Lycopene Modulates THP1 and Caco2 Cells Inflammatory State through Transcriptional and Nontranscriptional Processes
Bibliographic record
Abstract
We revisited the action of a carotenoid, the lycopene, on the expression of proinflammatory genes, reactive oxygen species (ROS) production, and metalloprotease (MMP9) activity. THP1 and Caco2 cell lines were used as in vitro models for the two main cell types found in intestine tissue, that is, monocytes and epithelial cells. Proinflammatory condition was induced using either phorbol ester acetate (PMA), lipopolysaccharide (LPS) or tumor necrosis factor (TNF). In THP1 cells, short term pretreatment (2 h) with a low concentration (2 μM) of lycopene reinforce proinflammatory gene expression. The extent of the effect of lycopene is dependent on the proinflammtory stimulus (PMA, LPS or TNF) used. Lycopene enhanced MMP9 secretion via a c-AMP-dependent process, and reduced ROS production at higher concentrations than 2 μM. Cell culture media, conditioned by PMA-treated monocytes and then transferred on CaCo-2 epithelial cells, induced a proinflammatory state in these cells. The extent of this inflammatory effect was reduced when cells has been pretreated (12 h) with lycopene. At low concentration (2 μM or less), lycopene appeared to promote an inflammatory state not correlated with ROS modulation. At higher concentration (5 μM-20 μM), an anti-inflammatory effect takes place as a decrease of ROS production was detected. So, both concentration and time have to be considered in order to define the exact issue of the effect of carotenoids present in meals.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".