Lepton flavor violation decays τ−→μ−P1P2\tau^-\to \mu^- P_1 P_2 in the topcolor-assisted technicolor model and the littlest Higgs model with TT parity

The new particles predicted by the topcolor-assisted technicolor ($TC2$) model and the littlest Higgs model with T-parity (called $LHT$ model) can induce the lepton flavor violation ($LFV$) couplings at tree level or one loop level, which might generate large contributions to some $LFV$ processes. Taking into account the constraints of the experimental data on the relevant free parameters, we calculate the branching ratios of the $LFV$ decay processes $\tau^-\to\mu^- P_1 P_2$ with $P_1 P_2$ = $\pi^+\pi^-$, $K^+K^-$ and $K^0\bar{K^0}$ in the context of these two kinds of new physics models. We find that the $TC2$ model and the $LHT$ model can indeed produce significant contributions to some of these $LFV$ decay processes.Comment: 24 pages, 7 figure

Modelling the effects of patch-plug configuration on the impact performance of patch-repaired composite laminates

The patch-plug configuration has been widely used to repair composite structures and restore the structural integrity of damaged composites. In the present research, single-sided CFRP patch-repaired panels, with different patch-plug configurations, are prepared. This is where a circular-shaped damaged area has been removed and a CFRP patch has been adhesively-bonded onto the panel. In some cases, a CFRP plug is inserted into the hole, caused by removal of the damaged area, before the patch is applied. Such patch-repaired panels, and the pristine CFRP panel, are subjected to a low-velocity impact at an energy of 7.5 J. These impacted pristine and repaired panels are then examined using ultrasonic C-scan and optical microscopy to inspect the impact-associated permanent indentation, interlaminar and intralaminar damage. A finite element analysis (FEA) model, which significantly extends a previously validated elastic-plastic (E-P) numerical damage model, has been developed to predict the impact behaviour of the pristine CFRP panel and the various designs of patch-repaired CFRP panels. The comparison between the experimental and numerical results for all the studied cases shows the maximum deviations for the loading response and the damage area are 12% and 15%, respectively. The good agreement between the experimentally-measured impact properties and those predicted using the numerical model demonstrates that the model is a useful design tool

Experimental and numerical investigations on the impact behaviour of pristine and patch-repaired composite laminates

The present paper investigates the impact behaviour of both pristine carbon-fibre-reinforced-plastic (CFRP) composite laminates and repaired CFRP laminates. For the patch-repaired CFRP specimen, the pristine CFRP panel specimen has been damaged by cutting out a central disc of the CFRP material and then repaired using an adhesively bonded patch of CFRP to cover the hole. Drop-weight, impact tests are performed on these two types of specimens and a numerical elastic-plastic, three-dimensional damage model is developed and employed to simulate the impact behaviour of both types of specimen. This numerical model is meso-scale in nature and assumes that cracks initiate in the CFRP at a nano-scale, in the matrix around fibres, and trigger sub-micrometre intralaminar matrix cracks during the impact event. These localized regions of intralaminar cracking then lead to interlaminar, i.e. delamination, cracking between the neighbouring plies which possess different fibre orientations. These meso-scale, intralaminar and interlaminar, damage processes are modelled using the numerical finite-element analysis model with each individual ply treated as a continuum. Good agreement is found between the results from the experimental studies and the predictions from the numerical simulations. This article is part of the theme issue 'Nanocracks in nature and industry'

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s = 7 TeV pp collisions with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb−1 of proton–proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.NovartisEli Lilly and CompanyAstraZenecaAbbViePfizer UKCelgeneEisaiGenentechMerck Sharp and DohmeRocheCancer Research UKGovernment of CanadaArray BioPharmaGenome CanadaNational Institutes of HealthEuropean CommissionMinistère de l'Économie, de l’Innovation et des Exportations du QuébecSeventh Framework ProgrammeCanadian Institutes of Health Researc

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy