Inflammation, stress and depression: An exploration of ketamine's therapeutic profile.

Well-established animal models of depression have described a proximal relationship between stress and central nervous system (CNS) inflammation - a relationship mirrored in the peripheral inflammatory biomarkers of individuals with depression. Evidence also suggests that stress-induced proinflammatory states can contribute to the neurobiology of treatment-resistant depression. Interestingly, ketamine, a rapid-acting antidepressant, can partially exert its therapeutic effects via anti-inflammatory actions on the hypothalamic-pituitary adrenal (HPA) axis, the kynurenine pathway or by cytokine suppression.

A skeleton from the Middle Jurassic of Scotland illuminates an earlier origin of large pterosaurs.

Pterosaurs were the first vertebrates to evolve flight and include the largest flying animals in Earth history. While some of the last-surviving species were the size of airplanes, pterosaurs were long thought to be restricted to small body sizes (wingspans ca. <1.

Somatic Symptom Severity, Not Injury Severity, Predicts Probable Posttraumatic Stress Disorder and Major Depressive Disorder in Wounded Service Members.

Although previous studies have reported an association between patient-reported somatic symptom severity and the development of posttraumatic stress disorder (PTSD) or major depressive disorder (MDD) in injured military service members (SMs), conclusions from other studies regarding the association between clinician-determined injury severity and PTSD or MDD remain unclear. The present study investigated whether somatic symptoms or injury severity predict the development of probable PTSD or MDD in wounded SMs medically evacuated from combat areas. Data including SM demographic characteristics, clinician-determined injury severity (i.

Novel track morphotypes from new tracksites indicate increased Middle Jurassic dinosaur diversity on the Isle of Skye, Scotland.

Dinosaur fossils from the Middle Jurassic are rare globally, but the Isle of Skye (Scotland, UK) preserves a varied dinosaur record of abundant trace fossils and rare body fossils from this time. Here we describe two new tracksites from Rubha nam Brathairean (Brothers' Point) near where the first dinosaur footprint in Scotland was found in the 1980s. These sites were formed in subaerially exposed mudstones of the Lealt Shale Formation of the Great Estuarine Group and record a dynamic, subtropical, coastal margin.

Integration of protein phosphorylation, acetylation, and methylation data sets to outline lung cancer signaling networks.

Protein posttranslational modifications (PTMs) have typically been studied independently, yet many proteins are modified by more than one PTM type, and cell signaling pathways somehow integrate this information. We coupled immunoprecipitation using PTM-specific antibodies with tandem mass tag (TMT) mass spectrometry to simultaneously examine phosphorylation, methylation, and acetylation in 45 lung cancer cell lines compared to normal lung tissue and to cell lines treated with anticancer drugs. This simultaneous, large-scale, integrative analysis of these PTMs using a cluster-filtered network (CFN) approach revealed that cell signaling pathways were outlined by clustering patterns in PTMs.

The long non-coding RNA promotes KAP1-dependent chromatin changes and regulates olfactory bulb neurogenesis.

Many long non-coding RNAs (lncRNAs) are expressed during central nervous system (CNS) development, yet their roles and mechanisms of action remain poorly understood. , a CNS-expressed lncRNA, controls neuroblastoma cell growth by binding and modulating the activity of transcriptional regulatory elements in a genome-wide manner. We show here that the lncRNA directly binds KAP1, an essential epigenetic regulatory protein, and thereby regulates the expression of shared target genes important for proliferation and neuronal differentiation.

Cell-specific prediction and application of drug-induced gene expression profiles.

Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space.

Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd.

Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO).

The first definitive Middle Jurassic atoposaurid (Crocodylomorpha, Neosuchia), and a discussion on the genus .

Atoposaurids were a clade of semiaquatic crocodyliforms known from the Late Jurassic to the latest Cretaceous. Tentative remains from Europe, Morocco, and Madagascar may extend their range into the Middle Jurassic. Here we report the first unambiguous Middle Jurassic (late Bajocian-Bathonian) atoposaurid: an anterior dentary from the Isle of Skye, Scotland, UK.

Glucocorticoid receptor isoforms direct distinct mitochondrial programs to regulate ATP production.

The glucocorticoid receptor (GR), a nuclear receptor and major drug target, has a highly conserved minor splice variant, GRγ, which differs by a single arginine within the DNA binding domain. GRγ, which comprises 10% of all GR transcripts, is constitutively expressed and tightly conserved through mammalian evolution, suggesting an important non-redundant role. However, to date no specific role for GRγ has been reported.

Drug-induced adverse events prediction with the LINCS L1000 data.

Motivation: Adverse drug reactions (ADRs) are a central consideration during drug development. Here we present a machine learning classifier to prioritize ADRs for approved drugs and pre-clinical small-molecule compounds by combining chemical structure (CS) and gene expression (GE) features. The GE data is from the Library of Integrated Network-based Cellular Signatures (LINCS) L1000 dataset that measured changes in GE before and after treatment of human cells with over 20 000 small-molecule compounds including most of the FDA-approved drugs.

Principal Angle Enrichment Analysis (PAEA): Dimensionally Reduced Multivariate Gene Set Enrichment Analysis Tool.

Gene set analysis of differential expression, which identifies collectively differentially expressed gene sets, has become an important tool for biology. The power of this approach lies in its reduction of the dimensionality of the statistical problem and its incorporation of biological interpretation by construction. Many approaches to gene set analysis have been proposed, but benchmarking their performance in the setting of real biological data is difficult due to the lack of a gold standard.

L1000CDS: LINCS L1000 characteristic direction signatures search engine.

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS.

Dynamics of the discovery process of protein-protein interactions from low content studies.

Background: Thousands of biological and biomedical investigators study of the functional role of single genes and their protein products in normal physiology and in disease. The findings from these studies are reported in research articles that stimulate new research. It is now established that a complex regulatory networks's is controlling human cellular fate, and this community of researchers are continually unraveling this network topology.

Scaffold hopping approach on the route to selective tankyrase inhibitors.

A virtual screening procedure was applied to identify new tankyrase inhibitors. Through pharmacophore screening of a compounds collection from the SPECS database, the methoxy[l]benzothieno[2,3-c]quinolin-6(5H)-one scaffold was identified as nicotinamide mimetic able to inhibit tankyrase activity at low micromolar concentration. In order to improve potency and selectivity, tandem structure-based and scaffold hopping approaches were carried out over the new scaffold leading to the discovery of the 2-(phenyl)-3H-benzo[4,5]thieno[3,2-d]pyrimidin-4-one as powerful chemotype suitable for tankyrase inhibition.

Lean Big Data integration in systems biology and systems pharmacology.

Data sets from recent large-scale projects can be integrated into one unified puzzle that can provide new insights into how drugs and genetic perturbations applied to human cells are linked to whole-organism phenotypes. Data that report how drugs affect the phenotype of human cell lines and how drugs induce changes in gene and protein expression in human cell lines can be combined with knowledge about human disease, side effects induced by drugs, and mouse phenotypes. Such data integration efforts can be achieved through the conversion of data from the various resources into single-node-type networks, gene-set libraries, or multipartite graphs.

Proteomics analysis of the non-muscle myosin heavy chain IIa-enriched actin-myosin complex reveals multiple functions within the podocyte.

MYH9 encodes non-muscle myosin heavy chain IIA (NMMHCIIA), the predominant force-generating ATPase in non-muscle cells. Several lines of evidence implicate a role for MYH9 in podocytopathies. However, NMMHCIIA's function in podocytes remains unknown.

The characteristic direction: a geometrical approach to identify differentially expressed genes.

Background: Identifying differentially expressed genes (DEG) is a fundamental step in studies that perform genome wide expression profiling. Typically, DEG are identified by univariate approaches such as Significance Analysis of Microarrays (SAM) or Linear Models for Microarray Data (LIMMA) for processing cDNA microarrays, and differential gene expression analysis based on the negative binomial distribution (DESeq) or Empirical analysis of Digital Gene Expression data in R (edgeR) for RNA-seq profiling.

Results: Here we present a new geometrical multivariate approach to identify DEG called the Characteristic Direction.

Induction of a hemogenic program in mouse fibroblasts.

Definitive hematopoiesis emerges during embryogenesis via an endothelial-to-hematopoietic transition. We attempted to induce this process in mouse fibroblasts by screening a panel of factors for hemogenic activity. We identified a combination of four transcription factors, Gata2, Gfi1b, cFos, and Etv6, that efficiently induces endothelial-like precursor cells, with the subsequent appearance of hematopoietic cells.

Network2Canvas: network visualization on a canvas with enrichment analysis.

Motivation: Networks are vital to computational systems biology research, but visualizing them is a challenge. For networks larger than ∼100 nodes and ∼200 links, ball-and-stick diagrams fail to convey much information. To address this, we developed Network2Canvas (N2C), a web application that provides an alternative way to view networks.

Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool.

Background: System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement.

Renoprotective effect of combined inhibition of angiotensin-converting enzyme and histone deacetylase.

The Connectivity Map database contains microarray signatures of gene expression derived from approximately 6000 experiments that examined the effects of approximately 1300 single drugs on several human cancer cell lines. We used these data to prioritize pairs of drugs expected to reverse the changes in gene expression observed in the kidneys of a mouse model of HIV-associated nephropathy (Tg26 mice). We predicted that the combination of an angiotensin-converting enzyme (ACE) inhibitor and a histone deacetylase inhibitor would maximally reverse the disease-associated expression of genes in the kidneys of these mice.

Sets2Networks: network inference from repeated observations of sets.

Background: The skeleton of complex systems can be represented as networks where vertices represent entities, and edges represent the relations between these entities. Often it is impossible, or expensive, to determine the network structure by experimental validation of the binary interactions between every vertex pair. It is usually more practical to infer the network from surrogate observations.

Genes2FANs: connecting genes through functional association networks.

Background: Protein-protein, cell signaling, metabolic, and transcriptional interaction networks are useful for identifying connections between lists of experimentally identified genes/proteins. However, besides physical or co-expression interactions there are many ways in which pairs of genes, or their protein products, can be associated. By systematically incorporating knowledge on shared properties of genes from diverse sources to build functional association networks (FANs), researchers may be able to identify additional functional interactions between groups of genes that are not readily apparent.

Recovering protein-protein and domain-domain interactions from aggregation of IP-MS proteomics of coregulator complexes.

Coregulator proteins (CoRegs) are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP) followed by mass spectrometry (MS) applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations.