59 research outputs found
The impacts of El Niño on the observed sea ice budget of West Antarctica
We assess the impact of El Niño-induced wind changes on seasonal West Antarctic sea ice concentrations using reanalysis data and sea ice observations. A novel ice budget analysis reveals that in autumn a previously identified east-west dipole of sea ice concentration anomalies is formed by dynamic and thermodynamic processes in response to El Niño-generated circulation changes. The dipole features decreased (increased) concentration in the Ross Sea (Amundsen and Bellingshausen Seas). Thermodynamic processes and feedback make a substantial contribution to ice anomalies in all seasons. The eastward propagation of this anomaly is partly driven by mean sea ice drift rather than anomalous winds. Our results demonstrate that linkages between sea ice anomalies and atmospheric variability are highly nonlocal in space and time. Therefore, we assert that caution should be applied when interpreting the results of studies that attribute sea ice changes without accounting for such temporally and spatially remote linkages
Inherited variation in immune genes and pathways and glioblastoma risk
To determine whether inherited variations in immune function single-nucleotide polymorphisms (SNPs), genes or pathways affect glioblastoma risk, we analyzed data from recent genome-wide association studies in conjunction with predefined immune function genes and pathways. Gene and pathway analyses were conducted on two independent data sets using 6629 SNPs in 911 genes on 17 immune pathways from 525 glioblastoma cases and 602 controls from the University of California, San Francisco (UCSF) and a subset of 6029 SNPs in 893 genes from 531 cases and 1782 controls from MD Anderson (MDA). To further assess consistency of SNP-level associations, we also compared data from the UK (266 cases and 2482 controls) and the Mayo Clinic (114 cases and 111 controls). Although three correlated epidermal growth factor receptor (EGFR) SNPs were consistently associated with glioblastoma in all four data sets (Mantel–Haenzel P values = 1 × 10−5 to 4 × 10−3), independent replication is required as genome-wide significance was not attained. In gene-level analyses, eight immune function genes were significantly (minP < 0.05) associated with glioblastoma; the IL-2RA (CD25) cytokine gene had the smallest minP values in both UCSF (minP = 0.01) and MDA (minP = 0.001) data sets. The IL-2RA receptor is found on the surface of regulatory T cells potentially contributing to immunosuppression characteristic of the glioblastoma microenvironment. In pathway correlation analyses, cytokine signaling and adhesion–extravasation–migration pathways showed similar associations with glioblastoma risk in both MDA and UCSF data sets. Our findings represent the first systematic description of immune genes and pathways that characterize glioblastoma risk
Exploring the Fundamental Dynamics of Error-Based Motor Learning Using a Stationary Predictive-Saccade Task
The maintenance of movement accuracy uses prior performance errors to correct future motor plans; this motor-learning process ensures that movements remain quick and accurate. The control of predictive saccades, in which anticipatory movements are made to future targets before visual stimulus information becomes available, serves as an ideal paradigm to analyze how the motor system utilizes prior errors to drive movements to a desired goal. Predictive saccades constitute a stationary process (the mean and to a rough approximation the variability of the data do not vary over time, unlike a typical motor adaptation paradigm). This enables us to study inter-trial correlations, both on a trial-by-trial basis and across long blocks of trials. Saccade errors are found to be corrected on a trial-by-trial basis in a direction-specific manner (the next saccade made in the same direction will reflect a correction for errors made on the current saccade). Additionally, there is evidence for a second, modulating process that exhibits long memory. That is, performance information, as measured via inter-trial correlations, is strongly retained across a large number of saccades (about 100 trials). Together, this evidence indicates that the dynamics of motor learning exhibit complexities that must be carefully considered, as they cannot be fully described with current state-space (ARMA) modeling efforts
Population-based targeted sequencing of 54 candidate genes identifies PALB2 as a susceptibility gene for high-grade serous ovarian cancer
Purpose: The known epithelial ovarian cancer (EOC) susceptibility genes account for less than 50% of the heritable risk of ovarian cancer suggesting that other susceptibility genes exist. The aim of this study was to evaluate the contribution to ovarian cancer susceptibility of rare deleterious germline variants in a set of candidate genes. Methods: We sequenced the coding region of 54 candidate genes in 6385 invasive EOC cases and 6115 controls of broad European ancestry. Genes with an increased frequency of putative deleterious variants in cases versus controls were further examined in an independent set of 14 135 EOC cases and 28 655 controls from the Ovarian Cancer Association Consortium and the UK Biobank. For each gene, we estimated the EOC risks and evaluated associations between germline variant status and clinical characteristics. Results: The ORs associated for high-grade serous ovarian cancer were 3.01 for PALB2 (95% CI 1.59 to 5.68; p=0.00068), 1.99 for POLK (95% CI 1.15 to 3.43; p=0.014) and 4.07 for SLX4 (95% CI 1.34 to 12.4; p=0.013). Deleterious mutations in FBXO10 were associated with a reduced risk of disease (OR 0.27, 95% CI 0.07 to 1.00, p=0.049). However, based on the Bayes false discovery probability, only the association for PALB2 in high-grade serous ovarian cancer is likely to represent a true positive. Conclusions: We have found strong evidence that carriers of PALB2 deleterious mutations are at increased risk of high-grade serous ovarian cancer. Whether the magnitude of risk is sufficiently high to warrant the inclusion of PALB2 in cancer gene panels for ovarian cancer risk testing is unclear; much larger sample sizes will be needed to provide sufficiently precise estimates for clinical counselling
A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses
Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of artificial intelligence to taxon identification. Using the North Atlantic deep sea as a case study, we propose a database structure to facilitate standardisation of morphospecies image catalogues between research groups and support future use in multiple front-end applications. We also propose a framework for coordination of international efforts to develop reference guides for the identification of marine species from images. The proposed structure maps to the Darwin Core standard to allow integration with existing databases. We suggest a management framework where high-level taxonomic groups are curated by a regional team, consisting of both end users and taxonomic experts. We identify a mechanism by which overall quality of data within a common reference guide could be raised over the next decade. Finally, we discuss the role of a common reference standard in advancing marine ecology and supporting sustainable use of this ecosystem
Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.
To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC
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