Alterations in Slow‐Twitch Muscle Phenotype in Transgenic Mice Overexpressing the Ca<sup>2+</sup> Buffering Protein Parvalbumin
Bibliographic record
Abstract
The purpose of this study was to determine whether induced expression of the Ca2+ buffering protein parvalbumin (PV) in slow-twitch fibres would lead to alterations in physiological, biochemical and molecular properties reflective of a fast fibre phenotype. Transgenic (TG) mice were generated that overexpressed PV in slow (type I) muscle fibres. In soleus muscle (SOL; 58 % type I fibres) total PV expression was 2- to 6-fold higher in TG compared to wild-type (WT) mice. Maximum twitch and tetanic tensions were similar in WT and TG but force at subtetanic frequencies (30 and 50 Hz) was reduced in TG SOL. Twitch time-to-peak tension and half-relaxation time were significantly decreased in TG SOL (time-to-peak tension: 39.3 +/- 2.6 vs. 55.1 +/- 4.7 ms; half-relaxation time: 42.1 +/- 3.5 vs. 68.1 +/- 9.6 ms, P < 0.05 for TG vs. WT, respectively; n = 8-10). There was a significant increase in expression of type IIa myosin heavy chain (MHC) and ryanodine receptor at the mRNA level in TG SOL but there were no differences in MHC expression at the protein level and thus no difference in fibre type. Whole muscle succinate dehydrogenase activity was reduced by 12 +/- 0.4 % in TG SOL and single fibre glycerol-3-phosphate dehydrogenase activity was decreased in a subset of type IIa fibres. These differences were associated with a 64 % reduction in calcineurin activity in TG SOL. These data show that overexpression of PV, resulting in decreased calcineurin activity, can alter the functional and metabolic profile of muscle and influence the expression of key marker genes in a predominantly slow-twitch muscle with minimal effects on the expression of muscle contractile proteins.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".