STX1A and Asperger syndrome: a replication study

Background Autism spectrum conditions (ASC) are a group of conditions characterized by difficulties in communication and social interaction, alongside unusually narrow interests and repetitive, stereotyped behaviour. Genetic association and expression studies have suggested an important role for the GABAergic circuits in ASC. Syntaxin 1A (STX1A) encodes a protein involved in regulation of serotonergic and GABAergic systems and its expression is altered in autism. Methods In this study, the association between three single nucleotide polymorphisms (SNPs) (rs4717806, rs941298 and rs6951030) in STX1A gene and Asperger syndrome (AS) were tested in 650 controls and 479 individuals with AS, all of Caucasian ancestry. Results rs4717806 (P=0.00334) and rs941298 (P=0.01741) showed a significant association with AS, replicating previous results. Both SNPs putatively alter transcription factor binding sites both directly and through other variants in high linkage disequilibrium. Conclusions The current study confirms the role of STX1A as an important candidate gene in ASC. The exact molecular mechanisms through which STX1A contributes to the etiology remain to be elucidated

2,2′-Diazinodimethylidyne)di-o-phenyl­ene) dibenzoate

The title compound, C28H20N2O4, was synthesized by the reaction of 2-(hydrazonometh­yl)phenyl benzoate with iodine. The mol­ecule possesses a crystallographically imposed center of symmetry at the mid-point of the hydrazine N—N bond. The substituents at the ends of the C=N bonds adopt an E,E configuration. Inter­molecular C—H⋯π(arene) hydrogen bonds and aromatic π–π stacking inter­actions [centroid–centroid distance 3.900 (1) Å] link the mol­ecules into (100) sheets. In addition, there is an inter­molecular C—H⋯O hydrogen-bond inter­action

Sharing of Encrypted files in Blockchain Made Simpler

Recently, blockchain technology has attracted much attention of the research community in several domains requiring transparency of data accountability, due to the removal of intermediate trust assumptions from third parties. One such application is enabling file sharing in blockchain enabled distributed cloud storage. Proxy re-encryption is a cryptographic primitive that allows such file sharing by re-encrypting ciphertexts towards legitimate users via semi-trusted proxies, without them learning any information about the underlying message. To facilitate secure data sharing in the distributed cloud, it is essential to construct efficient proxy re-encryption protocols. In this paper, we introduce the notion of proxy self re-encryption (SE-PRE) that is highly efficient, as compared to the existing PRE schemes in the literature. We show that our self encryption scheme is provably CCA secure based on the DLP assumption and our proxy re-encryption scheme with self encryption is CCA secure under the hardness of the Computational Diffie Hellman (CDH) and Discrete Logarithm (DLP) assumption. Our novel encryption scheme, called self encryption, has no exponentiation or costly pairing operation. Even the re-encryption in SE-PRE does not have such operations and this facilitates the service provider with efficiency gain

Impaired skin wound healing in peroxisome proliferator–activated receptor (PPAR)α and PPARβ mutant mice

We show here that the α, β, and γ isotypes of peroxisome proliferator–activated receptor (PPAR) are expressed in the mouse epidermis during fetal development and that they disappear progressively from the interfollicular epithelium after birth. Interestingly, PPARα and β expression is reactivated in the adult epidermis after various stimuli, resulting in keratinocyte proliferation and differentiation such as tetradecanoylphorbol acetate topical application, hair plucking, or skin wound healing. Using PPARα, β, and γ mutant mice, we demonstrate that PPARα and β are important for the rapid epithelialization of a skin wound and that each of them plays a specific role in this process. PPARα is mainly involved in the early inflammation phase of the healing, whereas PPARβ is implicated in the control of keratinocyte proliferation. In addition and very interestingly, PPARβ mutant primary keratinocytes show impaired adhesion and migration properties. Thus, the findings presented here reveal unpredicted roles for PPARα and β in adult mouse epidermal repair

Animal model integration to AutDB, a genetic database for autism

<p>Abstract</p> <p>Background</p> <p>In the post-genomic era, multi-faceted research on complex disorders such as autism has generated diverse types of molecular information related to its pathogenesis. The rapid accumulation of putative candidate genes/loci for Autism Spectrum Disorders (ASD) and ASD-related animal models poses a major challenge for systematic analysis of their content. We previously created the Autism Database (AutDB) to provide a publicly available web portal for ongoing collection, manual annotation, and visualization of genes linked to ASD. Here, we describe the design, development, and integration of a new module within AutDB for ongoing collection and comprehensive cataloguing of ASD-related animal models.</p> <p>Description</p> <p>As with the original AutDB, all data is extracted from published, peer-reviewed scientific literature. Animal models are annotated with a new standardized vocabulary of phenotypic terms developed by our researchers which is designed to reflect the diverse clinical manifestations of ASD. The new Animal Model module is seamlessly integrated to AutDB for dissemination of diverse information related to ASD. Animal model entries within the new module are linked to corresponding candidate genes in the original "Human Gene" module of the resource, thereby allowing for cross-modal navigation between gene models and human gene studies. Although the current release of the Animal Model module is restricted to mouse models, it was designed with an expandable framework which can easily incorporate additional species and non-genetic etiological models of autism in the future.</p> <p>Conclusions</p> <p>Importantly, this modular ASD database provides a platform from which data mining, bioinformatics, and/or computational biology strategies may be adopted to develop predictive disease models that may offer further insights into the molecular underpinnings of this disorder. It also serves as a general model for disease-driven databases curating phenotypic characteristics of corresponding animal models.</p

A Brain Region-Specific Predictive Gene Map for Autism Derived by Profiling a Reference Gene Set

Molecular underpinnings of complex psychiatric disorders such as autism spectrum disorders (ASD) remain largely unresolved. Increasingly, structural variations in discrete chromosomal loci are implicated in ASD, expanding the search space for its disease etiology. We exploited the high genetic heterogeneity of ASD to derive a predictive map of candidate genes by an integrated bioinformatics approach. Using a reference set of 84 Rare and Syndromic candidate ASD genes (AutRef84), we built a composite reference profile based on both functional and expression analyses. First, we created a functional profile of AutRef84 by performing Gene Ontology (GO) enrichment analysis which encompassed three main areas: 1) neurogenesis/projection, 2) cell adhesion, and 3) ion channel activity. Second, we constructed an expression profile of AutRef84 by conducting DAVID analysis which found enrichment in brain regions critical for sensory information processing (olfactory bulb, occipital lobe), executive function (prefrontal cortex), and hormone secretion (pituitary). Disease specificity of this dual AutRef84 profile was demonstrated by comparative analysis with control, diabetes, and non-specific gene sets. We then screened the human genome with the dual AutRef84 profile to derive a set of 460 potential ASD candidate genes. Importantly, the power of our predictive gene map was demonstrated by capturing 18 existing ASD-associated genes which were not part of the AutRef84 input dataset. The remaining 442 genes are entirely novel putative ASD risk genes. Together, we used a composite ASD reference profile to generate a predictive map of novel ASD candidate genes which should be prioritized for future research

Understanding the Role of PknJ in Mycobacterium tuberculosis: Biochemical Characterization and Identification of Novel Substrate Pyruvate Kinase A

Reversible protein phosphorylation is a prevalent signaling mechanism which modulates cellular metabolism in response to changing environmental conditions. In this study, we focus on previously uncharacterized Mycobacterium tuberculosis Ser/Thr protein kinase (STPK) PknJ, a putative transmembrane protein. PknJ is shown to possess autophosphorylation activity and is also found to be capable of carrying out phosphorylation on the artificial substrate myelin basic protein (MyBP). Previous studies have shown that the autophosphorylation activity of M. tuberculosis STPKs is dependent on the conserved residues in the activation loop. However, our results show that apart from the conventional conserved residues, additional residues in the activation loop may also play a crucial role in kinase activation. Further characterization of PknJ reveals that the kinase utilizes unusual ions (Ni2+, Co2+) as cofactors, thus hinting at a novel mechanism for PknJ activation. Additionally, as shown for other STPKs, we observe that PknJ possesses the capability to dimerize. In order to elucidate the signal transduction cascade emanating from PknJ, the M. tuberculosis membrane-associated protein fraction is treated with the active kinase and glycolytic enzyme Pyruvate kinase A (mtPykA) is identified as one of the potential substrates of PknJ. The phospholabel is found to be localized on serine and threonine residue(s), with Ser37 identified as one of the sites of phosphorylation. Since Pyk is known to catalyze the last step of glycolysis, our study shows that the fundamental pathways such as glycolysis can also be governed by STPK-mediated signaling