First-Principles Analysis of Potential-Dependent Proton Coupled Electron Transfer between Polypyridyl–Ruthenium Complexes and Oxygen-Modified Graphene Electrodes

Proton coupled electron transfer reactions which are pervasive throughout electrochemistry control a number of energy conversion strategies. First-principles density functional theoretical calculations are used herein to examine proton coupled electron transfer between a homogeneous mononuclear polypyridyl–ruthenium catalyst used in the catalytic oxidation of water and surface ketone groups on oxygen-modified graphene electrode surfaces. The potential-dependent interface energies were calculated for two proton transfer states: Ru^IIIOH···OC–graphene and Ru^IVO···HO–C–graphene. The reactivity for interfacial proton coupled electron transfer was found to be controlled by functional groups that terminate surface defect sites as well as graphene edge sites. The energy gap between the two proton transfer states becomes smaller as the number of surface ketone groups increases. Ab initio molecular dynamics simulations clearly show that increases in the number of surface ketone groups increase the hydrophilicity of the graphene basal plane. This significantly decreases the energy for proton transfer, thus providing a low-energy path that extends over a wide range of potentials. The surface ketone groups at the armchair edges of the graphene plane appear to be the most reactive oxygens on the graphene surface as they lead to direct reversible proton coupled electron transfer between the polypyridal–Ru complexes and the CO groups at the edges where the two proton transfer potential energy surfaces crossing at 0.2 V vs SHE. The graphene armchair edge helps to stabilize the Ru^IVO···HO–C–graphene-edge proton transfer state which is an important step in water oxidation catalysis

Mapping the Functional Tortuosity and Spatiotemporal Heterogeneity of Porous Polymer Membranes with Super-Resolution Nanoparticle Tracking

As particles flow through porous media, they follow complex pathways and experience heterogeneous environments that are challenging to characterize. Tortuosity is often used as a parameter to characterize the complexity of pathways in porous materials and is useful in understanding hindered mass transport in industrial filtration and mass separation processes. However, conventional calculations of tortuosity provide only average values under static conditions; they are insensitive to the intrinsic heterogeneity of porous media and do not account for potential effects of operating conditions. Here, we employ a high-throughput nanoparticle tracking method which enables the observation of actual particle trajectories in polymer membranes under relevant operating conditions. Our results indicate that tortuosity is not simply a structural material property but is instead a functional property that depends on flow rate and particle size. We also resolved the spatiotemporal heterogeneity of flowing particles in these porous media. The distributions of tortuosity and of local residence/retention times were surprisingly broad, exhibiting heavy tails representing a population of highly tortuous trajectories and local regions with anomalously long residence times. Interestingly, local tortuosity and residence times were directly correlated, suggesting the presence of highly confining regions that cause more meandering trajectories and longer retention times. The comprehensive information about tortuosity and spatiotemporal heterogeneity provided by these methods will advance the understanding of complex mass transport and assist rational design and synthesis of porous materials

Influence of Protein Surface Coverage on Anomalously Strong Adsorption Sites

Serum albumin is commonly used as a blocking agent to reduce nonspecific protein adsorption in bioassays and biodevices; however, the details of this process remain poorly understood. Using single molecule techniques, we investigated the dynamics of human serum albumin (HSA) on four model surfaces as a function of protein concentration. By constructing super-resolution maps, identifying anomalously strong adsorption sites, and quantifying surface heterogeneity, we found that the concentration required for site blocking varied dramatically with surface chemistry. When expressed in terms of protein surface coverage, however, a more consistent picture emerged, where a significant fraction of strong sites were passivated at a fractional coverage of 10^–4. On fused silica (FS), “non-fouling” oligo (ethylene glycol) functionalized FS, and hydrophobically modified FS, a modest additional site blocking effect continued at higher coverage. However, on amine-functionalized surfaces, the surface heterogeneity exhibited a minimum at a coverage of ∼10^–4. Using intermolecular Förster resonance energy transfer (FRET), we determined that new anomalous strong sites were created at higher coverage on amine surfaces and that adsorption to these sites was associated with protein–protein interactions, i.e., surface-induced aggregation

Main results of pooled odds ratios (ORs) with confidence interval (CI) in the meta-analysis.

<p>Main results of pooled odds ratios (ORs) with confidence interval (CI) in the meta-analysis.</p

Characteristics of the studies included in the meta-analysis.

<p>Characteristics of the studies included in the meta-analysis.</p

Genetic Analysis of the Relationship between Bone Mineral Density and Low-Density Lipoprotein Receptor-Related Protein 5 Gene Polymorphisms

<div><p>Background</p><p>A number of studies have examined the association between the polymorphisms of the low-density lipoprotein receptor-related protein 5 gene (LRP5), but previous results have been inconclusive. Thus we performed a meta-analysis of studies on the association between the LRP5 polymorphisms and bone mineral density (BMD) to assess their pooled effects.</p> <p>Methods</p><p>Published literature from PubMed, EMBASE and ISI web of science were searched for eligible publications. Weighted mean difference (WMD) and 95% confidence interval (CI) was calculated using fixed- or random-effects model.</p> <p>Results</p><p>A total of 19 studies with 25773 subjects were considered in this meta-analysis. Of them, 17 examined the association between the A1330V polymorphism and BMD, 8 were focused on the V667M polymorphism, and 2 analyzed the Q89R polymorphism. Individuals with the A1330V AA genotype showed significantly higher BMD than those with the AV/VV genotypes [at lumbar spine (LS): WMD = 0.02g/cm², 95% CI = 0.01-0.03, <i>P</i> < 10^-4; at femur neck (FN): WMD = 0.01g/cm², 95% CI = 0.00-0.02, <i>P</i> = 0.01] or VV genotype (at LS: WMD = 0.02g/cm², 95% CI = 0.01-0.04, <i>P</i> = 0.01). Significant associations were also detected in the analysis for V667M (VV vs. VM/MM: WMD at LS = 0.02g/cm², 95% CI = 0.02-0.03, <i>P</i> < 10^-5; WMD at FN = 0.01g/cm², 95% CI = 0.01-0.02, <i>P</i> = 0.0002). As for Q89R, subjects with the QQ genotype tended to have higher BMD than those with the QR/RR genotypes at FN (WMD = 0.03g/cm², 95% CI = 0.01-0.05, <i>P</i> = 0.005).</p> <p>Conclusion</p><p>This meta-analysis demonstrated that the <i>LRP5</i> polymorphisms may be modestly associated with BMD of LS and FN.</p> </div

Forest plot from the meta-analysis of ATLI and <i>CYP2E1</i>.

<p>Forest plot from the meta-analysis of ATLI and <i>CYP2E1</i>.</p

The Association between <em>KCNQ1</em> Gene Polymorphism and Type 2 Diabetes Risk: A Meta-Analysis

<div><h3>Background</h3><p>KCNQ1 (potassium voltage-gated channel KQT-like sub-family, member 1) encodes a pore-forming subunit of a voltage-gated K⁺ channel (KvLQT1) that plays a key role for the repolarization of the cardiac action potential as well as water and salt transport in epithelial tissues. Recently, genome-wide association studies have identified KCNQ1 as a type 2 diabetes (T2D) susceptibility gene in populations of Asian descent. After that, a number of studies reported that the rs2237892 and rs2237895 polymorphism in KCNQ1 has been implicated in T2D risk. However, studies on the association between these polymorphism and T2D remain conflicting. To investigate this inconsistency, we performed this meta-analysis.</p> <h3>Methods</h3><p>Databases including Pubmed, EMBASE, Web of Science and China National Knowledge Infrastructure (CNKI) were searched to find relevant studies. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association. Potential sources of heterogeneity were also assessed by subgroup analysis and meta-regression.</p> <h3>Results</h3><p>A total of 25 articles involving 70,577 T2D cases and 99,068 controls were included. Overall, the summary odds ratio of C allele for T2D was 1.32 (95% CI 1.26–1.38; P<10−5) and 1.24 (95% CI: 1.20–1.29; P<10−5) for KCNQ1 rs2237892 and rs2237895 polymorphisms, respectively. Significant results were also observed using co-dominant, dominant and recessive genetic models. After stratifying by ethnicity, sample size, and diagnostic criteria, significant associations were also obtained.</p> <h3>Conclusions</h3><p>This meta-analysis suggests that the rs2237892 and rs2237895 polymorphisms in KCNQ1 are associated with elevated type 2 diabetes susceptibility.</p> </div

Genetic Polymorphisms of Glutathione S-Transferase Genes GSTM1, GSTT1 and Risk of Hepatocellular Carcinoma

<div><h3>Background</h3><p>A number of case-control studies were conducted to investigate the association of glutathione S-transferase (GST) genetic polymorphisms and hepatocellular carcinoma (HCC) risk. However, these studies have yielded contradictory results. We therefore performed a meta-analysis to derive a more precise estimation of the association between polymorphisms on GSTM1, GSTT1 and HCC.</p> <h3>Methodology/Prinicpal Findings</h3><p>PubMed, EMBASE, ISI web of science and the CNKI databases were systematically searched to identify relevant studies. Data were abstracted independently by two reviewers. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to assess the strength of association. Potential sources of heterogeneity were also assessed by subgroup analysis and meta-regression. Funnel plots and Egger’s linear regression were used to test publication bias among the articles. A total of 34 studies including 4,463 cases and 6,857 controls were included in this meta-analysis. In a combined analysis, significantly increased HCC risks were found for null genotype of GSTM1 (OR = 1.29, 95% CI: 1.06–1.58; P = 0.01) and GSTT1 (OR = 1.43, 95% CI: 1.22–1.68; P<10⁻⁵). Potential sources of heterogeneity were explored by subgroup analysis and meta-regression. Significant results were found in East Asians and Indians when stratified by ethnicity; whereas no significant associations were found among Caucasians and African populations. By pooling data from 12 studies that considered combinations of GSTT1 and GSTM1 null genotypes, a statistically significant increased risk for HCC (OR = 1.88, 95% CI: 1.41–2.50; P<10⁻⁴) was detected for individuals with combined deletion mutations in both genes compared with positive genotypes.</p> <h3>Conclusions/Significance</h3><p>This meta-analysis suggests that the GSTM1 and GSTT1 null genotype may slightly increase the risk of HCC and that interaction between unfavourable GSTs genotypes may exist.</p> </div

Forest plot from the meta-analysis of ATLI and <i>NAT2</i>.

<p>Forest plot from the meta-analysis of ATLI and <i>NAT2</i>.</p