A Pilot Study to Assess Adenosine 5’-triphosphate Metabolism in Red Blood Cells as a Drug Target for Potential Cardiovascular Protection
Bibliographic record
Abstract
OBJECTIVE: To study the effect of exercise preconditioning on adenosine 5'triphosphate (ATP) metabolism in red blood cells and cardiovascular protection against injury induced by isoproterenol in vivo. METHODS: Male Sprague Dawley rats (SDR) were each exercised on a treadmill for 15 minutes at 10 m/min and 10% grade (n = 7) (LowEx), or 14 m/min and 22% grade (n = 8) (VigEx). Two hours after the exercise, each rat received a single dose of isoproterenol (30 mg/kg) by subcutaneous (sc) injection. Two separate groups of SDR were used as control: One received no exercise (n = 10) (NoEx) and the other received no exercise and no isoproterenol (n = 11) (NoIso). Serial blood samples were collected over 5 hours for measurement of ATP and its catabolites by a validated HPLC. Hemodynamic recording was collected continuously for the duration of the experiment. Data were analysed using ANOVA and t-tests and difference considered significant at p < 0.05. RESULTS: Exercise pre-conditioning (both LowEx and VigEx) reduced mortality after isoproterenol from 50% to < 30% (p > 0.05). It attenuated the rebound in blood pressure significantly (p < 0.05 between NoEx vs VigEx), attenuated the increase of RBC adenosine 5'-monophosphate (AMP) concentrations induced by isoproterenol, and also decreased the breakdown of ATP to AMP in the RBC (p < 0.05 vs NoEx). CONCLUSION: Exercise pre-conditioning decreased the blood pressure rebound and also breakdown of ATP in RBC after isoproterenol which may be exploited further as a drug target for cardiovascular protection and prevention.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".