Temporal effect of docetaxel on bone quality in a rodent model of vertebral metastases
Bibliographic record
Abstract
This study investigates the effects of the anticancer drug docetaxel (DTX) and its timing of administration on tumor development and resultant bone quality in a rodent model, considering both healthy animals and those with osteolytic bone metastases secondary to intra-cardiac injection (d0) of HeLa cells. Healthy and tumor-bearing rats were treated with DTX on d7 or d14 and compared to the control (no treatment) and an additional cohort treated with Zoledronic acid (ZOL). Notably, DTX administration on d7 markedly curtailed tumor growth, as evidenced by bioluminescence and histological analysis, indicating its effectiveness in reducing bone metastases. Bone metastases were more established in animals treated with later DTX administration and ZOL, but still reduced compared to no treatment. When considering bone quality, we found that both the organic and mineral phases of bone are impacted by DTX treatment. Tumor-bearing animals exhibited decreased hydroxyproline/proline ratios reflecting change in collagen metabolism compared to healthy controls, but these decreases were only significant with no treatment or DTX administration on d14. This suggests a positive impact of early DTX treatment similar to ZOL on bone quality from an organic perspective. As well, increased CaMean and CaPeak reflecting the degree of calcification was found in healthy rats treated early with DTX, similar to that seen with ZOL compared to the tumor-bearing treated groups. Overall, early docetaxel administration reduced tumor formation and improved bone quality, suggesting its potential benefit in managing bone metastases.
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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) | 0.000 | 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 | 0.001 |
| 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".