Repeated unilateral injections of botulinum toxin in masticatory muscles in adult rats do not amplify condylar and alveolar bone loss nor modify the volume of the hypertrophic bone proliferation at enthesis
Bibliographic record
Abstract
Abstract Objectives Botulinum toxin (BTX) induces muscle paralysis. It is used in human in masticatory muscles injections performed often repeatedly. A single BTX injection in masticatory muscles in animal induces mandibular bone loss (alveolar and condylar) with a muscle enthesis hypertrophic metaplasia. Our aim was to evaluate mandibular bone changes after unilateral repeated injections of BTX in temporal and masseter muscles in adult rats. Materials and Methods Mature male rats were randomized into 3 groups: one, two or three injections. Each injection was performed 4 weeks after the prior injection. Each rat received injections in right masseter and temporalis muscles. The left side was the control side. Microcomputed tomography was used to perform 2D and 3D analyses. Results Bone loss was evidenced on the right sides of alveolar and condylar bone. Alveolar bone volume increased in both control left side and injected right side whereas condylar bone volume remained constant in all groups, for both left and right sides. Enthesis bone hypertrophic metaplasias were evidenced on the BTX injected sides without any modification with the number of injections. Conclusions BTX repeated injections in masticatory muscles lead to major mandibular condylar and alveolar bone loss that does not worsen. They lead to the occurrence of an enthesis bone proliferation that is not dependent on the number of injections. Clinical relevance These results are an argument for the safety of BTX injections in masticatory muscles in human.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".