Computing special values of partial zeta functions

We discuss computation of the special values of partial zeta functions associated to totally real number fields. The main tool is the \emph{Eisenstein cocycle} $\Psi$, a group cocycle for $GL_{n} (\Z )$; the special values are computed as periods of $\Psi$, and are expressed in terms of generalized Dedekind sums. We conclude with some numerical examples for cubic and quartic fields of small discriminant.Comment: 10 p

Enhancing Next-Generation Sequencing-Guided Cancer Care Through Cognitive Computing

Background: Using next-generation sequencing (NGS) to guide cancer therapy has created challenges in analyzing and reporting large volumes of genomic data to patients and caregivers. Specifically, providing current, accurate information on newly approved therapies and open clinical trials requires considerable manual curation performed mainly by human “molecular tumor boards” (MTBs). The purpose of this study was to determine the utility of cognitive computing as performed by Watson for Genomics (WfG) compared with a human MTB. Materials and Methods: One thousand eighteen patient cases that previously underwent targeted exon sequencing at the University of North Carolina (UNC) and subsequent analysis by the UNCseq informatics pipeline and the UNC MTB between November 7, 2011, and May 12, 2015, were analyzed with WfG, a cognitive computing technology for genomic analysis. Results: Using a WfG-curated actionable gene list, we identified additional genomic events of potential significance (not discovered by traditional MTB curation) in 323 (32%) patients. The majority of these additional genomic events were considered actionable based upon their ability to qualify patients for biomarker-selected clinical trials. Indeed, the opening of a relevant clinical trial within 1 month prior to WfG analysis provided the rationale for identification of a new actionable event in nearly a quarter of the 323 patients. This automated analysis took <3 minutes per case. Conclusion: These results demonstrate that the interpretation and actionability of somatic NGS results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing could potentially improve patient care by providing a rapid, comprehensive approach for data analysis and consideration of up-to-date availability of clinical trials. Implications for Practice: The results of this study demonstrate that the interpretation and actionability of somatic next-generation sequencing results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing can significantly improve patient care by providing a fast, cost-effective, and comprehensive approach for data analysis in the delivery of precision medicine. Patients and physicians who are considering enrollment in clinical trials may benefit from the support of such tools applied to genomic data

Coping with the effects of fear of failure in young elite athletes

Coping with stress is an important element in effective functioning at the elite level in sports, and fear of failure (FF) is an example of a stressor that athletes experience. Three issues underpin the present preliminary study. First, the prevalence of problems attributed to FF in achievement settings. Second, sport is a popular and significant achievement domain for children and adolescents. Third, there is a lack of research on FF in sport among this population. Therefore, the objectives of the study were to examine the effects of FF on young athletes and to find out their coping responses to the effects of FF. Interviews were conducted individually with nine young elite ath­letes (5 males, 4 females; ages 14-17 years). It was inferred from the data that FF affected the athletes' well-being, interpersonal behavior, sport performance, and schoolwork. The athletes employed a combination of problem-focused, emotion-fo­cused, and avoidance-focused coping strategies, with avoidance strategies being the most frequently reported

Whole genome sequencing for the genetic diagnosis of heterogenous dystonia phenotypes

Introduction: Dystonia is a clinically and genetically heterogeneous disorder and a genetic cause is often difficult to elucidate. This is the first study to use whole genome sequencing (WGS) to investigate dystonia in a large sample of affected individuals. Methods: WGS was performed on 111 probands with heterogenous dystonia phenotypes. We performed analysis for coding and non-coding variants, copy number variants (CNVs), and structural variants (SVs). We assessed for an association between dystonia and 10 known dystonia risk variants. Results: A genetic diagnosis was obtained for 11.7% (13/111) of individuals. We found that a genetic diagnosis was more likely in those with an earlier age at onset, younger age at testing, and a combined dystonia phenotype. We identified pathogenic/likely-pathogenic variants in ADCY5 (n = 1), ATM (n = 1), GNAL (n = 2), GLB1 (n = 1), KMT2B (n = 2), PRKN (n = 2), PRRT2 (n = 1), SGCE (n = 2), and THAP1 (n = 1). CNVs were detected in 3 individuals. We found an association between the known risk variant ARSG rs11655081 and dystonia (p = 0.003). Conclusion: A genetic diagnosis was found in 11.7% of individuals with dystonia. The diagnostic yield was higher in those with an earlier age of onset, younger age at testing, and a combined dystonia phenotype. WGS may be particularly relevant for dystonia given that it allows for the detection of CNVs, which accounted for 23% of the genetically diagnosed cases. © 2019 The Author

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

Target highlights in CASP13: experimental target structures through the eyes of their authors

The functional and biological significance of selected CASP13 targets are described by the authors of the structures. The structural biologists discuss the most interesting structural features of the target proteins and assess whether these features were correctly reproduced in the predictions submitted to the CASP13 experiment

Meta-analysis of type 2 Diabetes in African Americans Consortium

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94)<P<5 × 10(-8), odds ratio (OR)  = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2 × 10(-23) < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.Peer reviewe