The effect of Nandrolone Decanoate on the frequency and concentration of satellite cells in skeletal muscle
Bibliographic record
Abstract
Nandrolone Decanoate is the most commonly used steroid to increase skeletal muscle mass and strength. However, little is known of its effect on satellite cells (SCs) which permit muscle growth and regeneration by becoming new myonuclei. We hypothesize that Nandrolone will increase the frequency (SCs/SCs+myonuclei) and concentration (number of SCs/plasmalemma surface area) of SCs as a mechanism of inducing hypertrophy. The Nandrolone group (n=4) was injected (30 mg) at weekly intervals into the left pectoralis muscle of female white leghorn chickens aged 63 days post‐hatch. The control group (n=4) received saline. After four weeks the pectoralis of each bird was excised and weighted, and samples removed. An antibody against Pax7 was used to identify SC nuclei. Applying immunocytochemical techniques and computer image analyses, fiber sizes and numbers of SCs and myonuclei were quantified. There was an approximate 24% increase in the fiber diameter. Also, the frequency and concentration SCs were significantly ( P <0.05) increased in the Nandrolone compared to the control group. These results demonstrate that Nandrolone induced skeletal muscle hypertrophy is associated with increased SC frequency and concentration. A Discovery Grant awarded to BWCR from the Natural Sciences and Engineering Research Council of Canada provided funds for this study.
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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 | 0.000 |
| 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".