ANTIOXIDANTS INCREASE LIPOPOLYSACCHARIDE-STIMULATED TNFα RELEASE IN MURINE MACROPHAGES: ROLE FOR ALTERED TNFα mRNA STABILITY
Bibliographic record
Abstract
Through their effects on gene activation, antioxidants have been reported to modulate cellular expression of several proinflammatory cytokines and adhesion molecules, an effect mediated by preventing translocation of the transcription factor nuclear factor-kappa B (NF-kappa B) into the nucleus. In addition, modulation of the intracellular redox state may have profound effects on cell activation and subsequent gene expression distinct from effects on NF-kappa B; these effects may account for the divergent effects of antioxidants on cytokine gene expression in various reports. In the present studies, we evaluated the effect of the antioxidant, pyrrolidine dithiocarbamate (PDTC), on murine and human myeloid cell tumor necrosis factor alpha (TNF alpha) gene and protein expression. PDTC-enhanced LPS-induced TNF alpha secretion in cells derived from a murine macrophage cell line (J774.1), as well as in primary murine peritoneal macrophages by 4-fold. The effect was both stimulus and species dependent, as TNF alpha secretion was attenuated by PDTC in human THP-1 cells and in murine cells stimulated with zymosan. Northern analysis demonstrated that these effects were evident at the level of mRNA expression. Electrophoretic mobility shift assays confirmed the down-regulatory effect of PDTC on human myeloid NF-kappa B activation, whereas in murine cells no such inhibitory effect was evident. Evaluation of TNF alpha mRNA stability in murine cells demonstrated that the potentiating effect of PDTC on TNF alpha mRNA expression was due to an increase in mRNA half-life from 37 to 93 min. Together, these data suggest that the effect of antioxidants on gene expression are both stimulus and species dependent and illustrate a novel mechanism whereby redox manipulation might modulate TNF alpha expression in vivo.
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) | 0.001 | 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) | 0.001 | 0.001 |
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".