2-Acetamidophenol (2-AAP) Suppresses the Progression of Atherosclerosis by Alleviating Hyperlipidemia and Attenuating the Ferroptosis Pathway.

Hyperlipidemia and consequent endothelial inflammation, along with foam cell generation, promote the progression of atherosclerosis (AS). Here, we aimed to investigate the effects of 2-acetamidophenol (2-AAP), which was selected by zebrafish phenotypic screening, in alleviating AS by relieving hyperlipidemia and inhibiting foam cell formation, as well as the underlying mechanisms. In a zebrafish hyperlipidemia model, 2-AAP increased lipid-lowering efficacy; alleviated TC, TG, LDL-C, and MDA levels; elevated HDL-C and T-SOD levels; significantly improved intravascular macrophage aggregation; and improved blood flow.

End-to-End Depression Recognition Based on a One-Dimensional Convolution Neural Network Model Using Two-Lead ECG Signal.

Purpose: Depression is a common mental illness worldwide and has become an important public health problem. The current clinical diagnosis of depression mainly relies on the doctor's experience and subjective diagnosis, which results in the low diagnostic efficiency and insufficient objectivity of diagnostic results. Therefore, establishing a physiological and psychological model for computer-aided diagnosis is an urgent task.

Automated detection of clinical depression based on convolution neural network model.

As a common mental disorder, depression is placing an increasing burden on families and society. However, the current methods of depression detection have some limitations, and it is essential to find an objective and efficient method. With the development of automation and artificial intelligence, computer-aided diagnosis has attracted more and more attention.

Discrimination of vestibular function based on inertial sensors.

Background And Objective: Vestibular dysfunction, as a common disease or symptom, can cause abnormalities in gait and balance. Since the existing detection methods are static detection and cannot obtain the dynamic vestibular information of patients, this paper proposes a simple method for detecting vestibular dysfunction based on gait signals of subjects.

Methods: In our study, the walking patterns of dynamic gait index (DGI) and inertial sensor were adopted for the data acquisition.