DALC: Distributed Automatic LSTM Customization for Fine-Grained Traffic Speed Prediction

Over the past decade, several approaches have been introduced for short-term traffic prediction. However, providing fine-grained traffic prediction for large-scale transportation networks where numerous detectors are geographically deployed to collect traffic data is still an open issue. To address this issue, in this paper, we formulate the problem of customizing an LSTM model for a single detector into a finite Markov decision process and then introduce an Automatic LSTM Customization (ALC) algorithm to automatically customize an LSTM model for a single detector such that the corresponding prediction accuracy can be as satisfactory as possible and the time consumption can be as low as possible. Based on the ALC algorithm, we introduce a distributed approach called Distributed Automatic LSTM Customization (DALC) to customize an LSTM model for every detector in large-scale transportation networks. Our experiment demonstrates that the DALC provides higher prediction accuracy than several approaches provided by Apache Spark MLlib.Comment: 12 pages, 5 figures, the 34th International Conference on Advanced Information Networking and Applications (AINA 2020), Springe

Pharmacogenomics of Interferon-ß Therapy in Multiple Sclerosis: Baseline IFN Signature Determines Pharmacological Differences between Patients

Multiple sclerosis (MS) is a heterogeneous disease. In order to understand the partial responsiveness to IFNbeta in Relapsing Remitting MS (RRMS) we studied the pharmacological effects of IFNbeta therapy. Large scale gene expression profiling was performed on peripheral blood of 16 RRMS patients at baseline and one month after the start of IFNbeta therapy. Differential gene expression was analyzed by Significance Analysis of Microarrays. Subsequent expression analyses on specific genes were performed after three and six months of treatment. Peripheral blood mononuclear cells (PBMC) were isolated and stimulated in vitro with IFNbeta. Genes of interest were measured and validated by quantitative realtime PCR. An independent group of 30 RRMS patients was used for validation. Pharmacogenomics revealed a marked variation in the pharmacological response to IFNbeta between patients. A total of 126 genes were upregulated in a subset of patients whereas in other patients these genes were downregulated or unchanged after one month of IFNbeta therapy. Most interestingly, we observed that the extent of the pharmacological response correlates negatively with the baseline expression of a specific set of 15 IFN response genes (R = -0.7208; p = 0.0016). The negative correlation was maintained after three (R = -0.7363; p = 0.0027) and six (R = -0.8154; p = 0.0004) months of treatment, as determined by gene expression levels of the most significant correlating gene. Similar results were obtained in an independent group of patients (n = 30; R = -0.4719; p = 0.0085). Moreover, the ex vivo results could be confirmed by in vitro stimulation of purified PBMCs at baseline with IFNbeta indicating that differential responsiveness to IFNbeta is an intrinsic feature of peripheral blood cells at baseline. These data imply that the expression levels of IFN response genes in the peripheral blood of MS patients prior to treatment could serve a role as biomarker for the differential clinical response to IFNbet

Acute kidney disease and renal recovery : consensus report of the Acute Disease Quality Initiative (ADQI) 16 Workgroup

Consensus definitions have been reached for both acute kidney injury (AKI) and chronic kidney disease (CKD) and these definitions are now routinely used in research and clinical practice. The KDIGO guideline defines AKI as an abrupt decrease in kidney function occurring over 7 days or less, whereas CKD is defined by the persistence of kidney disease for a period of > 90 days. AKI and CKD are increasingly recognized as related entities and in some instances probably represent a continuum of the disease process. For patients in whom pathophysiologic processes are ongoing, the term acute kidney disease (AKD) has been proposed to define the course of disease after AKI; however, definitions of AKD and strategies for the management of patients with AKD are not currently available. In this consensus statement, the Acute Disease Quality Initiative (ADQI) proposes definitions, staging criteria for AKD, and strategies for the management of affected patients. We also make recommendations for areas of future research, which aim to improve understanding of the underlying processes and improve outcomes for patients with AKD

Immunological mechanism of action and clinical profile of disease-modifying treatments in multiple sclerosis.

Multiple sclerosis (MS) is a life-long, potentially debilitating disease of the central nervous system (CNS). MS is considered to be an immune-mediated disease, and the presence of autoreactive peripheral lymphocytes in CNS compartments is believed to be critical in the process of demyelination and tissue damage in MS. Although MS is not currently a curable disease, several disease-modifying therapies (DMTs) are now available, or are in development. These DMTs are all thought to primarily suppress autoimmune activity within the CNS. Each therapy has its own mechanism of action (MoA) and, as a consequence, each has a different efficacy and safety profile. Neurologists can now select therapies on a more individual, patient-tailored basis, with the aim of maximizing potential for long-term efficacy without interruptions in treatment. The MoA and clinical profile of MS therapies are important considerations when making that choice or when switching therapies due to suboptimal disease response. This article therefore reviews the known and putative immunological MoAs alongside a summary of the clinical profile of therapies approved for relapsing forms of MS, and those in late-stage development, based on published data from pivotal randomized, controlled trials

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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