In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.

Q: Super-enhancers (SEs) are large clusters of transcriptional enhancers that are co-occupied by multiple lineage-specific transcription factors driving expression of genes that define cell identity. In embryonic stem cells (ESCs), SEs are highly enriched for the core pluripotency factors Oct4, Sox2, and Nanog. In this study, we sought to dissect the molecular control mechanism of SE activity in pluripotency and reprogramming. Starting from a protein interaction network surrounding Sox2, we identified Tex10 as a key pluripotency factor that plays a functionally significant role in ESC self-renewal, early embryo development, and reprogramming. Tex10 is enriched at SEs in a Sox2-dependent manner and coordinates histone acetylation and DNA demethylation at SEs. Tex10 activity is also important for pluripotency and reprogramming in human cells. Our study therefore highlights Tex10 as a core component of the pluripotency network and sheds light on its role in epigenetic control of SE activity for cell fate determination.

A: Tex10 Coordinates Epigenetic Control of Super-Enhancer Activity in Pluripotency and Reprogramming.
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Q: BACKGROUND Chronic obstructive pulmonary disease (COPD) has a high prevalence rate in Germany and a further increase is expected within the next years. Although risk factors on an individual level are widely understood, only little is known about the spatial heterogeneity and population-based risk factors of COPD. Background knowledge about broader, population-based processes could help to plan the future provision of healthcare and prevention strategies more aligned to the expected demand. The aim of this study is to analyze how the prevalence of COPD varies across northeastern Germany on the smallest spatial-scale possible and to identify the location-specific population-based risk factors using health insurance claims of the AOK Nordost.
METHODS To visualize the spatial distribution of COPD prevalence at the level of municipalities and urban districts, we used the conditional autoregressive Besag-York-Mollie (BYM) model. Geographically weighted regression modelling (GWR) was applied to analyze the location-specific ecological risk factors for COPD.
RESULTS The sex- and age-adjusted prevalence of COPD was 6.5% in 2012 and varied widely across northeastern Germany. Population-based risk factors consist of the proportions of insurants aged 65 and older, insurants with migration background, household size and area deprivation. The results of the GWR model revealed that the population at risk for COPD varies considerably across northeastern Germany.
CONCLUSION Area deprivation has a direct and an indirect influence on the prevalence of COPD. Persons ageing in socially disadvantaged areas have a higher chance of developing COPD, even when they are not necessarily directly affected by deprivation on an individual level. This underlines the importance of considering the impact of area deprivation on health for planning of healthcare. Additionally, our results reveal that in some parts of the study area, insurants with migration background and persons living in multi-persons households are at elevated risk of COPD.

A: Who is where at risk for Chronic Obstructive Pulmonary Disease? A spatial epidemiological analysis of health insurance claims for COPD in Northeastern Germany
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Q: OBJECTIVES Despite recognition of the important influence of environmental determinants on physical activity patterns, minimal empirical research has been done to assess the impact of environmental/contextual determinants of physical activity. This article aims to investigate environmental and sociodemographic determinants of physical activity and inactivity patterns among subpopulations of US adolescents. We define environmental determinants as modifiable factors in the physical environment that impose a direct influence on the opportunity to engage in physical activity. The present research examines environmental and sociodemographic determinants of physical activity and inactivity with the implication that these findings can point toward societal-level intervention strategies for increasing physical activity and decreasing inactivity among adolescents. STUDY DESIGN AND METHODOLOGY The study population consists of nationally representative data from the 1996 National Longitudinal Study of Adolescent Health on 17 766 US adolescents enrolled in US middle and high schools (including 3933 non-Hispanic blacks, 3148 Hispanics, and 1337 Asians). Hours/week of inactivity (TV/video viewing and video/computer games) and times/week of moderate to vigorous physical activity were collected by questionnaire. Outcome variables were moderate to vigorous physical activity and inactivity, which were broken into categories (physical activity: 0-2 times/week, 3-4 times/week, and >/=5 times/week; inactivity: 0-10 hours/week, 11-24 hours/week, and >/=25 hours/week). Sociodemographic and environmental correlates of physical activity and inactivity were used as exposure and control variables and included sex, age, urban residence, participation in school physical education program, use of community recreation center, total reported incidents of serious crime in neighborhood, socioeconomic status, ethnicity, generation of residence in the United States, presence of mother/father in household, pregnancy status, work status, in-school status, region, and month of interview. Logistic regression models of high versus low and medium physical activity and inactivity were used to investigate sex and ethnic interactions in relation to environmental and sociodemographic factors to examine evidence for the potential impact of physical education and recreation programs and sociodemographic factors on physical activity and inactivity patterns.
RESULTS Moderate to vigorous physical activity was lower and inactivity higher for non-Hispanic black and Hispanic adolescents. Participation in school physical education programs was considerably low for these adolescents and decreased with age. Participation in daily school physical education (PE) program classes (adjusted odds ratio [AOR]: 2.21; confidence interval [CI]: 1.82-2.68) and use of a community recreation center (AOR: 1.75; CI: 1.56-1.96) were associated with an increased likelihood of engaging in high level moderate to vigorous physical activity. Maternal education was inversely associated with high inactivity patterns; for example, having a mother with a graduate or professional degree was associated with an AOR of.61 (CI:.48-.76) for high inactivity. High family income was associated with increased moderate to vigorous physical activity (AOR: 1.43; CI: 1.22-1.67) and decreased inactivity (AOR:.70; CI:.59-.82). High neighborhood serious crime level was associated with a decreased likelihood of falling in the highest category of moderate to vigorous physical activity (AOR:.77; CI:.66-.91).
CONCLUSIONS These results show important associations between modifiable environmental factors, such as participation in school PE and community recreation programs, with activity patterns of adolescents. Despite the marked and significant impact of participation in school PE programs on physical activity patterns of US adolescents, few adolescents participated in such school PE programs; only 21.3% of all adolescents

A:
Determinants of adolescent physical activity and inactivity patterns.
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