Toc isomers modulation of inflammatory response in fhs 74 int fetal‐derived human intestinal cell line
Bibliographic record
Abstract
The effect of α‐Tocopherol (Toc), γ‐Toc and δ‐Toc in modulating inflammatory response of fetal‐derived intestinal cell line (FHs 74 Int) were determined. Toc isomer‐dependently promoted interleukin (IL) 8 expression from FHs 74 Int cells, with δ‐Toc eliciting greatest pro‐inflammatory effect, followed by γ‐Toc and α‐Toc. The IL8 promoting activity was associated with non‐α‐Toc isomers ability to promote NfκB and Nrf‐2 activation as evidenced by the increased nuclear translocation of the transcription factors. Nevertheless, non‐α‐Toc isomers, particularly δ‐Toc, were found to down‐regulate the glutamate cysteine ligase (GCLC) gene expression, an Nrf‐2 target gene that is also the first and rate limiting enzyme involved in glutathione biosynthesis. The possibility that non‐α‐Toc isomers plays role in down‐regulating glutathione biosynthesis was evidenced by the finding that δ‐Toc and to a lesser extent γ‐Toc not only down‐regulated GCLC protein expression but also the total glutathione content of FHs 74 Int cells. Taken together, it is suggested that the down‐regulation of glutathione biosynthesis compromised the cellular defense system that leads to the pro‐inflammatory effect observed for the non‐α‐Toc isomers. Grant Funding Source : Food Nutrition and Health Vitamin Research Fund
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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) | 0.002 | 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".