Same-Single-Cell Analysis for the Study of Drug Efflux Modulation of Multidrug Resistant Cells Using a Microfluidic Chip
Bibliographic record
Abstract
Since multidrug resistance (MDR) is a major cause of failure in cancer chemotherapy, we report a microfluidic approach combined with the same-single-cell analysis to investigate the modulation of MDR, manifested as the inhibition of drug efflux. A microfluidic chip that was capable of selecting and retaining a single multidrug-resistant cancer cell was used to investigate drug efflux inhibition in leukemia cell lines. Three advantages of the microfluidic-based same-single-cell analysis (dubbed as SASCA) method have been revealed. First, it readily detects the modulation of drug efflux of anticancer compounds (e.g., daunorubicin) by MDR modulators (e.g., verapamil) among cellular variations. Second, SASCA is able to compare the different cellular abilities in response to drug efflux modulation based on the drug transport kinetics of single cells. Third, SASCA requires only a small number of cells, which may be beneficial for investigating drug resistance in minor cell subpopulations (e.g., cancer "stem" cells).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".