Heteroskedasticity of Unknown Form in Spatial Autoregressive Models with Moving Average Disturbance Term

In this study, I investigate the necessary condition for the consistency of the maximum likelihood estimator (MLE) of spatial models with a spatial moving average process in the disturbance term. I show that the MLE of spatial autoregressive and spatial moving average parameters is generally inconsistent when heteroskedasticity is not considered in the estimation. I also show that the MLE of parameters of exogenous variables is inconsistent and determine its asymptotic bias. I provide simulation results to evaluate the performance of the MLE. The simulation results indicate that the MLE imposes a substantial amount of bias on both autoregressive and moving average parameters

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Serum Lipopolysaccharide Binding Protein Levels Predict Severity of Lung Injury and Mortality in Patients with Severe Sepsis

Background: There is a need for biomarkers insuring identification of septic patients at high-risk for death. We performed a prospective, multicenter, observational study to investigate the time-course of lipopolysaccharide binding protein (LBP) serum levels in patients with severe sepsis and examined whether serial serum levels of LBP could be used as a marker of outcome. Methodology/Principal Findings: LBP serum levels at study entry, at 48 hours and at day-7 were measured in 180 patients with severe sepsis. Data regarding the nature of infections, disease severity, development of acute lung injury (ALI) and acute respiratory distress syndrome (ARDS), and intensive care unit (ICU) outcome were recorded. LBP serum levels were similar in survivors and non-survivors at study entry (117.4±75.7 µg/mL vs. 129.8±71.3 µg/mL, P = 0.249) but there were significant differences at 48 hours (77.2±57.0 vs. 121.2±73.4 µg/mL, P<0.0001) and at day-7 (64.7±45.8 vs. 89.7±61.1 µg/ml, p = 0.017). At 48 hours, LBP levels were significantly higher in ARDS patients than in ALI patients (112.5±71.8 µg/ml vs. 76.6±55.9 µg/ml, P = 0.0001). An increase of LBP levels at 48 hours was associated with higher mortality (odds ratio 3.97; 95%CI: 1.84–8.56; P<0.001). Conclusions/Significance: Serial LBP serum measurements may offer a clinically useful biomarker for identification of patients with severe sepsis having the worst outcomes and the highest probability of developing sepsis-induced ARDS

Hydrologic Alterations from Climate Change Inform Assessment of Ecological Risk to Pacific Salmon in Bristol Bay, Alaska

<div><p>We developed an integrated hydrologic model of the upper Nushagak and Kvichak watersheds in the Bristol Bay region of southwestern Alaska, a region under substantial development pressure from large-scale copper mining. We incorporated climate change scenarios into this model to evaluate how hydrologic regimes and stream temperatures might change in a future climate, and to summarize indicators of hydrologic alteration that are relevant to salmon habitat ecology and life history. Model simulations project substantial changes in mean winter flow, peak flow dates, and water temperature by 2100. In particular, we find that annual hydrographs will no longer be dominated by a single spring thaw event, but will instead be characterized by numerous high flow events throughout the winter. Stream temperatures increase in all future scenarios, although these temperature increases are moderated relative to air temperatures by cool baseflow inputs during the summer months. Projected changes to flow and stream temperature could influence salmon through alterations in the suitability of spawning gravels, changes in the duration of incubation, increased growth during juvenile stages, and increased exposure to chronic and acute temperature stress. These climate-modulated changes represent a shifting baseline in salmon habitat quality and quantity in the future, and an important consideration to adequately assess the types and magnitude of risks associated with proposed large-scale mining in the region.</p></div