Induction of P-Glycoprotein by Antiretroviral Drugs in Human Brain Microvessel Endothelial Cells
Bibliographic record
Abstract
The membrane-associated drug transporter P-glycoprotein (P-gp) plays an essential role in drug efflux from the brain. Induction of this protein at the blood-brain barrier (BBB) could further affect the ability of a drug to enter the brain. At present, P-gp induction mediated by antiretroviral drugs at the BBB has not been fully investigated. Since P-gp expression is regulated by ligand-activated nuclear receptors, i.e., human pregnane X receptor (hPXR) and human constitutive androstane receptor (hCAR), these receptors could represent potential pathways involved in P-gp induction by antiretroviral drugs. The aims of this study were (i) to determine whether antiretroviral drugs currently used in HIV pharmacotherapy are ligands for hPXR or hCAR and (ii) to examine P-gp function and expression in human brain microvessel endothelial cells treated with antiretroviral drugs identified as ligands of hPXR and/or hCAR. Luciferase reporter gene assays were performed to examine the activation of hPXR and hCAR by antiretroviral drugs. The hCMEC/D3 cell line, which is known to display several morphological and biochemical properties of the BBB in humans, was used to examine P-gp induction following 72 h of exposure to these agents. Amprenavir, atazanavir, darunavir, efavirenz, ritonavir, and lopinavir were found to activate hPXR, whereas abacavir, efavirenz, and nevirapine were found to activate hCAR. P-gp expression and function were significantly induced in hCMEC/D3 cells treated with these drugs at clinical concentrations in plasma. Together, our data suggest that P-gp induction could occur at the BBB during chronic treatment with antiretroviral drugs identified as ligands of hPXR and/or hCAR.
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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 | 0.001 |
| 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".