A novel hindlimb immobilization procedure for studying skeletal muscle atrophy and recovery in mouse
Bibliographic record
Abstract
Skeletal muscle atrophy is a serious concern for patients afflicted by limb restriction due to surgery (e.g., arthrodesis), several articular pathologies (e.g., arthralgia), or simply following cast immobilization. To study the molecular events involved in this immobilization-induced debilitating condition, a convenient mouse model for atrophy is lacking. Here we provide a new immobilization procedure exploiting the normal flexion of the mouse hindlimb using a surgical staple to fix the ventral part of the foot to the distal part of the calf. Histological analysis revealed that our approach induced significant skeletal muscle atrophy by reducing the myofiber size of the tibialis anterior (TA) muscle by 36% compared with the untreated contralateral TA within a few days postimmobilization. Two molecular markers for atrophy, atrogin-1/muscle atrophy F-box (atrogin-1/MAFbx) and muscle ring finger 1 (MuRF-1) mRNAs, were significantly upregulated by 1.9- and 5.9-fold, respectively. Interestingly, our model also revealed the presence of an early inflammatory process during atrophy, characterized by the mRNA upregulation of TNF-alpha, IL-1, and IL-6 (1.9-, 2.4-, and 3.4-fold, respectively) simultaneously with the upregulation of the common leukocyte marker CD45 (6.1-fold). Moreover, muscle rapidly recovered on remobilization, an event associated with significantly increased levels of uncoupling protein-3 and peroxisome proliferator-activated receptor gamma coactivator-1alpha mRNA, key components of prooxidative muscle metabolism. This model offers unexpected new insights into the molecular events involved in immobilization atrophy.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".