The comorbidity of hypertension and psychological distress: a study of nine countries in the former Soviet Union.

BACKGROUND: Mental health problems in those with physical ailments are often overlooked, especially in the former Soviet Union (fSU) where this comorbidity has received little attention. Our study examines the comorbidity of psychological distress and hypertension in the fSU. METHODS: Nationally representative household survey data from Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia and Ukraine in 2001 and 2010 were analysed to compare the levels of psychological distress in people with and without self-reported hypertension. Multivariate regression analysed determinants of psychological distress in hypertensive respondents, and prevalence rate ratios were calculated to compare the change in distress between the two groups. RESULTS: There were significantly higher levels of psychological distress among hypertensive respondents (9.9%) than in the general population (4.9%), and a significant association between the two conditions [odds ratio (OR) = 2.27 (1.91; 2.70)]. Characteristics associated with distress among hypertensive respondents included residing in Armenia or Kyrgyzstan, being female, over age 50, with a poor economic situation, lower education, poor emotional support and limited access to medical drugs. Levels of distress declined between 2001 and 2010, but at a lesser rate in hypertensive respondents [rate ratio (RR) = 0.85 (0.75; 0.95)] than non-hypertensive respondents [RR = 0.65 (0.56; 0.75)]. CONCLUSIONS: There is a significant association between psychological distress and hypertension in the region

Philanthropic Connections: Mapping the Landscape of U.S. Funder Networks

This is a formal examination of grantmaker associations and networks in the U.S. The report, together with its directory and maps, is the first time the field has had a nationwide picture of the myriad and diverse ways grantmakers convene, collaborate, communicate and collectively act across this country. That picture is striking in its size and variety. More importantly it is encouraging - in its potential to serve as a robust nationwide but grassroots-based "web" through which grantmakers can collectively seize opportunities and respond to challenges

Grantees' Limited Engagement with Foundations' Social Media

It is not surprising that foundations are investing in social media tools. These tools can serve myriad functions for foundations, from promoting a culture of transparency to the public at large, to influencing thought leaders, to connecting with grantees

Phylogenomic analyses of non-Dikarya fungi supports horizontal gene transfer driving diversification of secondary metabolism in the amphibian gastrointestinal symbiont, Basidiobolus

Research into secondary metabolism (SM) production by fungi has resulted in the discovery of diverse, biologically active compounds with significant medicinal applications. However, the fungi rich in SM production are taxonomically restricted to Dikarya, two phyla of Kingdom Fungi, Ascomycota and Basidiomycota. Here, we explore the potential for SM production in Mucoromycota and Zoopagomycota, two phyla of nonflagellated fungi that are not members of Dikarya, by predicting and identifying core genes and gene clusters involved in SM. The majority of non-Dikarya have few genes and gene clusters involved in SM production except for the amphibian gut symbionts in the genus Basidiobolus . Basidiobolus genomes exhibit an enrichment of SM genes involved in siderophore, surfactin-like, and terpene cyclase production, all these with evidence of constitutive gene expression. Gene expression and chemical assays confirm that Basidiobolus has significant siderophore activity. The expansion of SMs in Basidiobolus are partially due to horizontal gene transfer from bacteria, likely as a consequence of its ecology as an amphibian gut endosymbiont

Modeling brain dynamics in brain tumor patients using the virtual brain

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance

Bacterial community profiles and Vibrio parahaemolyticus abundance in individual oysters and their association with estuarine ecology

Oysters naturally harbor the human gastric pathogen Vibrio parahaemolyticus, but the nature of this association is unknown. Because microbial interactions could influence the accumulation of V. parahaemolyticus in oysters, we investigated the composition of the microbiome in water and oysters at two ecologically unique sites in the Great Bay Estuary, New Hampshire using 16s rRNA profiling. We then evaluated correlations between bacteria inhabiting the oyster with V. parahaemolyticus abundance quantified using a most probable number (MPN) analysis. Even though oysters filter-feed, their microbiomes were not a direct snapshot of the bacterial community in overlaying water, suggesting they selectively accumulate some bacterial phyla. The microbiome of individual oysters harvested more centrally in the bay were relatively more similar to each other and had fewer unique phylotypes, but overall more taxonomic and metabolic diversity, than the microbiomes from tributary-harvested oysters that were individually more variable with lower taxonomic and metabolic diversity. Oysters harvested from the same location varied in V. parahaemolyticus abundance, with the highest abundance oysters collected from one location. This study, which to our knowledge is the first of its kind to evaluate associations of V. parahaemolyticus abundance with members of individual oyster microbiomes, implies that sufficient sampling and depth of sequencing may reveal microbiome members that could impact V. parahaemolyticus abundance

Reliability of single-subject neural activation patterns in speech production tasks

Traditional group fMRI (functional magnetic resonance imaging) analyses are not designed to detect individual differences that may be crucial to better understanding speech disorders. Single-subject research could therefore provide a richer characterization of the neural substrates of speech production in development and disease. Before this line of research can be tackled, however, it is necessary to evaluate whether healthy individuals exhibit reproducible brain activation across multiple sessions during speech production tasks. In the present study, we evaluated the reliability and discriminability of cortical functional magnetic resonance imaging data from twenty neurotypical subjects who participated in two experiments involving reading aloud mono- or bisyllabic speech stimuli. Using traditional methods like the Dice and intraclass correlation coefficients, we found that most individuals displayed moderate to high reliability, with exceptions likely due to increased head motion in the scanner. Further, this level of reliability for speech production was not directly correlated with reliable patterns in the underlying average blood oxygenation level dependent signal across the brain. Finally, we found that a novel machine-learning subject classifier could identify these individuals by their speech activation patterns with 97% accuracy from among a dataset of seventy-five subjects. These results suggest that single-subject speech research would yield valid results and that investigations into the reliability of speech activation in people with speech disorders are warranted.Accepted manuscrip