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Cited by 521

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Diabetic kidney disease in the db/db mouse

Sharma, Kumar, McCue, Peter, Dunn, Stephen R.·2003·American Journal of Physiology-Renal Physiology

Abstract

Diabetic nephropathy is increasing in incidence and is now the number one cause of end-stage renal disease in the industrialized world. To gain insight into the genetic susceptibility and pathophysiology of diabetic nephropathy, an appropriate mouse model of diabetic nephropathy would be critical. A large number of mouse models of diabetes have been identified and their kidney disease characterized to various degrees. Perhaps the best characterized and most intensively investigated model is the db/ db mouse. Because this model appears to exhibit the most consistent and robust increase in albuminuria and mesangial matrix expansion, it has been used as a model of progressive diabetic renal disease. In this review, we present the findings from various studies on the renal pathology of the db/ db mouse model of diabetes in the context of human diabetic nephropathy. Furthermore, we discuss shortfalls of assessing functional renal disease in mouse models of diabetic kidney disease.

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Crossref · 10.1152/ajprenal.00315.2002

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Metadata

Authors
Sharma, K., McCue, P., & Dunn, S. R.
Venue
American Journal of Physiology-Renal Physiology
Published
2003-06-01
Volume
284
Issue
6
Pages
F1138-F1144
ISSN
  • 1522-1466 (ISSN-L)
  • 1931-857X
OpenAlex
W2113664327
Cited by
521
References
2
FWCI
12.49
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Diabetic kidney disease in the db/db mouse. https://app.cochat.ai/papers/10.1152/ajprenal.00315.2002
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Sharma, K., McCue, P., & Dunn, S. R. (2003). Diabetic kidney disease in the db/db mouse. American Journal of Physiology-Renal Physiology. https://doi.org/10.1152/ajprenal.00315.2002

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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.