Cell-cycle-dependent turnover of P-glycoprotein in multidrug-resistant cells
Bibliographic record
Abstract
Regulation of P-glycoprotein (Pgp) expression occurs not only at the DNA and mRNA level but also at the protein level. We showed previously that Pgp was stabilized when multidrug-resistant CH(R)C5 and SKVCR 2.0 ovarian cell lines were subjected to serum-starved or high-cell-density growth conditions, whereas Pgp turnover in a leukemic multidrug-resistant cell line, CEMVLB0.1, was not affected by serum starvation (Muller et al., 1995). On further analysis, we have observed that the majority of the CH(R)C5 and SKVCR 2.0 cells under these conditions were in the G1/G0 phase of the cell cycle, whereas the cell cycle of CEMVLB0.1 cells was not affected. Pgp in CEMVLB0.1 cells was stabilized only when the cell cycle was delayed in the G1/G0 phase by using amino acid-deficient growth medium. In CH(R)C5 cells, Pgp half-life was also considerably increased when the cell cycle of these ovary-derived cells was delayed in the G1/G0 phase by using high concentrations of progesterone under normal serum growth conditions. In contrast, Pgp stability was not greatly affected if these cells were delayed in the S or G2/M phase of the cell cycle with Ara-C, cisplatin, or colchicine under the same conditions. Insulin-like growth factors could release the serum-starved CH(R)C5 and SKVCR2.0 cells from the G1/G0 phase and destabilized Pgp. These results indicate that Pgp turnover is a cell-cycle-related process in MDR cells.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".