Deep Probabilistic Modelling of Price Movements for High-Frequency Trading

In this paper we propose a deep recurrent architecture for the probabilistic modelling of high-frequency market prices, important for the risk management of automated trading systems. Our proposed architecture incorporates probabilistic mixture models into deep recurrent neural networks. The resulting deep mixture models simultaneously address several practical challenges important in the development of automated high-frequency trading strategies that were previously neglected in the literature: 1) probabilistic forecasting of the price movements; 2) single objective prediction of both the direction and size of the price movements. We train our models on high-frequency Bitcoin market data and evaluate them against benchmark models obtained from the literature. We show that our model outperforms the benchmark models in both a metric-based test and in a simulated trading scenarioComment: 8 pages, 2 columns, IJCN

Intra-Day Price Simulation with Generative Adversarial Modelling of the Order Flow

Intra-day price variations in financial markets are driven by the sequence of orders, called the order flow, that is submitted at high frequency by traders. This paper introduces a novel application of the Sequence Generative Adversarial Networks framework to model the order flow, such that random sequences of the order flow can then be generated to simulate the intra-day variation of prices. As a benchmark, a well-known parametric model from the quantitative finance literature is selected. The models are fitted, and then multiple random paths of the order flow sequences are sampled from each model. Model performances are then evaluated by using the generated sequences to simulate price variations, and we compare the empirical regularities between the price variations produced by the generated and real sequences. The empirical regularities considered include the distribution of the price log-returns, the price volatility, and the heavy-tail of the log-returns distributions. The results show that the order sequences from the generative model are better able to reproduce the statistical behaviour of real price variations than the sequences from the benchmark

The Effects of Different HIV Type 1 Strains on Human Thymic Function

Studies of HIV-1-infected humans indicate that the thymus can be infected by HIV-1. In some of these patients, there is a significant CD4+ T cell decline and a faster disease progression. This phenomenon is more evident in pediatric patients who depend heavily on their thymus for generation of new T cells. We hypothesize that HIV-1 causes T cell regenerative failure within the thymus, which has a profound impact on disease progression. Building on our established human thymopoiesis model, we include dynamic interactions between different HIV-1 strains (R5 and X4) and thymocytes. Our results predict that thymic infection with different HIV-1 strains induces thymic dysfunction to varying degrees, contributing to differences in disease progression as observed in both HIV-1-infected children and adults. Thymic infection in children is more severe than in adults, particularly during X4 infection. This outcome is likely due to both a higher viral load and a more active thymus in pediatric patients. Our results also indicate that a viral strain switch from R5 to X4 induces further deterioration in thymopoiesis. We predict that both viral and host factors play key roles in controlling thymic infection, including strain virulence and health status of the thymus.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63198/1/088922202320886280.pd

Soybean-derived Bowman-Birk inhibitor inhibits neurotoxicity of LPS-activated macrophages

<p>Abstract</p> <p>Background</p> <p>Lipopolysaccharide (LPS), the major component of the outer membrane of gram-negative bacteria, can activate immune cells including macrophages. Activation of macrophages in the central nervous system (CNS) contributes to neuronal injury. Bowman-Birk inhibitor (BBI), a soybean-derived protease inhibitor, has anti-inflammatory properties. In this study, we examined whether BBI has the ability to inhibit LPS-mediated macrophage activation, reducing the release of pro-inflammatory cytokines and subsequent neurotoxicity in primary cortical neural cultures.</p> <p>Methods</p> <p>Mixed cortical neural cultures from rat were used as target cells for testing neurotoxicity induced by LPS-treated macrophage supernatant. Neuronal survival was measured using a cell-based ELISA method for expression of the neuronal marker MAP-2. Intracellular reactive oxygen species (ROS) production in macrophages was measured via 2', 7'-dichlorofluorescin diacetate (DCFH₂DA) oxidation. Cytokine expression was determined by quantitative real-time PCR.</p> <p>Results</p> <p>LPS treatment of macrophages induced expression of proinflammatory cytokines (IL-1β, IL-6 and TNF-α) and of ROS. In contrast, BBI pretreatment (1-100 μg/ml) of macrophages significantly inhibited LPS-mediated induction of these cytokines and ROS. Further, supernatant from BBI-pretreated and LPS-activated macrophage cultures was found to be less cytotoxic to neurons than that from non-BBI-pretreated and LPS-activated macrophage cultures. BBI, when directly added to the neuronal cultures (1-100 μg/ml), had no protective effect on neurons with or without LPS-activated macrophage supernatant treatment. In addition, BBI (100 μg/ml) had no effect on N-methyl-D-aspartic acid (NMDA)-mediated neurotoxicity.</p> <p>Conclusions</p> <p>These findings demonstrate that BBI, through its anti-inflammatory properties, protects neurons from neurotoxicity mediated by activated macrophages.</p

Distinct, strict requirements for Gfi-1b in adult bone marrow red cell and platelet generation

The zinc finger transcriptional repressor Gfi-1b is essential for erythroid and megakaryocytic development in the embryo. Its roles in the maintenance of bone marrow erythropoiesis and thrombopoiesis have not been defined. We investigated Gfi-1b’s adult functions using a loxP-flanked Gfi-1b allele in combination with a novel doxycycline-inducible Cre transgene that efficiently mediates recombination in the bone marrow. We reveal strict, lineage-intrinsic requirements for continuous adult Gfi-1b expression at two distinct critical stages of erythropoiesis and megakaryopoiesis. Induced disruption of Gfi-1b was lethal within 3 wk with severely reduced hemoglobin levels and platelet counts. The erythroid lineage was arrested early in bipotential progenitors, which did not give rise to mature erythroid cells in vitro or in vivo. Yet Gfi-1b−/− progenitors had initiated the erythroid program as they expressed many lineage-restricted genes, including Klf1/Eklf and Erythropoietin receptor. In contrast, the megakaryocytic lineage developed beyond the progenitor stage in Gfi-1b’s absence and was arrested at the promegakaryocyte stage, after nuclear polyploidization, but before cytoplasmic maturation. Genome-wide analyses revealed that Gfi-1b directly regulates a wide spectrum of megakaryocytic and erythroid genes, predominantly repressing their expression. Together our study establishes Gfi-1b as a master transcriptional repressor of adult erythropoiesis and thrombopoiesis

Multilaboratory assessment of Epstein-Barr virus serologic assays: the case for standardization

IgA antibodies targeting Epstein-Barr virus (EBV) have been proposed for screening for nasopharyngeal carcinoma (NPC). However, methods differ, and the antigens used in these assays differ considerably between laboratories. To enable formal comparisons across a range of established EBV serology assays, we created a panel of 66 pooled serum samples and 66 pooled plasma samples generated from individuals with a broad range of IgA antibody levels. Aliquots from these panels were distributed to six laboratories and were tested by 26 assays measuring antibodies against VCA, EBNA1, EA-EBNA1, Zta, or EAd antigens. We estimated the correlation between assay pairs using Spearman coefficients (continuous measures) and percentages of agreement (positive versus negative, using predefined positivity cutoffs by each assay developer/manufacturer). While strong correlations were observed between some assays, considerable differences were also noted, even for assays that targeted the same protein. For VCA-IgA assays in serum, two distinct clusters were identified, with a median Spearman coefficient of 0.41 (range, 0.20 to 0.66) across these two clusters. EBNA1-IgA assays in serum grouped into a single cluster with a median Spearman coefficient of 0.79 (range, 0.71 to 0.89). Percentages of agreement differed broadly for both VCA-IgA (12% to 98%) and EBNA1-IgA (29% to 95%) assays in serum. Moderate-to-strong correlations were observed across assays in serum that targeted other proteins (correlations ranged from 0.44 to 0.76). Similar results were noted for plasma. We conclude that standardization of EBV serology assays is needed to allow for comparability of results obtained in different translational research studies across laboratories and populations

Differential symptom weighting in estimating empirical thresholds for underlying PTSD severity: Toward a “platinum” standard for diagnosis?

Objective: Symptom counts as the basis for Post-Traumatic Stress Disorder (PTSD) diagnoses in the DSM presume each symptom is equally reflective of underlying disorder severity. However, the “equal weight” assumption fails to fit PTSD symptom data when tested. The present study developed an enhanced PTSD diagnosis based on (a) a conventional PTSD diagnosis from a clinical interview and (b) an empirical classification of full PTSD that reflected the relative clinical weights of each symptom. Method: Baseline structured interview data from Project Harmony (N = 2658) was used. An enhanced diagnosis for full PTSD was estimated using an empirical threshold from moderated nonlinear factor analysis (MNLFA) latent PTSD scale scores, in combination with a full conventional PTSD diagnosis based on interview data. Results: One in 4 patients in the sample had a PTSD diagnosis that was inconsistent with their empirical PTSD grouping, such that the enhanced diagnostic standard reduced the diagnostic discrepancy rate by 20%. Veterans, and in particular female Veterans, were at greatest odds for discrepancy between their underlying PTSD severity and DSM diagnosis. Conclusion: Psychometric methodologies that differentially weight symptoms can complement DSM criteria and may serve as a platform for symptom prioritization for diagnoses in future editions of DSM

High Glucose Enhances Cytotoxic T Lymphocyte-Mediated Cytotoxicity

Cytotoxic T lymphocytes (CTLs) are key players to eliminate tumorigenic or pathogen-infected cells using lytic granules (LG) and Fas ligand (FasL) pathways. Depletion of glucose leads to severely impaired cytotoxic function of CTLs. However, the impact of excessive glucose on CTL functions still remains largely unknown. Here we used primary human CD8+ T cells, which were stimulated by CD3/CD28 beads and cultured in medium either containing high glucose (HG, 25 mM) or normal glucose (NG, 5.6 mM). We found that in HG-CTLs, glucose uptake and glycolysis were enhanced, whereas proliferation remained unaltered. Furthermore, CTLs cultured in HG exhibited an enhanced CTL killing efficiency compared to their counterparts in NG. Unexpectedly, expression of cytotoxic proteins (perforin, granzyme A, granzyme B and FasL), LG release, cytokine/cytotoxic protein release and CTL migration remained unchanged in HG-cultured CTLs. Interestingly, additional extracellular Ca2+ diminished HG-enhanced CTL killing function. Our findings suggest that in an environment with excessive glucose, CTLs could eliminate target cells more efficiently, at least for a certain period of time, in a Ca2+-dependent manner

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts