Characterizing and Understanding Development of Social Computing Through DBLP : A Data-Driven Analysis

During the past decades, the term 'social computing' has become a promising interdisciplinary area in the intersection of computer science and social science. In this work, we conduct a data-driven study to understand the development of social computing using the data collected from Digital Bibliography and Library Project (DBLP), a representative computer science bibliography website. We have observed a series of trends in the development of social computing, including the evolution of the number of publications, popular keywords, top venues, international collaborations, and research topics. Our findings will be helpful for researchers and practitioners working in relevant fields.publishedVersionPeer reviewe

A frameshift mutation in NOD2 associated with susceptibility to Crohn's disease

Crohn's disease is a chronic inflammatory disorder of the gastrointestinal tract, which is thought to result from the effect of environmental factors in a genetically predisposed host. A gene location in the pericentromeric region of chromosome 16, IBD1, that contributes to susceptibility to Crohn's disease has been established through multiple linkage studies(1-6), but the specific gene(s) has not been identified. NOD2, a gene that encodes a protein with homology to plant disease resistance gene products is located in the peak region of linkage on chromosome 16 (ref. 7). Here we show, by using the transmission disequilibium test and case-control analysis, that a frameshift mutation caused by a cytosine insertion, 3020insC, which is expected to encode a truncated NOD2 protein, is associated with Crohn's disease. Wild-type NOD2 activates nuclear factor NF-kappaB, making it responsive to bacterial lipopolysaccharides; however, this induction was deficient in mutant NOD2. These results implicate NOD2 in susceptibility to Crohn's disease, and suggest a link between an innate immune response to bacterial components and development of disease.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62856/1/411603a0.pd

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Olfactory Stem Cells, a New Cellular Model for Studying Molecular Mechanisms Underlying Familial Dysautonomia

International audienceBackground: Familial dysautonomia (FD) is a hereditary neuropathy caused by mutations in the IKBKAP gene, the most common of which results in variable tissue-specific mRNA splicing with skipping of exon 20. Defective splicing is especially severe in nervous tissue, leading to incomplete development and progressive degeneration of sensory and autonomic neurons. The specificity of neuron loss in FD is poorly understood due to the lack of an appropriate model system. To better understand and modelize the molecular mechanisms of IKBKAP mRNA splicing, we collected human olfactory ecto-mesenchymal stem cells (hOE-MSC) from FD patients. hOE-MSCs have a pluripotent ability to differentiate into various cell lineages, including neurons and glial cells.Methodology/Principal Findings: We confirmed IKBKAP mRNA alternative splicing in FD hOE-MSCs and identified 2 novel spliced isoforms also present in control cells. We observed a significant lower expression of both IKBKAP transcript and IKAP/hELP1 protein in FD cells resulting from the degradation of the transcript isoform skipping exon 20. We localized IKAP/hELP1 in different cell compartments, including the nucleus, which supports multiple roles for that protein. We also investigated cellular pathways altered in FD, at the genome-wide level, and confirmed that cell migration and cytoskeleton reorganization were among the processes altered in FD. Indeed, FD hOE-MSCs exhibit impaired migration compared to control cells. Moreover, we showed that kinetin improved exon 20 inclusion and restores a normal level of IKAP/hELP1 in FD hOE-MSCs. Furthermore, we were able to modify the IKBKAP splicing ratio in FD hOE-MSCs, increasing or reducing the WT (exon 20 inclusion):MU (exon 20 skipping) ratio respectively, either by producing free-floating spheres, or by inducing cells into neural differentiation.Conclusions/Significance: hOE-MSCs isolated from FD patients represent a new approach for modeling FD to better understand genetic expression and possible therapeutic approaches. This model could also be applied to other neurological genetic diseases

Macromolecular Crowding Directs Extracellular Matrix Organization and Mesenchymal Stem Cell Behavior

Microenvironments of biological cells are dominated in vivo by macromolecular crowding and resultant excluded volume effects. This feature is absent in dilute in vitro cell culture. Here, we induced macromolecular crowding in vitro by using synthetic macromolecular globules of nm-scale radius at physiological levels of fractional volume occupancy. We quantified the impact of induced crowding on the extracellular and intracellular protein organization of human mesenchymal stem cells (MSCs) via immunocytochemistry, atomic force microscopy (AFM), and AFM-enabled nanoindentation. Macromolecular crowding in extracellular culture media directly induced supramolecular assembly and alignment of extracellular matrix proteins deposited by cells, which in turn increased alignment of the intracellular actin cytoskeleton. The resulting cell-matrix reciprocity further affected adhesion, proliferation, and migration behavior of MSCs. Macromolecular crowding can thus aid the design of more physiologically relevant in vitro studies and devices for MSCs and other cells, by increasing the fidelity between materials synthesized by cells in vivo and in vitro

Gene-Centric Meta-Analysis of Lipid Traits in African, East Asian and Hispanic Populations

Meta-analyses of European populations has successfully identified genetic variants in over 100 loci associated with lipid levels, but our knowledge in other ethnicities remains limited. To address this, we performed dense genotyping of ∼2,000 candidate genes in 7,657 African Americans, 1,315 Hispanics and 841 East Asians, using the IBC array, a custom ∼50,000 SNP genotyping array. Meta-analyses confirmed 16 lipid loci previously established in European populations at genome-wide significance level, and found multiple independent association signals within these lipid loci. Initial discovery and in silico follow-up in 7,000 additional African American samples, confirmed two novel loci: rs5030359 within ICAM1 is associated with total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) $(p = 8.8×10^{−7} and p = 1.5×10^{−6}$ respectively) and a nonsense mutation rs3211938 within CD36 is associated with high-density lipoprotein cholesterol (HDL-C) levels $(p = 13.5×10^{−12})$. The rs3211938-G allele, which is nearly absent in European and Asian populations, has been previously found to be associated with CD36 deficiency and shows a signature of selection in Africans and African Americans. Finally, we have evaluated the effect of SNPs established in European populations on lipid levels in multi-ethnic populations and show that most known lipid association signals span across ethnicities. However, differences between populations, especially differences in allele frequency, can be leveraged to identify novel signals, as shown by the discovery of ICAM1 and CD36 in the current report

Cluster Headache Genomewide Association Study and Meta-Analysis Identifies Eight Loci and Implicates Smoking as Causal Risk Factor

Objective: The objective of this study was to aggregate data for the first genomewide association study meta-analysis of cluster headache, to identify genetic risk variants, and gain biological insights. Methods: A total of 4,777 cases (3,348 men and 1,429 women) with clinically diagnosed cluster headache were recruited from 10 European and 1 East Asian cohorts. We first performed an inverse-variance genomewide association meta-analysis of 4,043 cases and 21,729 controls of European ancestry. In a secondary trans-ancestry meta-analysis, we included 734 cases and 9,846 controls of East Asian ancestry. Candidate causal genes were prioritized by 5 complementary methods: expression quantitative trait loci, transcriptome-wide association, fine-mapping of causal gene sets, genetically driven DNA methylation, and effects on protein structure. Gene set and tissue enrichment analyses, genetic correlation, genetic risk score analysis, and Mendelian randomization were part of the downstream analyses. Results: The estimated single nucleotide polymorphism (SNP)-based heritability of cluster headache was 14.5%. We identified 9 independent signals in 7 genomewide significant loci in the primary meta-analysis, and one additional locus in the trans-ethnic meta-analysis. Five of the loci were previously known. The 20 genes prioritized as potentially causal for cluster headache showed enrichment to artery and brain tissue. Cluster headache was genetically correlated with cigarette smoking, risk-taking behavior, attention deficit hyperactivity disorder (ADHD), depression, and musculoskeletal pain. Mendelian randomization analysis indicated a causal effect of cigarette smoking intensity on cluster headache. Three of the identified loci were shared with migraine. Interpretation: This first genomewide association study meta-analysis gives clues to the biological basis of cluster headache and indicates that smoking is a causal risk factor