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The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.

Non-Transgenic Mouse Models of Kidney Disease

Open access
Rabe, Michael, Schaefer, Franz·2016·Nephron

Abstract

Animal models are essential tools to understand the mechanisms underlying the development and progression of renal disease and to study potential therapeutic approaches. Recently, interventional models suitable to induce acute and chronic kidney disease in the mouse have become a focus of interest due to the wide availability of genetically engineered mouse lines. These models differ by their damaging mechanism (cell toxicity, immune mechanisms, surgical renal mass reduction, ischemia, hypertension, ureter obstruction etc.), functional and histomorphological phenotype and disease evolution. The susceptibility to a damaging mechanism often depends on strain and gender. The C57BL/6 strain, the most commonly used genetic background of transgenic mice, appears to be relatively resistant against developing glomerulosclerosis, proteinuria and hypertension. This review serves to provide a comprehensive overview of interventional mouse models of acute and chronic kidney disease.

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Crossref · 10.1159/000445171

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Metadata

Authors
Rabe, M., & Schaefer, F.
Venue
Nephron
Publisher
S. Karger AG
Published
2016
Volume
133
Issue
1
Pages
53-61
ISSN
  • 1660-8151 (ISSN-L)
  • 2235-3186
OpenAlex
W2405183840
Cited by
1,922
References
38
FWCI
172.96
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Non-Transgenic Mouse Models of Kidney Disease. https://app.cochat.ai/papers/10.1159/000445171
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Rabe, M., & Schaefer, F. (2016). Non-Transgenic Mouse Models of Kidney Disease. Nephron. https://doi.org/10.1159/000445171

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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.