Maternal immune activation and strain specific interactions in the development of autism-like behaviors in mice.

It is becoming increasingly apparent that the causes of autism spectrum disorders (ASD) are due to both genetic and environmental factors. Animal studies provide important translational models for elucidating specific genetic or environmental factors that contribute to ASD-related behavioral deficits. For example, mouse research has demonstrated a link between maternal immune activation and the expression of ASD-like behaviors. Although these studies have provided insights into the potential causes of ASD, they are limited in their ability to model the important interactions between genetic variability and environmental insults. This is of particular concern given the broad spectrum of severity observed in the human population, suggesting that subpopulations may be more susceptible to the adverse effects of particular environmental insults. It is hypothesized that the severity of effects of maternal immune activation on ASD-like phenotypes is influenced by the genetic background in mice. To test this, pregnant dams of two inbred strains (that is, C57BL/6J and BTBR T(+)tf/J) were exposed to the viral mimic polyinosinic-polycytidylic acid (polyI:C), and their offspring were tested for the presence and severity of ASD-like behaviors. To identify differences in immune system regulation, spleens were processed and measured for alterations in induced cytokine responses. Strain-treatment interactions were observed in social approach, ultrasonic vocalization, repetitive grooming and marble burying behaviors. Interestingly, persistent dysregulation of adaptive immune system function was only observed in BTBR mice. Data suggest that behavioral and immunological effects of maternal immune activation are strain-dependent in mice

The Conformal Anomaly of M5-Branes

We show that the conformal anomaly for N M5-branes grows like $N^3$. The method we employ relates Coulomb branch interactions in six dimensions to interactions in four dimensions using supersymmetry. This leads to a relation between the six-dimensional conformal anomaly and the conformal anomaly of N=4 Yang-Mills. Along the way, we determine the structure of the four derivative interactions for the toroidally compactified (2,0) theory, while encountering interesting novelties in the structure of the six derivative interactions.Comment: 38 pages, LaTeX; references adde

Classifying the precancers: A metadata approach

BACKGROUND: During carcinogenesis, precancers are the morphologically identifiable lesions that precede invasive cancers. In theory, the successful treatment of precancers would result in the eradication of most human cancers. Despite the importance of these lesions, there has been no effort to list and classify all of the precancers. The purpose of this study is to describe the first comprehensive taxonomy and classification of the precancers. As a novel approach to disease classification, terms and classes were annotated with metadata (data that describes the data) so that the classification could be used to link precancer terms to data elements in other biological databases. METHODS: Terms in the UMLS (Unified Medical Language System) related to precancers were extracted. Extracted terms were reviewed and additional terms added. Each precancer was assigned one of six general classes. The entire classification was assembled as an XML (eXtensible Mark-up Language) file. A Perl script converted the XML file into a browser-viewable HTML (HyperText Mark-up Language) file. RESULTS: The classification contained 4700 precancer terms, 568 distinct precancer concepts and six precancer classes: 1) Acquired microscopic precancers; 2) acquired large lesions with microscopic atypia; 3) Precursor lesions occurring with inherited hyperplastic syndromes that progress to cancer; 4) Acquired diffuse hyperplasias and diffuse metaplasias; 5) Currently unclassified entities; and 6) Superclass and modifiers. CONCLUSION: This work represents the first attempt to create a comprehensive listing of the precancers, the first attempt to classify precancers by their biological properties and the first attempt to create a pathologic classification of precancers using standard metadata (XML). The classification is placed in the public domain, and comment is invited by the authors, who are prepared to curate and modify the classification

Nonabelian (2,0) Tensor Multiplets and 3-algebras

Using 3-algebras we obtain a nonabelian system of equations that furnish a representation of the (2,0)-supersymmetric tensor multiplet. The on-shell conditions are quite restrictive so that the system can be reduced to five-dimensional gauge theory along with six-dimensional abelian (2,0) tensor multiplets. We briefly discuss possible applications to D4-branes using a spacelike reduction and M5-branes using a null reduction.Comment: 17 pages, Latex; v2: Typos corrected and references adde

Detailed estimation of bioinformatics prediction reliability through the Fragmented Prediction Performance Plots

<p>Abstract</p> <p>Background</p> <p>An important and yet rather neglected question related to bioinformatics predictions is the estimation of the amount of data that is needed to allow reliable predictions. Bioinformatics predictions are usually validated through a series of figures of merit, like for example sensitivity and precision, and little attention is paid to the fact that their performance may depend on the amount of data used to make the predictions themselves.</p> <p>Results</p> <p>Here I describe a tool, named Fragmented Prediction Performance Plot (FPPP), which monitors the relationship between the prediction reliability and the amount of information underling the prediction themselves. Three examples of FPPPs are presented to illustrate their principal features. In one example, the reliability becomes independent, over a certain threshold, of the amount of data used to predict protein features and the intrinsic reliability of the predictor can be estimated. In the other two cases, on the contrary, the reliability strongly depends on the amount of data used to make the predictions and, thus, the intrinsic reliability of the two predictors cannot be determined. Only in the first example it is thus possible to fully quantify the prediction performance.</p> <p>Conclusion</p> <p>It is thus highly advisable to use FPPPs to determine the performance of any new bioinformatics prediction protocol, in order to fully quantify its prediction power and to allow comparisons between two or more predictors based on different types of data.</p

D-brane anomaly inflow revisited

Axial and gravitational anomaly of field theories, when embedded in string theory, must be accompanied by canceling inflow. We give a self-contained overview for various world-volume theories, and clarify the role of smeared magnetic sources in I-brane/D-brane cases. The proper anomaly descent of the source, as demanded by regularity of RR field strengths H's, turns out to be an essential ingredient. We show how this allows correct inflow to be generated for all such theories, including self-dual cases, and also that the mechanism is now insensitive to the choice between the two related but inequivalent forms of D-brane Chern-Simons couplings. In particular, SO(6)_R axial anomaly of d=4 maximal SYM is canceled by the inflow onto D3-branes via the standard minimal coupling to C_4. We also propose how, for the anomaly cancelation, the four types of Orientifold planes should be coupled to the spacetime curvatures, of which conflicting claims existed previously.Comment: 41 pages, references updated; version to appear in JHE

PocketMatch: A new algorithm to compare binding sites in protein structures

Background: Recognizing similarities and deriving relationships among protein molecules is a fundamental&#xd;&#xa;requirement in present-day biology. Similarities can be present at various levels which can be detected through comparison of protein sequences or their structural folds. In some cases similarities obscure at these levels could be present merely in the substructures at their binding sites. Inferring functional similarities between protein molecules by comparing their binding sites is still largely exploratory and not as yet a routine protocol. One of&#xd;&#xa;the main reasons for this is the limitation in the choice of appropriate analytical tools that can compare binding sites with high sensitivity. To benefit from the enormous amount of structural data that is being rapidly accumulated, it is essential to have high throughput tools that enable large scale binding site comparison.&#xd;&#xa;&#xd;&#xa;Results: Here we present a new algorithm PocketMatch for comparison of binding sites in a frame invariant&#xd;&#xa;manner. Each binding site is represented by 90 lists of sorted distances capturing shape and chemical nature of the site. The sorted arrays are then aligned using an incremental alignment method and scored to obtain PMScores for pairs of sites. A comprehensive sensitivity analysis and an extensive validation of the algorithm have been carried out. Perturbation studies where the geometry of a given site was retained but the residue types were changed randomly, indicated that chance similarities were virtually non-existent. Our analysis also demonstrates that shape information alone is insufficient to discriminate between diverse binding sites, unless&#xd;&#xa;combined with chemical nature of amino acids.&#xd;&#xa;&#xd;&#xa;Conclusions: A new algorithm has been developed to compare binding sites in accurate, efficient and&#xd;&#xa;high-throughput manner. Though the representation used is conceptually simplistic, we demonstrate that along&#xd;&#xa;with the new alignment strategy used, it is sufficient to enable binding comparison with high sensitivity. Novel methodology has also been presented for validating the algorithm for accuracy and sensitivity with respect to geometry and chemical nature of the site. The method is also fast and takes about 1/250th second for one comparison on a single processor. A parallel version on BlueGene has also been implemented

Insights into GABA receptor signalling in TM3 Leydig cells

gamma-Aminobutyric acid (GABA) is an emerging signalling molecule in endocrine organs, since it is produced by endocrine cells and acts via GABA(A) receptors in a paracrine/autocrine fashion. Testicular Leydig cells are producers and targets for GABA. These cells express GABA(A) receptor subunits and in the murine Leydig cell line TM3 pharmacological activation leads to increased proliferation. The signalling pathway of GABA in these cells is not known in this study. We therefore attempted to elucidate details of GABA(A) signalling in TM3 and adult mouse Leydig cells using several experimental approaches. TM3 cells not only express GABA(A) receptor subunits, but also bind the GABA agonist {[}H-3] muscimol with a binding affinity in the range reported for other endocrine cells (K-d = 2.740 +/- 0.721 nM). However, they exhibit a low B-max value of 28.08 fmol/mg protein. Typical GABA(A) receptor-associated events, including Cl- currents, changes in resting membrane potential, intracellular Ca2+ or cAMP, were not measurable with the methods employed in TM3 cells, or, as studied in part, in primary mouse Leydig cells. GABA or GABA(A) agonist isoguvacine treatment resulted in increased or decreased levels of several mRNAs, including transcription factors (c-fos, hsf-1, egr-1) and cell cycle-associated genes (Cdk2, cyclin D1). In an attempt to verify the cDNA array results and because egr-1 was recently implied in Leydig cell development, we further studied this factor. RT-PCR and Western blotting confirmed a time-dependent regulation of egr-1 in TM3. In the postnatal testis egr-1 was seen in cytoplasmic and nuclear locations of developing Leydig cells, which bear GABA(A) receptors and correspond well to TM3 cells. Thus, GABA acts via an untypical novel signalling pathway in TM3 cells. Further details of this pathway remain to be elucidated. Copyright (c) 2005 S. Karger AG, Base