Drug Accumulation Into Single Drug-Sensitive and Drug-Resistant Prostate Cancer Cells Conducted on the Single Cell Bioanalyzer
Bibliographic record
Abstract
Multidrug resistance (MDR) occurs in prostate cancer, and this happens when the cancer cells resist chemotherapeutic drugs by pumping them out of the cells. MDR inhibitors such as cyclosporin A (CsA) can stop the pumping and enhance the drugs accumulated in the cells. The cellular drug accumulation is monitored using a microfluidic chip mounted on a single cell bioanalyzer. This equipment has been developed to measure accumulation of drugs such as doxorubicin (DOX) and fluorescently labeled paclitaxel (PTX) in single prostate cancer cells. The inhibition of drug efflux on the same prostate cell was examined in drug-sensitive and drug-resistant cells. Accumulation of these drug molecules was not found in the MDR cells, PC-3 RX-DT2R cells. Enhanced drug accumulation was observed only after treating the MDR cell in the presence of 5 μM of CsA as the MDR inhibitor. We envision this monitoring of the accumulation of fluorescent molecules (drug or fluorescent molecules), if conducted on single patient cancer cells, can provide information for clinical monitoring of patients undergoing chemotherapy in the future.
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 | 0.000 |
| 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".