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The DOI matches its Crossref record; 84 of the 84 references it cites were found in a registry or an index.

Current advances in ischemic stroke research and therapies

Open access
Barthels, Derek, Das, Hiranmoy·2020·Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease

Abstract

With more than 795,000 cases occurring every year, stroke has become a major problem in the United States across all demographics. Stroke is the leading cause of long-term disability and is the fifth leading cause of death in the US. Ischemic stroke represents 87% of total strokes in the US, and is currently the main focus of stroke research. This literature review examines the risk factors associated with ischemic stroke, changes in cell morphology and signaling in the brain after stroke, and the advantages and disadvantages of in vivo and in vitro ischemic stroke models. Classification systems for stroke etiology are also discussed briefly, as well as current ischemic stroke therapies and new therapeutic strategies that focus on the potential of stem cells to promote stroke recovery.

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Crossref · 10.1016/j.bbadis.2018.09.012

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Metadata

Authors
Barthels, D., & Das, H.
Venue
Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease
Publisher
Elsevier BV
Published
2020-04
Volume
1866
Issue
4
Pages
165260
ISSN
0925-4439 (ISSN-L)
OpenAlex
W2891793399
Cited by
709
References
84
FWCI
14.49
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Current advances in ischemic stroke research and therapies. https://app.cochat.ai/papers/10.1016/j.bbadis.2018.09.012
The paper
Barthels, D., & Das, H. (2020). Current advances in ischemic stroke research and therapies. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. https://doi.org/10.1016/j.bbadis.2018.09.012

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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.