Forum Santé & Environnement

Fédération des Maisons Médicales et des Collectifs de santé francophone – Institut Bruxellois pour la gestion de l’Environnementinfo:eu-repo/semantics/publishe

Offline Detection, Identification, and Correction of Branch Parameter Errors Based on Several Measurement Snapshots

This paper proposes a three-stage offline approach to detect, identify, and correct series and shunt branch parameter errors. In Stage 1 the branches suspected of having parameter errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements adjacent to that branch, whose normalized residuals are higher than a specified threshold value, and the total number of measurements adjacent to that branch. Using several measurement snapshots, in Stage 2 the suspicious parameters are estimated, in a simultaneous multiple-state-and-parameter estimation, via an augmented state and parameter estimator which increases the V - theta state vector for the inclusion of suspicious parameters. Stage 3 enables the validation of the estimation obtained in Stage 2, and is performed via a conventional weighted least squares estimator. Several simulation results (with IEEE bus systems) have demonstrated the reliability of the proposed approach to deal with single and multiple parameter errors in adjacent and non-adjacent branches, as well as in parallel transmission lines with series compensation. Finally the proposed approach is confirmed on tests performed on the Hydro-Quebec TransEnergie network.FAPESPCNPQ[TPWRS-00185-2010

Tumour DDR1 promotes collagen fibre alignment to instigate immune exclusion

Immune exclusion predicts poor patient outcomes in multiple malignancies, including triple-negative breast cancer (TNBC)1. The extracellular matrix (ECM) contributes to immune exclusion2. However, strategies to reduce ECM abundance are largely ineffective or generate undesired outcomes3,4. Here we show that discoidin domain receptor 1 (DDR1), a collagen receptor with tyrosine kinase activity5, instigates immune exclusion by promoting collagen fibre alignment. Ablation of Ddr1 in tumours promotes the intratumoral penetration of T cells and obliterates tumour growth in mouse models of TNBC. Supporting this finding, in human TNBC the expression of DDR1 negatively correlates with the intratumoral abundance of anti-tumour T cells. The DDR1 extracellular domain (DDR1-ECD), but not its intracellular kinase domain, is required for immune exclusion. Membrane-untethered DDR1-ECD is sufficient to rescue the growth of Ddr1-knockout tumours in immunocompetent hosts. Mechanistically, the binding of DDR1-ECD to collagen enforces aligned collagen fibres and obstructs immune infiltration. ECD-neutralizing antibodies disrupt collagen fibre alignment, mitigate immune exclusion and inhibit tumour growth in immunocompetent hosts. Together, our findings identify a mechanism for immune exclusion and suggest an immunotherapeutic target for increasing immune accessibility through reconfiguration of the tumour ECM

Identification of SARS-CoV-2-specific immune alterations in acutely ill patients

Dysregulated immune profiles have been described in symptomatic patients infected with SARS-CoV-2. Whether the reported immune alterations are specific to SARS-CoV-2 infection or also triggered by other acute illnesses remains unclear. We performed flow cytometry analysis on fresh peripheral blood from a consecutive cohort of (a) patients hospitalized with acute SARS-CoV-2 infection, (b) patients of comparable age and sex hospitalized for another acute disease (SARS-CoV-2 negative), and (c) healthy controls. Using both data-driven and hypothesis-driven analyses, we found several dysregulations in immune cell subsets (e.g., decreased proportion of T cells) that were similarly associated with acute SARS-CoV-2 infection and non-COVID-19-related acute illnesses. In contrast, we identified specific differences in myeloid and lymphocyte subsets that were associated with SARS-CoV-2 status (e.g., elevated proportion of ICAM-1+ mature/activated neutrophils, ALCAM+ monocytes, and CD38+CD8+ T cells). A subset of SARS-CoV-2-specific immune alterations correlated with disease severity, disease outcome at 30 days, and mortality. Our data provide an understanding of the immune dysregulation specifically associated with SARS-CoV-2 infection among acute care hospitalized patients. Our study lays the foundation for the development of specific biomarkers to stratify SARS-CoV-2-positive patients at risk of unfavorable outcomes and to uncover candidate molecules to investigate from a therapeutic perspective

Auto-deconvolution and molecular networking of gas chromatography-mass spectrometry data.

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples