The El Nino-Southern Oscillation and winter precipitation extremes over India

Daily rainfall data for the winter season October-December for the long period of 102 years 1901-2002 over southeast peninsular India have been used to study the characteristics of daily precipitation extremes. The frequency and intensity of extreme precipitation events do not show statistically significant long-term trend. The relationship of El Nino-southern oscillation index with these extremes shows that this index can be used to predict frequency and intensity of extreme precipitation events, 4-6 months in advance. However spell lengths of continuous wet/dry days are not modulated by variations in Pacific sea surface temperatures

Impaired development of the cerebral cortex in infants with congenital heart disease is correlated to reduced cerebral oxygen delivery

Neurodevelopmental impairment is the most common comorbidity associated with complex congenital heart disease (CHD), while the underlying biological mechanism remains unclear. We hypothesised that impaired cerebral oxygen delivery in infants with CHD is a cause of impaired cortical development, and predicted that cardiac lesions most associated with reduced cerebral oxygen delivery would demonstrate the greatest impairment of cortical development. We compared 30 newborns with complex CHD prior to surgery and 30 age-matched healthy controls using brain MRI. The cortex was assessed using high resolution, motion-corrected T2-weighted images in natural sleep, analysed using an automated pipeline. Cerebral oxygen delivery was calculated using phase contrast angiography and pre-ductal pulse oximetry, while regional cerebral oxygen saturation was estimated using near-infrared spectroscopy. We found that impaired cortical grey matter volume and gyrification index in newborns with complex CHD was linearly related to reduced cerebral oxygen delivery, and that cardiac lesions associated with the lowest cerebral oxygen delivery were associated with the greatest impairment of cortical development. These findings suggest that strategies to improve cerebral oxygen delivery may help reduce brain dysmaturation in newborns with CHD, and may be most relevant for children with CHD whose cardiac defects remain unrepaired for prolonged periods after birth

Tissue Microenvironments Define and Get Reinforced by Macrophage Phenotypes in Homeostasis or during Inflammation, Repair and Fibrosis

Current macrophage phenotype classifications are based on distinct in vitro culture conditions that do not adequately mirror complex tissue environments. In vivo monocyte progenitors populate all tissues for immune surveillance which supports the maintenance of homeostasis as well as regaining homeostasis after injury. Here we propose to classify macrophage phenotypes according to prototypical tissue environments, e.g. as they occur during homeostasis as well as during the different phases of (dermal) wound healing. In tissue necrosis and/or infection, damage- and/or pathogen-associated molecular patterns induce proinflammatory macrophages by Toll-like receptors or inflammasomes. Such classically activated macrophages contribute to further tissue inflammation and damage. Apoptotic cells and antiinflammatory cytokines dominate in postinflammatory tissues which induce macrophages to produce more antiinflammatory mediators. Similarly, tumor-associated macrophages also confer immunosuppression in tumor stroma. Insufficient parenchymal healing despite abundant growth factors pushes macrophages to gain a profibrotic phenotype and promote fibrocyte recruitment which both enforce tissue scarring. Ischemic scars are largely devoid of cytokines and growth factors so that fibrolytic macrophages that predominantly secrete proteases digest the excess extracellular matrix. Together, macrophages stabilize their surrounding tissue microenvironments by adapting different phenotypes as feed-forward mechanisms to maintain tissue homeostasis or regain it following injury. Furthermore, macrophage heterogeneity in healthy or injured tissues mirrors spatial and temporal differences in microenvironments during the various stages of tissue injury and repair. Copyright (C) 2012 S. Karger AG, Base

ElliPro: a new structure-based tool for the prediction of antibody epitopes

<p>Abstract</p> <p>Background</p> <p>Reliable prediction of antibody, or B-cell, epitopes remains challenging yet highly desirable for the design of vaccines and immunodiagnostics. A correlation between antigenicity, solvent accessibility, and flexibility in proteins was demonstrated. Subsequently, Thornton and colleagues proposed a method for identifying continuous epitopes in the protein regions protruding from the protein's globular surface. The aim of this work was to implement that method as a web-tool and evaluate its performance on discontinuous epitopes known from the structures of antibody-protein complexes.</p> <p>Results</p> <p>Here we present ElliPro, a web-tool that implements Thornton's method and, together with a residue clustering algorithm, the MODELLER program and the Jmol viewer, allows the prediction and visualization of antibody epitopes in a given protein sequence or structure. ElliPro has been tested on a benchmark dataset of discontinuous epitopes inferred from 3D structures of antibody-protein complexes. In comparison with six other structure-based methods that can be used for epitope prediction, ElliPro performed the best and gave an AUC value of 0.732, when the most significant prediction was considered for each protein. Since the rank of the best prediction was at most in the top three for more than 70% of proteins and never exceeded five, ElliPro is considered a useful research tool for identifying antibody epitopes in protein antigens. ElliPro is available at <url>http://tools.immuneepitope.org/tools/ElliPro</url>.</p> <p>Conclusion</p> <p>The results from ElliPro suggest that further research on antibody epitopes considering more features that discriminate epitopes from non-epitopes may further improve predictions. As ElliPro is based on the geometrical properties of protein structure and does not require training, it might be more generally applied for predicting different types of protein-protein interactions.</p

Bioinformatic Characterization of P-Type ATPases Encoded Within the Fully Sequenced Genomes of 26 Eukaryotes

P-type ATPases play essential roles in numerous processes, which in humans include nerve impulse propagation, relaxation of muscle fibers, secretion and absorption in the kidney, acidification of the stomach and nutrient absorption in the intestine. Published evidence suggests that uncharacterized families of P-type ATPases with novel specificities exist. In this study, the fully sequenced genomes of 26 eukaryotes, including animals, plants, fungi and unicellular eukaryotes, were analyzed for P-type ATPases. We report the organismal distributions, phylogenetic relationships, probable topologies and conserved motifs of nine functionally characterized families and 13 uncharacterized families of these enzyme transporters. We have classified these proteins according to the conventions of the functional and phylogenetic IUBMB-approved transporter classification system (www.tcdb.org, Saier et al. in Nucleic Acids Res 34:181–186, 2006; Nucleic Acids Res 37:274–278, 2009)

Using equity premium survey data to estimate future wealth

We present the first systematic methods for combining different experts' responses to equity premium surveys. These techniques are based on the observation that the survey data are approximately gamma distributed. This distribution has convenient analytical properties that enable us to address three important problems that investment managers must face. First, we construct probability density functions for the future values of equity index tracker funds. Second, we calculate unbiased and minimum least square error estimators of the future value of these funds. Third, we derive optimal asset allocation weights between equities and the risk-free asset for risk-averse investors. Our analysis allows for both herding and biasedness in expert responses. We show that, unless investors are highly uncertain about expert biases or forecasts are very highly correlated, many investment decisions can be based solely on the mean of the survey data minus any expected bias. We also make recommendations for the design of future equity premium surveys

Small Heat Shock Protein αA-Crystallin Prevents Photoreceptor Degeneration in Experimental Autoimmune Uveitis

The small heat shock protein, αA-crystallin null (αA−/−) mice are known to be more prone to retinal degeneration than the wild type mice in Experimental Autoimmune Uveoretinitis (EAU). In this report we demonstrate that intravenous administration of αA preserves retinal architecture and prevents photoreceptor damage in EAU. Interestingly, only αA and not αB-crystallin (αB), a closely related small heat shock protein works, pointing to molecular specificity in the observed retinal protection. The possible involvement of αA in retinal protection through immune modulation is corroborated by adaptive transfer experiments, (employing αA−/− and wild type mice with EAU as donors and Rag2−/− as the recipient mice), which indicate that αA protects against the autoimmune challenge by modulating the systemic B and T cell immunity. We show that αA administration causes marked reduction in Th1 cytokines (TNF-α, IL-12 and IFN-γ), both in the retina and in the spleen; notably, IL-17 was only reduced in the retina suggesting local intervention. Importantly, expression of Toll-like receptors and their associated adaptors is also inhibited suggesting that αA protection, against photoreceptor loss in EAU, is associated with systemic suppression of both the adaptive and innate immune responses

Prediction of Peptide Reactivity with Human IVIg through a Knowledge-Based Approach

The prediction of antibody-protein (antigen) interactions is very difficult due to the huge variability that characterizes the structure of the antibodies. The region of the antigen bound to the antibodies is called epitope. Experimental data indicate that many antibodies react with a panel of distinct epitopes (positive reaction). The Challenge 1 of DREAM5 aims at understanding whether there exists rules for predicting the reactivity of a peptide/epitope, i.e., its capability to bind to human antibodies. DREAM 5 provided a training set of peptides with experimentally identified high and low reactivities to human antibodies. On the basis of this training set, the participants to the challenge were asked to develop a predictive model of reactivity. A test set was then provided to evaluate the performance of the model implemented so far

Pdx1 Is Post-Translationally Modified In vivo and Serine 61 Is the Principal Site of Phosphorylation

Maintaining sufficient levels of Pdx1 activity is a prerequisite for proper regulation of blood glucose homeostasis and beta cell function. Mice that are haploinsufficient for Pdx1 display impaired glucose tolerance and lack the ability to increase beta cell mass in response to decreased insulin signaling. Several studies have shown that post-translational modifications are regulating Pdx1 activity through intracellular localization and binding to co-factors. Understanding the signaling cues converging on Pdx1 and modulating its activity is therefore an attractive approach in diabetes treatment. We employed a novel technique called Nanofluidic Proteomic Immunoassay to characterize the post-translational profile of Pdx1. Following isoelectric focusing in nano-capillaries, this technology relies on a pan specific antibody for detection and it therefore allows the relative abundance of differently charged protein species to be examined simultaneously. In all eukaryotic cells tested we find that the Pdx1 protein separates into four distinct peaks whereas Pdx1 protein from bacteria only produces one peak. Of the four peaks in eukaryotic cells we correlate one of them to a phosphorylation Using alanine scanning and mass spectrometry we map this phosphorylation to serine 61 in both Min6 cells and in exogenous Pdx1 over-expressed in HEK293 cells. A single phosphorylation is also present in cultured islets but it remains unaffected by changes in glucose levels. It is present during embryogenesis but is not required for pancreas development

Exact analysis of summary statistics for continuous-time discrete-state Markov processes on networks using graph-automorphism lumping

We propose a unified framework to represent a wide range of continuous-time discrete-state Markov processes on networks, and show how many network dynamics models in the literature can be represented in this unified framework. We show how a particular sub-set of these models, referred to here as single-vertex-transition (SVT) processes, lead to the analysis of quasi-birth-and-death (QBD) processes in the theory of continuous-time Markov chains. We illustrate how to analyse a number of summary statistics for these processes, such as absorption probabilities and first-passage times. We extend the graph-automorphism lumping approach [Kiss, Miller, Simon, Mathematics of Epidemics on Networks, 2017; Simon, Taylor, Kiss, J. Math. Bio. 62(4), 2011], by providing a matrix-oriented representation of this technique, and show how it can be applied to a very wide range of dynamical processes on networks. This approach can be used not only to solve the master equation of the system, but also to analyse the summary statistics of interest. We also show the interplay between the graph-automorphism lumping approach and the QBD structures when dealing with SVT processes. Finally, we illustrate our theoretical results with examples from the areas of opinion dynamics and mathematical epidemiology