University of Iceland

About: University of Iceland is a education organization based out in Reykjavik, Suðurnes, Iceland. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 5423 authors who have published 16199 publications receiving 694762 citations. The organization is also known as: Háskóli Íslands.

Identifying Fishes through DNA Barcodes and Microarrays

Abstract: Background: International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection. Methodology/Principal Findings: This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S), cytochrome b (cyt b), and cytochrome oxidase subunit I (COI) for the identification of 50 European marine fish species by combining techniques of ‘‘DNA barcoding’’ and microarrays. In a DNA barcoding approach, neighbour Joining (NJ) phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the ‘‘position of label’’ effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (.90%) renders the DNA barcoding marker as rather unsuitable for this high-throughput technology. Conclusions/Significance: Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products.

Page curve for an evaporating black hole

Abstract: A Page curve for an evaporating black hole in asymptotically flat spacetime is computed by adapting the Quantum Ryu-Takayanagi (QRT) proposal to an analytically solvable semi-classical two-dimensional dilaton gravity theory. The Page time is found to be one third of the black hole lifetime, at leading order in semi-classical corrections. A Page curve is also obtained for a semi-classical eternal black hole, where energy loss due to Hawking evaporation is balanced by an incoming energy flux.

The role of the deep ocean in North Atlantic climate change between 70 and 130 kyr ago

Abstract: THE suggestion1 that changes in North Atlantic Deep Water (NADW) production are linked through surface heat flux to the atmospheric temperature over Greenland is supported by earlier indications2,3 that NADW production decreased during glacial times, and by the subsequent finding4–6 that it declined during the Younger Dryas cool period at the end of the last glaciation. Changes in North Atlantic surface temperatures have been found7 to mirror high-frequency temperature changes recorded in Greenland ice cores over the past 80 kyr, but the connection to abyssal circulation has yet to be established, except for one or two isolated oscillations8,9. Here we present carbon and oxygen isotope analyses of benthic foraminifera in a high-resolution North Atlantic deep-sea sediment core for the period 70–130 kyr ago. These data allow us to reconstruct the history of NADW production, which shows a close correlation with Greenland climate variability for much of this time interval, suggesting that the climate influence of NADW variability was widespread. We see no evidence, however, for changes in NADW production during substage 5e (the Eemian interglacial period), in contrast with recent ice-core data10 which suggest severe climate instability in Greenland during this time period. Our results may support suggestions, based on data from a second ice core, that this apparent instability is an artefact caused by ice flow11. Alternatively, the Eemian climate instability may have had a different origin from the subsequent climate events.

Mutational spectrum in a worldwide study of 29,700 families with BRCA1 or BRCA2 mutations

Abstract: The prevalence and spectrum of germline mutations in BRCA1 and BRCA2 have been reported in single populations, with the majority of reports focused on White in Europe and North America. The Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) has assembled data on 18,435 families with BRCA1 mutations and 11,351 families with BRCA2 mutations ascertained from 69 centers in 49 countries on six continents. This study comprehensively describes the characteristics of the 1,650 unique BRCA1 and 1,731 unique BRCA2 deleterious (disease-associated) mutations identified in the CIMBA database. We observed substantial variation in mutation type and frequency by geographical region and race/ethnicity. In addition to known founder mutations, mutations of relatively high frequency were identified in specific racial/ethnic or geographic groups that may reflect founder mutations and which could be used in targeted (panel) first pass genotyping for specific populations. Knowledge of the population-specific mutational spectrum in BRCA1 and BRCA2 could inform efficient strategies for genetic testing and may justify a more broad-based oncogenetic testing in some populations.

Multiple Kernel Learning for Hyperspectral Image Classification: A Review

Abstract: With the rapid development of spectral imaging techniques, classification of hyperspectral images (HSIs) has attracted great attention in various applications such as land survey and resource monitoring in the field of remote sensing. A key challenge in HSI classification is how to explore effective approaches to fully use the spatial–spectral information provided by the data cube. Multiple kernel learning (MKL) has been successfully applied to HSI classification due to its capacity to handle heterogeneous fusion of both spectral and spatial features. This approach can generate an adaptive kernel as an optimally weighted sum of a few fixed kernels to model a nonlinear data structure. In this way, the difficulty of kernel selection and the limitation of a fixed kernel can be alleviated. Various MKL algorithms have been developed in recent years, such as the general MKL, the subspace MKL, the nonlinear MKL, the sparse MKL, and the ensemble MKL. The goal of this paper is to provide a systematic review of MKL methods, which have been applied to HSI classification. We also analyze and evaluate different MKL algorithms and their respective characteristics in different cases of HSI classification cases. Finally, we discuss the future direction and trends of research in this area.