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Valproic acid restores the down-regulation of SDF-1 following kidney ischemia; experimental validation of a mathematical prediction
BACKGROUND AND PURPOSE: Stromal-derived factor (SDF)-1, a chemokine recruiting leucocytes and stem cells, plays an essential role in tissue regeneration. In a previous study, we have unexpectedly found that the expression of this chemokine declines following kidney ischemia reperfusion (IR). To expl...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7306248/ https://www.ncbi.nlm.nih.gov/pubmed/32582359 http://dx.doi.org/10.4103/1735-5362.283819 |
Sumario: | BACKGROUND AND PURPOSE: Stromal-derived factor (SDF)-1, a chemokine recruiting leucocytes and stem cells, plays an essential role in tissue regeneration. In a previous study, we have unexpectedly found that the expression of this chemokine declines following kidney ischemia reperfusion (IR). To explain this observation, a mathematical model was constructed which proposed histone deacetylase (HDAC) as the main driver of SDF-1 down-regulation. To experimentally verify this prediction, the effect of valproic acid (VPA), a potent HDAC inhibitor, on the kinetics of kidney SDF-1 expression was here assessed. EXPERIMENTAL APPROACH: Adult mice were subjected to IR or sham operation and received VPA or vehicle. Next, SDF-1 expression as well as tissue repair indices were measured in a time course manner. FINDINGS / RESULTS: The transcriptional expressions of Sdf-1 alpha, beta, and gamma isoforms were noisy in the sham groups but the fluctuations disappeared following IR where a continuous declining trend was observed. VPA induced the over-expression of gamma, but not alpha and beta mRNA in IR mice which was accompanied with protein upregulation. Remarkably, VPA deteriorated kidney injury. CONCLUSION AND IMPLICATIONS: HDAC inhibition restores SDF-1 down-regulation following kidney IR. The present study is a classic example of the potential of computational modeling for the prediction of biomedical phenomena. |
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