Efficient light coupling into a photonic crystal waveguide with flatband slow mode

We design an efficient coupler to transmit light from a strip waveguide into the flatband slow mode of a photonic crystal waveguide with ring-shaped holes. The coupler is a section of a photonic crystal waveguide with a higher group velocity, obtained by different ring dimensions. We demonstrate coupling efficiency in excess of 95% over the 8 nm wavelength range where the photonic crystal waveguide exhibits a quasi constant group velocity vg = c/37. An analysis based on the small Fabry-P\'erot resonances in the simulated transmission spectra is introduced and used for studying the effect of the coupler length and for evaluating the coupling efficiency in different parts of the coupler. The mode conversion efficiency within the coupler is more than 99.7% over the wavelength range of interest. The parasitic reflectance in the coupler, which depends on the propagation constant mismatch between the slow mode and the coupler mode, is lower than 0.6% within this wavelength range.Comment: 11 pages, 7 figures, submitted to Photonics and Nanostructures - Fundamentals and Application

Genetic Determinism vs. Phenotypic Plasticity in Protist Morphology

Untangling the relationships between morphology and phylogeny is key to building a reliable taxonomy, but is especially challenging for protists, where the existence of cryptic or pseudocryptic species makes finding relevant discriminant traits difficult. Here we use Hyalosphenia papilio (a testate amoeba) as a model species to investigate the contribution of phylogeny and phenotypic plasticity in its morphology. We study the response of H. papilio morphology (shape and pores number) to environmental variables in (i) a manipulative experiment with controlled conditions (water level), (ii) an observational study of a within-site natural ecological gradient (water level), and (iii) an observational study across 37 European peatlands (climate). We showed that H. papilio morphology is correlated to environmental conditions (climate and water depth) as well as geography, while no relationship between morphology and phylogeny was brought to light. The relative contribution of genetic inheritance and phenotypic plasticity in shaping morphology varies depending on the taxonomic group and the trait under consideration. Thus, our data call for a reassessment of taxonomy based on morphology alone. This clearly calls for a substantial increase in taxonomic research on these globally still under-studied organisms leading to a reassessment of estimates of global microbial eukaryotic diversity.</p

FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium

Background:Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium. Methods:Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression. Results:Little evidence of association with breast cancer risk was observed for SNPs in the FGF receptor genes. The strongest evidence in European women was for rs743682 in FGFR3; the estimated per-allele odds ratio was 1.05 (95 confidence interval=1.02-1.09, P=0.0020), which is substantially lower than that observed for SNPs in FGFR2. Conclusion:Our results suggest that common variants in the other FGF receptors are not associated with risk of breast cancer to the degree observed for FGFR2. © 2014 Cancer Research UK

UDP-glucuronosyltransferase UGT1A7 genetic polymorphisms in hepatocellular carcinoma: a differential impact according to seropositivity of HBV or HCV markers?

<p>Abstract</p> <p>Background:</p> <p>We conducted a case-control study to evaluate the role of UDP-glucuronosyltransferase 1A7 (UGT1A7) polymorphisms in the onset of hepatocellular carcinoma (HCC).</p> <p>Methods:</p> <p>The study included 165 patients with HCC, 134 with cirrhosis and 142 controls without liver disease, matched for age and hospital. All were men younger than 75 years. HCC and cirrhosis patients were stratified according to time since cirrhosis diagnosis.</p> <p>Results:</p> <p>We found a positive association between the UGT1A7*3/*3 genotype and HCC when the comparison was restricted to patients whose disease was of viral origin [OR = 3.4 (0.3–45)] but a negative association when it included only alcoholic patients [OR = 0.1 (0.02–0.6), p = 0.01].</p> <p>Conclusion:</p> <p>Our study shows that UGT1A7 may play a role in hepatocellular carcinogenesis and that this role may differ according to the primary cause of the cirrhosis.</p

Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer.

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.BCAC is funded by Cancer Research UK (C1287/A10118, C1287/A12014) and by the European Community's Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS). Meetings of the BCAC have been funded by the European Union COST programme (BM0606). Genotyping on the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710, C8197/A16565), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer program and the Ministry of Economic Development, Innovation and Export Trade of Quebec, grant PSR-SIIRI-701. Combination of the GWAS data was supported in part by the US National Institutes of Health (NIH) Cancer Post-Cancer GWAS initiative, grant 1 U19 CA148065-01 (DRIVE, part of the GAME-ON initiative). For a full description of funding and acknowledgments, see the Supplementary Note.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.324

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe