Efficacy assessment of sustained intraperitoneal paclitaxel therapy in a murine model of ovarian cancer using bioluminescent imaging
Bibliographic record
Abstract
We evaluated the pre-clinical efficacy of a novel intraperitoneal (i.p.) sustained-release paclitaxel formulation (PTX(ePC)) using bioluminescent imaging (BLI) in the treatment of ovarian cancer. Human ovarian carcinoma cells stably expressing the firefly luciferase gene (SKOV3(Luc)) were injected i.p. into SCID mice. Tumour growth was evaluated during sustained or intermittent courses of i.p. treatment with paclitaxel (PTX). In vitro bioluminescence strongly correlated with cell survival and cytotoxicity. Bioluminescent imaging detected tumours before their macroscopic appearance and strongly correlated with tumour weight and survival. As compared with intermittent therapy with Taxol, sustained PTX(ePC) therapy resulted in significant reduction of tumour proliferation, weight and BLI signal intensity, enhanced apoptosis and increased survival times. Our results demonstrate that BLI is a useful tool in the pre-clinical evaluation of therapeutic interventions for ovarian cancer. Moreover, these results provide evidence of enhanced therapeutic efficacy with the sustained PTX(ePC) implant system, which could potentially translate into successful clinical outcomes.
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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) | 0.001 | 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 | 0.001 | 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".