Cardiopulmonary reflex, cardiac cytokines, and nandrolone decanoate: response to resistance training in rats
Bibliographic record
Abstract
This study evaluated the effects of nandrolone associated with resistance training (RT) on cardiac cytokines, angiotensin-converting enzyme activity (ACEA), and the sensitivity of the Bezold-Jarisch reflex (BJR). Male Wistar rats were divided into 3 groups: CONT (received vehicle, no training); EXERC (RT: after one week of water adaptation, rats were exercised by jumping into water twice a week for 4 weeks), and ND+EXERC (received nandrolone decanoate 10 mg/kg, twice/week, i.m, associated with RT). The BJR was analysed by measuring bradycardic and hypotensive responses elicited by serotonin administration. Myocyte hypertrophy and matrix collagen deposition were determined by morphometric analysis of H&E and picrosirius red-stained samples, respectively. TNF-α and ACEA were also studied. RT promoted physiological myocyte hyrpertrophy but did not cause changes in the other parameters. The association of ND with RT increased myocyte hypertrophy, deposition of matrix type I collagen, TNF-α and ACEA; decreased IL-10, and impairment in the BJR were observed in ND+EXERC compared with CONT and EXERC. ND is associated with alterations in cardiac structure and function as a result of the development of pathological cardiac hypertrophy (cardiac cytokine imbalance, elevation of ACEA) and cardiac injury, even when combined with resistance training.
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 | 0.001 | 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".