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N6‐methyladenosine (m6A) is the most prevalent internal RNA modification in mammals. However, limited research has been conducted on the role of m6A in coronary artery disease (CAD). We conducted methylated RNA immunoprecipitation sequencing and RNA sequencing to obtain a genome‐wide profile of m6A‐modified long noncoding RNAs (lncRNAs) in human coronary artery smooth muscle cells either exposed to oxidized low‐density lipoprotein treatment or not, and the characteristics of the expression profiles were explored using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The predictive effects of seven selected lncRNAs on CAD were evaluated in peripheral blood mononuclear cells (PBMCs). The differentially m6A‐modified and expressed lncRNAs related genes were predominantly enriched in small GTPase‐mediated signal transduction, ErbB signaling, and Rap1 signaling. Additionally, the expression levels of uc003pes.1, ENST00000422847, and NR_110155 were significantly associated with CAD, with uc003pes.1 identified as an independent risk factor and NR_110155 as an independent protective factor for CAD. NR_110155 and uc003pes.1 in PBMCs have the potential to serve as biomarkers for predicting CAD. [ABSTRACT FROM AUTHOR]

Background: Online hospitals are part of an innovative model that allows China to explore telemedicine services based on national conditions with large populations, uneven distribution of medical resources, and lack of quality medical resources, especially among residents needing to be protected from COVID-19 infection. Objective: In this study, we built a hypothesis model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) in order to analyze the factors that may influence patients' willingness to use mobile medical services. This research was designed to assist in the development of mobile medical services. Residents who do not live in urban areas and cannot access medical assistance would greatly benefit from this research, as they could immediately go to the online hospital when needed. Methods: A cross-sectional study based at the West China Hospital, Sichuan University, was conducted in July 2020. A total of 407 respondents, 18 to 59 years old, in Western China were recruited by convenience sampling. We also conducted an empirical test for the hypothesis model and applied structural equation modeling to estimate the significance of path coefficients so that we could better understand the influencing factors. Results: Out of 407 respondents, 95 (23.3%) were aware of online hospitals, while 312 (76.7%) indicated that they have never heard of online hospitals before. Gender (P =.048) and education level (P =.04) affected people's willingness to use online hospitals, and both of these factors promoted the use of online hospitals (odds ratio [OR] 2.844, 95% CI 1.010-8.003, and OR 2.187, 95% CI 1.031-4.636, respectively). According to structural equation modeling, the results of the path coefficient analysis indicated that performance expectancy, effort expectancy, and facilitating conditions have positive effects on patients' willingness to use online hospitals. Conclusions: The goal of our research was to determine the factors that influence patients' awareness and willingness to use online hospitals. Currently, the public's awareness and usage of online hospitals is low. In fact, effort expectancy was the most important factor that influenced the use of online hospitals; being female and having a high education also played positive roles toward the use of mobile medical services. JMIR Mhealth Uhealth 2021;9(2):e25960 doi:10.2196/25960 [ABSTRACT FROM AUTHOR]