Masticatory muscles of mouse do not undergo atrophy in space
Bibliographic record
Abstract
Muscle loading is important for maintaining muscle mass; when load is removed, atrophy is inevitable. However, in clinical situations such as critical care myopathy, masticatory muscles do not lose mass. Thus, their properties may be harnessed to preserve mass. We compared masticatory and appendicular muscles responses to microgravity, using mice aboard the space shuttle Space Transportation System-135. Age- and sex-matched controls remained on the ground. After 13 days of space flight, 1 masseter (MA) and tibialis anterior (TA) were frozen rapidly for biochemical and functional measurements, and the contralateral MA was processed for morphologic measurements. Flight TA muscles exhibited 20 ± 3% decreased muscle mass, 2-fold decreased phosphorylated (P)-Akt, and 4- to 12-fold increased atrogene expression. In contrast, MAs had no significant change in mass but a 3-fold increase in P-focal adhesion kinase, 1.5-fold increase in P-Akt, and 50-90% lower atrogene expression compared with limb muscles, which were unaltered in microgravity. Myofibril force measurements revealed that microgravity caused a 3-fold decrease in specific force and maximal shortening velocity in TA muscles. It is surprising that myofibril-specific force from both control and flight MAs were similar to flight TA muscles, yet power was compromised by 40% following flight. Continued loading in microgravity prevents atrophy, but masticatory muscles have a different set point that mimics disuse atrophy in the appendicular muscle.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".