Enhancement of paclitaxel transport and cytotoxicity by 7,3’,4’-trimethoxyflavone, a P-glycoprotein inhibitor
Bibliographic record
Abstract
PURPOSE: Paclitaxel has problems with respect to bioavailability and resistance. The aim of this study was to select a P-glycoprotein (Pgp)- inhibitory flavonoid to enhance paclitaxel bioavailability in the Caco-2 cell monolayer. METHODS: Cytotoxicity and chemosensitization were determined using MTT assay. Paclitaxel transport was examined in the Caco-2 cell monolayer, which mimics the intestinal barrier. Paclitaxel concentrations were quantitated by HPLC assay using the internal standard method. RESULTS: Chemosensitizing indeces of 7,3',4'-trimethoxyflavone (TMF) and verapamil was > 333 and 152, respectively. The basolateral (BL)- to-apical (AP) transport of paclitaxel was more than 10-fold greater than its AP-to-BL transport. TMF and verapamil increased the AP-to-BL transport of paclitaxel but decreased its BL-to-AP transport in a concentration-dependent manner. The net absorptive effect of 50 microM TMF on paclitaxel transport was comparable to that of 50 muM verapamil. In addition, AP loading of TMF increased the paclitaxel sensitivity of paclitaxel-resistant SK-MES-1/PT4000 cells overexpressing Pgp on the BL side. CONCLUSIONS: These results indicate that TMF with low toxicity can be used as an enhancer of oral paclitaxel bioavailability and as a Pgp inhibitor.
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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".