Effects of radiation and surgery on healing of femoral fractures in a rat model
Bibliographic record
Abstract
Management of soft tissue sarcoma involves multimodality treatment, including surgery and radiotherapy. Pathologic fracture of the femur after such treatment in the thigh is one serious, late complication and nonunion rates of 80-90% are reported. We hypothesize that the combination of radiotherapy and periosteal stripping (during tumor resection) leads to greater impairment of the fracture repair process than either intervention alone. Female Wistar retired breeder rats were randomized into four treatment groups (control, radiotherapy, surgery, and combination of radiotherapy and surgery) and three end-points (21, 28, and 35 days post-fracture). Designated animals first underwent radiotherapy, followed by surgical stripping of the periosteum 3 weeks later and femoral fracture with fixation after another 3 weeks. Animals were sacrificed and fractures examined using microCT and histomorphometry. Simple transverse or short oblique femoral fractures were produced. By 35 days, control animals formed unions, periosteum-stripped animals formed hypertrophic non-unions and irradiated animals formed atrophic non-unions. Histomorphometry revealed an absence of chondroid and osteoid production in animals undergoing radiotherapy. The relative contribution of periosteal stripping to occurrence of non-union was statistically insignificant. Radiation prior to fracture reliably resulted in atrophic non-union in our model. The contribution of periosteal stripping was negligible.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".