Post-treatment recovery of docetaxel-treated prostate cancer monolayer and spheroid culture
Bibliographic record
Abstract
Abstract In the last half-century, it has become widely recognized that small 3D aggregates of cancer cells called tumor spheroids mimic some aspects of tumor behavior. Cell culture geometry has been shown to influence drug pharmacokinetics, delivery, and resistance. Despite the improved physiological relevance, the laborious nature of spheroids has limited clonogenic measurement and longitudinal observation of post-treatment recovery in docetaxel-treated prostate tumor spheroids. Agent-based modeling can complement spheroid experiments by probing questions of interest that are experimentally inaccessible. Here, we performed proliferation and clonogenic assays in docetaxel-treated PC3 cells cultured in monolayers and spheroids to assess and compare end-of-treatment survival and post-treatment recovery. We observed growth stimulation with no survival benefit in low dose docetaxel-treated monolayer and spheroid culture. However, agent-based modeling suggested that this hormetic effect may have been influenced by the active process of apoptosis. To the best of our knowledge, this is the first clonogenic measurement of docetaxel-treated spheroid culture and longitudinal observation of post-treatment docetaxel-dose dependent effects in prostate cancer cell culture.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".