Protective effect of grape seed extracts on human lymphocytes: a preliminary study
Bibliographic record
Abstract
Grape seed extracts (GSEs) possess a broad spectrum of antioxidative properties that protects various cells from free radicals and oxidative stress. In this study, the genoprotective effect of GSE on human lymphocytic DNA was studied using standard and lysed cell comet assays. Lymphocytes from 5 healthy subjects were pretreated with GSE in different concentrations. The standard and lysed cell comet assays were performed on treated, untreated, challenged, and unchallenged cells in parallel. Cells were then subjected to an oxidant challenge induced with 5-min exposures to hydrogen peroxide. In the standard comet assay, GSE significantly diminished hydrogen-peroxide-induced DNA damage in a dose-dependent manner. In the lysed cell assay, however, the antioxidant effect was diminished at a higher GSE concentration. Data indicate that the cell membrane might play a role in limiting cellular access to antioxidants, which directly affects the genoprotective or potential pro-oxidant effect of antioxidants on human DNA. Using both standard and lysed cell comet assays in parallel could be a useful way to elucidate the mechanism of protection or damage by antioxidants.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".