Cationic Alkylaluminum-Complexed Zirconocene Hydrides: NMR-Spectroscopic Identification, Crystallographic Structure Determination, and Interconversion with Other Zirconocene Cations

The ansa-zirconocene complex rac-Me_2Si(1-indenyl)_2ZrCl_2 ((SBI)ZrCl_2) reacts with diisobutylaluminum hydride and trityl tetrakis(perfluorophenyl)borate in hydrocarbon solutions to give the cation [(SBI)Zr(μ-H)_3(Al^iBu_2)_2]^+, the identity of which is derived from NMR data and supported by a crystallographic structure determination. Analogous reactions proceed with many other zirconocene dichloride complexes. [(SBI)Zr(μ-H)_3(Al^iBu2)_2]^+ reacts reversibly with ClAl^iBu_2 to give the dichloro-bridged cation [(SBI)Zr(μ-Cl)_2Al^iBu_2]^+. Reaction with AlMe_3 first leads to mixed-alkyl species [(SBI)Zr(μ-H)_3(AlMe_x^iBu_(2−x))_2^]+ by exchange of alkyl groups between aluminum centers. At higher AlMe_3/Zr ratios, [(SBI)Zr(μ-Me)_2AlMe_2]^+, a constituent of methylalumoxane-activated catalyst systems, is formed in an equilibrium, in which the hydride cation [(SBI)Zr(μ-H)_3(AlR_2)_2]^+ strongly predominates at comparable HAl^iBu_2 and AlMe_3 concentrations, thus implicating the presence of this hydride cation in olefin polymerization catalyst systems

Road Weather Severity Based on Environmental Energy

Effective and efficient removal of snow and ice from public roadways is a key outcome for winter road maintenance operations. This outcome depends on the severity of the wintry weather as well as the quality and quantity of resources used to treat the roadways. Wintry weather conditions vary substantially from hour-to-hour, storm-to-storm, and season-to-season. Many different transportation departments have used empirical statistical models and machine learning methods based upon weather parameters to develop indices to estimate the severity of winter weather. Many of these previous studies used summary statistics, such as the number of days with certain events (snowfall, freezing rain, frost), to provide a seasonal index of winter severity. While summarizing the winter severity for the entire season is quite useful, providing information over shorter time periods will allow for more precise evaluation of maintenance performance during a winter season. A winter weather severity index has been developed that can be used to evaluate the performance of winter weather maintenance. This project involves the development of a physically-based analysis of winter severity, using estimates of the hourly rate of deposition of new snow/ice and the energy required melt it. The “Road Weather Severity Based on Environmental Energy” (RWSBEE) index can be considered an accumulation of energy, beyond that which is available from the environment, needed to melt snow/ice that has been deposited on the road surface on an hourly basis. The energy not provided by the environment that would be required to melt new snow can be thought of as a measure of the work required to remove the new snow from the road surface. We expect that RWSBEE will provide a clearer understanding of the severity of the weather, allowing INDOT to better evaluate their performance, assist with after-action review of recent storms, and improve the reaction to future weather events. Measurable improvements in the winter maintenance decision-making process are expected as a result. Winter weather conditions that occur across different regions vary substantially from hour-to-hour, storm-to-storm, and season-to-season. The methods of road maintenance for fighting snow and ice can also vary between different maintenance units. It is important for organizations that perform road maintenance to be able to quantify the severity of the winter weather conditions, for purposes of monitoring, planning, and evaluating their performance. The Indiana Department of Transportation (INDOT) currently uses estimates of winter weather hours to quantify the severity of winter weather. The definition of a “weather hour” is fairly straightforward: any hour when wintry precipitation (snow, ice pellets, freezing rain) is falling with air temperatures below 35 °F. While this definition is reasonable, it does not take into account numerous factors that can strongly affect road conditions and subsequent efforts needed for road treatment, such as: precipitation rate, wind speed, and availability of sunshine. Consequently, INDOT has determined that the information provided by the weather hour estimates result in wide variations in roadway treatment expenses across Indiana. In order to more accurately and effectively evaluate the performance of winter maintenance, it is important to have detailed data related to winter weather conditions that provide useful information regarding the impact of winter weather on road conditions. State-of-the-art weather information can provide a clearer understanding of the severity of the weather, allowing INDOT to better evaluate their performance, assist with after-action review of recent storms, and improve the reaction to future weather events

Predicting Raccoon, Procyon lotor, Occurrence Through the Use of Microhabitat Variables

Recent increases in Raccoon (Procyon lotor) abundance have been implicated for decreased nesting success of songbirds and transmission of rabies. Understanding the relationship between occurrence and microhabitat factors should be helpful in managing this species, though our current understanding of this relationship is inadequate. Therefore, we conducted a study in western Tennessee during 2000–2002 to determine this association. Occurrence (capture) data were assessed from results of live trapping at 176 and 112 trap sites during winter and summer, respectively, at three sites. A maximum of 26 habitat variables were measured at each trap location; all grids were combined for statistical analyses to account for varying relationships between occurrence and microhabitat factors across different landscapes. Univariate and stepwise logistic-regression analyses were used to assess associations among microhabitat variables and occurrence. Resulting models were validated through the jackknife procedure. Predictive equations were constructed from logistic-regression models to compute capture probabilities. Univariate analyses yielded numerous significant variables with those representing forest characteristics and proximity to water generally the most significant. Strong concordance was observed between winter and summer seasons for most variables though several differed (number of large hardwood snags, ground dens, and plant food species, distance to potential water and roads). Such temporal variability was expected due to seasonal differences in habitat components and biological needs of Raccoons. Variables included in derived models were similar to those scoring highest in univariate analyses; classification rates for models (winter = 72%; summer = 78%) were among the highest recorded for generalist species. By accounting for landscape attributes and replicating across sites, more accurate and useful models were developed. Such models should provide the information required to effectively manage this species

18FDG PET-CT imaging detects arterial inflammation and early atherosclerosis in HIV-infected adults with cardiovascular disease risk factors

BACKGROUND: Persistent vascular inflammation has been implicated as an important cause for a higher prevalence of cardiovascular disease (CVD) in HIV-infected adults. In several populations at high risk for CVD, vascular (18)Fluorodeoxyglucose ((18)FDG) uptake quantified using 3D-positron emission-computed tomography (PET-CT) has been used as a molecular level biomarker for the presence of metabolically active proinflammatory macrophages in rupture-prone early atherosclerotic plaques. We hypothesized that (18)FDG PET-CT imaging would detect arterial inflammation and early atherosclerosis in HIV-infected adults with modest CVD risk. METHODS: We studied 9 HIV-infected participants with fully suppressed HIV viremia on antiretroviral therapy (8 men, median age 52 yrs, median BMI 29 kg/m(2), median CD4 count 655 cells/μL, 33% current smokers) and 5 HIV-negative participants (4 men, median age 44 yrs, median BMI 25 kg/m(2), no current smokers). Mean Framingham Risk Scores were higher for HIV-infected persons (9% vs. 2%, p < 0.01). (18)FDG (370 MBq) was administered intravenously. 3D-PET-CT images were obtained 3.5 hrs later. (18)FDG uptake into both carotid arteries and the aorta was compared between the two groups. RESULTS: Right and left carotid (18)FDG uptake was greater (P < 0.03) in the HIV group (1.77 ±0.26, 1.33 ±0.09 target to background ratio (TBR)) than the control group (1.05 ± 0.10, 1.03 ± 0.05 TBR). (18)FDG uptake in the aorta was greater in HIV (1.50 ±0.16 TBR) vs control group (1.24 ± 0.05 TBR), but did not reach statistical significance (P = 0.18). CONCLUSIONS: Carotid artery (18)FDG PET-CT imaging detected differences in vascular inflammation and early atherosclerosis between HIV-infected adults with CVD risk factors and healthy HIV-seronegative controls. These findings confirm the utility of this molecular level imaging approach for detecting and quantifying glucose uptake into inflammatory macrophages present in metabolically active, rupture-prone atherosclerotic plaques in HIV infected adults; a population with increased CVD risk

Orthotopic cardiac transplantation after minimally invasive direct coronary artery bypass

AbstractJ Thorac Cardiovasc Surg 1999;117:390-

Origin of entropy convergence in hydrophobic hydration and protein folding

An information theory model is used to construct a molecular explanation why hydrophobic solvation entropies measured in calorimetry of protein unfolding converge at a common temperature. The entropy convergence follows from the weak temperature dependence of occupancy fluctuations for molecular-scale volumes in water. The macroscopic expression of the contrasting entropic behavior between water and common organic solvents is the relative temperature insensitivity of the water isothermal compressibility. The information theory model provides a quantitative description of small molecule hydration and predicts a negative entropy at convergence. Interpretations of entropic contributions to protein folding should account for this result.Comment: Phys. Rev. Letts. (in press 1996), 3 pages, 3 figure

Computational, Integrative, and Comparative Methods for the Elucidation of Genetic Coexpression Networks

Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively coregulated genes and their annotation using gene ontology analysis and cis-regulatory element discovery. The causal basis for coregulation is detected through the use of quantitative trait locus mapping