Exposure of LS-180 Cells to Drugs of Diverse Physicochemical and Therapeutic Properties Up-regulates P-glycoprotein Expression and Activity
Bibliographic record
Abstract
PURPOSE: Drug transporters are increasingly recognized as important determinants of variability in drug disposition and therapeutic response, both in pre-clinical and clinical stages of drug development process. The role P-glycoprotein (P-gp) plays in drug interactions via its inhibition is well established. However, much less knowledge is available about drugs effect on P-gp up-regulation. The objective of this work was to in vitro investigate and rank commonly used drugs according to their potencies to up-regulate P-gp activity utilizing the same experimental conditions. METHODS: The in vitro potencies of several drugs of diverse physicochemical and therapeutic properties including rifampicin, dexamethasone, caffeine, verapamil, pentylenetetrazole, hyperforin, and β-estradiol over broad concentration range to up-regulate P-gp expression and activity were examined. For dose-response studies, LS-180 cells were treated with different concentrations of the selected drugs followed by P-gp protein and gene expressions analyses. P-gp functionality was determined by uptake studies with rhodamine 123 as a P-gp substrate, followed by Emax/EC50 evaluation. RESULTS: The results demonstrated a dose-dependent increase in P-gp expression and activity following treatments. At 50 uM concentration (hyperforin, 0.1 uM), examined drugs increased P-gp protein and gene expressions by up to 5.5 and 6.2-fold, respectively, while enhanced P-gp activity by 1.8-4-fold. The rank order of these drugs potencies to up-regulate P-gp activity was as following: hyperforin >>> dexamethasone ~ beta-estradiol > caffeine > rifampicin ~ pentylenetetrazole > verapamil. CONCLUSIONS: These drugs have the potential to be involved in drug interactions when administered with other drugs that are P-gp substrates. Further studies are needed to in vivo evaluate these drugs and verify the consequences of such induction on P-gp activity for in vitro-in vivo correlation purposes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".