Short-Term Price Forecasting Models Based on Artificial Neural Networks for Intraday Sessions in the Iberian Electricity Market

This paper presents novel intraday session models for price forecasts (ISMPF models) for hourly price forecasting in the six intraday sessions of the Iberian electricity market (MIBEL) and the analysis of mean absolute percentage errors (MAPEs) obtained with suitable combinations of their input variables in order to find the best ISMPF models. Comparisons of errors from different ISMPF models identified the most important variables for forecasting purposes. Similar analyses were applied to determine the best daily session models for price forecasts (DSMPF models) for the day-ahead price forecasting in the daily session of the MIBEL, considering as input variables extensive hourly time series records of recent prices, power demands and power generations in the previous day, forecasts of demand, wind power generation and weather for the day-ahead, and chronological variables. ISMPF models include the input variables of DSMPF models as well as the daily session prices and prices of preceding intraday sessions. The best ISMPF models achieved lower MAPEs for most of the intraday sessions compared to the error of the best DSMPF model; furthermore, such DSMPF error was very close to the lowest limit error for the daily session. The best ISMPF models can be useful for MIBEL agents of the electricity intraday market and the electric energy industry

Comparison of next-generation sequencing (NGS) and next-generation flow (NGF) for minimal residual disease (MRD) assessment in multiple myeloma

Detecting persistent minimal residual disease (MRD) allows the identification of patients with an increased risk of relapse and death. In this study, we have evaluated MRD 3 months after transplantation in 106 myeloma patients using a commercial next-generation sequencing (NGS) strategy (LymphoTrack®), and compared the results with next-generation flow (NGF, EuroFlow). The use of different marrow pulls and the need of concentrating samples for NGS biased the applicability for MRD evaluation and favored NGF. Despite that, correlation between NGS and NGF was high (R = 0.905). The 3-year progression-free survival (PFS) rates by NGS and NGF were longer for undetectable vs. positive patients (NGS: 88.7% vs. 56.6%; NGF: 91.4% vs. 50%; p < 0.001 for both comparisons), which resulted in a 3-year overall survival (OS) advantage (NGS: 96.2% vs. 77.3%; NGF: 96.6% vs. 74.9%, p < 0.01 for both comparisons). In the Cox regression model, NGS and NGF negativity had similar results but favoring the latter in PFS (HR: 0.20, 95% CI: 0.09-0.45, p < 0.001) and OS (HR: 0.21, 95% CI: 0.06-0.75, p = 0.02). All these results reinforce the role of MRD detection by different strategies in patient prognosis and highlight the use of MRD as an endpoint for multiple myeloma treatment

Subtype Specificity of Genetic Loci Associated With Stroke in 16 664 Cases and 32 792 Controls

Background: Genome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischemic and hemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes. Methods: We performed Bayesian multinomial regression in 16 664 stroke cases and 32 792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under 2 commonly used stroke classification systems, TOAST (Trial of Org 10172 Acute Stroke Treatment) and causative classification of stroke. All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel. Results: Sixteen loci were considered for analysis. Seven loci influenced both hemorrhagic and ischemic stroke, 3 of which influenced ischemic and hemorrhagic subtypes under both TOAST and causative classification of stroke. Under causative classification of stroke, 4 loci influenced both small vessel stroke and intracerebral hemorrhage. An EDNRA locus demonstrated opposing effects on ischemic and hemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction, and only one locus (12q24) was predicted to influence all ischemic stroke subtypes. Conclusions: Heterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between hemorrhagic and ischemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms

Subtype Specificity of Genetic Loci Associated With Stroke in 16 664 Cases and 32 792 Controls

Background: Genome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischemic and hemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes. Methods: We performed Bayesian multinomial regression in 16 664 stroke cases and 32 792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under 2 commonly used stroke classification systems, TOAST (Trial of Org 10172 Acute Stroke Treatment) and causative classification of stroke. All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel. Results: Sixteen loci were considered for analysis. Seven loci influenced both hemorrhagic and ischemic stroke, 3 of which influenced ischemic and hemorrhagic subtypes under both TOAST and causative classification of stroke. Under causative classification of stroke, 4 loci influenced both small vessel stroke and intracerebral hemorrhage. An EDNRA locus demonstrated opposing effects on ischemic and hemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction, and only one locus (12q24) was predicted to influence all ischemic stroke subtypes. Conclusions: Heterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between hemorrhagic and ischemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms

JTT-130, a microsomal triglyceride transfer protein (MTP) inhibitor lowers plasma triglycerides and LDL cholesterol concentrations without increasing hepatic triglycerides in guinea pigs

BACKGROUND: Microsomal transfer protein inhibitors (MTPi) have the potential to be used as a drug to lower plasma lipids, mainly plasma triglycerides (TG). However, studies with animal models have indicated that MTPi treatment results in the accumulation of hepatic TG. The purpose of this study was to evaluate whether JTT-130, a unique MTPi, targeted to the intestine, would effectively reduce plasma lipids without inducing a fatty liver. METHODS: Male guinea pigs (n = 10 per group) were used for this experiment. Initially all guinea pigs were fed a hypercholesterolemic diet containing 0.08 g/100 g dietary cholesterol for 3 wk. After this period, animals were randomly assigned to diets containing 0 (control), 0.0005 or 0.0015 g/100 g of MTPi for 4 wk. A diet containing 0.05 g/100 g of atorvastatin, an HMG-CoA reductase inhibitor was used as the positive control. At the end of the 7(th )week, guinea pigs were sacrificed to assess drug effects on plasma and hepatic lipids, composition of LDL and VLDL, hepatic cholesterol and lipoprotein metabolism. RESULTS: Plasma LDL cholesterol and TG were 25 and 30% lower in guinea pigs treated with MTPi compared to controls (P < 0.05). Atorvastatin had the most pronounced hypolipidemic effects with a 35% reduction in LDL cholesterol and 40% reduction in TG. JTT-130 did not induce hepatic lipid accumulation compared to controls. Cholesteryl ester transfer protein (CETP) activity was reduced in a dose dependent manner by increasing doses of MTPi and guinea pigs treated with atorvastatin had the lowest CETP activity (P < 0.01). In addition the number of molecules of cholesteryl ester in LDL and LDL diameter were lower in guinea pigs treated with atorvastatin. In contrast, hepatic enzymes involved in maintaining cholesterol homeostasis were not affected by drug treatment. CONCLUSION: These results suggest that JTT-130 could have potential clinical applications due to its plasma lipid lowering effects with no alterations in hepatic lipid concentrations

GISCOME – Genetics of Ischaemic Stroke Functional Outcome network: A protocol for an international multicentre genetic association study

© 2017, © European Stroke Organisation 2017. Introduction: Genome-wide association studies have identified several novel genetic loci associated with stroke risk, but how genetic factors influence stroke outcome is less studied. The Genetics of Ischaemic Stroke Functional outcome network aims at performing genetic studies of stroke outcome. We here describe the study protocol and methods basis of Genetics of Ischaemic Stroke Functional outcome. Methods: The Genetics of Ischaemic Stroke Functional outcome network has assembled patients from 12 ischaemic stroke projects with genome-wide genotypic and outcome data from the International Stroke Genetics Consortium and the National Institute of Neurological Diseases Stroke Genetics Network initiatives. We have assessed the availability of baseline variables, outcome metrics and time-points for collection of outcome data. Results: We have collected 8831 ischaemic stroke cases with genotypic and outcome data. Modified Rankin score was the outcome metric most readily available. We detected heterogeneity between cohorts for age and initial stroke severity (according to the NIH Stroke Scale), and will take this into account in analyses. We intend to conduct a first phase genome-wide association outcome study on ischaemic stroke cases with data on initial stroke severity and modified Rankin score within 60–190 days. To date, we have assembled 5762 such cases and are currently seeking additional cases meeting these criteria for second phase analyses. Conclusion: Genetics of Ischaemic Stroke Functional outcome is a unique collection of ischaemic stroke cases with detailed genetic and outcome data providing an opportunity for discovery of genetic loci influencing functional outcome. Genetics of Ischaemic Stroke Functional outcome will serve as an exploratory study where the results as well as the methodological observations will provide a basis for future studies on functional outcome. Genetics of Ischaemic Stroke Functional outcome can also be used for candidate gene replication or assessing stroke outcome non-genetic association hypotheses

Genome-wide association meta-analysis of functional outcome after ischemic stroke

Objective To discover common genetic variants associated with poststroke outcomes using a genome-wide association (GWA) study. Methods The study comprised 6,165 patients with ischemic stroke from 12 studies in Europe, the United States, and Australia included in the GISCOME (Genetics of Ischaemic Stroke Functional Outcome) network. The primary outcome was modified Rankin Scale score after 60 to 190 days, evaluated as 2 dichotomous variables (0-2 vs 3-6 and 0-1 vs 2-6) and subsequently as an ordinal variable. GWA analyses were performed in each study independently and results were meta-analyzed. Analyses were adjusted for age, sex, stroke severity (baseline NIH Stroke Scale score), and ancestry. The significance level was p <5 x 10(-8). Results We identified one genetic variant associated with functional outcome with genome-wide significance (modified Rankin Scale scores 0-2 vs 3-6, p = 5.3 x 10(-9)). This intronic variant (rs1842681) in the LOC105372028 gene is a previously reported trans-expression quantitative trait locus for PPP1R21, which encodes a regulatory subunit of protein phosphatase 1. This ubiquitous phosphatase is implicated in brain functions such as brain plasticity. Several variants detected in this study demonstrated suggestive association with outcome (p <10(-5)), some of which are within or near genes with experimental evidence of influence on ischemic stroke volume and/or brain recovery (e.g., NTN4, TEK, and PTCH1). Conclusions In this large GWA study on functional outcome after ischemic stroke, we report one significant variant and several variants with suggestive association to outcome 3 months after stroke onset with plausible mechanistic links to poststroke recovery. Future replication studies and exploration of potential functional mechanisms for identified genetic variants are warranted.Peer reviewe

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

Hunt for new phenomena using large jet multiplicities and missing transverse momentum with ATLAS in 4.7 fb−1 of s√=7TeV proton-proton collisions

Results are presented of a search for new particles decaying to large numbers of jets in association with missing transverse momentum, using 4.7 fb−1 of pp collision data at s√=7TeV collected by the ATLAS experiment at the Large Hadron Collider in 2011. The event selection requires missing transverse momentum, no isolated electrons or muons, and from ≥6 to ≥9 jets. No evidence is found for physics beyond the Standard Model. The results are interpreted in the context of a MSUGRA/CMSSM supersymmetric model, where, for large universal scalar mass m 0, gluino masses smaller than 840 GeV are excluded at the 95% confidence level, extending previously published limits. Within a simplified model containing only a gluino octet and a neutralino, gluino masses smaller than 870 GeV are similarly excluded for neutralino masses below 100 GeV