Electronic stress tensor analysis of hydrogenated palladium clusters

We study the chemical bonds of small palladium clusters Pd_n (n=2-9) saturated by hydrogen atoms using electronic stress tensor. Our calculation includes bond orders which are recently proposed based on the stress tensor. It is shown that our bond orders can classify the different types of chemical bonds in those clusters. In particular, we discuss Pd-H bonds associated with the H atoms with high coordination numbers and the difference of H-H bonds in the different Pd clusters from viewpoint of the electronic stress tensor. The notion of "pseudo-spindle structure" is proposed as the region between two atoms where the largest eigenvalue of the electronic stress tensor is negative and corresponding eigenvectors forming a pattern which connects them.Comment: 22 pages, 13 figures, published online, Theoretical Chemistry Account

Calculation of molecular thermochemical data and their availability in databases

Thermodynamic properties of molecules can be obtained by experiment, by statistical mechanics in conjunction with electronic structure theory and by empirical rules like group additivity. The latter two methods are briefly re-viewed in this chapter. The overview of electronic structure methods is intended for readers less experienced in electronic structure theory and focuses on concepts without going into mathematical details. This is followed by a brief description of group additivity schemes; finally, an overview of databases listing reliable thermochemical data is given

Validation of food store environment secondary data source and the role of neighborhood deprivation in Appalachia, Kentucky

Background Based on the need for better measurement of the retail food environment in rural settings and to examine how deprivation may be unique in rural settings, the aims of this study were: 1) to validate one commercially available data source with direct field observations of food retailers; and 2) to examine the association between modified neighborhood deprivation and the modified retail food environment score (mRFEI). Methods Secondary data were obtained from a commercial database, InfoUSA in 2011, on all retail food outlets for each census tract. In 2011, direct observation identifying all listed food retailers was conducted in 14 counties in Kentucky. Sensitivity and positive predictive values (PPV) were compared. Neighborhood deprivation index was derived from American Community Survey data. Multinomial regression was used to examine associations between neighborhood deprivation and the mRFEI score (indicator of retailers selling healthy foods such as low-fat foods and fruits and vegetables relative to retailers selling more energy dense foods). Results The sensitivity of the commercial database was high for traditional food retailers (grocery stores, supermarkets, convenience stores), with a range of 0.96-1.00, but lower for non-traditional food retailers; dollar stores (0.20) and Farmer’s Markets (0.50). For traditional food outlets, the PPV for smaller non-chain grocery stores was 38%, and large chain supermarkets was 87%. Compared to those with no stores in their neighborhoods, those with a supercenter [OR 0.50 (95% CI 0.27. 0.97)] or convenience store [OR 0.67 (95% CI 0.51, 0.89)] in their neighborhood have lower odds of living in a low deprivation neighborhood relative to a high deprivation neighborhood. Conclusion The secondary commercial database used in this study was insufficient to characterize the rural retail food environment. Our findings suggest that neighborhoods with high neighborhood deprivation are associated with having certain store types that may promote less healthy food options

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

Meeting abstrac

Maximal Extraction of Biological Information from Genetic Interaction Data

Targeted genetic perturbation is a powerful tool for inferring gene function in model organisms. Functional relationships between genes can be inferred by observing the effects of multiple genetic perturbations in a single strain. The study of these relationships, generally referred to as genetic interactions, is a classic technique for ordering genes in pathways, thereby revealing genetic organization and gene-to-gene information flow. Genetic interaction screens are now being carried out in high-throughput experiments involving tens or hundreds of genes. These data sets have the potential to reveal genetic organization on a large scale, and require computational techniques that best reveal this organization. In this paper, we use a complexity metric based in information theory to determine the maximally informative network given a set of genetic interaction data. We find that networks with high complexity scores yield the most biological information in terms of (i) specific associations between genes and biological functions, and (ii) mapping modules of co-functional genes. This information-based approach is an automated, unsupervised classification of the biological rules underlying observed genetic interactions. It might have particular potential in genetic studies in which interactions are complex and prior gene annotation data are sparse

Staphylococcus aureus bacteriuria as a prognosticator for outcome of Staphylococcus aureus bacteremia: a case-control study

<p>Abstract</p> <p>Background</p> <p>When <it>Staphylococcus aureus </it>is isolated in urine, it is thought to usually represent hematogenous spread. Because such spread might have special clinical significance, we evaluated predictors and outcomes of <it>S. aureus </it>bacteriuria among patients with <it>S. aureus </it>bacteremia.</p> <p>Methods</p> <p>A case-control study was performed at John H. Stroger Jr. Hospital of Cook County among adult inpatients during January 2002-December 2006. Cases and controls had positive and negative urine cultures, respectively, for <it>S. aureus</it>, within 72 hours of positive blood culture for <it>S. aureus</it>. Controls were sampled randomly in a 1:4 ratio. Univariate and multivariable logistic regression analyses were done.</p> <p>Results</p> <p>Overall, 59% of patients were African-American, 12% died, 56% of infections had community-onset infections, and 58% were infected with methicillin-susceptible <it>S. aureus </it>(MSSA). Among 61 cases and 247 controls, predictors of <it>S. aureus </it>bacteriuria on multivariate analysis were urological surgery (OR = 3.4, p = 0.06) and genitourinary infection (OR = 9.2, p = 0.002). Among patients who died, there were significantly more patients with bacteriuria than among patients who survived (39% vs. 17%; p = 0.002). In multiple Cox regression analysis, death risks in bacteremic patients were bacteriuria (hazard ratio 2.9, CI 1.4-5.9, p = 0.004), bladder catheter use (2.0, 1.0-4.0, p = 0.06), and Charlson score (1.1, 1.1-1.3, p = 0.02). Neither length of stay nor methicillin-resistant <it>Staphylococcus aureus </it>(MRSA) infection was a predictor of <it>S. aureus </it>bacteriuria or death.</p> <p>Conclusions</p> <p>Among patients with <it>S. aureus </it>bacteremia, those with <it>S. aureus </it>bacteriuria had 3-fold higher mortality than those without bacteriuria, even after adjustment for comorbidities. Bacteriuria may identify patients with more severe bacteremia, who are at risk of worse outcomes.</p

A roadmap for the Human Developmental Cell Atlas

The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development

Transforming growth factor β receptor 1 is a new candidate prognostic biomarker after acute myocardial infarction

<p>Abstract</p> <p>Background</p> <p>Prediction of left ventricular (LV) remodeling after acute myocardial infarction (MI) is clinically important and would benefit from the discovery of new biomarkers.</p> <p>Methods</p> <p>Blood samples were obtained upon admission in patients with acute ST-elevation MI who underwent primary percutaneous coronary intervention. Messenger RNA was extracted from whole blood cells. LV function was evaluated by echocardiography at 4-months.</p> <p>Results</p> <p>In a test cohort of 32 MI patients, integrated analysis of microarrays with a network of protein-protein interactions identified subgroups of genes which predicted LV dysfunction (ejection fraction ≤ 40%) with areas under the receiver operating characteristic curve (AUC) above 0.80. Candidate genes included transforming growth factor beta receptor 1 (TGFBR1). In a validation cohort of 115 MI patients, TGBFR1 was up-regulated in patients with LV dysfunction (P < 0.001) and was associated with LV function at 4-months (P = 0.003). TGFBR1 predicted LV function with an AUC of 0.72, while peak levels of troponin T (TnT) provided an AUC of 0.64. Adding TGFBR1 to the prediction of TnT resulted in a net reclassification index of 8.2%. When added to a mixed clinical model including age, gender and time to reperfusion, TGFBR1 reclassified 17.7% of misclassified patients. TGFB1, the ligand of TGFBR1, was also up-regulated in patients with LV dysfunction (P = 0.004), was associated with LV function (P = 0.006), and provided an AUC of 0.66. In the rat MI model induced by permanent coronary ligation, the TGFB1-TGFBR1 axis was activated in the heart and correlated with the extent of remodeling at 2 months.</p> <p>Conclusions</p> <p>We identified TGFBR1 as a new candidate prognostic biomarker after acute MI.</p

Reduced Neutrophil Apoptosis in Diabetic Mice during Staphylococcal Infection Leads to Prolonged Tnfα Production and Reduced Neutrophil Clearance

Diabetes is a frequent underlying medical condition among individuals with Staphylococcus aureus infections, and diabetic patients often suffer from chronic inflammation and prolonged infections. Neutrophils are the most abundant inflammatory cells during the early stages of bacterial diseases, and previous studies have reported deficiencies in neutrophil function in diabetic hosts. We challenged age-matched hyperglycemic and normoglycemic NOD mice intraperitoneally with S. aureus and evaluated the fate of neutrophils recruited to the peritoneal cavity. Neutrophils were more abundant in the peritoneal fluids of infected diabetic mice by 48 h after bacterial inoculation, and they showed prolonged viability ex vivo compared to neutrophils from infected nondiabetic mice. These differences correlated with reduced apoptosis of neutrophils from diabetic mice and were dependent upon the presence of S. aureus and a functional neutrophil respiratory burst. Decreased apoptosis correlated with impaired clearance of neutrophils by macrophages both in vitro and in vivo and prolonged production of proinflammatory tumor necrosis factor alpha by neutrophils from diabetic mice. Our results suggest that defects in neutrophil apoptosis may contribute to the chronic inflammation and the inability to clear staphylococcal infections observed in diabetic patients