ABSTRACT
@#Abstract: Objective To predict the potential distribution of talaromycosis marneffei (TSM) and analyze its driving factors, so as to provide evidence for the surveillance and prevention of this disease. Methods The data of all laboratory-confirmed, non-duplicating TSM published in the English and Chinese literature from the first case in January 1964 to December 2018 was collected. A Maxent ecology model using environmental variables, Rhizomys distribution and HIV/AIDS epidemic was developed to forecast ecological niche of TSM worldwide, as well as identify the driving factors. Results A total of 705 articles (477 in Chinese and 228 in English) were obtained during the study period. After excluding imported cases, a total of 100 foci information were included in the model. The area under the receiver operating characteristic (ROC) curve (AUC) of the model was 0.997 for the training set and 0.991 for the test set. Maxent model revealed that Rhizomys distribution, mean temperature of warmest quarter, precipitation of wettest month, HIV/AIDS epidemic and mean temperature of driest quarter were the top 5 important variables affecting TSM distribution. In addition to identifying traditional TSM endemic areas (South of the Yangtze River in China, Southeast Asian, North and Northeast India), other potential endemic areas were also identified, including parts of the North of the Yangtze River, Central America, West Coast of Africa, East Coast of South America, the Korean Peninsula and Japan. Conclusion Our finding has discovered hidden high-risk areas and provided insights about driving factors of TSM distribution, which will help inform surveillance strategies and improve the effectiveness of public health interventions against TM infections.
ABSTRACT
BACKGROUND: Platelet-rich plasma (PRP) is a plasma component of autologous blood containing a high concentration of platelets. PRP is used to promote healing of damaged tissues. However, there are not many studies on the composition and expression patterns of active proteins in PRP. The purpose of this study was to identify unknown factors that contribute to tissue healing by proteomic analysis of proteins in PRP.METHODS: Three men in their 30s with no basal disease participated in this study. All identified proteins were classified for tissue healing-related functions on the basis of the gene ontology analysis of adhesion molecule with Ig-like domain 2 (AmiGO2). PRP was prepared by using the ACP kit and GPS III kit.RESULTS: We identified a total of 125 proteins related to wound healing, along with three proteins for angiogenesis involved in wound healing, two proteins for fibroblast migration, four proteins for collagen biosynthesis process, two proteins for glycosaminoglycan biosynthesis process, and 13 proteins for glycosaminoglycan binding. So, in addition to the growth factors that have been already known to be involved in tissue healing, 25 new proteins were identified.CONCLUSIONS: We identified the unknown proteins associated with tissue healing in PRP. Our findings may serve as a foundation for the establishment of basic medical evidence for PRP applications.