Basal, but not overload-induced, myonuclear addition is attenuated by <i>N</i><sup>G</sup>-nitro-<scp>l</scp>-arginine methyl ester (<scp>l</scp>-NAME) administration
Bibliographic record
Abstract
The purpose of this study was to examine the effect of blocking nitric oxide synthase (NOS) activity via NG-nitro-l-arginine methyl ester (l-NAME) on myonuclear addition in skeletal muscle under basal and overloaded conditions. Female Sprague–Dawley rats (approx. 220 g) were placed into 1 of the following 4 groups (n = 7–9/group): 7-day skeletal muscle overload (O), sham operation (S), skeletal muscle overload with l-NAME treatment (OLN), and sham operation with l-NAME treatment (SLN). Plantaris muscles were overloaded via bilateral surgical ablation of the gastrocnemius muscles and l-NAME (0.75 mg/mL) was administered in the animals’ daily drinking water starting 2 days prior to surgery and continued until sacrifice. Myonuclear addition was assessed as subsarcolemmal incorporation of nuclei labeled with 5-bromo-2′-deoxyuridine (approx. 25 mg·(kg body mass)–1·day–1) delivered via osmotic pump during the overload period. As expected, muscle wet mass, total protein content, fiber cross-sectional area, and myonuclear addition were significantly higher (p ≤ 0.05) in O vs. S; however, only the increase in wet mass and total protein content (per body mass) were attenuated by l-NAME administration. Interestingly, l-NAME significantly reduced myonuclear addition by 75% in nonoverloaded muscles (SLN vs. S). Muscle hepatocyte growth factor protein content increased with overload, but was unaffected by l-NAME in either loading state. These data indicate that NOS inhibition in rat plantaris muscle attenuates myonuclear addition under basal, but not overloaded, 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".