Protective effects of polyphenolic compounds on oxidative stress‐induced cytotoxicity in PC12 cells
Bibliographic record
Abstract
Elevated reactive oxygen species (ROS) have been implicated in the pathogenesis of many diseases, including atherosclerosis and Parkinson's. Foods rich in polyphenols such as fruits, wines and teas have proven to decrease oxidative stress. Further, antioxidant properties of polyphenols increase cell viability under oxidative stress conditions and increase overall health. In the current study 12 polyphenols were screened for their ability to increase viability in PC12 cells subject to oxidative stress induced via cobalt chloride (CoCl 2 ) and hydrogen peroxide (H 2 O 2 ). Results from MTT assays show that pre‐treatment with 50µM methyl gallate increases cell viability by 26.6% (P<0.01) under H 2 O 2 stress and does not increase viability under CoCl 2 stress. Pre‐treatment with 100µM epigallocatechin gallate (EGCG) shows a 63.4% (P<0.01) increase in viability compared to control, however shows no viability increase in stress conditions. Treatments with 50µM myricetin and gallic acid show no effect on basal viability and decrease viability when delivered as a pre‐treatment prior to H 2 O 2 exposure. Remaining polyphenols did not alter basal viability or increase viability under stress. Lastly, DCFDA determination of intracellular ROS confirms the ability of screened polyphenols to significantly reduce ROS levels. These results suggest that methyl gallate and EGCG may have potential therapeutic properties.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".