Resveratrol upregulates miR-455-5p to antagonize cisplatin ototoxicity via modulating the PTEN–PI3K–AKT axis
Bibliographic record
Abstract
Resveratrol is a non-flavonoid polyphenol compound that exists in many plants, and is considered an antitoxin. This study explores the effects from the regulation of miR-455-5p by resveratrol on cisplatin-induced ototoxicity via the PTEN-PI3K-AKT signaling pathway. For this, House Ear Institute-Organ of Corti 1 (HEI-OC1) cells were transfected with miR-455-5p inhibitor and treated with cisplatin and resveratrol, then cell proliferation, apoptosis, and oxidative stress were evaluated. A mouse model of hearing loss was established, and these mice were treated with cisplatin, resveratrol, or cisplatin combined with resveratrol, by intraperitoneal injection. The auditory brainstem response (ABR) threshold was measured, and hair cells were examined using immunofluorescence staining. The expression levels of miR-455-5p, PTEN, and PI3K/Akt proteins were examined. The results from our in-vitro experiments indicate that resveratrol promoted viability and reduced apoptosis and oxidative stress in cisplatin-induced HEI-OC1 cells. Resveratrol upregulated miR-455-5p, downregulated PTEN, and activated the PI3K-Akt axis. These effects of resveratrol were reversed by knock-down of miR-455-5p. The results from our in-vivo experiments indicate that resveratrol protected hearing and inhibited the hair-cell injury caused by cisplatin ototoxicity. Resveratrol also upregulated miR-455-5p, downregulated PTEN, and activated the PTEN-PI3K-Akt axis in cochlear tissues from cisplatin-treated mice. These results indicate that resveratrol upregulates miR-455-5p to target PTEN and activate the PI3K-Akt signaling pathway to counteract cisplatin ototoxicity.
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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 | 0.001 |
| 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".