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Cited by 523

The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.

Atherosclerosis: Known and unknown

Fan, Jianglin, Watanabe, Teruo·2022·Pathology International

Abstract

Atherosclerotic disease, such as myocardial infarction and stroke, is the number one killer worldwide. Atherosclerosis is considered to be caused by multiple factors, including genetic and environmental factors. In humans, it takes several decades until the clinical complications develop. There are many known risk factors for atherosclerosis, including hypercholesterolemia, hypertension, diabetes and smoking, which are involved in the pathogenesis of atherosclerosis; however, it is generally believed that atherosclerosis is vascular chronic inflammation initiated by interactions of these risk factors and arterial wall cells. In the past 30 years, the molecular mechanisms underlying the pathogenesis of atherosclerosis have been investigated extensively using genetically modified animals, and lipid‐reducing drugs, such as statins, have been demonstrated as the most effective for the prevention and treatment of atherosclerosis. However, despite this progress, questions regarding the pathogenesis of atherosclerosis remain and there is a need to develop new animal models and novel therapeutics to treat patients who cannot be effectively treated by statins. In this review, we will focus on two topics of atherosclerosis, “pathology” and “pathogenesis,” and discuss unanswered questions.

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Metadata

Authors
Fan, J., & Watanabe, T.
Venue
Pathology International
Publisher
Wiley
Published
2022-01-25
Volume
72
Issue
3
Pages
151-160
ISSN
  • 1320-5463 (ISSN-L)
  • 1440-1827
OpenAlex
W4206955857
Cited by
523
References
63
FWCI
30.81
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Atherosclerosis: Known and unknown. https://app.cochat.ai/papers/10.1111/pin.13202
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Fan, J., & Watanabe, T. (2022). Atherosclerosis: Known and unknown. Pathology International. https://doi.org/10.1111/pin.13202

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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.