Inositol-Stabilized Arginine Silicate Reduces Exercise Induced Muscle Damage and Increases Perceived Energy
Bibliographic record
Abstract
Introduction: Inositol-stabilized arginine silicate (ASI; Nitrosigine®) significantly increases circulating arginine and nitric oxide (NO). We examined ASI effects on objective and subjective indicators of muscle recovery, blood flow and energy. Methods: In a double-blind, placebo-controlled crossover-design, subjects (n=16) were given ASI (1,500 mg/day) or placebo for 4 days, with a 7-day washout period. Measurements occurred at baseline, 24, 48, and 72 h. On test days, subjects performed stress inducing leg extension exercises associated with muscle soreness. Following exercise, recovery markers creatine kinase (CK), myoglobin and lactate dehydrogenase (LDH), doppler ultrasound blood flow, leg circumference, salivary nitrite tests were measured. The Profile Mood States (POMS), VAS scales, vigor-activity cognitive tests were administered. Results: Serum CK but not LDH was significantly reduced in the ASI group on day 1 and 24, 48, and 72 h post-exercise (p<0.05); myoglobin was reduced on d1 and at 24 h post-exercise. No negative heart rate or blood pressure effects were observed. Reactive hyperemia indicated by leg circumference showed greater increases in the ASI group at 72 h (p<0.05). No differences were found in salivary nitrite levels (p=0.265). Perceived energy POMS responses increased in the ASI group compared to placebo (p=0.039) but no differences were found in subjective muscle recovery as determined by VASs. Conclusions: ASI may be beneficial for fitness goals by increasing blood flow, and reducing muscle damage and perceived energy.
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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) | 0.001 | 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".