Publications by authors named "H Pei"

Background: Hypertrophic scar (HS) is a fibroproliferative disorder resulting from abnormal healing of skin tissue after injury. Although various therapies are currently employed in clinical to treat HSs, there is no widely accepted standard therapy. Micro-plasma radiofrequency (MPR) and autologous chyle fat grafting are emerging treatments for this condition, and they have demonstrated promising therapeutic outcomes in clinical applications.

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Background: Retinoblastoma (Rb), the primary intraocular malignancy in children, poses significant risks, yet its overall burden remains inadequately assessed. This study aims to analyze global Rb trends using Global Burden of Disease, Injuries, and Risk Factors study (GBD) 2021 data.

Methods: GBD 2021 data was analyzed to assess Rb incidence, mortality, and disability-adjusted life years (DALYs) from 1990 to 2021.

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Background: The low-pressure, hypoxic environment characteristic of high-altitude regions significantly affects the cardiovascular and autonomic nervous system functions of individuals, consequently impairing their sleep quality. Heart rate variability, a non-invasive indicator of autonomic nervous system activity and balance within the cardiovascular system, has not been thoroughly investigated in terms of its patterns during acclimatization and de-acclimatization phases for individuals traveling to and residing in high-altitude areas and its relationship with sleep stability.

Methods: Data was collected from 22 medical staff members who traveled from Chengdu to Yecheng, with measurements taken before leaving Chengdu, 1 week in Yecheng, 3 months in Yecheng, and 1 week after returning to Chengdu.

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Thermophilic proteins, mesophiles proteins and psychrophilic proteins have wide industrial applications, as enzymes with different optimal temperatures are often needed for different purposes. Convenient methods are needed to determine the optimal temperatures for proteins; however, laboratory methods for this purpose are time-consuming and laborious, and existing machine learning methods can only perform binary classification of thermophilic and non-thermophilic proteins, or psychrophilic and non-psychrophilic proteins. Here, we developed a deep learning model, PSTP-BERT, based on protein sequences that can directly perform Three classes identification of thermophilic, mesophilic, and psychrophilic proteins.

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Air pollution is closely associated with the development of multiple metabolic diseases. Circadian syndrome (CircS), as an extended concept of metabolic syndrome (MetS), has been proven to be a better predictor of metabolic diseases than MetS. However, the relationship between volatile organic compounds (VOCs) and CircS in pre- and postmenopausal remains unclear.

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