Institution
University of the Basque Country
Education•Leioa, Spain•
About: University of the Basque Country is a education organization based out in Leioa, Spain. It is known for research contribution in the topics: Population & Catalysis. The organization has 19941 authors who have published 49627 publications receiving 1070780 citations. The organization is also known as: UPV/EHU & Euskal Herriko Unibertsitatea.
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TL;DR: In this paper, a selfconsistent density functional method using standard norm-conserving pseudopotentials and a flexible, numerical linear combination of atomic orbitals basis set, which includes multiple-zeta and polarization orbitals, was developed and implemented.
Abstract: We have developed and implemented a selfconsistent density functional method using standard norm-conserving pseudopotentials and a flexible, numerical linear combination of atomic orbitals basis set, which includes multiple-zeta and polarization orbitals. Exchange and correlation are treated with the local spin density or generalized gradient approximations. The basis functions and the electron density are projected on a real-space grid, in order to calculate the Hartree and exchange-correlation potentials and matrix elements, with a number of operations that scales linearly with the size of the system. We use a modified energy functional, whose minimization produces orthogonal wavefunctions and the same energy and density as the Kohn-Sham energy functional, without the need for an explicit orthogonalization. Additionally, using localized Wannier-like electron wavefunctions allows the computation time and memory required to minimize the energy to also scale linearly with the size of the system. Forces and stresses are also calculated efficiently and accurately, thus allowing structural relaxation and molecular dynamics simulations.
7,811 citations
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TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy 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.
For example, 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 versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase 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. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy.
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. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. 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 assays, we hope to encourage technical innovation in the field.
4,756 citations
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TL;DR: A basic taxonomy of feature selection techniques is provided, providing their use, variety and potential in a number of both common as well as upcoming bioinformatics applications.
Abstract: Feature selection techniques have become an apparent need in many bioinformatics applications. In addition to the large pool of techniques that have already been developed in the machine learning and data mining fields, specific applications in bioinformatics have led to a wealth of newly proposed techniques.
In this article, we make the interested reader aware of the possibilities of feature selection, providing a basic taxonomy of feature selection techniques, and discussing their use, variety and potential in a number of both common as well as upcoming bioinformatics applications.
Contact: yvan.saeys@psb.ugent.be
Supplementary information: http://bioinformatics.psb.ugent.be/supplementary_data/yvsae/fsreview
4,232 citations
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Johns Hopkins University1, University of Alabama at Birmingham2, University of Birmingham3, Oklahoma Medical Research Foundation4, Laval University5, University of Manchester6, University College London7, University of California, Los Angeles8, Lund University9, Northwestern University10, Hanyang University11, Dalhousie University12, University of Toronto13, McGill University14, North Shore-LIJ Health System15, Allegheny General Hospital16, University of California, San Diego17, University of Pennsylvania18, Monklands Hospital19, University of the Basque Country20, St Thomas' Hospital21, University of Copenhagen22, New York University23, University of North Carolina at Chapel Hill24, Karolinska Institutet25, SUNY Downstate Medical Center26, University of Manitoba27, Wake Forest University28, University of Louisville29, Emory University30, Istanbul University31, Medical University of South Carolina32, University of Texas Health Science Center at San Antonio33, Cedars-Sinai Medical Center34, University of Maryland, Baltimore35
TL;DR: The Systemic Lupus International Collaborating Clinics (SLICC) group revised and validated the American College of Rheumatology (ACR) systemic lupus erythematosus (SLE) classification criteria in order to improve clinical relevance, meet stringent methodology requirements, and incorporate new knowledge regarding the immunology of SLE.
Abstract: Objective The Systemic Lupus International Collaborating Clinics (SLICC) group revised and validated the American College of Rheumatology (ACR) systemic lupus erythematosus (SLE) classification criteria in order to improve clinical relevance, meet stringent methodology requirements, and incorporate new knowledge regarding the immunology of SLE. Methods The classification criteria were derived from a set of 702 expert-rated patient scenarios. Recursive partitioning was used to derive an initial rule that was simplified and refined based on SLICC physician consensus. The SLICC group validated the classification criteria in a new validation sample of 690 new expert-rated patient scenarios. Results Seventeen criteria were identified. In the derivation set, the SLICC classification criteria resulted in fewer misclassifications compared with the current ACR classification criteria (49 versus 70; P = 0.0082) and had greater sensitivity (94% versus 86%; P < 0.0001) and equal specificity (92% versus 93%; P = 0.39). In the validation set, the SLICC classification criteria resulted in fewer misclassifications compared with the current ACR classification criteria (62 versus 74; P = 0.24) and had greater sensitivity (97% versus 83%; P < 0.0001) but lower specificity (84% versus 96%; P < 0.0001). Conclusion The new SLICC classification criteria performed well in a large set of patient scenarios rated by experts. According to the SLICC rule for the classification of SLE, the patient must satisfy at least 4 criteria, including at least one clinical criterion and one immunologic criterion OR the patient must have biopsy-proven lupus nephritis in the presence of antinuclear antibodies or antidouble-stranded DNA antibodies. (Less)
2,869 citations
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University Hospital Bonn1, University of California, Riverside2, Harvard University3, Case Western Reserve University4, University of Illinois at Chicago5, European Institute6, Stanford University7, VA Palo Alto Healthcare System8, Spanish National Research Council9, Cleveland Clinic Lerner Research Institute10, Hong Kong University of Science and Technology11, University of California, Los Angeles12, University of Southern Denmark13, University of Cambridge14, University of the Basque Country15, Ikerbasque16, University of Manchester17, RIKEN Brain Science Institute18, University of Eastern Finland19, University of Massachusetts Medical School20, University of Bonn21, Center of Advanced European Studies and Research22, University of Southern California23, University of South Florida24, Duke University25, Southampton General Hospital26, University of Southampton27, Moorgreen Hospital28, Louisiana State University29, Imperial College London30, Centre national de la recherche scientifique31, Karolinska Institutet32, Max Planck Society33, University of Tübingen34, University of Groningen35, University of Colorado Denver36, Douglas Mental Health University Institute37
TL;DR: Genome-wide analysis suggests that several genes that increase the risk for sporadic Alzheimer's disease encode factors that regulate glial clearance of misfolded proteins and the inflammatory reaction.
Abstract: Increasing evidence suggests that Alzheimer's disease pathogenesis is not restricted to the neuronal compartment, but includes strong interactions with immunological mechanisms in the brain. Misfolded and aggregated proteins bind to pattern recognition receptors on microglia and astroglia, and trigger an innate immune response characterised by release of inflammatory mediators, which contribute to disease progression and severity. Genome-wide analysis suggests that several genes that increase the risk for sporadic Alzheimer's disease encode factors that regulate glial clearance of misfolded proteins and the inflammatory reaction. External factors, including systemic inflammation and obesity, are likely to interfere with immunological processes of the brain and further promote disease progression. Modulation of risk factors and targeting of these immune mechanisms could lead to future therapeutic or preventive strategies for Alzheimer's disease.
2,815 citations
Authors
Showing all 19941 results
Name | H-index | Papers | Citations |
---|---|---|---|
Wolfgang Wagner | 156 | 2342 | 123391 |
Jose M. Diego | 132 | 480 | 99536 |
Andrea Castro | 132 | 1500 | 90019 |
E. K. U. Gross | 119 | 1154 | 75970 |
Andrew L. Warshaw | 110 | 638 | 44002 |
Angel Rubio | 110 | 930 | 52731 |
Munther A. Khamashta | 109 | 623 | 50205 |
Jonathan N. Coleman | 108 | 396 | 78362 |
Luis Serrano | 105 | 452 | 42515 |
José Luis García Fierro | 100 | 1027 | 47228 |
Richard M. Caprioli | 97 | 490 | 32749 |
Hermenegildo García | 97 | 792 | 46585 |
Tom Broadhurst | 96 | 422 | 30074 |
Konrad Kuijken | 94 | 449 | 28265 |
Petra Schwille | 92 | 421 | 31393 |