Development of the mouse mandibles and clavicles in the absence of skeletal myogenesis
Bibliographic record
Abstract
In this report we employed double-knock-out \nmouse embryos and fetuses (designated as Myf5-/-: \nMyoD-/- that completely lacked striated musculature to \nstudy bone development in the absence of mechanical \nstimuli from the musculature and to distinguish between \nthe effects that static loading and weight-bearing exhibit \non embryonic development of skeletal system. We \nconcentrated on development of the mandibles (= \ndentary) and clavicles because their formation is \ncharacterized by intramembranous and endochondral \nossification via formation of secondary cartilage that is \ndependent on mechanical stimuli from the adjacent \nmusculature. We employed morphometry and \nmorphology at different embryonic stages and compared \nbone development in double-mutant and control \nembryos and fetuses. Our findings can be summarized as \nfollows: a) the examined mutant bones had significantly \naltered shape and size that we described \nmorphometrically, b) the effects of muscle absence \nvaried depending on the bone (clavicles being more dependent than mandibles) and even within the same \nbone (e.g., the mandible), and c) we further supported \nthe notion that, from the evolutionary point of view, \nmammalian clavicles arise under different influences \nfrom those that initiate the furcula (wishbone) in birds. \nTogether, our data show that the development of \nsecondary cartilage, and in turn the development of the \nfinal shape and size of the bones, is strongly influenced \nby mechanical cues from the skeletal musculature.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".