Effect of Cardiovascular Injury on Catabolism of Adenosine and Adenosine 5-‘Triphosphate in Systemic Blood in a Freely Moving Rat Model In Vivo
Bibliographic record
Abstract
BACKGROUND: Previous studies have shown that catabolism of adenosine 5'-triphosphate (ATP) in red blood cell (RBC) may be a key factor for cardiovascular protection and maintaining cardiovascular homeostasis. OBJECTIVE: To investigate the effect of cardiovascular injury on adenosine and ATP catabolism in systemic blood using a freely moving rat model in vivo. METHOD: After acclimatized to the experimental environment, Sprague Dawley (SD) rats were each given either isoproterenol (30 mg/kg) or saline (1 mL/kg) by subcutaneous (sc) injection. Blood samples were collected sequentially for up to 6 hours for measurement of red blood cell (RBC) concentrations of adenine nucleotides and plasma concentrations of adenosine and its oxypurine metabolites. RESULTS: We have found isoproterenol induced 50% mortality under the experimental condition. Plasma concentrations of adenosine (ADO) and uric acid (UA) and red blood cell (RBC) concentrations of adenosine 5'-diphosphate (ADP) and adenosine 5'-monophosphate (AMP) in RBC were significantly higher in the isoproterenol treated rats (p < 0.05 for all the comparison). On the other hand, plasma concentrations of hypoxanthine (HYP) were higher in the control group (p < 0.05), but there was no statistically significant changes in ATP concentrations in the RBC (p > 0.05). CONCLUSION: Cardiovascular injury induced by isoproterenol resulted in breakdown of ATP to ADP and AMP in the RBC and also breakdown of ADO to UA in plasma and other tissues.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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".