Plasmonic-enhanced photocatalysis reactions using gold nanostructured films

This work shows the enhancement of the visible photocatalytic activity of TiO2 NPs film using the localized surface plasmonic resonance of Au nanostructures. We adopted a simple yet effective surface treatment to tune the size distribution, and plasmonic resonance spectrum of Au nanostructured films on glass substrates, by hot plate annealing in air at low temperatures. A hybrid photocatalytic film of TiO2:Au is utilized to catalyse a selective photodegradation reaction of Methylene Blue in solution. Irradiation at the plasmonic resonance wavelength of the Au nanostructures provides more effective photodegradation compared to broadband artificial sunlight of significantly higher intensity. This improvement is attributed to the active contribution of the plasmonic hot electrons injected into the TiO2. The broadband source initiates competing photoreactions in the photocatalyst, so that carrier transfer from the catalyst surface to the solution is less efficient. The proposed hybrid photocatalyst can be integrated with a variety of device architectures and designs, which makes it highly attractive for low-cost photocatalysis applications

Bio-nanotechnology application in wastewater treatment

The nanoparticles have received high interest in the field of medicine and water purification, however, the nanomaterials produced by chemical and physical methods are considered hazardous, expensive, and leave behind harmful substances to the environment. This chapter aimed to focus on green-synthesized nanoparticles and their medical applications. Moreover, the chapter highlighted the applicability of the metallic nanoparticles (MNPs) in the inactivation of microbial cells due to their high surface and small particle size. Modifying nanomaterials produced by green-methods is safe, inexpensive, and easy. Therefore, the control and modification of nanoparticles and their properties were also discussed

Expression of delta-like ligand 4 (Dll4) and markers of hypoxia in colon cancer

BACKGROUND: Delta-like ligand 4 (Dll4) is a Notch ligand that is upregulated by hypoxia and vascular endothelial growth factor-A (VEGF-A) and is reported to have a role in tumor angiogenesis. Evidence from xenograft studies suggests that inhibiting Dll4-Notch signalling may overcome resistance to anti-VEGF therapy. The aim of this study was to characterise the expression of Dll4 in colon cancer and to assess whether it is associated with markers of hypoxia and prognosis. METHOD: In all, 177 colon cancers were represented in tissue microarrays. Immunohistochemistry was performed using validated antibodies against Dll4, VEGF, hypoxia-inducible factor (HIF)-1alpha, HIF-2alpha, prolyl hydroxylase (PHD)1, PHD2, PHD3 and carbonic anhydrase 9 (CA9). RESULTS: The expression of Dll4 was observed preferentially in the endothelium of 71% (125 out of 175) of colon cancers, but not in the endothelium adjacent to normal mucosa (none out of 107, P<0.0001). The expression of VEGF was significantly associated with HIF-2alpha (P<0.0001) and Dll4 (P=0.010). Only HIF-2alpha had a significant multivariate prognostic effect (hazard ratio 1.61, 95% confidence interval 1.01-2.57). Delta-like ligand 4 was also expressed by neoplastic cells, particularly neoplastic goblet cells. CONCLUSION: Endothelial expression of Dll4 is not a prognostic factor, but is significantly associated with VEGF. Assessing endothelial Dll4 expression may be critical in predicting response to anti-VEGF therapies

Homocysteine and Coronary Heart Disease: Meta-analysis of MTHFR Case-Control Studies, Avoiding Publication Bias

Robert Clarke and colleagues conduct a meta-analysis of unpublished datasets to examine the causal relationship between elevation of homocysteine levels in the blood and the risk of coronary heart disease. Their data suggest that an increase in homocysteine levels is not likely to result in an increase in risk of coronary heart disease

Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use

BACKGROUND: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. METHODS: We analyzed similar to 250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. RESULTS: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. CONCLUSIONS: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.Peer reviewe

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations withP <5 x 10(-8)in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P <5 x 10(-8)) in the discovery samples. Ten novel SNVs, including rs12616219 nearTMEM182, were followed-up and five of them (rs462779 inREV3L, rs12780116 inCNNM2, rs1190736 inGPR101, rs11539157 inPJA1, and rs12616219 nearTMEM182) replicated at a Bonferroni significance threshold (P <4.5 x 10(-3)) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, inCCDC141and two low-frequency SNVs inCEP350andHDGFRP2. Functional follow-up implied that decreased expression ofREV3Lmay lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.Peer reviewe

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P &lt; 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.</p

Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk.

Blood pressure is a heritable trait influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (≥140 mm Hg systolic blood pressure or  ≥90 mm Hg diastolic blood pressure). Even small increments in blood pressure are associated with an increased risk of cardiovascular events. This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.J.D. is a British Heart Foundation Professor, European Research Council Senior Investigator and NIHR Senior Investigator. J.D.E. and A.D.J. were supported by NHLBI Intramural Research Program funds. N.F. is supported by R21HL123677-01 and R56 DK104806-01A1. N.S. is supported by the British Heart Foundation and is an NIHR Senior Investigator. T.L.A. is supported by NIH career development award K23DK088942. This work was funded by the UK Medical Research Council (G0800270), the British Heart Foundation (SP/09/002), the UK National Institute for Health Research Cambridge Biomedical Research Centre, the European Research Council (268834), European Commission Framework Programme 7 (HEALTH-F2-2012-279233) and Pfizer. The eQTL database construction was supported by NHLBI intramural funds