Modulation of p‐glycoprotein function by caveolin‐1 phosphorylation
Bibliographic record
Abstract
p-glycoprotein (p-gp) is an ATP-binding cassette transporter and its overexpression is responsible for the acquisition of the multidrug resistance phenotype in human tumors. p-gp is localized at the blood-brain barrier and is involved in brain cytoprotection. Our previous work used immunoprecipitation to show that caveolin-1 can interact with p-gp. In this study, we provide evidence that caveolin-1 regulates p-gp transport activity in a rat brain endothelial cell line (RBE4). Down-regulation of caveolin-1 by siRNA reduced the interaction between p-gp and caveolin-1, followed by a decrease in [3H]-Taxol and [3H]-Vinblastine accumulation in RBE4 cells. The latter result showed that down-regulation of caveolin-1 enhanced p-gp transport activity. RBE4 cells were also transfected with Sarcoma in order to modulate caveolin-1 phosphorylation. Overexpression of Sarcoma, a protein tyrosine kinase, stimulated caveolin-1 phosphorylation and increased both [3H]-Taxol and [3H]-Vinblastine accumulation as well as Hoechst 33342 accumulation. Transfection of caveolin-1 inhibits p-gp transport activity. Conversely, transfection of the mutant cavY14F decreased the p-gp/caveolin-1 interaction and reduced accumulation of the two p-gp substrates. Thus, our data show that caveolin-1 regulates p-gp function through the phosphorylation state of caveolin-1 in endothelial cells from the blood-brain barrier.
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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".