Bayesian spatio-temporal analysis and geospatial risk factors of Human Monocytic Ehrlichiosis

Citation: Raghavan RK, Neises D, Goodin DG, Andresen DA, Ganta RR (2014) Bayesian Spatio-Temporal Analysis and Geospatial Risk Factors of Human Monocytic Ehrlichiosis. PLoS ONE 9(7): e100850. doi:10.1371/journal.pone.0100850Variations in spatio-temporal patterns of Human Monocytic Ehrlichiosis (HME) infection in the state of Kansas, USA were examined and the relationship between HME relative risk and various environmental, climatic and socio-economic variables were evaluated. HME data used in the study was reported to the Kansas Department of Health and Environment between years 2005–2012, and geospatial variables representing the physical environment [National Land cover/Land use, NASA Moderate Resolution Imaging Spectroradiometer (MODIS)], climate [NASA MODIS, Prediction of Worldwide Renewable Energy (POWER)], and socio-economic conditions (US Census Bureau) were derived from publicly available sources. Following univariate screening of candidate variables using logistic regressions, two Bayesian hierarchical models were fit; a partial spatio-temporal model with random effects and a spatio-temporal interaction term, and a second model that included additional covariate terms. The best fitting model revealed that spatio-temporal autocorrelation in Kansas increased steadily from 2005–2012, and identified poverty status, relative humidity, and an interactive factor, ‘diurnal temperature range x mixed forest area’ as significant county-level risk factors for HME. The identification of significant spatio-temporal pattern and new risk factors are important in the context of HME prevention, for future research in the areas of ecology and evolution of HME, and as well as climate change impacts on tick-borne diseases

Hierarchical Bayesian Spatio-Temporal Analysis of Climatic and Socio-Economic Determinants of Rocky Mountain Spotted Fever

Citation: Raghavan, R. K., Goodin, D. G., Neises, D., Anderson, G. A., & Ganta, R. R. (2016). Hierarchical Bayesian Spatio-Temporal Analysis of Climatic and Socio-Economic Determinants of Rocky Mountain Spotted Fever. Plos One, 11(3), 17. doi:10.1371/journal.pone.0150180This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF) prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socio-economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio-temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio-economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main-effects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (> 35 degrees C) in the region, and the relevance of these factors in the context of climate-change impacts on tick-borne diseases are discussed

Rational Design and Characterization of D-Phe-Pro-D-Arg-Derived Direct Thrombin Inhibitors

The tremendous social and economic impact of thrombotic disorders, together with the considerable risks associated to the currently available therapies, prompt for the development of more efficient and safer anticoagulants. Novel peptide-based thrombin inhibitors were identified using in silico structure-based design and further validated in vitro. The best candidate compounds contained both l- and d-amino acids, with the general sequence d-Phe(P3)-Pro(P2)-d-Arg(P1)-P1′-CONH2. The P1′ position was scanned with l- and d-isomers of natural or unnatural amino acids, covering the major chemical classes. The most potent non-covalent and proteolysis-resistant inhibitors contain small hydrophobic or polar amino acids (Gly, Ala, Ser, Cys, Thr) at the P1′ position. The lead tetrapeptide, d-Phe-Pro-d-Arg-d-Thr-CONH2, competitively inhibits α-thrombin's cleavage of the S2238 chromogenic substrate with a Ki of 0.92 µM. In order to understand the molecular details of their inhibitory action, the three-dimensional structure of three peptides (with P1′ l-isoleucine (fPrI), l-cysteine (fPrC) or d-threonine (fPrt)) in complex with human α-thrombin were determined by X-ray crystallography. All the inhibitors bind in a substrate-like orientation to the active site of the enzyme. The contacts established between the d-Arg residue in position P1 and thrombin are similar to those observed for the l-isomer in other substrates and inhibitors. However, fPrC and fPrt disrupt the active site His57-Ser195 hydrogen bond, while the combination of a P1 d-Arg and a bulkier P1′ residue in fPrI induce an unfavorable geometry for the nucleophilic attack of the scissile bond by the catalytic serine. The experimental models explain the observed relative potency of the inhibitors, as well as their stability to proteolysis. Moreover, the newly identified direct thrombin inhibitors provide a novel pharmacophore platform for developing antithrombotic agents by exploring the conformational constrains imposed by the d-stereochemistry of the residues at positions P1 and P1′

Supramolecular behaviour and fluorescence of rhodamine-functionalised ROMP polymers

Inherently fluorescent polymers are of interest in materials and medicine. We report a ring-opening metathesis polymerisation (ROMP) platform for creation of amphiphilic block copolymers in which one block is formed from rhodamine B-containing monomers. The polymers self-assemble into well-defined micelles which are able to sequester molecular dyes and further interact with them by energy transfer. Despite incorporating a cationic dye known to bind DNA, the polymer micelles do not interact with DNA, indicating that they are potentially safe for use in bioanalytical applications