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pregnancy. Copyright © 2020 Godbole et al.Children with neurodevelopmental disabilities (NDD) suffer poor oral health problems (OHP) leading to adverse health outcomes. We examined the association between NDD and OHP among children in the United States (US) ages 3-17 years using data from the National Survey of Children's Health (NSCH) 2016-17. The prevalence of OHP was 19.1%. Children with NDD had about 40% greater likelihood of poor oral health compared to their non-NDD counterparts (p less then 0.0001). Living at or above 200%-300% of the federal poverty level (FPL), private insurance coverage, and living with a least a college educated adult were found to be protective factors against poor oral health among children. Copyright © 2020 Yusuf et al.The aim of the study was to evaluate the association between fetal stillbirth and advanced maternal age in the United States (US). This was a population-based study using the Natality and Fetal Death datasets for the years 2003-2017. We built Cox proportional regression models to examine the likelihood of stillbirth among women aged ≥40 years. Out of a total of 57,273,305 births, stillbirth was observed in 302,522, yielding a stillbirth rate of 5 per 1000. After adjusting for confounders, women of advanced age (≥40 years) had a 40-50% greater risk of stillbirth compared to women 20-29 years of age. Copyright © 2020 Dongarwar et al.To estimate the risk of stillbirth following infertility treatment in the United States (US), we analyzed data from the US Natality and Fetal Death files from 2014 to 2017. We built Cox proportional regression models to generate adjusted hazard ratios (HR) for the risk of stillbirth among women who utilized various modalities of infertility treatment within the study period. Women who used any infertility treatment and, specifically, assisted reproductive technology (ART), had an elevated risk of stillbirth (HR 1.21, 95% CI1.09 -1.33) compared to women who did not use ART. We concluded that in this population, the risk of stillbirth was elevated among women using infertility treatment. Copyright © 2020 Dongarwar and Salihu.We examined the trends in stillbirth across gestational age in the United States (US).We conducted a trend analysis using the U.S. Natality and Fetal Death datasets covering 1982 and 2017. We compared the incidence and rates of stillbirth for term, all preterm, moderate-to-late preterm, very preterm, and extreme preterm phenotypes. The incidence of stillbirth decreased for the entire birth cohort over the 36-year period. https://www.selleckchem.com/PI3K.html The rates of overall, term, all preterm, very preterm and moderate-to-late preterm stillbirth decreased from 1982 to 2017; however, the rates for extreme preterm stillbirth increased by about 7.6% over the same study period. Copyright © 2020 Dongarwar et al.Background or Objectives Worldwide, men who have sex with men (MSM) and Transgender persons are vulnerable to psychosocial factors associated with high risk for HIV, and suffer disproportionately high rates of HIV/AIDS. In the United States (US), the House Ball Community (HBC) is a social network comprised predominantly of Black and Hispanic MSM and Transgender persons who reside in communal settings. This study explores Western New York HBC leaders' perceptions of HIV in their communities and their knowledge of HIV prevention strategies, including HIV vaccine trials. Methods The project was conducted using an exploratory approach based on the principles of Community-Based Participatory Research (CBPR) methods. An HIV behavioral risk assessment provided descriptive data, while qualitative measures explored psychosocial and behavioral factors. Results Behavioral assessments indicated high levels of risky sexual behaviors and experiences of violence. Interviews with 14 HBC leaders revealed that knowledge of HIV and local HIV vaccines trials was limited. Barriers to HIV knowledge included fear of peer judgment, having inaccurate information, and lack of formal education. Experiencing violence was identified as barrier to positive health behavior. Nevertheless, the HBC was described as a safe and creative space for marginalized MSM and Transgender youth. Conclusion and Global Health Implications Findings suggest that the interrelation between health problems and social context amplify HIV risk in the HBC. The organizational structure and resources of the HBC, and MSM/Transgender communities worldwide can be instrumental in informing interventions to address HIV-related risk behaviors and create appropriate recruitment tools to ensure their representation in HIV research. Copyright © 2020 Alio et al.Artificial Intelligence (AI) applications in medicine have grown considerably in recent years. AI in the forms of Machine Learning, Natural Language Processing, Expert Systems, Planning and Logistics methods, and Image Processing networks provide great analytical aptitude. While AI methods were first conceptualized for radiology, investigations today are established across all medical specialties. The necessity for proper infrastructure, skilled labor, and access to large, well-organized data sets has kept the majority of medical AI applications in higher-income countries. However, critical technological improvements, such as cloud computing and the near-ubiquity of smartphones, have paved the way for use of medical AI applications in resource-poor areas. Global health initiatives (GHI) have already begun to explore ways to leverage medical AI technologies to detect and mitigate public health inequities. For example, AI tools can help optimize vaccine delivery and community healthcare worker routes, thus enabling limited resources to have a maximal impact. Other promising AI tools have demonstrated an ability to predict burn healing time from smartphone photos; track regions of socioeconomic disparity combined with environmental trends to predict communicable disease outbreaks; and accurately predict pregnancy complications such as birth asphyxia in low resource settings with limited patient clinical data. In this commentary, we discuss the current state of AI-driven GHI and explore relevant lessons from past technology-centered GHI. Additionally, we propose a conceptual framework to guide the development of sustainable strategies for AI-driven GHI, and we outline areas for future research. Copyright © 2020 Hadley et al.