Oroxylin A improves the sensitivity of HT-29 human colon cancer cells to 5-FU through modulation of the COX-2 signaling pathway
Bibliographic record
Abstract
5-Fluorouracil (5-FU) is a principal drug for the treatment of colorectal cancer. Due to its low response and high toxicity, synergistic effects of 5-FU in combination with other drugs have been widely researched. This study investigated whether oroxylin A improved the sensitivity of HT-29 human colon cancer cells to 5-FU. A correlation between COX-2 inhibition by oroxylin A and a synergistic effect of 5-FU on the growth of HT-29 cells was observed, and a COX-2 pathway for this effect was recognized; oroxylin A evidently elevated the level of reactive oxygen species in HT-29 cells, which subsequently inhibited COX-2 expression and enhanced the susceptibility of HT-29 cells to 5-FU. Likely also related to COX-2 inhibition, oroxylin A decreased PGE(2) levels in HT-29 cells. The synergistic effect of 5-FU induced by oroxylin A was also found in the suppression of Bcl-2 and in the activation of P53, Bax, PARP, and procaspase-3 proteins in HT-29 cells. Ultimately, a combination of 5-FU with oroxylin A significantly reduced the growth of HT-29 tumors in nude mice compared with treatment with 5-FU or oroxylin A alone. In conclusion, a combination of 5-FU and oroxylin A has a significant synergistic effect in the inhibition of HT-29 cell proliferation in vitro and controls HT-29 tumor growth in vivo. This synergistic effect may be mainly related to COX-2 inhibition by oroxylin A in HT-29 cells.
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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".