Evaluation of testing solution and storage for measuring passive elastic modulus of rat tibialis anterior whole muscle
Bibliographic record
Abstract
Ex-vivo tensile testing is widely used to evaluate the passive mechanical properties of skeletal muscle, particularly the elastic modulus. Researchers commonly use different testing solutions, such as relaxing and carbogen-bubbled Tyrode, and often store small samples in glycerinated solution prior to testing. This paper investigated the effects of testing solutions and storage conditions on the passive elastic modulus of whole muscles in three studies. The objectives were to compare the elastic modulus of whole muscles tested in relaxing solution, Tyrode's solution, and carbogen-bubbled Tyrode's solution (Studies A&B) and to determine whether storage methods can preserve muscles' passive mechanical properties (Study C). Tibialis Anterior muscles (left and right) from 28 male Sprague-Dawley rats were harvested. In Study A, six rats were studied to compare the effect of using relaxing and Tyrode's solutions. Study B involved muscles from eight rats to assess the impact of carbogen aeration in Tyrode's solution. In Study C, 14 rats were used to evaluate the effects of storing muscles in glycerinated solution compared to fresh muscles using three different methods with varying storage durations. The results indicated no significant differences in elastic moduli between relaxing and Tyrode's solutions (p = 0.70) or between carbogen bubbled and non-bubbled Tyrode's solutions (p = 0.81). Also, none of the storage methods preserved the passive elastic modulus of whole muscles compared to fresh muscles, highlighting the need for new storage methodologies if storing whole muscle is required prior to testing. These findings improve the interpretation of passive mechanical property measurements across studies with different conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".