Cytoprotective effects of Avenathramide C against oxidative and inflammatory stress in normal human dermal fibroblasts
Bibliographic record
Abstract
Abstract Natural polyphenols are promising anti-aging compounds not only for their antioxidant activity, but also their ability to activate specific cellular pathways mediating the aging process. Avenanthramide C (Avn C), found exclusively in oats, is a natural antioxidant associated with free radical scavenging; however, it is how this compound elicits other protective effects. We investigated the intracellular antioxidant activity of Avn C and other cytoprotective potential in normal human skin fibroblasts exposed to extracellular stress. Avn C reduced H2O2-induced oxidative stress by reducing intracellular free radical levels and antioxidant gene transcripts. Avn C also resulted in decreased levels of gene transcripts encoding pro-inflammatory cytokines in response to H2O2 or tumor necrosis factor-α (TNF-α). This reduction in cytokine gene transcription occurred concomitantly with reduced phosphorylated nuclear factor-κB (NF-κB) p65, and decreased NF-κB DNA binding. Avn C further induced heme oxygense-1 (HO-1) expression through increased Nrf2 DNA binding activity, demonstrating a second mechanism by which Avn C attenuates cellular stress. Collectively, our findings indicate that Avn C protects normal human skin fibroblasts against oxidative stress and inflammatory response through NF-κB inhibition and Nrf2/HO-1 activation.
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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 | 0.000 |
| 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) | 0.001 | 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".