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Cited by 227

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

In Vitro Models of Traumatic Brain Injury

Morrison, Barclay, Elkin, Benjamin S., Dollé, Jean-Pierre, Yarmush, Martin L.·2011·Annual Review of Biomedical Engineering

Abstract

In vitro models of traumatic brain injury (TBI) are helping elucidate the pathobiological mechanisms responsible for dysfunction and delayed cell death after mechanical stimulation of the brain. Researchers have identified compounds that have the potential to break the chain of molecular events set in motion by traumatic injury. Ultimately, the utility of in vitro models in identifying novel therapeutics will be determined by how closely the in vitro cascades recapitulate the sequence of cellular events that play out in vivo after TBI. Herein, the major in vitro models are reviewed, and a discussion of the physical injury mechanisms and culture preparations is employed. A comparison between the efficacy of compounds tested in vitro and in vivo is presented as a critical evaluation of the fidelity of in vitro models to the complex pathobiology that is TBI. We conclude that in vitro models were greater than 88% predictive of in vivo results.

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Crossref · 10.1146/annurev-bioeng-071910-124706

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Metadata

Authors
Morrison, B., Elkin, B. S., Dollé, J.-P., & Yarmush, M. L.
Venue
Annual Review of Biomedical Engineering
Published
2011-08-15
Volume
13
Issue
1
Pages
91-126
ISSN
  • 1523-9829 (ISSN-L)
  • 1545-4274
OpenAlex
W2132907436
Cited by
227
References
13
FWCI
1.27
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: In Vitro Models of Traumatic Brain Injury. https://app.cochat.ai/papers/10.1146/annurev-bioeng-071910-124706
The paper
Morrison, B., Elkin, B. S., Dollé, J.-P., & Yarmush, M. L. (2011). In Vitro Models of Traumatic Brain Injury. Annual Review of Biomedical Engineering. https://doi.org/10.1146/annurev-bioeng-071910-124706

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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.