Vitamin C Inhibits NF-κB Activation by TNF Via the Activation of p38 Mitogen-Activated Protein Kinase
Bibliographic record
Abstract
The transcription factor NF-kappaB is a central mediator of altered gene expression during inflammation, and is implicated in a number of pathologies, including cancer, atherosclerosis, and viral infection. We report in this study that vitamin C inhibits the activation of NF-kappaB by multiple stimuli, including IL-1 and TNF in the endothelial cell line ECV304 and in primary HUVECs. The induction of a NF-kappaB-dependent gene, IL-8, by TNF was also inhibited. The effect requires millimolar concentrations of vitamin C, which occur intracellularly in vivo, particularly during inflammation. Vitamin C was not toxic to cells, did not inhibit another inducible transcription factor, STAT1, and had no effect on the DNA binding of NF-kappaB. Inhibition by vitamin C was not simply an antioxidant effect, because redox-insensitive pathways to NF-kappaB were also blocked. Vitamin C was shown to block IL-1- and TNF-mediated degradation and phosphorylation of I-kappaBalpha (inhibitory protein that dissociates from NF-kappaB), due to inhibition of I-kappaB kinase (IKK) activation. Inhibition of TNF-driven IKK activation was mediated by p38 mitogen-activated protein kinase, because treatment of cells with vitamin C led to a rapid and sustained activation of p38, and the specific p38 inhibitor SB203580 reversed the inhibitory effect of vitamin C on IKK activity, I-kappaBalpha phosphorylation, and NF-kappaB activation. The results identify p38 as an intracellular target for high dose vitamin C.
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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".