Murine Model of Oligotrophic Tibial Nonunion
Bibliographic record
Abstract
OBJECTIVES: This study aimed to use modified distraction osteogenesis techniques to develop a reliable mouse fracture nonunion model with an oligotrophic phenotype. METHODS: Twenty-six 10- to 14-week-old C57BL/6 male mice underwent a proximal diaphyseal tibial osteotomy with a 2-mm bone resection. An external fixation device was applied to the tibia using cerclage wires. A total of 2.25 mm of distraction was applied over 3 days, resulting in an average distraction gap of 4.28 mm. Plain radiographs were taken at regular intervals until euthanasia at 7 (n = 9), 10 (n = 13), or 12 (n = 4) weeks. After euthanasia, all samples were fixed in formalin, scanned with microcomputed tomography, decalcified in formic acid, prepared in paraffin, and stained with Alcian blue/Mayer's hematoxylin. RESULTS: In the distraction groups, five mice were prematurely euthanized as a result of wound complications stemming from loss of distal fixation. Of the remaining 21, two healed, resulting in a 90% nonunion rate. These nonunions radiographically resembled clinical nonunions with tapered, cone-like fracture ends and histologically demonstrated evidence of attempted healing as seen with cartilage capping. Additionally, the plain radiographic appearance of those nonunions from mice euthanized at 10 and 12 weeks did not change over the final 4 to 6 weeks. CONCLUSIONS: The use of 2-mm tibial resection osteotomy with 2-mm distraction provides a predictable model for fracture nonunion in mice with the oligotrophic phenotype closely resembling the clinical correlate. This model offers a promising means for characterization of the molecular events that occur during the development of fracture nonunion and for evaluation of noninvasive methods of nonunion rescue.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".