Publications by authors named "R T D'Aquila"
Background: Syphilis rates in the United States have dramatically increased in recent years and are high among young men who have sex with men and transgender women. Yet, few studies have examined a wide-range of risk factors for syphilis incidence prospectively in young sexual and gender minority (YSGM) populations in the U.S.
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- A study involving 1,296 sexual and gender minority people assigned male at birth in Chicago highlighted an increasing trend in methamphetamine use from 2015 to 2023, particularly among those aged 25 and older.
- The average age for first-time use of methamphetamine was found to be around 23.9 years.
- The research indicated that those with a history of HIV diagnosis had a two-fold higher risk of initiating methamphetamine use, and higher inflammation levels (measured by C-reactive protein) also increased the likelihood of first-time use.
Heart failure with preserved ejection fraction (HFpEF) is commonly found in persons living with HIV (PLWH) even when antiretroviral therapy suppresses HIV viremia. However, studying this condition has been challenging because an appropriate animal model is not available. In this article, we studied calcium transient in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) in culture to simulate the cardiomyocyte relaxation defect noted in PLWH and HFpEF and assess whether various drugs have an effect.
View Article and Find Full Text PDFBackground: We estimated the predictive value of rectal (bacterial sexually transmitted infection [bSTI]) pathogen detection for future HIV seroconversion among young adult sexual and gender minorities (YSGMs) assigned male at birth (AMAB).
Methods: Data were collected between March 2018 and August 2022 from RADAR, a longitudinal cohort study of YSGMs AMAB living in the Chicago metropolitan area (n = 1022). Rates of rectal bSTIs and the proportion of self-reported rectal bSTI symptoms are reported.
Introduction: The rapid development of artificial intelligence (AI) in healthcare has exposed the unmet need for growing a multidisciplinary workforce that can collaborate effectively in the learning health systems. Maximizing the synergy among multiple teams is critical for Collaborative AI in Healthcare.
Methods: We have developed a series of data, tools, and educational resources for cultivating the next generation of multidisciplinary workforce for Collaborative AI in Healthcare.