Increased hazard of myocardial infarction with insulin‐provision therapy in actively smoking patients with diabetes mellitus and stable ischemic heart disease: The BARI 2D (Bypass Angioplasty Revascularization Investigation 2 Diabetes) trial

Background In the BARI 2D (Bypass Angioplasty Revascularization Investigation 2 Diabetes) trial, randomization of diabetic patients with stable ischemic heart disease to insulin provision ( IP ) therapy, as opposed to insulin sensitization ( IS ) therapy, resulted in biochemical evidence of impaired fibrinolysis but no increase in adverse clinical outcomes. We hypothesized that the prothrombotic effect of IP therapy in combination with the hypercoagulable state induced by active smoking would result in an increased risk of myocardial infarction ( MI ). Methods and Results We analyzed BARI 2D patients who were active smokers randomized to IP or IS therapy. The primary end point was fatal or nonfatal MI . PAI ‐1 (plasminogen activator inhibitor 1) activity was analyzed at 1, 3, and 5 years. Of 295 active smokers, MI occurred in 15.4% randomized to IP and in 6.8% randomized to IS over the 5.3 years ( P =0.023). IP therapy was associated with a 3.2‐fold increase in the hazard of MI compared with IS therapy (hazard ratio: 3.23; 95% confidence interval, 1.43–7.28; P =0.005). Baseline PAI ‐1 activity (19.0 versus 17.5 Au/mL, P =0.70) was similar in actively smoking patients randomized to IP or IS therapy. However, IP therapy resulted in significantly increased PAI ‐1 activity at 1 year (23.0 versus 16.0 Au/mL, P =0.001), 3 years (24.0 versus 18.0 Au/mL, P =0.049), and 5 years (29.0 versus 15.0 Au/mL, P =0.004) compared with IS therapy. Conclusions Among diabetic patients with stable ischemic heart disease who were actively smoking, IP therapy was independently associated with a significantly increased hazard of MI . This finding may be explained by higher PAI ‐1 activity in active smokers treated with IP therapy. Clinical Trial Registration URL : http://www.clinicaltrials.gov . Unique identifier: NCT 00006305. </jats:sec

Estimating regional evapotranspiration from remotely sensed data by surface energy balance models

Spatial and temporal variations of surface radiative temperatures of the burned and unburned areas of the Konza tallgrass prairie were studied. The role of management practices, topographic conditions and the uncertainties associated with in situ or airborne surface temperature measurements were assessed. Evaluation of diurnal and seasonal spectral characteristics of the burned and unburned areas of the prairie was also made. This was accomplished based on the analysis of measured spectral reflectance of the grass canopies under field conditions, and modelling their spectral behavior using a one dimensional radiative transfer model

TNFα-stimulated gene-6 (TSG6) activates macrophage phenotype transition to prevent inflammatory lung injury

TNFα-stimulated gene-6 (TSG6), a 30-kDa protein generated by activated macrophages, modulates inflammation; however, its mechanism of action and role in the activation of macrophages are not fully understood. Here we observed markedly augmented LPS-induced inflammatory lung injury and mortality in TSG6−/− mice compared with WT (TSG6+/+) mice. Treatment of mice with intratracheal instillation of TSG6 prevented LPS-induced lung injury and neutrophil sequestration, and increased survival in mice. We found that TSG6 inhibited the association of TLR4withMyD88, thereby suppressing NF-κB activation. TSG6 also prevented the expression of proinflammatory proteins (iNOS, IL-6, TNFα, IL-1β, and CXCL1) while increasing the expression of antiinflammatory proteins (CD206, Chi3l3, IL-4, and IL-10) in macrophages. This shift was associated with suppressed activation of proinflammatory transcription factors STAT1 and STAT3. In addition, we observed that LPS itself up-regulated the expression of TSG6 in TSG6+/+ mice, suggesting an autocrine role for TSG6 in transitioning macrophages. Thus, TSG6 functions by converting macrophages from a proinflammatory to an anti-inflammatory phenotype secondary to suppression of TLR4/NF-κB signaling and STAT1 and STAT3 activation

Genetic Variation Is the Major Determinant of Individual Differences in Leukocyte Endothelial Adhesion

Objective: To determine the genetic contribution to leukocyte endothelial adhesion.Methods: Leukocyte endothelial adhesion was assessed through a novel cell-based assay using human lymphoblastoid cell lines. A high-throughput screening method was developed to evaluate the inter-individual variability in leukocyte endothelial adhesion using lymphoblastoid cell lines derived from different donors. To assess heritability, ninety-two lymphoblastoid cell lines derived from twenty-three monozygotic twin pairs and twenty-three sibling pairs were compared. These lymphoblastoid cell lines were plated with the endothelial cell line EA.hy926 and labeled with Calcein AM dye. Fluorescence was assessed to determine endothelial cell adhesion to each lymphoblastoid cell line. Intra-pair similarity was determined for monozygotic twins and siblings using Pearson pairwise correlation coefficients.Results: A leukocyte endothelial adhesion assay for lymphoblastoid cell lines was developed and optimized (CV = 8.68, Z′-factor = 0.67, SNR = 18.41). A higher adhesion correlation was found between the twins than that between the siblings. Intra-pair similarity for leukocyte endothelial adhesion in monozygotic twins was 0.60 compared to 0.25 in the siblings. The extent to which these differences are attributable to underlying genetic factors was quantified and the heritability of leukocyte endothelial adhesion was calculated to be 69.66% (p-valueConclusions: There is a heritable component to leukocyte endothelial adhesion. Underlying genetic predisposition plays a significant role in inter-individual variability of leukocyte endothelial adhesion.</p

Modeling sustainability : Population, inequality, consumption, and bidirectional coupling of the Earth and human systems

Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. We argue that in order to understand the dynamics of either system, Earth SystemModels must be coupled with Human SystemModels through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as United Nations population projections.This makes current models likely to miss important feedbacks in the real Earth-Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models.The importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth-Human system models for devising effective science-based policies and measures to benefit current and future generations

An Earth-system prediction initiative for the twenty-first century

International audienceSome scientists have proposed the Earth-System Prediction Initiative (EPI) at the 2007 GEO Summit in Cape Town, South Africa. EPI will draw upon coordination between international programs for Earth system observations, prediction, and warning, such as the WCRP, WWRP, GCOS, and hence contribute to GEO and the GEOSS. It will link with international organizations, such as the International Council for Science (ICSU), Intergovernmental Oceanographic Commission (IOC), UNEP, WMO, and World Health Organization (WHO). The proposed initiative will provide high-resolution climate models that capture the properties of regional high-impact weather events, such as tropical cyclones, heat wave, and sand and dust storms associated within multi-decadal climate projections of climate variability and change. Unprecedented international collaboration and goodwill are necessary for the success of EPI