Viability Assessment Following Anticancer Treatment Requires Single-Cell Visualization
Bibliographic record
Abstract
A subset of cells within solid tumors become highly enlarged and enter a state of dormancy (sustained proliferation arrest) in response to anticancer treatment. Although dormant cancer cells might be scored as "dead" in conventional preclinical assays, they remain viable, secrete growth-promoting factors, and can give rise to progeny with stem cell-like properties. Furthermore, cancer cells exhibiting features of apoptosis (e.g., caspase-3 activation) following genotoxic stress can undergo a reversal process called anastasis and survive. Consistent with these observations, single-cell analysis of adherent cultures (solid tumor-derived cell lines with differing p53 status) has demonstrated that virtually all cells-irrespective of their size and morphology-that remain adherent to the culture dish for a long time (weeks) after treatment with anticancer agents exhibit the ability to metabolize 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl- tetrazolium bromide (MTT). The purpose of this commentary is to briefly review these findings and discuss the significance of single-cell (versus population averaged) observation methods for assessment of cancer cell viability and metabolic activity.
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) | 0.000 | 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) | 0.000 | 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".