The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Animal models as tools to study the pathophysiology of depression
Open accessAbstract
The incidence of depressive illness is high worldwide, and the inadequacy of currently available drug treatments contributes to the significant health burden associated with depression. A basic understanding of the underlying disease processes in depression is lacking; therefore, recreating the disease in animal models is not possible. Popular current models of depression creatively merge ethologically valid behavioral assays with the latest technological advances in molecular biology. Within this context, this study aims to evaluate animal models of depression and determine which has the best face, construct, and predictive validity. These models differ in the degree to which they produce features that resemble a depressive-like state, and models that include stress exposure are widely used. Paradigms that employ acute or sub-chronic stress exposure include learned helplessness, the forced swimming test, the tail suspension test, maternal deprivation, chronic mild stress, and sleep deprivation, to name but a few, all of which employ relatively short-term exposure to inescapable or uncontrollable stress and can reliably detect antidepressant drug response.
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Cites
Depression: a new animal model sensitive to antidepressant treatments
PORSOLT, R. D., LE PICHON, M., & JALFRE, M. (1977) · Nature · doi:10.1038/266730a0 · Cited by 4,451
The molecular neurobiology of depression
Krishnan, V., & Nestler, E. J. (2008) · Nature · doi:10.1038/nature07455 · Cited by 2,889
Animal models of neuropsychiatric disorders
Nestler, E. J., & Hyman, S. E. (2010) · Nature Neuroscience · doi:10.1038/nn.2647 · Cited by 2,023
Willner, P. (1997) · Psychopharmacology · doi:10.1007/s002130050456 · Cited by 1,832
Long story short: the serotonin transporter in emotion regulation and social cognition
Canli, T., & Lesch, K.-P. (2007) · Nature Neuroscience · doi:10.1038/nn1964 · Cited by 1,034
Katz, R. J., Roth, K. A., & Carroll, B. J. (1981) · Neuroscience & Biobehavioral Reviews · doi:10.1016/0149-7634(81)90005-1 · Cited by 889
Takamori, S., Rhee, J. S., Rosenmund, C., & Jahn, R. (2000) · Nature · doi:10.1038/35025070 · Cited by 862
Malberg, J. E., & Duman, R. S. (2003) · Neuropsychopharmacology · doi:10.1038/sj.npp.1300234 · Cited by 815
Glutamate and GABA systems as targets for novel antidepressant and mood-stabilizing treatments
Krystal, J. H., Sanacora, G., Blumberg, H., Anand, A., Charney, D. S., Marek, G., Epperson, C. N., Goddard, A., & Mason, G. F. (2002) · Molecular Psychiatry · doi:10.1038/sj.mp.4001021 · Cited by 553
Targeting the murine serotonin transporter: insights into human neurobiology
Murphy, D. L., & Lesch, K.-P. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2284 · Cited by 478
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Liang, S., Wang, T., Hu, X., Luo, J., Li, W., Wu, X., Duan, Y., & Jin, F. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.09.033 · Cited by 651
The role of inflammation and microglial activation in the pathophysiology of psychiatric disorders
Réus, G. Z., Fries, G. R., Stertz, L., Badawy, M., Passos, I. C., Barichello, T., Kapczinski, F., & Quevedo, J. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.05.018 · Cited by 594
Self-citationPhillips, C. (2017) · Neural Plasticity · doi:10.1155/2017/7260130 · Cited by 450
The microbiota–gut–brain axis in gastrointestinal disorders: stressed bugs, stressed brain or both?
De Palma, G., Collins, S. M., Bercik, P., & Verdu, E. F. (2014) · The Journal of Physiology · doi:10.1113/jphysiol.2014.273995 · Cited by 293
Aleksandrova, L. R., Phillips, A. G., & Wang, Y. T. (2017) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.160175 · Cited by 228
Metadata
- Authors
- Abelaira, H. M., Reus, G. Z., & Quevedo, J.
- Venue
- Revista Brasileira de Psiquiatria
- Publisher
- EDITORA SCIENTIFIC
- Published
- 2013
- Volume
- 35
- Issue
- suppl 2
- Pages
- S112-S120
- ISSN
- 1516-4446 (ISSN-L)
- OpenAlex
- W2010509095
- Cited by
- 236
- References
- 20
- FWCI
- 4.63
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Abelaira, H. M., Reus, G. Z., & Quevedo, J. (2013). Animal models as tools to study the pathophysiology of depression. Revista Brasileira de Psiquiatria. https://doi.org/10.1590/1516-4446-2013-1098
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
