Nitric oxide synthase inhibition prevents activity‐induced NFAT nuclear accumulation and skeletal muscle adaptation
Bibliographic record
Abstract
Involvement of calcineurin/NFAT signaling in the regulation of skeletal muscle myosin heavy chain (MHC)‐based fast‐to‐slower isoform adaptations (F‐S) is recognized. Less is known about the role nitric oxide (NO) plays in this process. OBJECTIVE To investigate the necessity of NO in activity‐induced skeletal muscle F‐S in vivo. METHODS Endogenous NO production was blocked by administering L‐NAME (0.75 mg ml −1 ; ~100 mg kg −1 day −1 ) during 0, 1, 2, 5 or 10 days of chronic low‐frequency stimulation (CLFS; 10 Hz, 12 h d −1 ) applied to the tibialis anterior and extensor digitorum longus muscles of rats (L‐Stim; n=6 each group). Control rats received only CLFS (Stim; n=6 each group). RESULTS CLFS induced increases in NFATc1 nuclear localization in Stim, which did not occur in L‐Stim at any time point. These results were confirmed by western blot analyses. Moreover, MHC mRNA, protein and fibre type analyses revealed CLFS‐induced F‐S occurred in Stim, but were completely abolished in L‐Stim. CONCLUSIONS NO may be regulating activity‐induced MHC‐based F‐S at the transcriptional level via NFAT nuclear accumulation in vivo. *Authors contributed equally. Funded by NSERC, AHFMR, CIHR and CRC.
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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) | 0.000 | 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) | 0.001 | 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".