Support induced charge transfer effects on electrochemical characteristics of Pt nanoparticle electrocatalysts

The electrokinetic properties of Pt nanoparticles supported on Carbon (Pt/C) and Boron Carbide-Graphite composite (Pt/BC) are compared over a wide potential range. The influence of the support on the electronic state of Pt was investigated via in-situ X-ray Absorption Spectroscopy. Pt d-band filling, determined from XANES white line analysis, was lower and nearly constant between 0.4 and 0.95V vs. RHE for Pt/BC, indicating more positively charged particles in the double layer region and a delay in the onset of oxide formation by about 0.2V compared to the Pt/C catalyst, which showed a marked increase in d-band vacancies above 0.8V vs. RHE. Moreover, δμ analysis of the XANES data indicated a lack of sub-surface oxygen for the Pt/BC catalyst compared to the Pt/C catalyst above 0.9V vs. RHE. Additional anion adsorption on the Pt/BC in the double layer region, detected by CO displacement, was also confirmed by XANES analysis of the d-band occupancy. The H 2 oxidation activities of electrodes with low catalyst loadings were assessed under high mass transport conditions using the floating electrode methodology. The metal-support interaction between the Pt and BC support improved the maximum hydrogen oxidation current density by 1.4 times when compared to Pt/C

Evaluation of a Bayesian inference network for ligand-based virtual screening

Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to enable a Bayesian inference network to be used for chemical similarity searching, where a database is ranked in order of decreasing probability of bioactivity. Results Bayesian inference networks were implemented using two different types of network and four different types of belief function. Experiments with the MDDR and WOMBAT databases show that a Bayesian inference network can be used to provide effective ligand-based screening, especially when the active molecules being sought have a high degree of structural homogeneity; in such cases, the network substantially out-performs a conventional, Tanimoto-based similarity searching system. However, the effectiveness of the network is much less when structurally heterogeneous sets of actives are being sought. Conclusion A Bayesian inference network provides an interesting alternative to existing tools for ligand-based virtual screening

CRANKITE: a fast polypeptide backbone conformation sampler

Background: CRANKITE is a suite of programs for simulating backbone conformations of polypeptides and proteins. The core of the suite is an efficient Metropolis Monte Carlo sampler of backbone conformations in continuous three-dimensional space in atomic details. Methods: In contrast to other programs relying on local Metropolis moves in the space of dihedral angles, our sampler utilizes local crankshaft rotations of rigid peptide bonds in Cartesian space. Results: The sampler allows fast simulation and analysis of secondary structure formation and conformational changes for proteins of average length

Inter- and Intra-Observer Repeatability of Quantitative Whole-Body, Diffusion-Weighted Imaging (WBDWI) in Metastatic Bone Disease.

Quantitative whole-body diffusion-weighted MRI (WB-DWI) is now possible using semi-automatic segmentation techniques. The method enables whole-body estimates of global Apparent Diffusion Coefficient (gADC) and total Diffusion Volume (tDV), both of which have demonstrated considerable utility for assessing treatment response in patients with bone metastases from primary prostate and breast cancers. Here we investigate the agreement (inter-observer repeatability) between two radiologists in their definition of Volumes Of Interest (VOIs) and subsequent assessment of tDV and gADC on an exploratory patient cohort of nine. Furthermore, each radiologist was asked to repeat his or her measurements on the same patient data sets one month later to identify the intra-observer repeatability of the technique. Using a Markov Chain Monte Carlo (MCMC) estimation method provided full posterior probabilities of repeatability measures along with maximum a-posteriori values and 95% confidence intervals. Our estimates of the inter-observer Intraclass Correlation Coefficient (ICCinter) for log-tDV and median gADC were 1.00 (0.97-1.00) and 0.99 (0.89-0.99) respectively, indicating excellent observer agreement for these metrics. Mean gADC values were found to have ICCinter = 0.97 (0.81-0.99) indicating a slight sensitivity to outliers in the derived distributions of gADC. Of the higher order gADC statistics, skewness was demonstrated to have good inter-user agreement with ICCinter = 0.99 (0.86-1.00), whereas gADC variance and kurtosis performed relatively poorly: 0.89 (0.39-0.97) and 0.96 (0.69-0.99) respectively. Estimates of intra-observer repeatability (ICCintra) demonstrated similar results: 0.99 (0.95-1.00) for log-tDV, 0.98 (0.89-0.99) and 0.97 (0.83-0.99) for median and mean gADC respectively, 0.64 (0.25-0.88) for gADC variance, 0.85 (0.57-0.95) for gADC skewness and 0.85 (0.57-0.95) for gADC kurtosis. Further investigation of two anomalous patient cases revealed that a very small proportion of voxels with outlying gADC values lead to instability in higher order gADC statistics. We therefore conclude that estimates of median/mean gADC and tumour volume demonstrate excellent inter- and intra-observer repeatability whilst higher order statistics of gADC should be used with caution when ascribing significance to clinical changes

OrChem - An open source chemistry search engine for Oracle®

<p>Abstract</p> <p>Background</p> <p>Registration, indexing and searching of chemical structures in relational databases is one of the core areas of cheminformatics. However, little detail has been published on the inner workings of search engines and their development has been mostly closed-source. We decided to develop an open source chemistry extension for Oracle, the de facto database platform in the commercial world.</p> <p>Results</p> <p>Here we present OrChem, an extension for the Oracle 11G database that adds registration and indexing of chemical structures to support fast substructure and similarity searching. The cheminformatics functionality is provided by the Chemistry Development Kit. OrChem provides similarity searching with response times in the order of seconds for databases with millions of compounds, depending on a given similarity cut-off. For substructure searching, it can make use of multiple processor cores on today's powerful database servers to provide fast response times in equally large data sets.</p> <p>Availability</p> <p>OrChem is free software and can be redistributed and/or modified under the terms of the GNU Lesser General Public License as published by the Free Software Foundation. All software is available via <url>http://orchem.sourceforge.net</url>.</p

Breast imaging technology: Application of magnetic resonance imaging to angiogenesis in breast cancer

Magnetic resonance imaging (MRI) techniques enable vascular function to be mapped with high spatial resolution. Current methods for imaging in breast cancer are described, and a review of recent studies that compared dynamic contrast-enhanced MRI with histopathological indicators of tumour vascular status is provided. These studies show correlation between in vivo dynamic contrast measurements and in vitro histopathology. Dynamic contrast enhanced MRI is also being applied to assessment of the response of breast tumours to treatment

Effects of an exercise programme with people living with HIV: Research in a disadvantaged setting

This study aimed to analyse the physical health effects of a community based 10-week physical activity programme with people living with HIV. It was developed, implemented and evaluated in a disadvantaged community in South Africa. A pre-post research design was chosen. Major recruitment and adherence challenges resulted in a small sample. Among the 23 participants who took part in both baseline and final testing, compliant participants (n = 12) were compared to non-compliant participants (n = 11). Immunological (CD4, viral load), anthropometric (height, weight, skinfolds and waist to hip ratio), muscular strength (h1RM) and cardiopulmonary fitness (time on treadmill) parameters were measured. The compliant and non-compliant groups were not different at baseline. Muscular strength was the parameter most influenced by compliance with the physical activity programme (F = 4.516, p = 0.047). Weight loss and improvement in cardiopulmonary fitness were restricted by the duration of the programme, compliance and influencing factors (e.g. nutrition, medication). The increase in strength is significant and meaningful in the context, as the participants goals were to look healthy and strong to avoid HIV related stigma. The improvements in appearance were a motivational factor, especially since the changes were made visible in a short time. Practical implications for health promotion are described. More research contextualised in disadvantaged settings is needed.DHE

Epidemiology of nasopharyngeal carriage of respiratory bacterial pathogens in children and adults: cross-sectional surveys in a population with high rates of pneumococcal disease

<p>Abstract</p> <p>Background</p> <p>To determine the prevalence of carriage of respiratory bacterial pathogens, and the risk factors for and serotype distribution of pneumococcal carriage in an Australian Aboriginal population.</p> <p>Methods</p> <p>Surveys of nasopharyngeal carriage of <it>Streptococcus pneumoniae</it>, non-typeable <it>Haemophilus influenzae</it>, and <it>Moraxella catarrhalis </it>were conducted among adults (≥16 years) and children (2 to 15 years) in four rural communities in 2002 and 2004. Infant seven-valent pneumococcal conjugate vaccine (7PCV) with booster 23-valent pneumococcal polysaccharide vaccine was introduced in 2001. Standard microbiological methods were used.</p> <p>Results</p> <p>At the time of the 2002 survey, 94% of eligible children had received catch-up pneumococcal vaccination. 324 adults (538 examinations) and 218 children (350 examinations) were enrolled. Pneumococcal carriage prevalence was 26% (95% CI, 22-30) among adults and 67% (95% CI, 62-72) among children. Carriage of non-typeable <it>H. influenzae </it>among adults and children was 23% (95% CI, 19-27) and 57% (95% CI, 52-63) respectively and for <it>M. catarrhalis</it>, 17% (95% CI, 14-21) and 74% (95% CI, 69-78) respectively. Adult pneumococcal carriage was associated with increasing age (p = 0.0005 test of trend), concurrent carriage of non-typeable <it>H. influenzae </it>(Odds ratio [OR] 6.74; 95% CI, 4.06-11.2) or <it>M. catarrhalis </it>(OR 3.27; 95% CI, 1.97-5.45), male sex (OR 2.21; 95% CI, 1.31-3.73), rhinorrhoea (OR 1.66; 95% CI, 1.05-2.64), and frequent exposure to outside fires (OR 6.89; 95% CI, 1.87-25.4). Among children, pneumococcal carriage was associated with decreasing age (p < 0.0001 test of trend), and carriage of non-typeable <it>H. influenzae </it>(OR 9.34; 95% CI, 4.71-18.5) or <it>M. catarrhalis </it>(OR 2.67; 95% CI, 1.34-5.33). Excluding an outbreak of serotype 1 in children, the percentages of serotypes included in 7, 10, and 13PCV were 23%, 23%, and 29% (adults) and 22%, 24%, and 40% (2-15 years). Dominance of serotype 16F, and persistent 19F and 6B carriage three years after initiation of 7PCV is noteworthy.</p> <p>Conclusions</p> <p>Population-based carriage of <it>S. pneumoniae</it>, non-typeable <it>H. influenzae</it>, and <it>M. catarrhalis </it>was high in this Australian Aboriginal population. Reducing smoke exposure may reduce pneumococcal carriage. The indirect effects of 10 or 13PCV, above those of 7PCV, among adults in this population may be limited.</p

Spatial chemical distance based on atomic property fields

Similarity of compound chemical structures often leads to close pharmacological profiles, including binding to the same protein targets. The opposite, however, is not always true, as distinct chemical scaffolds can exhibit similar pharmacology as well. Therefore, relying on chemical similarity to known binders in search for novel chemicals targeting the same protein artificially narrows down the results and makes lead hopping impossible. In this study we attempt to design a compound similarity/distance measure that better captures structural aspects of their pharmacology and molecular interactions. The measure is based on our recently published method for compound spatial alignment with atomic property fields as a generalized 3D pharmacophoric potential. We optimized contributions of different atomic properties for better discrimination of compound pairs with the same pharmacology from those with different pharmacology using Partial Least Squares regression. Our proposed similarity measure was then tested for its ability to discriminate pharmacologically similar pairs from decoys on a large diverse dataset of 115 protein–ligand complexes. Compared to 2D Tanimoto and Shape Tanimoto approaches, our new approach led to improvement in the area under the receiver operating characteristic curve values in 66 and 58% of domains respectively. The improvement was particularly high for the previously problematic cases (weak performance of the 2D Tanimoto and Shape Tanimoto measures) with original AUC values below 0.8. In fact for these cases we obtained improvement in 86% of domains compare to 2D Tanimoto measure and 85% compare to Shape Tanimoto measure. The proposed spatial chemical distance measure can be used in virtual ligand screening

Evaluation of machine-learning methods for ligand-based virtual screening

Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it is little different in screening performance from a previously described kernel that had been developed specifically for the analysis of binary fingerprint representations of molecular structure. We then evaluate the performance of an NBC when the training-set contains only a very few active molecules. In such cases, a simpler approach based on group fusion would appear to provide superior screening performance, especially when structurally heterogeneous datasets are to be processed