Matrix Models and D-branes in Twistor String Theory

We construct two matrix models from twistor string theory: one by dimensional reduction onto a rational curve and another one by introducing noncommutative coordinates on the fibres of the supertwistor space P^(3|4)->CP^1. We comment on the interpretation of our matrix models in terms of topological D-branes and relate them to a recently proposed string field theory. By extending one of the models, we can carry over all the ingredients of the super ADHM construction to a D-brane configuration in the supertwistor space P^(3|4). Eventually, we present the analogue picture for the (super) Nahm construction.Comment: 1+37 pages, reference added, JHEP style, published versio

Treatment response classes in major depressive disorder identified by model-based clustering and validated by clinical prediction models

The identification of generalizable treatment response classes (TRC[s]) in major depressive disorder (MDD) would facilitate comparisons across studies and the development of treatment prediction algorithms. Here, we investigated whether such stable TRCs can be identified and predicted by clinical baseline items. We analyzed data from an observational MDD cohort (Munich Antidepressant Response Signature [MARS] study, N = 1017), treated individually by psychopharmacological and psychotherapeutic means, and a multicenter, partially randomized clinical/pharmacogenomic study (Genome-based Therapeutic Drugs for Depression [GENDEP], N = 809). Symptoms were evaluated up to week 16 (or discharge) in MARS and week 12 in GENDEP. Clustering was performed on 809 MARS patients (discovery sample) using a mixed model with the integrated completed likelihood criterion for the assessment of cluster stability, and validated through a distinct MARS validation sample and GENDEP. A random forest algorithm was used to identify prediction patterns based on 50 clinical baseline items. From the clustering of the MARS discovery sample, seven TRCs emerged ranging from fast and complete response (average 4.9 weeks until discharge, 94% remitted patients) to slow and incomplete response (10% remitted patients at week 16). These proved stable representations of treatment response dynamics in both the MARS and the GENDEP validation sample. TRCs were strongly associated with established response markers, particularly the rate of remitted patients at discharge. TRCs were predictable from clinical items, particularly personality items, life events, episode duration, and specific psychopathological features. Prediction accuracy improved significantly when cluster-derived slopes were modelled instead of individual slopes. In conclusion, model-based clustering identified distinct and clinically meaningful treatment response classes in MDD that proved robust with regard to capturing response profiles of differently designed studies. Response classes were predictable from clinical baseline characteristics. Conceptually, model-based clustering is translatable to any outcome measure and could advance the large-scale integration of studies on treatment efficacy or the neurobiology of treatment response

Applied immuno-epidemiological research: an approach for integrating existing knowledge into the statistical analysis of multiple immune markers.

BACKGROUND: Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists' hypotheses about the underlying biological mechanisms to be integrated. RESULTS: We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies. We demonstrate i) how to deal with interdependencies among multiple measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach. CONCLUSION: The proposed analytical approach may be especially useful to quantify complex immune responses in immuno-epidemiological studies, where investigators examine the relationship among epidemiological patterns, immune response, and disease outcomes

The Risk of Severe Infections Following Rituximab Administration in Patients With Autoimmune Kidney Diseases: Austrian ABCDE Registry Analysis.

OBJECTIVE: To characterize the incidence, type, and risk factors of severe infections (SI) in patients with autoimmune kidney diseases treated with rituximab (RTX). METHODS: We conducted a multicenter retrospective cohort study of adult patients with immune-related kidney diseases treated with at least one course of RTX between 2015 and 2019. As a part of the ABCDE Registry, detailed data on RTX application and SI were collected. SI were defined by Common Terminology Criteria for Adverse Events v5.0 as infectious complications grade 3 and above. Patients were dichotomized between "nephrotic" and "nephritic" indications. The primary outcome was the incidence of SI within 12 months after the first RTX application. RESULTS: A total of 144 patients were included. Twenty-five patients (17.4%) presented with SI, mostly within the first 3 months after RTX administration. Most patients in the nephritic group had ANCA-associated vasculitis, while membranous nephropathy was the leading entity in the nephrotic group. Respiratory infections were the leading SI (n= 10, 40%), followed by urinary tract (n=3, 12%) and gastrointestinal infections (n=2, 8%). On multivariable analysis, body mass index (BMI, 24.6 kg/m2versus 26.9 kg/m2, HR: 0.88; 95%CI: 0.79-0.99; p=0.039) and baseline creatinine (HR: 1.25; 95%CI: 1.04-1.49; p=0.017) were significantly associated with SI. All patients in the nephritic group (n=19; 100%) who experienced a SI received oral glucocorticoid (GC) treatment at the time of infection. Hypogammaglobulinemia was frequent (58.5%) but not associated with SI. CONCLUSIONS: After RTX administration, impaired kidney function and lower BMI are independent risk factors for SI. Patients with nephritic glomerular diseases having concomitant GC treatment might be at higher risk of developing SI

SLAM-associated protein deficiency causes imbalanced early signal transduction and blocks downstream activation in T cells from X-linked lymphoproliferative disease patients

Deficiency of SAP (SLAM (signaling lymphocyte activation molecule)-associated protein) protein is associated with a severe immunodeficiency, the X-linked lymphoproliferative disease (XLP) characterized by an inappropriate immune reaction against Epstein-Barr virus infection often resulting in a fatal clinical course. Several studies demonstrated altered NK and T cell function in XLP patients; however, the mechanisms underlying XLP disease are still largely unknown. Here, we show that non-transformed T cell lines obtained from XLP patients were defective in several activation events such as IL-2 production, CD25 expression, and homotypic cell aggregation when cells were stimulated via T cell antigen receptor (TCR).CD3 but not when early TCR-dependent events were bypassed by stimulation with phorbol 12-myristate 13-acetate/ionomycin. Analysis of proximal T cell signaling revealed imbalanced TCR.CD3-induced signaling in SAP-deficient T cells. Although phospholipase C gamma 1 phosphorylation and calcium response were both enhanced in T cells from XLP patients, phosphorylation of VAV and downstream signal transduction events such as mitogen-activated protein kinase phosphorylation and IL-2 production were diminished. Importantly, reconstitution of SAP expression by retroviral-mediated gene transfer completely restored abnormal signaling events in T cell lines derived from XLP patients. In conclusion, SAP mutation or deletion in XLP patients causes profound defects in T cell activation, resulting in immune deficiency. Moreover, these data provide evidence that SAP functions as an essential integrator in early TCR signal transduction

Additional file 1: of Applied immuno-epidemiological research: an approach for integrating existing knowledge into the statistical analysis of multiple immune markers

Table S1. Distributions of recoded ordinal cytokine data (818 children from SCAALA Salvador). Table S2. Bivariate association analysis for IL-13 responsiveness produced under different culture conditions in vitro using data collected from 818 children in SCAALA Salvador. Table S3. Comparison of statistical approaches used to model the effect of cytokine concentrations on the outcome sIgE (maximum concentration of five antigens). Figure S1. Boxplots of cytokine concentrations (in pg/ml) obtained from different cell cultures (N=818 children from SCAALA Salvador). Figure S2. Intra-cytokine analysis: Correspondence pattern among IL-13 measures. Figure S3. Th2 inter-cytokine analysis: correspondence analysis biplots IL-5 vs. IL-13. Figure S4. Correspondence analysis biplots Th2 response and Th1/Th2 balance vs. T-Reg response. (DOCX 332 kb

Cell Reports / mTOR Senses Environmental Cues to Shape the Fibroblast-like Synoviocyte Response to Inflammation

Accumulating evidence suggests that metabolic-master regulators, including mTOR, regulate adaptive and innate immune responses. Resident mesenchymal tissue components are increasingly recognized as key effector cells in inflammation. Whether mTOR also controls the inflammatory response in fibroblasts is insufficiently studied. Here, we show that TNF signaling co-opts the mTOR pathway to shift synovial fibroblast (FLS) inflammation toward an IFN response. mTOR pathway activation is associated with decreased NF-kappa B-mediated gene expression (e.g., PTGS2, IL-6, and IL-8) but increased STAT1-dependent gene expression (e.g., CXCL11 and TNFSF13B). We further demonstrate how metabolic inputs, such as amino acids, impinge on TNF-mTORC1 signaling to differentially regulate pro-inflammatory signaling circuits. Our results define a critical role for mTOR in the regulation of the pro-inflammatory response in FLSs and unfold its pathogenic involvement in TNF-driven diseases, such as rheumatoid arthritis (RA).(VLID)456268

The Neuronal Transporter Gene SLC6A15 Confers Risk to Major Depression

SummaryMajor depression (MD) is one of the most prevalent psychiatric disorders and a leading cause of loss in work productivity. A combination of genetic and environmental risk factors probably contributes to MD. We present data from a genome-wide association study revealing a neuron-specific neutral amino acid transporter (SLC6A15) as a susceptibility gene for MD. Risk allele carrier status in humans and chronic stress in mice were associated with a downregulation of the expression of this gene in the hippocampus, a brain region implicated in the pathophysiology of MD. The same polymorphisms also showed associations with alterations in hippocampal volume and neuronal integrity. Thus, decreased SLC6A15 expression, due to genetic or environmental factors, might alter neuronal circuits related to the susceptibility for MD. Our convergent data from human genetics, expression studies, brain imaging, and animal models suggest a pathophysiological mechanism for MD that may be accessible to drug targeting