Education • Pécs, Hungary •
About:University of Pécs is a education organization based out in Pécs, Hungary. It is known for research contribution in the topics: Population & Receptor. The organization has 6514 authors who have published 13377 publications receiving 283993 citations. The organization is also known as: University of Pecs & Pécsi Tudományegyetem.
Papers published on a yearly basis
TL;DR:Associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses.
Abstract:精神分裂症是一种高度遗传障碍。基因tic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.
Radboud University Nijmegen Medical Centre 1,University of Michigan 2,Radboud University Nijmegen 3,University of Toronto 4,McGill University 5,University of Basel 6,University of Florence 7,Auckland City Hospital 8,University of Pittsburgh 9,查利特 10,University of California, Los Angeles 11,University College London 12,University of Zurich 13,University of Paris 14,Marche Polytechnic University 15,University of Texas Health Science Center at Houston 16,Newcastle University 17,University of Pécs 18,Georgetown University 19,Istanbul University 20,医疗University of Białystok 21,University of Giessen 22,Seconda Università degli Studi di Napoli 23,University College Dublin 24,Stanford University 25,University of Colorado Denver 26,National Health Service 27,医疗College of Wisconsin 28,University of Alabama at Birmingham 29,University of Manchester 30,Rutgers University 31,Thomas Jefferson University 32,University of Toledo 33,Amgen 34,Boston University 35,医疗University of South Carolina 36,University of Pennsylvania 37,Northwestern University 38
TL;DR:The ACR/EULAR classification criteria for SSc performed better than the 1980 ACR criteria and should allow for more patients to be classified correctly as having the disease.
Abstract:OBJECTIVE: The 1980 American College of Rheumatology (ACR) classification criteria for systemic sclerosis (SSc) lack sensitivity for early SSc and limited cutaneous SSc. The present work, by a joint committee of the ACR and the European League Against Rheumatism (EULAR), was undertaken for the purpose of developing new classification criteria for SSc. METHODS: Using consensus methods, 23 candidate items were arranged in a multicriteria additive point system with a threshold to classify cases as SSc. The classification system was reduced by clustering items and simplifying weights. The system was tested by 1) determining specificity and sensitivity in SSc cases and controls with scleroderma-like disorders, and 2) validating against the combined view of a group of experts on a set of cases with or without SSc. RESULTS: It was determined that skin thickening of the fingers extending proximal to the metacarpophalangeal joints is sufficient for the patient to be classified as having SSc; if that is not present, 7 additive items apply, with varying weights for each: skin thickening of the fingers, fingertip lesions, telangiectasia, abnormal nailfold capillaries, interstitial lung disease or pulmonary arterial hypertension, Raynaud's phenomenon, and SSc-related autoantibodies. Sensitivity and specificity in the validation sample were, respectively, 0.91 and 0.92 for the new classification criteria and 0.75 and 0.72 for the 1980 ACR classification criteria. All selected cases were classified in accordance with consensus-based expert opinion. All cases classified as SSc according to the 1980 ACR criteria were classified as SSc with the new criteria, and several additional cases were now considered to be SSc. CONCLUSION: The ACR/EULAR classification criteria for SSc performed better than the 1980 ACR criteria for SSc and should allow for more patients to be classified correctly as having the disease.
TL;DR:In this article, the authors used a Bayesian hierarchical model to estimate trends in diabetes prevalence, defined as fasting plasma glucose of 7.0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs in 200 countries and territories in 21 regions, by sex and from 1980 to 2014.
Abstract:Background: One of the global targets for non-communicable diseases is to halt, by 2025, the rise in the age standardised adult prevalence of diabetes at its 2010 levels. We aimed to estimate worldwide trends in diabetes, how likely it is for countries to achieve the global target, and how changes in prevalence, together with population growth and ageing, are aff ecting the number of adults with diabetes. Methods: We pooled data from population-based studies that had collected data on diabetes through measurement of its biomarkers. We used a Bayesian hierarchical model to estimate trends in diabetes prevalence-defined as fasting plasma glucose of 7.0 mmol/L or higher, or history of diagnosis with diabetes, or use of insulin or oral hypoglycaemic drugs-in 200 countries and territories in 21 regions, by sex and from 1980 to 2014. We also calculated the posterior probability of meeting the global diabetes target if post-2000 trends continue. Findings: We used data from 751 studies including 4372000 adults from 146 of the 200 countries we make estimates for. Global age-standardised diabetes prevalence increased from 4.3% (95% credible interval 2.4-17.0) in 1980 to 9.0% (7.2-11.1) in 2014 in men, and from 5.0% (2.9-7.9) to 7.9% (6.4-9.7) in women. The number of adults with diabetes in the world increased from 108 million in 1980 to 422 million in 2014 (28.5% due to the rise in prevalence, 39.7% due to population growth and ageing, and 31.8% due to interaction of these two factors). Age-standardised adult diabetes prevalence in 2014 was lowest in northwestern Europe, and highest in Polynesia and Micronesia, at nearly 25%, followed by Melanesia and the Middle East and north Africa. Between 1980 and 2014 there was little change in age-standardised diabetes prevalence in adult women in continental western Europe, although crude prevalence rose because of ageing of the population. By contrast, age-standardised adult prevalence rose by 15 percentage points in men and women in Polynesia and Micronesia. In 2014, American Samoa had the highest national prevalence of diabetes (>30% in both sexes), with age-standardised adult prevalence also higher than 25% in some other islands in Polynesia and Micronesia. If post-2000 trends continue, the probability of meeting the global target of halting the rise in the prevalence of diabetes by 2025 at the 2010 level worldwide is lower than 1% for men and is 1% for women. Only nine countries for men and 29 countries for women, mostly in western Europe, have a 50% or higher probability of meeting the global target. Interpretation: Since 1980, age-standardised diabetes prevalence in adults has increased, or at best remained unchanged, in every country. Together with population growth and ageing, this rise has led to a near quadrupling of the number of adults with diabetes worldwide. The burden of diabetes, both in terms of prevalence and number of adults aff ected, has increased faster in low-income and middle-income countries than in high-income countries.
University of California, Santa Barbara 1,University of Texas at Austin 2,University of Wrocław 3,Dresden University of Technology 4,University of Tartu 5,Gulu University 6,Middle East University 7,Stockholm University 8,University of the Punjab 9,University of Nigeria, Nsukka 10,Istanbul University 11,Franklin & Marshall College 12,Norwegian University of Science and Technology 13,University of Algiers 14,Australian National University 15,Russian Academy of Sciences 16,Russian State University for the Humanities 17,İzmir University of Economics 18,University of Social Sciences and Humanities 19,Université catholique de Louvain 20,Ankara University 21,Pontifical Catholic University of Peru 22,Cumhuriyet University 23,University of the Republic 24,ISCTE – University Institute of Lisbon 25,The Chinese University of Hong Kong 26,National Autonomous University of Mexico 27,University of Pécs 28,University of Constantine the Philosopher 29,University of Maribor 30,University of Zagreb 31,University of Malaya 32,Central University of Finance and Economics 33,University of Crete 34,University of Primorska 35,Institute of Molecular and Cell Biology 36,University of Amsterdam 37,Catholic University of the Sacred Heart 38,VU University Amsterdam 39,University of Granada 40,University of Delhi 41,University of Havana 42,Pontifical Catholic University of Rio de Janeiro 43,University of Vienna 44,Universiti Utara Malaysia 45,Vilnius University 46,University of British Columbia 47,University of Sussex 48,Romanian Academy 49,Comenius University in Bratislava 50,Slovak Academy of Sciences 51,University of Monterrey 52,SAS Institute 53,DHA Suffa University 54,Pontifical Catholic University of Chile 55,South-West University "Neofit Rilski" 56,University of São Paulo 57,Kyung Hee University 58,University of Ljubljana 59
TL;DR:This work combines this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets and finds that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model of mate preference integration.
Abstract:Humans express a wide array of ideal mate preferences. Around the world, people desire romantic partners who are intelligent, healthy, kind, physically attractive, wealthy, and more. In order for these ideal preferences to guide the choice of actual romantic partners, human mating psychology must possess a means to integrate information across these many preference dimensions into summaries of the overall mate value of their potential mates. Here we explore the computational design of this mate preference integration process using a large sample of n = 14,487 people from 45 countries around the world. We combine this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets. Across cultures, people higher in mate value appear to experience greater power of choice on the mating market in that they set higher ideal standards, better fulfill their preferences in choice, and pair with higher mate value partners. Furthermore, we find that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model of mate preference integration.