Neural correlates of music familiarity and likability in hospital noise masking: A functional near-infrared spectroscopy study.

Subjective factors of music have been proven to significantly influence the effect of music masking, while the neural mechanism of music masking is unknown. This study aims to explore the neural mechanism by which music masking improves subjective perception of noise in the population. A total of 40 healthy subjects were recruited for both the subjective evaluation and functional near-infrared spectroscopy scanning during music masking of hospital noise.

Noise characteristics and its influence analysis of the waiting areas in a Chinese children's hospital.

Compared to the general hospital, the children's hospital has significantly higher noise levels. This seriously influences hospital environment quality and medical service level. The noise characteristic and its influence were studied with field measurements and questionnaire surveys conducted in Kunming Children's Hospital.

Identifying , and as Baicalein's Potential Hub Targets in Parkinson's Disease-related α-synuclein-mediated Pathways by Integrated Bioinformatics Strategies.

Background: The overexpression, accumulation, and cell-to-cell transmission of α-synuclein leads to the deterioration of Parkinson's disease (PD). Previous studies suggest that Baicalein (BAI) can bind to α-synuclein and inhibit α-synuclein aggregation and secretion. However, it is still unclear whether BAI can intervene with the pathogenic molecules in α-synuclein-mediated PD pathways beyond directly targeting α-synuclein per se.

Ozone pollution mitigation in guangxi (south China) driven by meteorology and anthropogenic emissions during the COVID-19 lockdown.

With the implementation of COVID-19 restrictions and consequent improvement in air quality due to the nationwide lockdown, ozone (O) pollution was generally amplified in China. However, the O levels throughout the Guangxi region of South China showed a clear downward trend during the lockdown. To better understand this unusual phenomenon, we investigated the characteristics of conventional pollutants, the influence of meteorological and anthropogenic factors quantified by a multiple linear regression (MLR) model, and the impact of local sources and long-range transport based on a continuous emission monitoring system (CEMS) and the HYSPLIT model.