Correlates of Sun Protection Behaviors in Racially and Ethnically Diverse U.S. Adults

Although skin cancer incidence is highest among non-Hispanic Whites, minority populations are often diagnosed with more advanced stage disease and are more likely to experience poor outcomes. Fewer people of color do not practice primary prevention of skin cancer according to recommendations, but public health education and interventions to promote sun protection behaviors have consistently targeted non-Hispanic Whites. This study examines performance of sun protection behaviors in a multiethnic sample and whether demographic, lifestyle and psychosocial predictors of these behaviors differ by race and ethnicity. In this study, a probability-based sample of 1742 adults completed an online survey in 2015. Main outcomes of interest included sunscreen use, wearing a sleeved shirt, and seeking shade. We stratified the sample into racial/ethnic groups (White, Black, Hispanic, Asian) and investigated demographic, lifestyle and psychosocial correlates of these behaviors in each group. Differences in adjusted estimates from each behavior-specific model were tested across strata. Racial/ethnic groups were significantly different in regards to sunscreen use and wearing a sleeved shirt, but similarly engaged in seeking shade. Results from multivariate ordered logistic regression models for each behavior revealed important demographic, lifestyle and psychosocial predictors and the importance of some demographic correlates varied between racial/ethnic groups. This study provides insight into the practice and correlates of skin cancer prevention among a multiethnic sample. Our findings suggest that targeting public health education efforts and interventions to promote sun protection in minority populations may be a beneficial approach to addressing heightened skin cancer morbidity and mortality in these groups

Generalized Cross-Validation as a Method of Hyperparameter Search for MTGV Regularization

The concept of generalized cross-validation (GCV) is applied to modified total generalized variation (MTGV) regularization. Current implementations of the MTGV regularization rely on manual (or semi-manual) hyperparameter optimization, which is both time-consuming and subject to bias. The combination of MTGV-regularization and GCV allows for a straightforward hyperparameter search during regularization. This significantly increases the efficiency of the MTGV-method, because it limits the number of hyperparameters, which have to be tested and, improves the practicality of MTGV regularization as a standard technique for inversion of NMR signals. The combined method is applied to simulated and experimental NMR data and the resulting reconstructed distributions are presented. It is shown that for all data sets studied the proposed combination of MTGV and GCV minimizes the GCV score allowing an optimal hyperparameter choice

A Multi-Platform Metabolomics Approach Identifies Highly Specific Biomarkers of Bacterial Diversity in the Vagina of Pregnant and Non-Pregnant Women

Bacterial vaginosis (BV) increases transmission of HIV, enhances the risk of preterm labour, and is associated with malodour. Clinical diagnosis often relies on microscopy, which may not reflect the microbiota composition accurately. We use an untargeted metabolomics approach, whereby we normalize the weight of samples prior to analysis, to obtained precise measurements of metabolites in vaginal fluid. We identify biomarkers for BV with high sensitivity and specificity (AUC = 0.99) in a cohort of 131 pregnant and non-pregnant Rwandan women, and demonstrate that the vaginal metabolome is strongly associated with bacterial diversity. Metabolites associated with high diversity and clinical BV include 2-hydroxyisovalerate and γ-hydroxybutyrate (GHB), but not succinate, which is produced by both Lactobacillus crispatus and BV-associated anaerobes in vitro. Biomarkers associated with high diversity and clinical BV are independent of pregnancy status, and were validated in a blinded replication cohort from Tanzania (n = 45), where we predicted clinical BV with 91% accuracy. Correlations between the metabolome and microbiota identified Gardnerella vaginalis as a putative producer of GHB, and we demonstrate production by this species in vitro. This work illustrates how changes in community structure alter the chemical composition of the vagina, and identifies highly specific biomarkers for a common condition

Foot Symptoms are Independently Associated with Poor Self-Reported and Performance-Based Physical Function: The Johnston County Osteoarthritis Project

To examine associations of foot symptoms with self-reported and performance-based measures of physical function in a large, bi-racial, community-based sample of individuals ≥ 45 years old

Quantifying air quality co-benefits to industrial decarbonization: the local Air Emissions Tracking Atlas

IntroductionMany decarbonization technologies have the added co-benefit of reducing short-lived climate pollutants, such as particulate matter (PM), nitrogen oxides (NOx), and sulfur dioxide (SO2), creating a unique opportunity for identifying strategies that promote both climate change solutions and opportunities for air quality improvement. However, stakeholders and decision-makers may struggle to quantify how these co-benefits will impact public health for the communities most affected by industrial air pollution.MethodsTo address this problem, the LOCal Air Emissions Tracking Atlas (LOCAETA) fills a data availability and analysis gap by providing estimated air quality benefits from industrial decarbonization options, such as carbon capture and storage (CCS). These co-benefits are calculated using an algorithm that connects disparate datasets that separately report greenhouse gas emissions and other pollutants at U.S. industrial facilities.ResultsVersion 1.0 of LOCAETA displays the estimated primary PM2.5 emission reduction co-benefits from additional pretreatment equipment for CCS on industrial and power facilities across the state of Louisiana, as well as the potential for VOC and NH3 generation. The emission reductions are presented in the tool alongside facility pollutant emissions information and relevant air quality, environmental, demographic, and public health datasets, such as air toxics cancer risk, satellite and in situ pollutant measurements, and population vulnerability metrics.DiscussionLOCAETA enables regulators, policymakers, environmental justice communities, and industrial and commercial users to compare and contrast quantifiable public health benefits due to air quality impacts from various climate change mitigation strategies using a free and publicly-available tool. Additional pollutant reductions can be calculated using the same methodology and will be available in future versions of the tool

Vaginal Microbiome and Epithelial Gene Array in Post-Menopausal Women with Moderate to Severe Dryness

After menopause, many women experience vaginal dryness and atrophy of tissue, often attributed to the loss of estrogen. An understudied aspect of vaginal health in women who experience dryness due to atrophy is the role of the resident microbes. It is known that the microbiota has an important role in healthy vaginal homeostasis, including maintaining the pH balance and excluding pathogens. The objectives of this study were twofold: first to identify the microbiome of post-menopausal women with and without vaginal dryness and symptoms of atrophy; and secondly to examine any differences in epithelial gene expression associated with atrophy. The vaginal microbiome of 32 post-menopausal women was profiled using Illumina sequencing of the V6 region of the 16S rRNA gene. Sixteen subjects were selected for follow-up sampling every two weeks for 10 weeks. In addition, 10 epithelial RNA samples (6 healthy and 4 experiencing vaginal dryness) were acquired for gene expression analysis by Affymetrix Human Gene array. The microbiota abundance profiles were relatively stable over 10 weeks compared to previously published data on premenopausal women. There was an inverse correlation between Lactobacillus ratio and dryness and an increased bacterial diversity in women experiencing moderate to severe vaginal dryness. In healthy participants, Lactobacillus iners and L. crispatus were generally the most abundant, countering the long-held view that lactobacilli are absent or depleted in menopause. Vaginal dryness and atrophy were associated with down-regulation of human genes involved in maintenance of epithelial structure and barrier function, while those associated with inflammation were up-regulated consistent with the adverse clinical presentation

Hippocampal connectivity patterns echo macroscale cortical evolution in the primate brain

While the hippocampus is key for human cognitive abilities, it is also a phylogenetically old cortex and paradoxically considered evolutionarily preserved. Here, we introduce a comparative framework to quantify preservation and reconfiguration of hippocampal organisation in primate evolution, by analysing the hippocampus as an unfolded cortical surface that is geometrically matched across species. Our findings revealed an overall conservation of hippocampal macro- and micro-structure, which shows anterior-posterior and, perpendicularly, subfield-related organisational axes in both humans and macaques. However, while functional organisation in both species followed an anterior-posterior axis, we observed a marked reconfiguration in the latter across species, which mirrors a rudimentary integration of the default-mode-network in non-human primates. Here we show that microstructurally preserved regions like the hippocampus may still undergo functional reconfiguration in primate evolution, due to their embedding within heteromodal association networks

A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network

The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required