OpenMI: the essential concepts and their implications for legacy software

International audienceInformation & Communication Technology (ICT) tools such as computational models are very helpful in designing river basin management plans (rbmp-s). However, in the scientific world there is consensus that a single integrated modelling system to support e.g. the implementation of the Water Framework Directive cannot be developed and that integrated systems need to be very much tailored to the local situation. As a consequence there is an urgent need to increase the flexibility of modelling systems, such that dedicated model systems can be developed from available building blocks. The HarmonIT project aims at precisely that. Its objective is to develop and implement a standard interface for modelling components and other relevant tools: The Open Modelling Interface (OpenMI) standard. The OpenMI standard has been completed and documented. It relies entirely on the "pull" principle, where data are pulled by one model from the previous model in the chain. This paper gives an overview of the OpenMI standard, explains the foremost concepts and the rational behind it

Does Infall End Before the Class I Stage?

We have observed HCO+ J=3-2 toward 16 Class I sources and 18 Class 0 sources, many of which were selected from Mardones et al. (1997). Eight sources have profiles significantly skewed to the blue relative to optically thin lines. We suggest six sources as new infall candidates. We find an equal "blue excess" among Class 0 and Class I sources after combining this sample with that of Gregersen et al. (1997). We used a Monte Carlo code to simulate the temporal evolution of line profiles of optically thick lines of HCO+, CS and H2CO in a collapsing cloud and found that HCO+ had the strongest asymmetry at late times. If a blue-peaked line profile implies infall, then the dividing line between the two classes does not trace the end of the infall stage.Comment: 21 pages, 8 figures, accepted by ApJ for April 20, 2000, added acknowledgmen

Tailoring temporal description logics for reasoning over temporal conceptual models

Temporal data models have been used to describe how data can evolve in the context of temporal databases. Both the Extended Entity-Relationship (EER) model and the Unified Modelling Language (UML) have been temporally extended to design temporal databases. To automatically check quality properties of conceptual schemas various encoding to Description Logics (DLs) have been proposed in the literature. On the other hand, reasoning on temporally extended DLs turn out to be too complex for effective reasoning ranging from 2ExpTime up to undecidable languages. We propose here to temporalize the ‘light-weight’ DL-Lite logics obtaining nice computational results while still being able to represent various constraints of temporal conceptual models. In particular, we consider temporal extensions of DL-Lite^N_bool, which was shown to be adequate for capturing non-temporal conceptual models without relationship inclusion, and its fragment DL-Lite^N_core with most primitive concept inclusions, which are nevertheless enough to represent almost all types of atemporal constraints (apart from covering)

Erratum: Distinct HLA Associations with Rheumatoid Arthritis Subsets Defined by Serological Subphenotype (The American Journal of Human Genetics (2019) 105(3) (616–624), (S0002929719303052), (10.1016/j.ajhg.2019.08.002))

© 2019 The Author(s) (The American Journal of Human Genetics 105, 616–624; September 5, 2019) In the originally published version of this article, the first author, Chikashi Tereo, had footnotes indicating affiliations with the first seven institutions. The correct affiliations are the first six plus footnote 17, indicating equal contribution. This error has been corrected here and online, and the authors and copyeditor express their regret for the mistake

Methods for high-dimensonal analysis of cells dissociated from cyropreserved synovial tissue

© 2018 The Author(s). Background: Detailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples. Methods: Multiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq. Results: Upon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~ 30 arthroplasty and ~ 20 biopsy samples yielded a consensus digestion protocol using 100 μg/ml of Liberase™ TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4+ and CD8+ T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified. Conclusions: We have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers

Fine mapping seronegative and seropositive rheumatoid arthritis to shared and distinct HLA alleles by adjusting for the effects of heterogeneity

Despite progress in defining human leukocyte antigen (HLA) alleles for anti-citrullinated-protein-autoantibody-positive (ACPA(+)) rheumatoid arthritis (RA), identifying HLA alleles for ACPA-negative (ACPA(-)) RA has been challenging because of clinical heterogeneity within clinical cohorts. We imputed 8,961 classical HLA alleles, amino acids, and SNPs from Immunochip data in a discovery set of 2,406 ACPA(-) RA case and 13,930 control individuals. We developed a statistical approach to identify and adjust for clinical heterogeneity within ACPA(-) RA and observed independent associations for serine and leucine at position 11 in HLA-DRbeta1 (p = 1.4 x 10(-13), odds ratio [OR] = 1.30) and for aspartate at position 9 in HLA-B (p = 2.7 x 10(-12), OR = 1.39) within the peptide binding grooves. These amino acid positions induced associations at HLA-DRB1( *)03 (encoding serine at 11) and HLA-B( *)08 (encoding aspartate at 9). We validated these findings in an independent set of 427 ACPA(-) case subjects, carefully phenotyped with a highly sensitive ACPA assay, and 1,691 control subjects (HLA-DRbeta1 Ser11+Leu11: p = 5.8 x 10(-4), OR = 1.28; HLA-B Asp9: p = 2.6 x 10(-3), OR = 1.34). Although both amino acid sites drove risk of ACPA(+) and ACPA(-) disease, the effects of individual residues at HLA-DRbeta1 position 11 were distinct (p \u3c 2.9 x 10(-107)). We also identified an association with ACPA(+) RA at HLA-A position 77 (p = 2.7 x 10(-8), OR = 0.85) in 7,279 ACPA(+) RA case and 15,870 control subjects. These results contribute to mounting evidence that ACPA(+) and ACPA(-) RA are genetically distinct and potentially have separate autoantigens contributing to pathogenesis. We expect that our approach might have broad applications in analyzing clinical conditions with heterogeneity at both major histocompatibility complex (MHC) and non-MHC regions

IRAS 20050+2720: Anatomy of a young stellar cluster

IRAS 20050+2720 is young star forming region at a distance of 700 pc without apparent high mass stars. We present results of our multiwavelength study of IRAS 20050+2720 which includes observations by Chandra and Spitzer, and 2MASS and UBVRI photometry. In total, about 300 YSOs in different evolutionary stages are found. We characterize the distribution of young stellar objects (YSOs) in this region using a minimum spanning tree (MST) analysis. We newly identify a second cluster core, which consists mostly of class II objects, about 10 arcmin from the center of the cloud. YSOs of earlier evolutionary stages are more clustered than more evolved objects. The X-ray luminosity function (XLF) of IRAS 20050+2720 is roughly lognormal, but steeper than the XLF of the more massive Orion nebula complex. IRAS 20050+2720 shows a lower N_H/A_K ratio compared with the diffuse ISM.Comment: 15 pages, 12 figures, accepted by A