59 research outputs found

    AQP4-IgG-seronegative patient outcomes in the N-MOmentum trial of inebilizumab in neuromyelitis optica spectrum disorder

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    BACKGROUND: The N-MOmentum trial, a double-blind, randomized, placebo-controlled, phase 2/3 study of inebilizumab in neuromyelitis optica spectrum disorder (NMOSD), enrolled participants who were aquaporin-4-immunoglobulin G (AQP4-IgG)-seropositive (AQP4+) or -seronegative (AQP4−). This manuscript reports AQP4− participant outcomes. METHODS: AQP4-IgG serostatus was determined for all screened participants by a central laboratory, using a validated, fluorescence-observation cell-binding assay. Medical histories and screening data for AQP4− participants were assessed independently by an eligibility committee of three clinical experts during screening. Diagnosis of NMOSD was confirmed by majority decision using the 2006 neuromyelitis optica criteria. Myelin oligodendrocyte glycoprotein-immunoglobulin G (MOG-IgG) serology (using a clinically validated, flow cytometry assay) and annualized attack rates (AARs) were evaluated post hoc. Efficacy outcomes were assessed by comparing pre-study and on-study AARs in treated participants. RESULTS: Only 18/50 AQP4− screened participants (36%) were initially considered eligible for randomization; 16 were randomized and received full treatment, 4 to placebo (1 MOG-IgG-seropositive [MOG+]) and 12 to inebilizumab (6 MOG+). The most common reason for failure to pass screening among prospective AQP4− participants was failure to fulfill the 2006 NMO MRI criteria. In inebilizumab-treated AQP4− participants, on-study AARs (95% confidence interval [CI]) calculated from treatment initiation (whether from randomization or when received at the start of the open-label period) to the end of study were lower than pre-study rates: for all AQP4− participants (n = 16), mean (95% CI) AAR was 0.048 (0.02–0.15) versus 1.70 (0.74–2.66), respectively. For the subset of AQP4−/MOG+ participants (n = 7), AAR was 0.043 (0.006–0.302) after treatment versus 1.93 (1.10–3.14) before the study. For the subset of AQP4−/MOG− participants (n = 9), post-treatment AAR was 0.051 (0.013–0.204) versus 1.60 (1.02–2.38). Three attacks occurred during the randomized controlled period in the AQP4− inebilizumab group and were of mild severity; no attacks occurred in the AQP4− placebo group. The low number of participants receiving placebo (n = 4) confounds direct comparison with the inebilizumab group. No attacks were seen in any AQP4− participant after the second infusion of inebilizumab. Inebilizumab was generally well tolerated by AQP4− participants and the adverse event profile observed was similar to that of AQP4+ participants. CONCLUSION: The high rate of rejection of AQP4− participants from enrollment into the study highlights the challenges of implementing the diagnostic criteria of AQP4− NMOSD. An apparent reduction of AAR in participants with AQP4− NMOSD who received inebilizumab warrants further investigation

    CD95-mediated calcium signaling promotes T helper 17 trafficking to inflamed organs in lupus-prone mice

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    CD95 ligand (CD95L) is expressed by immune cells and triggers apoptotic death. Metalloprotease-cleaved CD95L (cl-CD95L) is released into the bloodstream but does not trigger apoptotic signaling. Hence, the pathophysiological role of cl-CD95L remains unclear. We observed that skin-derived endothelial cells from systemic lupus erythematosus (SLE) patients expressed CD95L and that after cleavage, cl-CD95L promoted T helper 17 (Th17) lymphocyte transmigration across the endothelial barrier at the expense of T regulatory cells. T cell migration relied on a direct interaction between the CD95 domain called calcium-inducing domain (CID) and the Src homology 3 domain of phospholipase Cγ1. Th17 cells stimulated with cl-CD95L produced sphingosine-1-phosphate (S1P), which promoted endothelial transmigration by activating the S1P receptor 3. We generated a cell-penetrating CID peptide that prevented Th17 cell transmigration and alleviated clinical symptoms in lupus mice. Therefore, neutralizing the CD95 non-apoptotic signaling pathway could be an attractive therapeutic approach for SLE treatment

    Disability outcomes in the N-MOmentum trial of inebilizumab in neuromyelitis optica spectrum disorder

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    OBJECTIVE: To assess treatment effects on Expanded Disability Status Scale (EDSS) score worsening and modified Rankin Scale (mRS) scores in the N-MOmentum trial of inebilizumab, a humanized anti-CD19 monoclonal antibody, in participants with neuromyelitis optica spectrum disorder (NMOSD). METHODS: Adults (N = 230) with aquaporin-4 immunoglobulin G-seropositive NMOSD or -seronegative neuromyelitis optica and an EDSS score ≤8 were randomized (3:1) to receive inebilizumab 300 mg or placebo on days 1 and 15. The randomized controlled period (RCP) was 28 weeks or until adjudicated attack, with an option to enter the inebilizumab open-label period. Three-month EDSS-confirmed disability progression (CDP) was assessed using a Cox proportional hazard model. The effect of baseline subgroups on disability was assessed by interaction tests. mRS scores from the RCP were analyzed by the Wilcoxon-Mann-Whitney odds approach. RESULTS: Compared with placebo, inebilizumab reduced the risk of 3-month CDP (hazard ratio [HR]: 0.375; 95% CI: 0.148-0.952; p = 0.0390). Baseline disability, prestudy attack frequency, and disease duration did not affect the treatment effect observed with inebilizumab (HRs: 0.213-0.503; interaction tests: all p > 0.05, indicating no effect of baseline covariates on outcome). Mean EDSS scores improved with longer-term treatment. Inebilizumab-treated participants were more likely to have a favorable mRS outcome at the end of the RCP (OR: 1.663; 95% CI: 1.195-2.385; p = 0.0023). CONCLUSIONS: Disability outcomes were more favorable with inebilizumab vs placebo in participants with NMOSD

    TRAIL Death Receptor-4, Decoy Receptor-1 and Decoy Receptor-2 Expression on CD8+ T Cells Correlate with the Disease Severity in Patients with Rheumatoid Arthritis

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    BACKGROUND: Rheumatoid Arthritis (RA) is a chronic autoimmune inflammatory disorder. Although the pathogenesis of disease is unclear, it is well known that T cells play a major role in both development and perpetuation of RA through activating macrophages and B cells. Since the lack of TNF-Related Apoptosis Inducing Ligand (TRAIL) expression resulted in defective thymocyte apoptosis leading to an autoimmune disease, we explored evidence for alterations in TRAIL/TRAIL receptor expression on peripheral T lymphocytes in the molecular mechanism of RA development. METHODS: The expression of TRAIL/TRAIL receptors on T cells in 20 RA patients and 12 control individuals were analyzed using flow cytometry. The correlation of TRAIL and its receptor expression profile was compared with clinical RA parameters (RA activity scored as per DAS28) using Spearman Rho Analysis. RESULTS: While no change was detected in the ratio of CD4+ to CD8+ T cells between controls and RA patient groups, upregulation of TRAIL and its receptors (both death and decoy) was detected on both CD4+ and CD8+ T cells in RA patients compared to control individuals. Death Receptor-4 (DR4) and the decoy receptors DcR1 and DcR2 on CD8+ T cells, but not on CD4+ T cells, were positively correlated with patients' DAS scores. CONCLUSIONS: Our data suggest that TRAIL/TRAIL receptor expression profiles on T cells might be important in revelation of RA pathogenesis

    Simulation Model Development Based On The Function Point Metric

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    The research project SESAM (Software Engineering Simulation by Animated Models) aims at providing a training environment for future project managers. The basic idea is to create a model of the software development process that can be interpreted by a simulator. The student using the simulator can control the simulated project interactively, leading it more or less successfully. In this paper, the simulation system is presented. Then, a new simulation model, the QA (Quality Assurance) model, is introduced. Discussion focuses on the metrics system used. The QA model covers all activities of software development, from requirements specification to product delivery. It especially emphasises the effects of quality assurance activities. Finally, simulation results obtained by executing the model are presented and discussed. 1. INTRODUCTION Over the last twenty-five years, software development projects have increasingly been plagued by schedule and cost overruns, while product quality is oft..

    Modeling and Simulation of Software Projects

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    Introduction to SESAM Over the last twenty five years, software development projects have increasingly been plagued by schedule and cost overruns, while product quality is often poor. The term "software crisis" has been coined to highlight this situation. The lack of adequate methods and tools to support software development, and of techniques to simplify project management tasks have been identified as major factors contributing to the "software crisis". In reaction to this, the software engineering community has attempted to devise a number of analytical and constructive operations to both handle the complexity of software development and assure quality of the resulting products. However, despite an impressive evolution of methods and technology in the past years, neither the software development process nor overall product quality have improved significantly. Part of the reason for this appears to be a serious lack of understanding of the software development process. It i

    Forschungsprojekt SESAM

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