Reaction mechanism and kinetics for CO₂ reduction on nickel single atom catalysts from quantum mechanics

Experiments have shown that graphene-supported Ni-single atom catalysts (Ni-SACs) provide a promising strategy for the electrochemical reduction of CO₂ to CO, but the nature of the Ni sites (Ni-N₂C₂, Ni-N₃C₁, Ni-N₄) in Ni-SACs has not been determined experimentally. Here, we apply the recently developed grand canonical potential kinetics (GCP-K) formulation of quantum mechanics to predict the kinetics as a function of applied potential (U) to determine faradic efficiency, turn over frequency, and Tafel slope for CO and H₂ production for all three sites. We predict an onset potential (at 10 mA cm⁻²) U_(onset) = −0.84 V (vs. RHE) for Ni-N₂C₂ site and U_(onset) = −0.92 V for Ni-N₃C₁ site in agreement with experiments, and U_(onset) = −1.03 V for Ni-N₄. We predict that the highest current is for Ni-N₄, leading to 700 mA cm⁻² at U = −1.12 V. To help determine the actual sites in the experiments, we predict the XPS binding energy shift and CO vibrational frequency for each site

A spectral study of gamma-ray emitting AGN

In this paper we present a statistical analysis of the gamma-ray spectra of flat-spectrum radio quasars (FSRQ) compared to those of BL Lacs. The average spectra and possible systematic deviations from power-law behaviour are investigated by summing up the intensity and the power-law fit statistic for both classes of objects. We also compare the time-averaged spectrum to that at the time of gamma-ray outbursts. The spectrum of the average AGN is softer than that of the extragalactic gamma-ray background. It may be that BL Lacs, which on average have a harder spectrum than FSRQs, make up the bulk of the extragalactic background. We also find apparent cut-offs at both low and high energies in the spectra of FSRQs at the time of gamma-ray outbursts. While the cut-off at high energies may have something to do with opacity, the cut-off at low energies may be taken as indication that the gamma-ray emission of FSRQs is not a one component spectrum.Comment: 8 pages, accepted for publication in A&

Accounting for genomic pre-selection in national BLUP evaluations in dairy cattle

<p>Abstract</p> <p>Background</p> <p>In future Best Linear Unbiased Prediction (BLUP) evaluations of dairy cattle, genomic selection of young sires will cause evaluation biases and loss of accuracy once the selected ones get progeny.</p> <p>Methods</p> <p>To avoid such bias in the estimation of breeding values, we propose to include information on all genotyped bulls, including the culled ones, in BLUP evaluations. Estimated breeding values based on genomic information were converted into genomic pseudo-performances and then analyzed simultaneously with actual performances. Using simulations based on actual data from the French Holstein population, bias and accuracy of BLUP evaluations were computed for young sires undergoing progeny testing or genomic pre-selection. For bulls pre-selected based on their genomic profile, three different types of information can be included in the BLUP evaluations: (1) data from pre-selected genotyped candidate bulls with actual performances on their daughters, (2) data from bulls with both actual and genomic pseudo-performances, or (3) data from all the genotyped candidates with genomic pseudo-performances. The effects of different levels of heritability, genomic pre-selection intensity and accuracy of genomic evaluation were considered.</p> <p>Results</p> <p>Including information from all the genotyped candidates, i.e. genomic pseudo-performances for both selected and culled candidates, removed bias from genetic evaluation and increased accuracy. This approach was effective regardless of the magnitude of the initial bias and as long as the accuracy of the genomic evaluations was sufficiently high.</p> <p>Conclusions</p> <p>The proposed method can be easily and quickly implemented in BLUP evaluations at the national level, although some improvement is necessary to more accurately propagate genomic information from genotyped to non-genotyped animals. In addition, it is a convenient method to combine direct genomic, phenotypic and pedigree-based information in a multiple-step procedure.</p

Bioaccumulation of some metals by Green mussel Perna viridis (Linnaeus 1758) from Pekan, Pahang, Malaysia

A study was conducted to determine the bioaccumulation of some essential and non-essential heavy metals by the soft tissue of Perna viridis (Green mussel) collected from Pekan, Pahang during November 2009. A total of fifty individuals of Green lipped mussel P. viridis (Family: Mytilidae) were sampled and metals such as Iron (Fe), Zinc (Zn), Copper (Cu), Cobalt (Co), Lead (Pb) and Cadmium (Cd) concentration were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The observed mean concentration of Fe, Zn, Cu, Co, Pb and Cd in the soft edible tissue of P. viridis was 576.45±87.78, 45.54±8.75, 19.05±4.12, 17.85±2.28, 0.47±0.14 and 0.3±0.06 μg g-1, respectively. The bioaccumulation of metals in the soft tissue flowed in Fe>Zn>Cu >Co>Pb>Cd order indicating that the essential heavy metal accumulates in faster rate than non-essential metals. Comparison with earlier studies showed that Fe and Cu bioaccumulation level was higher in samples from Pekan area with average of 576.45 and 19.05 μg g-1, respectively. All the other metals concentration was lower in the soft tissue of green mussel indicating comparatively lower heavy metal contamination in the Pekan, Pahang compared with other coasts

The association of health literacy with adherence in older 2 adults, and its role in interventions: a systematic meta-review

Background: Low health literacy is a common problem among older adults. It is often suggested to be associated with poor adherence. This suggested association implies a need for effective adherence interventions in low health literate people. However, previous reviews show mixed results on the association between low health literacy and poor adherence. A systematic meta-review of systematic reviews was conducted to study the association between health literacy and adherence in adults above the age of 50. Evidence for the effectiveness of adherence interventions among adults in this older age group with low health literacy was also explored. Methods: Eight electronic databases (MEDLINE, ERIC, EMBASE, PsycINFO, CINAHL, DARE, the Cochrane Library, and Web of Knowledge) were searched using a variety of keywords regarding health literacy and adherence. Additionally, references of identified articles were checked. Systematic reviews were included if they assessed the association between health literacy and adherence or evaluated the effectiveness of interventions to improve adherence in adults with low health literacy. The AMSTAR tool was used to assess the quality of the included reviews. The selection procedure, data-extraction, and quality assessment were performed by two independent reviewers. Seventeen reviews were selected for inclusion. Results: Reviews varied widely in quality. Both reviews of high and low quality found only weak or mixed associations between health literacy and adherence among older adults. Reviews report on seven studies that assess the effectiveness of adherence interventions among low health literate older adults. The results suggest that some adherence interventions are effective for this group. The interventions described in the reviews focused mainly on education and on lowering the health literacy demands of adherence instructions. No conclusions could be drawn about which type of intervention could be most beneficial for this population. Conclusions: Evidence on the association between health literacy and adherence in older adults is relatively weak. Adherence interventions are potentially effective for the vulnerable population of older adults with low levels of health literacy, but the evidence on this topic is limited. Further research is needed on the association between health literacy and general health behavior, and on the effectiveness of interventions

Determination of some heavy metal concentrations in razor clam (Solen brevis) from Tanjung Lumpur Coastal waters, Pahang, Malaysia

An effort to analyze selected heavy metal accumulation by the razor clam (Solen brevis) from Tanjung Lumpur was conducted on January to April 2010. A total of fifty individuals of Razor clam Solen brevis were sampled and metals such as Iron (Fe), Zinc (Zn), Copper (Cu), Manganase (Mn), Lead (Pb) and Cadmium (Cd) Concentrations were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Among the metals Fe occurred in elevated concentration in the soft tissue of razor clam followed by Zn. Cd was found to be in least concentration in the sample. Mean concentration of Fe, Zn, Mn, Cu, Cd and Pb in the soft tissue were 415.2±56.52, 87.74±11.85, 18.71±2.10, 8.64±1.75, 0.67±0.29 and 1.61±0.45 μg g-1 dw, respectively indicating that the bioaccumulation of essential metals in the soft tissue was greater than the non essential heavy metals. Metal accumulation in the soft tissue of razor clam followed Fe > Zn > Mn > Cu > Pb > Cd order in present study. The observed concentration of acute toxicity of metals in Solen brevis (Family: Solenidae) from Tanjung Lumpur Coastal waters was lower than the permissible limit recommended by National and international standards proved that this species could be utilized for human consumption

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

Rule based classifier for the analysis of gene-gene and gene-environment interactions in genetic association studies

<p>Abstract</p> <p>Background</p> <p>Several methods have been presented for the analysis of complex interactions between genetic polymorphisms and/or environmental factors. Despite the available methods, there is still a need for alternative methods, because no single method will perform well in all scenarios. The aim of this work was to evaluate the performance of three selected rule based classifier algorithms, RIPPER, RIDOR and PART, for the analysis of genetic association studies.</p> <p>Methods</p> <p>Overall, 42 datasets were simulated with three different case-control models, a varying number of subjects (300, 600), SNPs (500, 1500, 3000) and noise (5%, 10%, 20%). The algorithms were applied to each of the datasets with a set of algorithm-specific settings. Results were further investigated with respect to a) the Model, b) the Rules, and c) the Attribute level. Data analysis was performed using WEKA, SAS and PERL.</p> <p>Results</p> <p>The RIPPER algorithm discovered the true case-control model at least once in >33% of the datasets. The RIDOR and PART algorithm performed poorly for model detection. The RIPPER, RIDOR and PART algorithm discovered the true case-control rules in more than 83%, 83% and 44% of the datasets, respectively. All three algorithms were able to detect the attributes utilized in the respective case-control models in most datasets.</p> <p>Conclusions</p> <p>The current analyses substantiate the utility of rule based classifiers such as RIPPER, RIDOR and PART for the detection of gene-gene/gene-environment interactions in genetic association studies. These classifiers could provide a valuable new method, complementing existing approaches, in the analysis of genetic association studies. The methods provide an advantage in being able to handle both categorical and continuous variable types. Further, because the outputs of the analyses are easy to interpret, the rule based classifier approach could quickly generate testable hypotheses for additional evaluation. Since the algorithms are computationally inexpensive, they may serve as valuable tools for preselection of attributes to be used in more complex, computationally intensive approaches. Whether used in isolation or in conjunction with other tools, rule based classifiers are an important addition to the armamentarium of tools available for analyses of complex genetic association studies.</p

Bias in the physical examination of patients with lumbar radiculopathy

<p>Abstract</p> <p>Background</p> <p>No prior studies have examined systematic bias in the musculoskeletal physical examination. The objective of this study was to assess the effects of bias due to prior knowledge of lumbar spine magnetic resonance imaging findings (MRI) on perceived diagnostic accuracy of the physical examination for lumbar radiculopathy.</p> <p>Methods</p> <p>This was a cross-sectional comparison of the performance characteristics of the physical examination with blinding to MRI results (the 'independent group') with performance in the situation where the physical examination was not blinded to MRI results (the 'non-independent group'). The reference standard was the final diagnostic impression of nerve root impingement by the examining physician. Subjects were recruited from a hospital-based outpatient specialty spine clinic. All adults age 18 and older presenting with lower extremity radiating pain of duration ≤ 12 weeks were evaluated for participation. 154 consecutively recruited subjects with lumbar disk herniation confirmed by lumbar spine MRI were included in this study. Sensitivities and specificities with 95% confidence intervals were calculated in the independent and non-independent groups for the four components of the radiculopathy examination: 1) provocative testing, 2) motor strength testing, 3) pinprick sensory testing, and 4) deep tendon reflex testing.</p> <p>Results</p> <p>The perceived sensitivity of sensory testing was higher with prior knowledge of MRI results (20% vs. 36%; p = 0.05). Sensitivities and specificities for exam components otherwise showed no statistically significant differences between groups.</p> <p>Conclusions</p> <p>Prior knowledge of lumbar MRI results may introduce bias into the pinprick sensory testing component of the physical examination for lumbar radiculopathy. No statistically significant effect of bias was seen for other components of the physical examination. The effect of bias due to prior knowledge of lumbar MRI results should be considered when an isolated sensory deficit on examination is used in medical decision-making. Further studies of bias should include surgical clinic populations and other common diagnoses including shoulder, knee and hip pathology.</p