Title |
Models for preclinical studies in aging-related disorders: One is not for all.
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Published in |
Translational Medicine @ UniSa, January 2016
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Pubmed ID | |
Authors |
Gaetano Santulli, Consuelo Borras, Jean Bousquet, Laura Calzà, Antonio Cano, Maddalena Illario, Claudio Franceschi, Giuseppe Liotta, Marcello Maggio, William D Molloy, Nunzia Montuori, Rónán O'Caoimh, Francesc Orfila, Amelia P Rauter, Aurelia Santoro, Guido Iaccarino |
Abstract |
Preclinical studies are essentially based on animal models of a particular disease. The primary purpose of preclinical efficacy studies is to support generalization of treatment-effect relationships to human subjects. Researchers aim to demonstrate a causal relationship between an investigational agent and a disease-related phenotype in such models. Numerous factors can muddle reliable inferences about such cause-effect relationships, including biased outcome assessment due to experimenter expectations. For instance, responses in a particular inbred mouse might be specific to the strain, limiting generalizability. Selecting well-justified and widely acknowledged model systems represents the best start in designing preclinical studies, especially to overcome any potential bias related to the model itself. This is particularly true in the research that focuses on aging, which carries unique challenges, mainly attributable to the fact that our already long lifespan makes designing experiments that use people as subjects extremely difficult and largely impractical. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Spain | 3 | 50% |
Venezuela, Bolivarian Republic of | 1 | 17% |
United States | 1 | 17% |
Unknown | 1 | 17% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 5 | 83% |
Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 51 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 12 | 24% |
Researcher | 10 | 20% |
Student > Bachelor | 5 | 10% |
Student > Ph. D. Student | 5 | 10% |
Student > Postgraduate | 4 | 8% |
Other | 6 | 12% |
Unknown | 9 | 18% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 8 | 16% |
Medicine and Dentistry | 7 | 14% |
Agricultural and Biological Sciences | 6 | 12% |
Neuroscience | 4 | 8% |
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 6% |
Other | 12 | 24% |
Unknown | 11 | 22% |