Up‐regulation of P‐glycoprotein by HIV protease inhibitors in a human brain microvessel endothelial cell line
Bibliographic record
Abstract
A major concern regarding the chronic administration of antiretroviral drugs is the potential for induction of drug efflux transporter expression (i.e., P-glycoprotein, P-gp) at tissue sites that can significantly affect drug distribution and treatment efficacy. Previous data have shown that the inductive effect of human immunodeficiency virus protease inhibitors (PIs) is mediated through the human orphan nuclear receptor, steroid xenobiotic receptor (SXR or hPXR). The objectives of this study were to investigate transport and inductive properties on efflux drug transporters of two PIs, atazanavir and ritonavir, at the blood-brain barrier by using a human brain microvessel endothelial cell line, hCMEC/D3. Transport properties of PIs by the drug efflux transporters P-gp and multidrug resistance protein 1 (MRP1) were assessed by measuring the cellular uptake of (3)H-atazanavir or (3)H-ritonavir in P-gp and MRP1 overexpressing cells as well as hCMEC/D3. Whereas the P-gp inhibitor, PSC833, increased atazanavir and ritonavir accumulation in hCMEC/D3 cells by 2-fold, the MRP inhibitor MK571 had no effect. P-gp, MRP1, and hPXR expression and localization were examined by Western blot analysis and immunogold cytochemistry at the electron microscope level. Treatment of hCMEC/D3 cells for 72 hr with rifampin or SR12813 (two well-established hPXR ligands) or PIs (atazanavir or ritonavir) resulted in an increase in P-gp expression by 1.8-, 6-, and 2-fold, respectively, with no effect observed for MRP1 expression. In hCMEC/D3 cells, cellular accumulation of these PIs appears to be primarily limited by P-gp efflux activity. Long-term exposure of atazanavir or ritonavir to brain microvessel endothelium may result in further limitations in brain drug permeability as a result of the up-regulation of P-gp expression and function.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".