The DOI matches its Crossref record; 283 of the 283 references it cites were found in a registry or an index.
Modeling the Positive Symptoms of Schizophrenia in Genetically Modified Mice: Pharmacology and Methodology Aspects
Open accessAbstract
In recent years, there have been huge advances in the use of genetically modified mice to study pathophysiological mechanisms involved in schizophrenia. This has allowed rapid progress in our understanding of the role of several proposed gene mechanisms in schizophrenia, and yet this research has also revealed how much still remains unresolved. Behavioral studies in genetically modified mice are reviewed with special emphasis on modeling psychotic-like behavior. I will particularly focus on observations on locomotor hyperactivity and disruptions of prepulse inhibition (PPI). Recommendations are included to address pharmacological and methodological aspects in future studies. Mouse models of dopaminergic and glutamatergic dysfunction are then discussed, reflecting the most important and widely studied neurotransmitter systems in schizophrenia. Subsequently, psychosis-like behavior in mice with modifications in the most widely studied schizophrenia susceptibility genes is reviewed. Taken together, the available studies reveal a wealth of available data which have already provided crucial new insight and mechanistic clues which could lead to new treatments or even prevention strategies for schizophrenia.
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Cites
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Cited by
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Metadata
- Authors
- van den Buuse, M.
- Venue
- Schizophrenia Bulletin
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-11-09
- Volume
- 36
- Issue
- 2
- Pages
- 246-270
- ISSN
- 0586-7614 (ISSN-L)
- 1745-1701
- OpenAlex
- W2168351657
- Cited by
- 346
- References
- 283
- FWCI
- 11.26
- Type
- journal article
- Language
- en
- Open access
- bronze
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- van den Buuse, M. (2010). Modeling the Positive Symptoms of Schizophrenia in Genetically Modified Mice: Pharmacology and Methodology Aspects. Schizophrenia Bulletin. https://doi.org/10.1093/schbul/sbp132
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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