Cyanidin-3-O-glucoside attenuates high glucose–induced podocyte dysfunction by inhibiting apoptosis and promoting autophagy via activation of SIRT1/AMPK pathway
Bibliographic record
Abstract
Diabetic nephropathy (DN) is a common and complicated chronic kidney disease around the world. To elucidate and find effective therapies of DN is of vital importance. In this paper, we have discovered that cyanidin-3-O-glucoside (C3G), which is one of the anthocyanins, could alleviate high glucose–induced podocyte dysfunction. MTT, flow cytometry assay, and Western blot analysis showed that C3G could reverse the increase of cell apoptosis under high glucose treatment in MPC5 cells by upregulation of Bcl2 and downregulation of Bax and cleaved caspase-3. Moreover, C3G improved the autophagy decrease that was induced by high glucose through regulating the expression level of LC3-II/LC3-I, Beclin1, and p62. In addition, C3G inhibited epithelial-mesenchymal transition (EMT) by increasing E-cadherin and reducing Vimentin. By further study of the mechanisms, we found C3G activated the SIRT1 and AMPK which were inhibited in high glucose condition. Silencing SIRT1 blocked the effect of C3G on regulating cell apoptosis, autophagy, and EMT. In summary, our current findings suggest the protective effect of C3G against high glucose–induced podocyte dysfunction is by improving autophagy and reducing apoptosis and EMT via activating SIRT1/AMPK pathway. It might be a new insight for the treatment of DN.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".