| Title |
Effect of echinacoside on kidney fibrosis by inhibition of TGF-β1/Smads signaling pathway in the db/db mice model of diabetic nephropathy
|
|---|---|
| Published in |
Drug Design, Development and Therapy, September 2017
|
| DOI | 10.2147/dddt.s143805 |
| Pubmed ID | |
| Authors |
Fengjuan Tang, Yarong Hao, Xue Zhang, Jian Qin |
| Abstract |
Kidney fibrosis and renal tubular epithelial-to-mesenchymal transition (EMT) are the main pathological changes of diabetic nephropathy (DN), which eventually leads to end-stage renal disease. Previous studies have suggested that echinacoside (ECH) is antifibrotic in the liver. However, the effect of ECH on kidney fibrosis in DN and its mechanisms are unknown. This study was performed to explore the effect of ECH on kidney fibrosis and also the molecular mechanisms of ECH in a db/db mice model of DN. Our results showed that, relative to db/db mice, the mice in the ECH group had an improved general state and reduced blood glucose and 24-hour urinary protein levels. The deterioration of renal function was delayed due to treatment with ECH. We also observed that ECH can improve histopathological findings in the kidneys of db/db mice, including collagen deposition, mesangial cell and mesangial matrix hyperplasia, basement membrane thickening, and podocyte reduction. Moreover, ECH inhibited the TGF-β1/Smads signaling pathway, downregulated fibronectin (FN), collagen IV, and alpha-smooth muscle actin (α-SMA) levels, and upregulated E-cadherin level in the db/db mice model of DN. Our findings indicate that ECH has a therapeutic effect on DN, including the inhibition of renal tubular EMT and kidney fibrosis. Furthermore, ECH inhibits kidney fibrosis through regulation of the TGF-β1/Smads signaling pathway. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 2 | 20% |
| Student > Ph. D. Student | 1 | 10% |
| Student > Bachelor | 1 | 10% |
| Researcher | 1 | 10% |
| Student > Postgraduate | 1 | 10% |
| Other | 0 | 0% |
| Unknown | 4 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 20% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 10% |
| Agricultural and Biological Sciences | 1 | 10% |
| Biochemistry, Genetics and Molecular Biology | 1 | 10% |
| Computer Science | 1 | 10% |
| Other | 1 | 10% |
| Unknown | 3 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 December 2023.
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#20,663,600
of 25,382,440 outputs
Outputs from Drug Design, Development and Therapy
#1,436
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#251,382
of 324,453 outputs
Outputs of similar age from Drug Design, Development and Therapy
#39
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