Tibial Nerve Transection - A Standardized Model for Denervation-induced Skeletal Muscle Atrophy in Mice
Bibliographic record
Abstract
The tibial nerve transection model is a well-tolerated, validated, and reproducible model of denervation-induced skeletal muscle atrophy in rodents. Although originally developed and used extensively in the rat due to its larger size, the tibial nerve in mice is big enough that it can be easily manipulated with either crush or transection, leaving the peroneal and sural nerve branches of the sciatic nerve intact and thereby preserving their target muscles. Thus, this model offers the advantages of inducing less morbidity and impediment of ambulation than the sciatic nerve transection model and also allows investigators to study the physiologic, cellular and molecular biologic mechanisms regulating the process of muscle atrophy in genetically engineered mice. The tibial nerve supplies the gastrocnemius, soleus and plantaris muscles, so its transection permits the study of denervated skeletal muscle composed of fast twitch type II fibers and/or slow twitch type I fibers. Here we demonstrate the tibial nerve transection model in the C57Black6 mouse. We assess the atrophy of the gastrocnemius muscle, as a representative muscle, at 1, 2, and 4 weeks post-denervation by measuring muscle weights and fiber type specific cross-sectional area on paraffin-embedded histologic sections immunostained for fast twitch myosin.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".