TREATMENT AFFECTS LOAD-TO-FAILURE AND MICRODAMAGE ACCUMULATION IN HEALTHY AND OSTEOLYTIC RAT VERTEBRAE
Bibliographic record
Abstract
Bone turnover and microdamage are impacted by skeletal metastases which can contribute to increased fracture risk. Treatments for metastatic disease may further impact bone quality. This study aimed to establish an understanding of microdamage accumulation and load to failure in healthy and osteolytic vertebrae following cancer treatment (stereotactic body radiotherapy (SBRT), zoledronic acid (ZA), or docetaxel (DTX)). Forty-two 6-week old athymic female rats (Hsd:RH-Foxn1rnu, Envigo) were studied; 22 were inoculated with HeLa cervical cancer cells through intracardiac injection (day 0). Animals were randomly assigned to four groups: untreated (healthy=5, osteolytic=6), SBRT on day 14 (healthy=6, osteolytic=6), ZA on day 7 (healthy=4, osteolytic=5), and DTX on day 14 (healthy=5, osteolytic=5). Animals were euthanized on day 21. L1-L3 motion segments were compression loaded to failure and force-displacement data recorded. T13 vertebrae were stained with BaSO4 and µCT imaged (90kVp, 44uA, 4.9µm) to visualize microdamage location and volume. Damage volume fraction (DV/BV) was calculated as the ratio of BaSO4 to bone volume. Differences in mean load-to-failure were compared using three-way ANOVA (disease status, treatment, cells injected). Differences in mean DV/BV between treatment groups were compared using one-way ANOVA. Treatment had a significant effect on load-to-failure (p=0.004) with ZA strengthening the healthy and osteolytic vertebrae. Reduced strength post SBRT seen in the metastatic (but not the healthy) group may be explained by greater tumor involvement secondary to higher cell injection concentrations. Untreated metastatic samples had higher DV/BV (16.25±2.54%) compared to all treatment groups (p<0.05) suggesting a benefit of treatment to bone quality. Focal and systemic cancer treatments were shown to effect load-to-failure and microdamage accumulation in healthy and osteolytic vertebrae. Developing a better understanding of how treatments effect bone quality and mechanical stability is critical for effective management of patients with spinal 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 | 0.001 | 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".