Exercise improves hemodynamic profiles and increases red blood cell concentrations of purine nucleotides in a rodent model
Bibliographic record
Abstract
OBJECTIVE: To study the effect of exercise on hemodynamic profiles and red blood cell (RBC) concentrations of adenosine-5'-triphosphate (ATP). METHODS: Male Sprague-Dawley (SD) rats (n = 9) were exercised on a treadmill for 15 min at a speed of 10 m/min with a 5% gradient after an hour settling down in a restrainer. Blood samples were collected via an indwelling carotid artery catheter using a 'Stopping Solution' from each rat before, during and after exercise. Hemodynamic recordings were collected continuously throughout the experiment. Concentrations of ATP and other purine nucleotides in the RBCs were determined by a validated high-performance liquid chromatography (HPLC) assay. A control group (n = 12) was treated the same way except without the exercise. Data between groups were analyzed by analysis of variance (ANOVA) and Student's t-test, and differences were considered significant when p < 0.05. RESULTS: Exercise increased systolic blood pressure (SBP; 141±23 vs. 132±17 mmHg) and heart rate (HR; 420±33 vs. 397±41 bpm), but decreased diastolic blood pressure (DBP; 105±18 vs. 110±14 mmHg). This was followed by a postexercise condition when SBP, DBP, and HR were decreased for the remainder of the experiment. RBC concentrations of ATP and guanosine-5'-triphosphate (GTP) increased significantly during exercise and continued to increase for 5 hours postexercise (1.5±0.75 vs. 0.96 vs. 0.36 mM for ATP; and 0.14±0.061 vs. 0.058±0.030 mM) (p < 0.05). CONCLUSION: Exercise increased RBC ATP concentrations in a rodent model, which was correlated with the decrease in BP and HR postexercise.
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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 | 0.000 |
| 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".