Area-level and individual correlates of active transportation among adults in Germany: A population-based multilevel study

This study aimed at estimating the prevalence in adults of complying with the aerobic physical activity (PA) recommendation through transportation-related walking and cycling. Furthermore, potential determinants of transportation-related PA recommendation compliance were investigated. 10,872 men and 13,144 women aged 18 years or older participated in the cross-sectional 'German Health Update 2014/15 - EHIS' in Germany. Transportation-related walking and cycling were assessed using the European Health Interview Survey-Physical Activity Questionnaire. Three outcome indicators were constructed: walking, cycling, and total active transportation (>= 600 metabolic equivalent, MET-min/week). Associations were analyzed using multilevel regression analysis. Forty-two percent of men and 39% of women achieved >= 600 MET-min/week with total active transportation. The corresponding percentages for walking were 27% and 28% and for cycling 17% and 13%, respectively. Higher population density, older age, lower income, higher work-related and leisure-time PA, not being obese, and better self-perceived health were positively associated with transportation-related walking and cycling and total active transportation among both men and women. The promotion of walking and cycling among inactive people has great potential to increase PA in the general adult population and to comply with PA recommendations. Several correlates of active transportation were identified which should be considered when planning public health policies and interventions

A generalized framework to predict continuous scores from medical ordinal labels

Many variables of interest in clinical medicine, like disease severity, are recorded using discrete ordinal categories such as normal/mild/moderate/severe. These labels are used to train and evaluate disease severity prediction models. However, ordinal categories represent a simplification of an underlying continuous severity spectrum. Using continuous scores instead of ordinal categories is more sensitive to detecting small changes in disease severity over time. Here, we present a generalized framework that accurately predicts continuously valued variables using only discrete ordinal labels during model development. We found that for three clinical prediction tasks, models that take the ordinal relationship of the training labels into account outperformed conventional multi-class classification models. Particularly the continuous scores generated by ordinal classification and regression models showed a significantly higher correlation with expert rankings of disease severity and lower mean squared errors compared to the multi-class classification models. Furthermore, the use of MC dropout significantly improved the ability of all evaluated deep learning approaches to predict continuously valued scores that truthfully reflect the underlying continuous target variable. We showed that accurate continuously valued predictions can be generated even if the model development only involves discrete ordinal labels. The novel framework has been validated on three different clinical prediction tasks and has proven to bridge the gap between discrete ordinal labels and the underlying continuously valued variables

Nuclear receptors in vascular biology

Nuclear receptors sense a wide range of steroids and hormones (estrogens, progesterone, androgens, glucocorticoid, and mineralocorticoid), vitamins (A and D), lipid metabolites, carbohydrates, and xenobiotics. In response to these diverse but critically important mediators, nuclear receptors regulate the homeostatic control of lipids, carbohydrate, cholesterol, and xenobiotic drug metabolism, inflammation, cell differentiation and development, including vascular development. The nuclear receptor family is one of the most important groups of signaling molecules in the body and as such represent some of the most important established and emerging clinical and therapeutic targets. This review will highlight some of the recent trends in nuclear receptor biology related to vascular biology

Pregnane X receptor regulates drug metabolism and transport in the vasculature and protects from oxidative stress

Aims Circulating endogenous, dietary and foreign chemicals can contribute to vascular dysfunction. The mechanism by which the vasculature protects itself from these chemicals is unknown. This study investigates whether the pregnane X receptor (PXR), the major transcriptional regulator of hepatic drug metabolism and transport that responds to such xenobiotics, mediates vascular protection by co-ordinating a defence gene program in the vasculature.Methods and Results PXR was detected in primary human and rat aortic endothelial and smooth muscle cells and blood vessels including human and rat aorta. Metabolic PXR target genes cytochrome P450 3A, 2B, 2C and glutathione-S-transferase mRNA and activity were induced by PXR ligands in rodent and human vascular cells and absent in the aortas from PXR null mice stimulated in vivo or in rat aortic smooth muscle cells expressing dominant negative PXR. Activation of aortic PXR by classical agonists had several protective effects; increased xenobiotic metabolism demonstrated by bio-activation of the pro-drug clopidogrel, which reduced adenosine diphosphate-induced platelet aggregation; increased expression of multidrug resistance protein 1, mediating chemical efflux from the vasculature; and protection from reactive oxygen species-mediated cell death.Conclusions PXR co-ordinately up-regulates drug metabolism, transport and anti-oxidant genes to protect the vasculature from endogenous and exogenous insults, thus representing a novel gatekeeper for vascular defence

What Do Men Want from a Health Screening Mobile App? A Qualitative Study.

There is a lack of mobile app which aims to improve health screening uptake developed for men. As part of the study to develop an effective mobile app to increase health screening uptake in men, we conducted a needs assessment to find out what do men want from a health screening mobile app. In-depth interviews and focus group discussions were conducted with 31 men from a banking institution in Kuala Lumpur. The participants were purposely sampled according to their job position, age, ethnicity and screening status. The recruitment was stopped once data saturation was achieved. The audio-recorded interviews were transcribed verbatim and analyzed using thematic approach. Three themes emerged from the analysis and they were: content, feature and dissemination. In terms of the content, men wanted the app to provide information regarding health screening and functions that can assess their health; which must be personalized to them and are trustable. The app must have user-friendly features in terms of information delivery, ease of use, attention allocation and social connectivity. For dissemination, men proposed that advertisements, recommendations by health professionals, providing incentive and integrating the app as into existing systems may help to increase the dissemination of the app. This study identified important factors that need to be considered when developing a mobile app to improve health screening uptake. Future studies on mobile app development should elicit users' preference and need in terms of its content, features and dissemination strategies to improve the acceptability and the chance of successful implementation

Federated Learning for Breast Density Classification: A Real-World Implementation

Building robust deep learning-based models requires large quantities of diverse training data. In this study, we investigate the use of federated learning (FL) to build medical imaging classification models in a real-world collaborative setting. Seven clinical institutions from across the world joined this FL effort to train a model for breast density classification based on Breast Imaging, Reporting & Data System (BI-RADS). We show that despite substantial differences among the datasets from all sites (mammography system, class distribution, and data set size) and without centralizing data, we can successfully train AI models in federation. The results show that models trained using FL perform 6.3% on average better than their counterparts trained on an institute's local data alone. Furthermore, we show a 45.8% relative improvement in the models' generalizability when evaluated on the other participating sites' testing data.Comment: Accepted at the 1st MICCAI Workshop on "Distributed And Collaborative Learning"; add citation to Fig. 1 & 2 and update Fig.

Association between actual weight status, perceived weight and depressive, anxious symptoms in Chinese adolescents: a cross-sectional study

<p>Abstract</p> <p>Backgroud</p> <p>The purpose of this study was to describe actual measured weight and perceived weight and to explore associations with depressive, anxiety symptoms in school adolescents in China.</p> <p>Methods</p> <p>A sample of 1144 Chinese adolescents was randomly selected from four schools in Wuhan, China, including 665 boys and 479 girls with ages ranging between 10 and 17 years. Actual measured weight and height and perceived weight status were compared to anxiety and depressive symptoms measured using the revised Self-Rating Anxiety Scale and Children's Depression Inventory. A general linear model was used to compare differences in psychological symptoms among the teenagers with different measured and perceived weights.</p> <p>Results</p> <p>When compared with standardized weight tables (WHO age- and gender-specific body mass index (BMI) cutoffs (2007 reference)), girls were more likely to misperceive themselves as overweight, whereas more boys misclassified their weight status as underweight. The adolescents who perceived themselves as overweight were more likely to experience depressive and anxiety symptoms (except girls) than those who perceived themselves as normal and/or underweight. However, no significant association was found between depressive and anxiety symptoms actual measured weight status.</p> <p>Conclusions</p> <p>Perceived weight status, but not the actual weight status, was associated with psychological symptoms.</p