Simultaneous optical and fluorescent microscopic measurement of drug retention in single cancer cells
Bibliographic record
Abstract
A single cancer cell was isolated and captured by a microfluidic single-cell biochip. The chip was made of glass and was fabricated by standard photolithography and wet etch process. Simultaneous optical observation and fluorescent measurement were achieved on the captured cancer cell. This was achieved by using red light to observe the cell; whereas the green fluorescent emission was measured photometrically to monitor the drug concentration. A CCD camera was used to image the cell morphology. At the same time, a PMT detector was used to monitor the cellular drug concentrations change in the single cell as a decrease in the cellular fluorescence intensity. Kinetic information of drug concentration change was obtained by analyzing the real time PMT data. This experiment revealed that during the efflux process, the anti-cancer drug (daunorubicin, DNR) decreased as the drug was pumped out of the cell because of multidrug resistance. The reversal effect of a multidrug resistance inhibitor (Sodium orthovanadate, OVN) on the cellular drug retention in single cancer cells was examined in this study. It was found that a higher cellular DNR concentration was resulted when OVN was present.
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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) | 0.001 | 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 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".