Institution
University of Zurich
Education•Zurich, Switzerland•
About: University of Zurich is a education organization based out in Zurich, Switzerland. It is known for research contribution in the topics: Population & Transplantation. The organization has 50842 authors who have published 124042 publications receiving 5304521 citations. The organization is also known as: UZH & Uni Zurich.
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University of Minnesota1, State University of New York System2, University of Washington3, Laval University4, Malmö University5, Aarhus University6, Aarhus University Hospital7, VU University Amsterdam8, University of Naples Federico II9, University of Michigan10, University of Zurich11, Johns Hopkins University12, University of Copenhagen13, Katholieke Universiteit Leuven14, University of Kentucky15, University of North Carolina at Chapel Hill16, University of Sydney17, HealthPartners18, University of Minnesota System19, University of Auvergne20
TL;DR: The newly recommended evidence-based new DC/TMD protocol is appropriate for use in both clinical and research settings and includes both a valid screener for detecting any pain-related TMD as well as valid diagnostic criteria for differentiating the most common pain- related TMD.
Abstract: Temporomandibular disorders (TMD) are a significant public health problem affecting approximately 5% to 12% of the population.1 TMD is the second most common musculoskeletal condition (after chronic low back pain) resulting in pain and disability.1 Pain-related TMD can impact the individual's daily activities, psychosocial functioning, and quality of life. Overall, the annual TMD management cost in the USA, not including imaging, has doubled in the last decade to $4 billion.1
Patients often seek consultation with dentists for their TMD, especially for pain-related TMD. Diagnostic criteria for TMD with simple, clear, reliable, and valid operational definitions for the history, examination, and imaging procedures are needed to render physical diagnoses in both clinical and research settings. In addition, biobehavioral assessment of pain-related behavior and psychosocial functioning—an essential part of the diagnostic process—is required and provides the minimal information whereby one can determine whether the patient's pain disorder, especially when chronic, warrants further multidisciplinary assessment. Taken together, a new dual-axis Diagnostic Criteria for TMD (DC/TMD) will provide evidence-based criteria for the clinician to use when assessing patients, and will facilitate communication regarding consultations, referrals, and prognosis.2
The research community benefits from the ability to use well-defined and clinically relevant characteristics associated with the phenotype in order to facilitate more generalizable research. When clinicians and researchers use the same criteria, taxonomy, and nomenclature, then clinical questions and experience can be more easily transferred into relevant research questions, and research findings are more accessible to clinicians to better diagnose and manage their patients. The Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) have been the most widely employed diagnostic protocol for TMD research since its publication in 1992.3 This classification system was based on the biopsychosocial model of pain4 that included an Axis I physical assessment, using reliable and well-operationalized diagnostic criteria, and an Axis II assessment of psychosocial status and pain-related disability. The intent was to simultaneously provide a physical diagnosis and identify other relevant characteristics of the patient that could influence the expression and thus management of their TMD. Indeed, the longer the pain persists, the greater the potential for emergence and amplification of cognitive, psychosocial, and behavioral risk factors, with resultant enhanced pain sensitivity, greater likelihood of additional pain persistence, and reduced probability of success from standard treatments.5
The RDC/TMD (1992) was intended to be only a first step toward improved TMD classification, and the authors stated the need for future investigation of the accuracy of the Axis I diagnostic algorithms in terms of reliability and criterion validity—the latter involving the use of credible reference standard diagnoses. Also recommended was further assessment of the clinical utility of the Axis II instruments. The original RDC/TMD Axis I physical diagnoses have content validity based on the critical review by experts of the published diagnostic approach in use at that time and were tested using population-based epidemiologic data.6 Subsequently, a multicenter study showed that, for the most common TMD, the original RDC/TMD diagnoses exhibited sufficient reliability for clinical use.7 While the validity of the individual RDC/TMD diagnoses has been extensively investigated, assessment of the criterion validity for the complete spectrum of RDC/TMD diagnoses had been absent until recently.8
For the original RDC/TMD Axis II instruments, good evidence for their reliability and validity for measuring psychosocial status and pain-related disability already existed when the classification system was published.9–13 Subsequently, a variety of studies have demonstrated the significance and utility of the original RDC/TMD biobehavioral measures in such areas as predicting outcomes of clinical trials, escalation from acute to chronic pain, and experimental laboratory settings.14–20
Other studies have shown that the original RDC/TMD biobehavioral measures are incomplete in terms of prediction of disease course.21–23 The overall utility of the biobehavioral measures in routine clinical settings has, however, yet to be demonstrated, in part because most studies have to date focused on Axis I diagnoses rather than Axis II biobehavioral factors.24
The aims of this article are to present the evidence-based new Axis I and Axis II DC/TMD to be used in both clinical and research settings, as well as present the processes related to their development.
2,283 citations
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French Institute of Health and Medical Research1, Institut Gustave Roussy2, University of Paris-Sud3, University of Texas Southwestern Medical Center4, Thomas Jefferson University5, University of Massachusetts Medical School6, Roswell Park Cancer Institute7, Johns Hopkins University School of Medicine8, Penn State Milton S. Hershey Medical Center9, Goethe University Frankfurt10, St. Jude Children's Research Hospital11, University of Zurich12, University College London13, University of Adelaide14, South Australia Pathology15, Ludwig Institute for Cancer Research16, University of Graz17, Istituto Superiore di Sanità18, University of Michigan19, Northwestern University20, University of Rome Tor Vergata21, University of Cambridge22, University of Bern23, Ghent University24, Harvard University25, Karolinska Institutet26, University of Leicester27
TL;DR: A functional classification of cell death subroutines is proposed that applies to both in vitro and in vivo settings and includes extrinsic apoptosis, caspase-dependent or -independent intrinsic programmed cell death, regulated necrosis, autophagic cell death and mitotic catastrophe.
Abstract: In 2009, the Nomenclature Committee on Cell Death (NCCD) proposed a set of recommendations for the definition of distinct cell death morphologies and for the appropriate use of cell death-related terminology, including 'apoptosis', 'necrosis' and 'mitotic catastrophe'. In view of the substantial progress in the biochemical and genetic exploration of cell death, time has come to switch from morphological to molecular definitions of cell death modalities. Here we propose a functional classification of cell death subroutines that applies to both in vitro and in vivo settings and includes extrinsic apoptosis, caspase-dependent or -independent intrinsic apoptosis, regulated necrosis, autophagic cell death and mitotic catastrophe. Moreover, we discuss the utility of expressions indicating additional cell death modalities. On the basis of the new, revised NCCD classification, cell death subroutines are defined by a series of precise, measurable biochemical features.
2,238 citations
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TL;DR: The Motivation Crowding Effect as mentioned in this paper suggests that external intervention via monetary incentives or punishments may undermine, and under different identifiable conditions strengthen, intrinsic motivation, which can, in specific cases, even dominate the traditional relative price effect.
Abstract: The Motivation Crowding Effect suggests that external intervention via monetary incentives or punishments may undermine, and under different identifiable conditions strengthen, intrinsic motivation. As of today, the theoretical possibility of motivation crowding has been the main subject of discussion among economists. This study demonstrates that the effect is also of empirical relevance. There exist a large number of studies, offering empirical evidence in support of the existence of crowding–out and crowding–in. The study is based on circumstantial evidence, laboratory studies by both psychologists and economists, as well as field research by econometric studies. The pieces of evidence presented refer to a wide variety of areas of the economy and society and have been collected for many different countries and periods of time. Crowding effects thus are an empirically relevant phenomenon, which can, in specific cases, even dominate the traditional relative price effect.
2,237 citations
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Institut Gustave Roussy1, University of Paris-Sud2, French Institute of Health and Medical Research3, Icahn School of Medicine at Mount Sinai4, University of Texas Southwestern Medical Center5, Thomas Jefferson University6, McMaster University7, University of Massachusetts Medical School8, LSU Health Sciences Center New Orleans9, Roswell Park Cancer Institute10, University of Gothenburg11, Boston Children's Hospital12, University of Freiburg13, University of California, San Francisco14, Buck Institute for Research on Aging15, Centre national de la recherche scientifique16, National Institutes of Health17, Technion – Israel Institute of Technology18, University of Leicester19, University of Chieti-Pescara20, Istituto Superiore di Sanità21, University of North Carolina at Chapel Hill22, New York University23, University of Pennsylvania24, Howard Hughes Medical Institute25, Yale University26, University of Ulm27, University of Burgundy28, Aix-Marseille University29, Pasteur Institute30, University of Strasbourg31, Johns Hopkins University32, University of Zurich33, University of Tokyo34, Weizmann Institute of Science35, University of Michigan36, University College London37, Duke University38, University of Graz39, Ghent University40, Trinity College, Dublin41, University of Amsterdam42, University of Lyon43, University of Rome Tor Vergata44, Stony Brook University45, University of Göttingen46, Kyoto University47, Merck & Co.48, Austrian Academy of Sciences49, National University of Singapore50, University of Chicago51, Royal College of Surgeons in Ireland52, La Trobe University53, University of Buenos Aires54, University of Padua55, University of Lisbon56, University of Cambridge57, University of Würzburg58, University of Geneva59, University of Bern60, Rockefeller University61, University of Lausanne62, Osaka University63, University of California, San Diego64, University of Glasgow65, Harvard University66, Karolinska Institutet67
TL;DR: A nonexhaustive comparison of methods to detect cell death with apoptotic or nonapoptotic morphologies, their advantages and pitfalls is provided and the importance of performing multiple, methodologically unrelated assays to quantify dying and dead cells is emphasized.
Abstract: Cell death is essential for a plethora of physiological processes, and its deregulation characterizes numerous human diseases Thus, the in-depth investigation of cell death and its mechanisms constitutes a formidable challenge for fundamental and applied biomedical research, and has tremendous implications for the development of novel therapeutic strategies It is, therefore, of utmost importance to standardize the experimental procedures that identify dying and dead cells in cell cultures and/or in tissues, from model organisms and/or humans, in healthy and/or pathological scenarios Thus far, dozens of methods have been proposed to quantify cell death-related parameters However, no guidelines exist regarding their use and interpretation, and nobody has thoroughly annotated the experimental settings for which each of these techniques is most appropriate Here, we provide a nonexhaustive comparison of methods to detect cell death with apoptotic or nonapoptotic morphologies, their advantages and pitfalls These guidelines are intended for investigators who study cell death, as well as for reviewers who need to constructively critique scientific reports that deal with cellular demise Given the difficulties in determining the exact number of cells that have passed the point-of-no-return of the signaling cascades leading to cell death, we emphasize the importance of performing multiple, methodologically unrelated assays to quantify dying and dead cells
2,218 citations
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TL;DR: The familiar pick-a-point approach and the much less familiar Johnson-Neyman technique for probing interactions in linear models are described and macros for SPSS and SAS are introduced to simplify the computations and facilitate the probing of interactions in ordinary least squares and logistic regression.
Abstract: Researchers often hypothesize moderated effects, in which the effect of an independent variable on an outcome variable depends on the value of a moderator variable. Such an effect reveals itself statistically as an interaction between the independent and moderator variables in a model of the outcome variable. When an interaction is found, it is important to probe the interaction, for theories and hypotheses often predict not just interaction but a specific pattern of effects of the focal independent variable as a function of the moderator. This article describes the familiar pick-a-point approach and the much less familiar Johnson-Neyman technique for probing interactions in linear models and introduces macros for SPSS and SAS to simplify the computations and facilitate the probing of interactions in ordinary least squares and logistic regression. A script version of the SPSS macro is also available for users who prefer a point-and-click user interface rather than command syntax.
2,204 citations
Authors
Showing all 51384 results
Name | H-index | Papers | Citations |
---|---|---|---|
Richard A. Flavell | 231 | 1328 | 205119 |
Peer Bork | 206 | 697 | 245427 |
Thomas C. Südhof | 191 | 653 | 118007 |
Stuart H. Orkin | 186 | 715 | 112182 |
Ruedi Aebersold | 182 | 879 | 141881 |
Tadamitsu Kishimoto | 181 | 1067 | 130860 |
Stanley B. Prusiner | 168 | 745 | 97528 |
Yang Yang | 164 | 2704 | 144071 |
Tomas Hökfelt | 158 | 1033 | 95979 |
Dan R. Littman | 157 | 426 | 107164 |
Hans Lassmann | 155 | 724 | 79933 |
Matthias Egger | 152 | 901 | 184176 |
Lorenzo Bianchini | 152 | 1516 | 106970 |
Robert M. Strieter | 151 | 612 | 73040 |
Ashok Kumar | 151 | 5654 | 164086 |