Guanidinoacetic acid provides superior cardioprotection to its combined use with betaine and (or) creatine in HIIT-trained rats
Bibliographic record
Abstract
This study aimed to determine how guanidinoacetic acid (GAA) or its combined administration with betaine (B) or creatine (C) influences the cardiac function, morphometric parameters, and redox status of rats subjected to high-intensity interval training (HIIT). This research was conducted on male Wistar albino rats exposed to HIIT for 4 weeks. The animals were randomly divided into five groups: HIIT, HIIT + GAA, HIIT + GAA + C, HIIT + GAA + B, and HIIT + GAA + C + B. After completing the training protocol, GAA (300 mg/kg), C (280 mg/kg), and B (300 mg/kg) were applied daily per os for 4 weeks. GAA supplementation in combination with HIIT significantly decreased the level of both systemic and cardiac prooxidants ([Formula: see text], H 2 O 2 , [Formula: see text], and thiobarbituric acid reactive substances) compared with nontreated HIIT ( p < 0.05). Also, GAA treatment led to an increase in glutathione and superoxide dismutase levels. None of the treatment regimens altered cardiac function. A larger degree of cardiomyocyte hypertrophy was observed in the HIIT + GAA group, which was reflected through an increase of the cross-sectional area of 27% ( p < 0.05) and that of the left ventricle wall thickness of 27% ( p < 0.05). Since we showed that GAA in combination with HIIT may ameliorate oxidative stress and does not alter cardiac function, the present study is a basis for future research exploring the mechanisms of cardioprotection induced by this supplement in an HIIT scenario.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".