Institution
University College Cork
Education•Cork, Ireland•
About: University College Cork is a education organization based out in Cork, Ireland. It is known for research contribution in the topics: Population & Context (language use). The organization has 12056 authors who have published 28452 publications receiving 958414 citations. The organization is also known as: Coláiste na hOllscoile Corcaigh & National University of Ireland, Cork.
Topics: Population, Context (language use), Irish, Gut flora, Health care
Papers published on a yearly basis
Papers
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TL;DR: The Global Burden of Disease 2015 Study provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015, finding several countries in sub-Saharan Africa had very large gains in life expectancy, rebounding from an era of exceedingly high loss of life due to HIV/AIDS.
4,804 citations
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Daniel J. Klionsky1, Fábio Camargo Abdalla2, Hagai Abeliovich3, Robert T. Abraham4 +1284 more•Institutions (463)
TL;DR: These guidelines are presented for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
4,316 citations
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Max Planck Society1, Broad Institute2, University of California, Berkeley3, European Bioinformatics Institute4, National Institutes of Health5, University of Massachusetts Medical School6, Spanish National Research Council7, University of Washington8, University of Montana9, Croatian Academy of Sciences and Arts10, University of Oviedo11, University of Bonn12, Emory University13, University College Cork14, Harvard University15
TL;DR: The genomic data suggest that Neandertals mixed with modern human ancestors some 120,000 years ago, leaving traces of Ne andertal DNA in contemporary humans, suggesting that gene flow from Neand Bertals into the ancestors of non-Africans occurred before the divergence of Eurasian groups from each other.
Abstract: Neandertals, the closest evolutionary relatives of present-day humans, lived in large parts of Europe and western Asia before disappearing 30,000 years ago. We present a draft sequence of the Neandertal genome composed of more than 4 billion nucleotides from three individuals. Comparisons of the Neandertal genome to the genomes of five present-day humans from different parts of the world identify a number of genomic regions that may have been affected by positive selection in ancestral modern humans, including genes involved in metabolism and in cognitive and skeletal development. We show that Neandertals shared more genetic variants with present-day humans in Eurasia than with present-day humans in sub-Saharan Africa, suggesting that gene flow from Neandertals into the ancestors of non-Africans occurred before the divergence of Eurasian groups from each other.
3,575 citations
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University of Gothenburg1, University College Cork2, Paul Scherrer Institute3, Weizmann Institute of Science4, Chalmers University of Technology5, Norwegian Meteorological Institute6, University of Antwerp7, Carnegie Mellon University8, Centre national de la recherche scientifique9, University of Lyon10, University of California, Berkeley11, University of York12, Leibniz Institute for Neurobiology13, University of Mainz14, University of Florida15, University of Colorado Boulder16, Forschungszentrum Jülich17, Ghent University18, University of Manchester19, Aix-Marseille University20, California Institute of Technology21
TL;DR: In this article, an overview of the atmospheric degradation mechanisms for SOA precursors, gas-particle partitioning theory and analytical techniques used to determine the chemical composition of SOA is presented.
Abstract: Secondary organic aerosol (SOA) accounts for a significant fraction of ambient tropospheric aerosol and a detailed knowledge of the formation, properties and transformation of SOA is therefore required to evaluate its impact on atmospheric processes, climate and human health. The chemical and physical processes associated with SOA formation are complex and varied, and, despite considerable progress in recent years, a quantitative and predictive understanding of SOA formation does not exist and therefore represents a major research challenge in atmospheric science. This review begins with an update on the current state of knowledge on the global SOA budget and is followed by an overview of the atmospheric degradation mechanisms for SOA precursors, gas-particle partitioning theory and the analytical techniques used to determine the chemical composition of SOA. A survey of recent laboratory, field and modeling studies is also presented. The following topical and emerging issues are highlighted and discussed in detail: molecular characterization of biogenic SOA constituents, condensed phase reactions and oligomerization, the interaction of atmospheric organic components with sulfuric acid, the chemical and photochemical processing of organics in the atmospheric aqueous phase, aerosol formation from real plant emissions, interaction of atmospheric organic components with water, thermodynamics and mixtures in atmospheric models. Finally, the major challenges ahead in laboratory, field and modeling studies of SOA are discussed and recommendations for future research directions are proposed.
3,324 citations
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TL;DR: It is demonstrated that the new models developed for the structure program allow structure to be detected at lower levels of divergence, or with less data, than the original structure models or principal components methods, and that they are not biased towards detecting structure when it is not present.
Abstract: Genetic clustering algorithms require a certain amount of data to produce informative results. In the common situation that individuals are sampled at several locations, we show how sample group information can be used to achieve better results when the amount of data is limited. New models are developed for the structure program, both for the cases of admixture and no admixture. These models work by modifying the prior distribution for each individual's population assignment. The new prior distributions allow the proportion of individuals assigned to a particular cluster to vary by location. The models are tested on simulated data, and illustrated using microsatellite data from the CEPH Human Genome Diversity Panel. We demonstrate that the new models allow structure to be detected at lower levels of divergence, or with less data, than the original structure models or principal components methods, and that they are not biased towards detecting structure when it is not present. These models are implemented in a new version of structure which is freely available online at http://pritch.bsd.uchicago.edu/structure.html.
3,105 citations
Authors
Showing all 12300 results
Name | H-index | Papers | Citations |
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Stephen J. O'Brien | 153 | 1062 | 93025 |
James J. Collins | 151 | 669 | 89476 |
J. Wouter Jukema | 124 | 785 | 61555 |
John F. Cryan | 124 | 723 | 58938 |
Fergus Shanahan | 117 | 705 | 51963 |
Timothy G. Dinan | 116 | 689 | 60561 |
John M. Starr | 116 | 695 | 48761 |
Gordon G. Wallace | 114 | 1267 | 69095 |
Colin Hill | 112 | 693 | 54484 |
Robert Clarke | 111 | 512 | 90049 |
Douglas B. Kell | 111 | 634 | 50335 |
Thomas Bein | 109 | 677 | 42800 |
Steven C. Hayes | 106 | 450 | 51556 |
Åke Borg | 105 | 444 | 53835 |
Eamonn Martin Quigley | 103 | 685 | 39585 |