Wounding promotes ovarian cancer progression and decreases efficacy of cisplatin in a syngeneic mouse model
Bibliographic record
Abstract
BACKGROUND: Primary cytoreductive surgery followed by adjuvant chemotherapy is the standard treatment for advanced epithelial ovarian cancer. The average interval between surgery and chemotherapy initiation is approximately 4-weeks at most centers; however, since surgery may accelerate residual tumor growth, a shorter interval may be more beneficial. METHODS: The murine ID8 cell model of ovarian cancer was used to examine the efficacy of cisplatin treatment administered perioperatively or 7 days after surgical wounding. Luciferase-expressing cells ID8 cells were injected intraperitoneally (i.p.) into female C57/Bl6 mice. Fourteen days post-injection, animals received an abdominal incision or anesthesia alone and received i.p. cisplatin either on the surgical day or 7 days later, or received no chemotherapy. Additional animals received cisplatin 28 days after wounding for comparison. RESULTS: Abdominal tumor mass increased 2.5-fold in wounded vs. unwounded animals as determined by bioluminescent in vivo tumor imaging. Cisplatin administered on the day of wounding decreased tumor burden by 50%, as compared to 90% in unwounded animals. Cisplatin on day 7 or day 28 decreased tumor burden by 80 and 37% respectively. CONCLUSIONS: Surgical wounding increases ovarian tumor mass and decreases perioperative cisplatin efficacy in this animal model. Administration of cisplatin 1 week after surgery was more effective than cisplatin administered perioperatively or 4 weeks after surgery.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".