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Assessment of Kidney Function in Mouse Models of Glomerular Disease
Published on: June 30, 2018
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Local CD34-positive capillaries decrease in mouse models of kidney disease associating with the severity of
Md Abdul Masum1, Osamu Ichii1, Yaser Hosny Ali Elewa1,2
1Laboratory of Anatomy, Graduate School of Veterinary Medicine, Hokkaido University, Kita 18, Nishi 9, Kita-ku, Sapporo, Japan.
BMC Nephrology
|September 6, 2017
Summary
This study reveals that reduced capillary numbers in kidney lesions correlate with disease severity in mouse models. Understanding these changes in renal vasculature is key for diagnosing and treating kidney diseases.
Area of Science:
- Nephrology
- Vascular Biology
- Immunopathology
Background:
- The renal vasculature is crucial for kidney function and disease.
- Pathological changes in kidney microvasculature contribute to disease progression.
Purpose of the Study:
- To investigate pathological alterations in the renal microvasculature.
- To examine changes in capillary density and endothelial integrity in mouse models of kidney disease.
Main Methods:
- Studied glomerular lesions (GLs) in BXSB/MpJ-Yaa mice and tubulointerstitial lesions (TILs) in unilateral ureteral obstruction (UUO) models.
- Utilized histopathology, immunohistochemistry (CD34+ staining), and microscopy (SEM, fluorescence, TEM).
- Employed nonparametric statistical tests (Mann-Whitney U, Kruskal-Wallis) for group comparisons.
Main Results:
- Yaa mice showed autoimmune glomerulonephritis with decreased glomerular capillaries.
- UUO-treated mice exhibited tubulointerstitial lesions with reduced tubulointerstitial capillaries and fibrosis.
- Both models displayed increased immune cell infiltration and capillary endothelial injury.
- Capillary density negatively correlated with lesion severity in both GLs and TILs.
Conclusions:
- A significant inverse correlation exists between capillary number and kidney disease severity.
- These findings highlight the role of microvascular changes in kidney pathology.
- Understanding these correlations can inform therapeutic strategies for kidney diseases.
