Reversal of P-glycoprotein-medicated multidrug resistance by LBM-A5 in vitro and a study of its pharmacokinetics in vivo
Bibliographic record
Abstract
The overexpression of P-glycoprotein (P-gp) in tumors leads to multidrug resistance (MDR), which is a significant obstacle in clinical cancer chemotherapy. The co-administration of anticancer drugs and MDR modulators is a promising strategy for overcoming this problem. Our study aimed to explore the reversal mechanism and safety of the MDR modulator LBM-A5 in vitro, and evaluate its pharmacokinetics and effects on doxorubicin metabolism in vivo. We evaluated an MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay of anticancer agents mediated by LBM-A5, the effect of LBM-A5 on rhodamine123 intracellular accumulation, and the efflux in K562/DOX cells to investigate the reversal mechanisms of LBM-A5. The results showed that LBM-A5 inhibits rhodamine123 efflux and increases intracellular accumulation by inhibiting the efflux pump function of P-gp. Furthermore, the therapeutic index and CYP3A4 activity analysis in vitro suggested that LBM-A5 is reasonably safe to use. Also, LBM-A5 (10 mg/kg body mass) achieved the required plasma concentration in sufficient time to reverse MDR in vivo. Importantly, the LBM-A5 treatment group shared similar doxorubicin (DOX) pharmacokinetics with the free DOX group. Our results suggest that LBM-A5 effectively reverses MDR (EC50 = 483.6 ± 81.7 nmol·L(-1)) by inhibiting the function of P-gp, with relatively ideal pharmacokinetics and in a safe manner, and so may be a promising candidate for cancer chemotherapy research.
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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) | 0.001 | 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".