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Record W4416510096 · doi:10.1101/2025.11.17.688723

Post-treatment recovery of docetaxel-treated prostate cancer monolayer and spheroid culture

2025· preprint· W4416510096 on OpenAlexafffund
Steph Swanson, Catherine B. McKenna, Elahe Cheraghi, Ernest Osei

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Language
FieldMathematics
TopicMathematical Biology Tumor Growth
Canadian institutionsRegional Municipality of WaterlooUniversity of Waterloo
FundersProstate Cancer Fight FoundationMitacs
KeywordsSpheroidClonogenic assayProstate cancerCell cultureProstateMonolayerCancer

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.248
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

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