Pre-exposure prophylaxis uptake for high-risk men who have sex with men in China: a multi-city cross-sectional survey.

BACKGROUND: Pre-exposure prophylaxis (PrEP) is a proven biomedical strategy to prevent HIV transmission among men who have sex with men (MSM). Despite oral PrEP is safe and effective in MSM, the use of PrEP has been discouraging, especially in high-risk MSM. And there are no relevant studies showing the use of PrEP in high-risk MSM. The purpose of this study was to get the rate of PrEP use and the factors influencing PrEP use among high-risk MSM. METHODS: A cross-sectional study was conducted through an electronic questionnaire on the "i guardian Platform", and "snowballing" method was used to recruit MSM in six cities in China, including Beijing, Shenzhen, Chengdu, Changsha, Jinan and Nanjing in China, from January to April 2021. Univariate and multivariate logistic regression analysis were used to analyze the factors associated with the use of PrEP among high-risk MSM who had heard about PrEP. RESULTS: Among the 1865 high-risk MSM who had heard of PrEP, the rates of those who were willing to use PrEP, had knowledge awareness of PrEP, and had used PrEP were 96.7%, 24.7%, and 22.4%, respectively. Multivariate logistic regression analysis of PrEP use in high-risk MSM showed that more PrEP was used by those who were 26 years or older (OR = 1.86, 95%CI 1.17 ~ 2.99), had master degree or above (OR = 2.37, 95% CI 1.21 ~ 4.72), had unstable work (OR = 1.86, 95% CI 1.16 ~ 2.96), had tested five or more HIV times in the past year (OR = 3.09, 95% CI 1.65 ~ 6.04), had consulted PrEP (OR = 22.05, 95% CI 14.87 ~ 33.91) and had PrEP knowledge awareness (OR = 1.90, 95% CI 1.41 ~ 2.55) (P < 0.05). CONCLUSIONS: The rate of PrEP use in high-risk MSM was relatively low. PrEP was used more by high-risk MSM with unstable jobs, higher education, frequent HIV testing, and PrEP counseling. Public education on PrEP for MSM should continue to be enhanced to help them use PrEP in a timely and accurate manner.

[Data Mining for CVs Spectra in LAMOST-DR1].

LAMOST-DR1 is the first data released by Guoshoujing telescop, which has the largest number of stellar spectra in the world at present. The data set provides the data source for searching for special and rare celestial objects like cataclysmic variable stars.Meanwhile, it requires more advanced astronomical data processing methods and techniques. A data mining method for cataclysmic variable spectra in massive spectra data is proposed in this paper. Different types of celestial spectra show obvious difference in the feature space constructed with Laplacian Eigenmap method. The parameters of artificial neural network are optimized with particle swarm optimization method and the total LAMOST-DR1 data is processed. 7 cataclysmic variable star spectra are found in the experiment including 2 dwarf nova, 2 nova like variables and a highly polarized AM Her type. The newly found spectra enrich the current cataclysmic variable spectra library. The experiment is the first attempt of searching for cataclysmic variable star spectra with Guoshoujing telescope data and the results show that our approach is feasible in LAMOST data. This method is also applicable for mining other special celestial objects in sky survey telescope data.