CCR2⁺CD103⁻ intestinal dendritic cells develop from DC-committed precursors and induce interleukin-17 production by T cells

The identification of intestinal macrophages (m phi s) and dendritic cells (DCs) is a matter of intense debate. Although CD103(+) mononuclear phagocytes (MPs) appear to be genuine DCs, the nature and origins of CD103(-) MPs remain controversial. We show here that intestinal CD103(-)CD11b(+) MPs can be separated clearly into DCs and m phi s based on phenotype, gene profile, and kinetics. CD64(-)CD103(-)CD11b(+) MPs are classical DCs, being derived from Flt3 ligand-dependent, DC-committed precursors, not Ly6C hi monocytes. Surprisingly, a significant proportion of these CD103(-)CD11b(+) DCs express CCR2 and there is a selective decrease in CD103(-)CD11b(+) DCs in mice lacking this chemokine receptor. CCR2(+)CD103(-) DCs are present in both the murine and human intestine, drive interleukin (IL)-17a production by Tcells in vitro, and show constitutive expression of IL-12/IL-23p40. These data highlight the heterogeneity of intestinal DCs and reveal a bona fide population of CCR2(+) DCs that is involved in priming mucosal T helper type 17 (Th17) responses

Automatic Detection of Cyberbullying in Social Media Text

While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online. Recent studies report that cyberbullying constitutes a growing problem among youngsters. Successful prevention depends on the adequate detection of potentially harmful messages and the information overload on the Web requires intelligent systems to identify potential risks automatically. The focus of this paper is on automatic cyberbullying detection in social media text by modelling posts written by bullies, victims, and bystanders of online bullying. We describe the collection and fine-grained annotation of a training corpus for English and Dutch and perform a series of binary classification experiments to determine the feasibility of automatic cyberbullying detection. We make use of linear support vector machines exploiting a rich feature set and investigate which information sources contribute the most for this particular task. Experiments on a holdout test set reveal promising results for the detection of cyberbullying-related posts. After optimisation of the hyperparameters, the classifier yields an F1-score of 64% and 61% for English and Dutch respectively, and considerably outperforms baseline systems based on keywords and word unigrams.Comment: 21 pages, 9 tables, under revie

Re-Annotation Is an Essential Step in Systems Biology Modeling of Functional Genomics Data

One motivation of systems biology research is to understand gene functions and interactions from functional genomics data such as that derived from microarrays. Up-to-date structural and functional annotations of genes are an essential foundation of systems biology modeling. We propose that the first essential step in any systems biology modeling of functional genomics data, especially for species with recently sequenced genomes, is gene structural and functional re-annotation. To demonstrate the impact of such re-annotation, we structurally and functionally re-annotated a microarray developed, and previously used, as a tool for disease research. We quantified the impact of this re-annotation on the array based on the total numbers of structural- and functional-annotations, the Gene Annotation Quality (GAQ) score, and canonical pathway coverage. We next quantified the impact of re-annotation on systems biology modeling using a previously published experiment that used this microarray. We show that re-annotation improves the quantity and quality of structural- and functional-annotations, allows a more comprehensive Gene Ontology based modeling, and improves pathway coverage for both the whole array and a differentially expressed mRNA subset. Our results also demonstrate that re-annotation can result in a different knowledge outcome derived from previous published research findings. We propose that, because of this, re-annotation should be considered to be an essential first step for deriving value from functional genomics data

Contributions of a global network of tree diversity experiments to sustainable forest plantations

status: publishe

Chromosome-Biased Binding and Gene Regulation by the Caenorhabditis elegans DRM Complex

DRM is a conserved transcription factor complex that includes E2F/DP and pRB family proteins and plays important roles in development and cancer. Here we describe new aspects of DRM binding and function revealed through genome-wide analyses of the Caenorhabditis elegans DRM subunit LIN-54. We show that LIN-54 DNA-binding activity recruits DRM to promoters enriched for adjacent putative E2F/DP and LIN-54 binding sites, suggesting that these two DNA–binding moieties together direct DRM to its target genes. Chromatin immunoprecipitation and gene expression profiling reveals conserved roles for DRM in regulating genes involved in cell division, development, and reproduction. We find that LIN-54 promotes expression of reproduction genes in the germline, but prevents ectopic activation of germline-specific genes in embryonic soma. Strikingly, C. elegans DRM does not act uniformly throughout the genome: the DRM recruitment motif, DRM binding, and DRM-regulated embryonic genes are all under-represented on the X chromosome. However, germline genes down-regulated in lin-54 mutants are over-represented on the X chromosome. We discuss models for how loss of autosome-bound DRM may enhance germline X chromosome silencing. We propose that autosome-enriched binding of DRM arose in C. elegans as a consequence of germline X chromosome silencing and the evolutionary redistribution of germline-expressed and essential target genes to autosomes. Sex chromosome gene regulation may thus have profound evolutionary effects on genome organization and transcriptional regulatory networks.National Institutes of Health (U.S.) (grant GM24663)National Institutes of Health (U.S.) (grant DK068429)National Institutes of Health (U.S.) (grant GM082971)National Institutes of Health (U.S.) (grant GM076378

First-Episode Psychosis Patients Who Deteriorated in the Premorbid Period Do Not Have Higher Polygenic Risk Scores Than Others: A Cluster Analysis of EU-GEI Data

Cluster studies identified a subgroup of patients with psychosis whose premorbid adjustment deteriorates before the onset, which may reflect variation in genetic influence. However, other studies reported a complex relationship between distinctive patterns of cannabis use and cognitive and premorbid impairment that is worthy of consideration. We examined whether: (1) premorbid social functioning (PSF) and premorbid academic functioning (PAF) in childhood and adolescence and current intellectual quotient (IQ) define different clusters in 802 first-episode of psychosis (FEP) patients; resulting clusters vary in (2) polygenic risk scores (PRSs) for schizophrenia (SCZ_PRS), bipolar disorder (BD_PRS), major depression (MD_PRS), and IQ (IQ_PRS), and (3) patterns of cannabis use, compared to 1,263 population-based controls. Four transdiagnostic clusters emerged (BIC = 2268.5): (1) high-cognitive-functioning (n = 205), with the highest IQ (Mean = 106.1, 95% CI: 104.3, 107.9) and PAF, but low PSF. (2) Low-cognitive-functioning (n = 223), with the lowest IQ (Mean = 73.9, 95% CI: 72.2, 75.7) and PAF, but normal PSF. (3) Intermediate (n = 224) (Mean_IQ = 80.8, 95% CI: 79.1, 82.5) with low-improving PAF and PSF. 4) Deteriorating (n = 150) (Mean_IQ = 80.6, 95% CI: 78.5, 82.7), with normal-deteriorating PAF and PSF. The PRSs explained 7.9% of between-group membership. FEP had higher SCZ_PRS than controls [F(4,1319) = 20.4, P < .001]. Among the clusters, the deteriorating group had lower SCZ_PRS and was likelier to have used high-potency cannabis daily. Patients with FEP clustered according to their premorbid and cognitive abilities. Pronounced premorbid deterioration was not typical of most FEP, including those more strongly predisposed to schizophrenia, but appeared in a cluster with a history of high-potency cannabis use

QCD and strongly coupled gauge theories : challenges and perspectives

We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.Peer reviewe