Adiposity Is Associated with Gender-Specific Reductions in Left Ventricular Myocardial Perfusion during Dobutamine Stress

Background

Obesity and visceral adiposity are increasingly recognized risk factors for cardiovascular disease. Visceral fat may reduce myocardial perfusion by impairing vascular endothelial function. Women experience more anginal symptoms compared to men despite less severe coronary artery stenosis, as assessed by angiography. Women and men have different fat storage patterns which may account for the observed differences in cardiovascular disease. Therefore, our objective was to evaluate the relationship between visceral adipose tissue distributions and myocardial perfusion in men and women.

Methods

Visceral and subcutaneous fat distributions and myocardial perfusion were measured in 69 men and women without coronary artery disease using magnetic resonance imaging techniques. Myocardial perfusion index was quantified after first-pass perfusion with gadolinium contrast at peak dose dobutamine stress.

Results

We observed inverse relationships between female gender (r = -0.35, p = 0.003), pericardial fat (r = -0.36, p = 0.03), intraperitoneal fat (r = -0.37, p = 0.001), and retroperitoneal fat (r = -0.36, p = 0.002) and myocardial perfusion index. Visceral fat depots were not associated with reduced myocardial perfusion at peak dose dobutamine in men. However, in women, BMI (r = -0.33, p = 0.04), pericardial fat (r = -0.53, p = 0.02), subcutaneous fat (r = -0.39, p = 0.01) and intraperitoneal fat (r = -0.30, p = 0.05) were associated with reduced myocardial perfusion during dobutamine stress.

Conclusions

Higher visceral fat volumes are associated with reduced left ventricular myocardial perfusion at peak dose dobutamine stress in women but not in men. These findings suggest that visceral fat may contribute to abnormal microcirculatory coronary artery perfusion syndromes, explaining why some women exhibit more anginal symptoms despite typically lower grade epicardial coronary artery stenoses than men.     

Examining the Gap between Science and Public Opinion about Genetically Modified Food and Global Warming

There is great uncertainty due to challenges of escalating population growth and climate change. Public perception that diverges from the scientific community may decrease the effectiveness of scientific inquiry and innovation as tools to solve these challenges. The objective of this study was to identify the factors associated with the divergence of public opinion from scientific consensus regarding the safety of genetically modified (GM) foods and human involvement in global warming (GW). Results indicate that the effects of knowledge on public opinion are complex and non-uniform across types of knowledge (i.e., perceived and actual) or issues. Political affiliation affects agreement with science; Democrats were more likely to agree that GM food is safe and human actions cause GW. Respondents who had relatively higher cognitive function or held illusionary correlations about GM food or GW were more likely to have an opinion that differed from the scientific community.     

Genetic and Quantitative Trait Locus Analysis for Bio-Oil Compounds after Fast Pyrolysis in Maize Cobs

Fast pyrolysis has been identified as one of the biorenewable conversion platforms that could be a part of an alternative energy future, but it has not yet received the same attention as cellulosic ethanol in the analysis of genetic inheritance within potential feedstocks such as maize. Ten bio-oil compounds were measured via pyrolysis/gas chromatography-mass spectrometry (Py/GC-MS) in maize cobs. 184 recombinant inbred lines (RILs) of the intermated B73 x Mo17 (IBM) Syn4 population were analyzed in two environments, using 1339 markers, for quantitative trait locus (QTL) mapping. QTL mapping was performed using composite interval mapping with significance thresholds established by 1000 permutations at α = 0.05. 50 QTL were found in total across those ten traits with R² values ranging from 1.7 to 5.8%, indicating a complex quantitative inheritance of these traits.     

IL-33-Dependent Endothelial Activation Contributes to Apoptosis and Renal Injury in Orientia tsutsugamushi-Infected Mice

Endothelial cells (EC) are the main target for Orientia tsutsugamushi infection and EC dysfunction is a hallmark of severe scrub typhus in patients. However, the molecular basis of EC dysfunction and its impact on infection outcome are poorly understood. We found that C57BL/6 mice that received a lethal dose of O. tsutsugamushi Karp strain had a significant increase in the expression of IL-33 and its receptor ST2L in the kidneys and liver, but a rapid reduction of IL-33 in the lungs. We also found exacerbated EC stress and activation in the kidneys of infected mice, as evidenced by elevated angiopoietin (Ang) 2/Ang1 ratio, increased endothelin 1 (ET-1) and endothelial nitric oxide synthase (eNOS) expression. Such responses were significantly attenuated in the IL-33^-/- mice. Importantly, IL-33^-/- mice also had markedly attenuated disease due to reduced EC stress and cellular apoptosis. To confirm the biological role of IL-33, we challenged wild-type (WT) mice with a sub-lethal dose of O. tsutsugamushi and gave mice recombinant IL-33 (rIL-33) every 2 days for 10 days. Exogenous IL-33 significantly increased disease severity and lethality, which correlated with increased EC stress and activation, increased CXCL1 and CXCL2 chemokines, but decreased anti-apoptotic gene BCL-2 in the kidneys. To further examine the role of EC stress, we infected human umbilical vein endothelial cells (HUVEC) in vitro. We found an infection dose-dependent increase in the expression of IL-33, ST2L soluble ST2 (sST2), and the Ang2/Ang1 ratio at 24 and 48 hours post-infection. This study indicates a pathogenic role of alarmin IL-33 in a murine model of scrub typhus and highlights infection-triggered EC damage and IL-33-mediated pathological changes during the course of Orientia infection.     

PARylation of the forkhead‐associated domain protein DAWDLE regulates plant immunity

Protein poly(ADP‐ribosyl)ation (PARylation) primarily catalyzed by poly(ADP‐ribose) polymerases (PARPs) plays a crucial role in controlling various cellular responses. However, PARylation targets and their functions remain largely elusive. Here, we deployed an Arabidopsis protein microarray coupled with in vitro PARylation assays to globally identify PARylation targets in plants. Consistent with the essential role of PARylation in plant immunity, the forkhead‐associated (FHA) domain protein DAWDLE (DDL), one of PARP2 targets, positively regulates plant defense to both adapted and non‐adapted pathogens. Arabidopsis PARP2 interacts with and PARylates DDL, which was enhanced upon treatment of bacterial flagellin. Mass spectrometry and mutagenesis analysis identified multiple PARylation sites of DDL by PARP2. Genetic complementation assays indicate that DDL PARylation is required for its function in plant immunity. In contrast, DDL PARylation appears to be dispensable for its previously reported function in plant development partially mediated by the regulation of microRNA biogenesis. Our study uncovers many previously unknown PARylation targets and points to the distinct functions of DDL in plant immunity and development mediated by protein PARylation and small RNA biogenesis, respectively.     

FLEXc: protein flexibility prediction using context-based statistics,predicted structural features,and sequence information

Background

The fluctuation of atoms around their average positions in protein structures provides important information regarding protein dynamics. This flexibility of protein structures is associated with various biological processes. Predicting flexibility of residues from protein sequences is significant for analyzing the dynamic properties of proteins which will be helpful in predicting their functions.

Results

In this paper, an approach of improving the accuracy of protein flexibility prediction is introduced. A neural network method for predicting flexibility in 3 states is implemented. The method incorporates sequence and evolutionary information, context-based scores, predicted secondary structures and solvent accessibility, and amino acid properties. Context-based statistical scores are derived, using the mean-field potentials approach, for describing the different preferences of protein residues in flexibility states taking into consideration their amino acid context.The 7-fold cross validated accuracy reached 61 % when context-based scores and predicted structural states are incorporated in the training process of the flexibility predictor.

Conclusions

Incorporating context-based statistical scores with predicted structural states are important features to improve the performance of predicting protein flexibility, as shown by our computational results. Our prediction method is implemented as web service called “FLEXc” and available online at: http://hpcr.cs.odu.edu/flexc.