, there is a lack of relevant bibliometric studies. Therefore, this study aims to provide a visual analysis of global trends in brain atrophy research over the past 16 years.

Assessing the role of combination of stem cell and light-based treatments on skin wound repair: A meta-analysis.

The meta-analysis aims to evaluate and compare the impact of the combination of stem cells (SCs) and light-based treatments (LBTs) on skin wound (SW) repair. Examinations comparing SCs to LBT with SCs for SW repair was among the meta-analysis from various languages that met the inclusion criteria. Using continuous random-effect models, the results of these investigations were examined, and the mean difference (MD) with 95% confidence intervals was computed (CIs).

Automated polyp segmentation for colonoscopy images: A method based on convolutional neural networks and ensemble learning.

Purpose: To automatically and efficiently segment the lesion area of the colonoscopy polyp image, a polyp segmentation method has been presented.

Methods: An ensemble model of pretrained convolutional neural networks was proposed, using Unet-VGG, SegNet-VGG, and PSPNet. Firstly, the Unet-VGG is obtained by the first 10 layers of VGG16 as the contraction path of the left half of the Unet.

ATP Binding Cassette Subfamily A Member 2 (ABCA2) Expression and Methylation are Associated with Alzheimer's Disease.

BACKGROUND ABCA2 has been genetically linked to Alzheimer's disease (AD) risk, but its mRNA expression and epigenetics in AD have not been investigated. MATERIAL AND METHODS To explore the diagnosis value of ABCA2 mRNA expression in AD, 2 datasets GES15222 and GSE33000 containing expression profile of brain cortex tissues and 2 datasets GSE63063 (Cohort 1) and GSE63063 (Cohort 2) containing expression profile of blood were downloaded from the NCBI GEO database and analyzed by receiver operating characteristic curve (ROC) analyses and logistic regression. The ABCA2 co-expressed genes were also analyzed by GO annotation to investigate the potential molecular mechanisms.