Institution
Shanghai Jiao Tong University
Education•Shanghai, Shanghai, China•
About: Shanghai Jiao Tong University is a education organization based out in Shanghai, Shanghai, China. It is known for research contribution in the topics: Population & Cancer. The organization has 157524 authors who have published 184620 publications receiving 3451038 citations. The organization is also known as: Shanghai Communications University & Shanghai Jiaotong University.
Topics: Population, Cancer, Microstructure, Cell growth, Metastasis
Papers published on a yearly basis
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12 Aug 2007
TL;DR: This paper proposes a co-clustering based classification (CoCC) algorithm, used as a bridge to propagate the class structure and knowledge from the in-domain to the out-of-domain, and shows that the algorithm greatly improves the classification performance over the traditional learning algorithms.
Abstract: In many real world applications, labeled data are in short supply. It often happens that obtaining labeled data in a new domain is expensive and time consuming, while there may be plenty of labeled data from a related but different domain. Traditional machine learning is not able to cope well with learning across different domains. In this paper, we address this problem for a text-mining task, where the labeled data are under one distribution in one domain known as in-domain data, while the unlabeled data are under a related but different domain known as out-of-domain data. Our general goal is to learn from the in-domain and apply the learned knowledge to out-of-domain. We propose a co-clustering based classification (CoCC) algorithm to tackle this problem. Co-clustering is used as a bridge to propagate the class structure and knowledge from the in-domain to the out-of-domain. We present theoretical and empirical analysis to show that our algorithm is able to produce high quality classification results, even when the distributions between the two data are different. The experimental results show that our algorithm greatly improves the classification performance over the traditional learning algorithms.
367 citations
TL;DR: An important role for hypoxia/HIF-1α in modulating the amyloidogenic processing of APP is demonstrated and a molecular mechanism for increased incidence of AD following cerebral ischemic and stroke injuries is provided.
366 citations
University Medical Center Groningen1, Harvard University2, World Health Organization3, Leipzig University4, Stony Brook University5, University of Groningen6, Katholieke Universiteit Leuven7, University of Barcelona8, Saint George Hospital9, University of Tokyo10, University of Otago11, Group Health Cooperative12, University of Michigan13, Shanghai Jiao Tong University14
TL;DR: Despite often higher disability, mental disorders are under-treated compared with physical disorders in both high-income and in low- and middle-income countries.
Abstract: Background Advocates of expanded mental health treatment assert that mental disorders are as disabling as physical disorders, but little evidence supports this assertion. Aims To establish the disability and treatment of specific mental and physical disorders in high-income and low- and middle-income countries. Method Community epidemiological surveys were administered in 15 countries through the World Health Organization World Mental Health (WMH) Survey Initiative. Results Respondents in both high-income and low- and middle-income countries attributed higher disability to mental disorders than to the commonly occurring physical disorders included in the surveys. This pattern held for all disorders and also for treated disorders. Disaggregation showed that the higher disability of mental than physical disorders was limited to disability in social and personal role functioning, whereas disability in productive role functioning was generally comparable for mental and physical disorders. Conclusions Despite often higher disability, mental disorders are under-treated compared with physical disorders in both high-income and in low- and middle-income countries.
366 citations
TL;DR: In this paper, the authors examined the energy efficiency performance of a sample of 71 developed and developing countries between 1990 and 2014 and found evidence of a significant positive influence of both green innovation and institutional quality on energy efficiency enhancement having controlled for some variables.
365 citations
University of Michigan1, Cornell University2, University of Pennsylvania3, University of Massachusetts Medical School4, University of Naples Federico II5, Baylor College of Medicine6, Spanish National Research Council7, Complutense University of Madrid8, New York University9, Boston Children's Hospital10, University of Rome Tor Vergata11, NewYork–Presbyterian Hospital12, University of Pittsburgh13, French Institute of Health and Medical Research14, University of Paris15, National University of Cuyo16, Albert Einstein College of Medicine17, University of New Mexico18, Goethe University Frankfurt19, Weizmann Institute of Science20, University of Turku21, Sapienza University of Rome22, Virginia Commonwealth University23, St. Jude Children's Research Hospital24, Discovery Institute25, University of Copenhagen26, University of Tromsø27, Eötvös Loránd University28, Merck & Co.29, University of Freiburg30, Babraham Institute31, University of Adelaide32, University of South Australia33, University of Oviedo34, University of Chicago35, University of Graz36, National Institutes of Health37, City University of New York38, Queens College39, University of Tokyo40, University of Zurich41, Austrian Academy of Sciences42, University of British Columbia43, University of California, San Francisco44, Russian Academy of Sciences45, University Medical Center Groningen46, University of Cambridge47, University of Glasgow48, Rutgers University49, University of Padua50, Kazan Federal University51, University of Bern52, University of Oxford53, University of Oslo54, Oslo University Hospital55, University of Crete56, Foundation for Research & Technology – Hellas57, Francis Crick Institute58, Osaka University59, Chinese Academy of Sciences60, Harvard University61, Icahn School of Medicine at Mount Sinai62, Shanghai Jiao Tong University63, Karolinska Institutet64
TL;DR: In this paper, preclinical data linking autophagy dysfunction to the pathogenesis of major human disorders including cancer as well as cardiovascular, neurodegenerative, metabolic, pulmonary, renal, infectious, musculoskeletal, and ocular disorders.
Abstract: Autophagy is a core molecular pathway for the preservation of cellular and organismal homeostasis. Pharmacological and genetic interventions impairing autophagy responses promote or aggravate disease in a plethora of experimental models. Consistently, mutations in autophagy-related processes cause severe human pathologies. Here, we review and discuss preclinical data linking autophagy dysfunction to the pathogenesis of major human disorders including cancer as well as cardiovascular, neurodegenerative, metabolic, pulmonary, renal, infectious, musculoskeletal, and ocular disorders.
365 citations
Authors
Showing all 158621 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Meir J. Stampfer | 277 | 1414 | 283776 |
| Richard A. Flavell | 231 | 1328 | 205119 |
| Jie Zhang | 178 | 4857 | 221720 |
| Yang Yang | 171 | 2644 | 153049 |
| Lei Jiang | 170 | 2244 | 135205 |
| Gang Chen | 167 | 3372 | 149819 |
| Thomas S. Huang | 146 | 1299 | 101564 |
| Barbara J. Sahakian | 145 | 612 | 69190 |
| Jean-Laurent Casanova | 144 | 842 | 76173 |
| Kuo-Chen Chou | 143 | 487 | 57711 |
| Weihong Tan | 140 | 892 | 67151 |
| Xin Wu | 139 | 1865 | 109083 |
| David Y. Graham | 138 | 1047 | 80886 |
| Bin Liu | 138 | 2181 | 87085 |
| Jun Chen | 136 | 1856 | 77368 |