Chlorogenic Acid and Its Microbial Metabolites Exert Anti-Proliferative Effects, S-Phase Cell-Cycle Arrest and Apoptosis in Human Colon Cancer Caco-2 Cells
Bibliographic record
Abstract
Chlorogenic acid (CGA) decreases colon cancer-cell proliferation but the combined anti-cancer effects of CGA with its major colonic microbial metabolites, caffeic acid (CA), 3-phenylpropionic acid (3-PPA) and benzoic acid (BA), needs elucidation as they occur together in colonic digesta. Caco-2 cancer cells were treated for 24 h with the four compounds individually (50–1000 µM) and as an equimolar ratio (1:1:1:1; MIX). The effective concentration to decrease cell proliferation by 50% (EC50) was lower for MIX (431 ± 51.84 µM) and CA (460 ± 21.88) versus CGA (758 ± 19.09 µM). The EC50 for cytotoxicity measured by lactate dehydrogenase release in MIX (527 ± 75.34 µM) showed more potency than CA (740 ± 38.68 µM). Cell proliferation was decreased by 3-PPA and BA at 1000 µM with no cytotoxicity. Cell-cycle arrest was induced at the S-phase by CA (100 µM), MIX (100 µM), CGA (250 µM) and 3-PPA (500 µM) with activation of caspase-3 by CGA, CA, MIX (500 and 1000 µM). Mitochondrial DNA content was reduced by 3-PPA (1000 µM). The anti-cancer effects occurred at markedly lower concentrations of each compound within MIX than when provided singly, indicating that they function together to enhance anti-colon cancer activities.
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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".