Quantitative myocardial perfusion and coronary reserve in rats with 13N-ammonia and small animal PET: impact of anesthesia and pharmacologic stress agents.
Bibliographic record
Abstract
UNLABELLED: The purpose of this study was to evaluate the effects of 2 anesthetic agents on myocardial perfusion and coronary reserve in rats under resting and stress conditions with small animal PET. METHODS: Twenty-four rest/stress studies were performed in 6 rats. Each animal received all 4 possible combinations of anesthetic agents (propofol, isoflurane) and pharmacologic stress agents (dobutamine, adenosine) to increase myocardial perfusion. For each stress or rest study, a 10-min dynamic acquisition was performed in list mode with 185 MBq of (13)N-NH(3). Data analysis was performed according to a 3-compartment myocardial blood flow model. Pharmacologic stimulation by either dobutamine or adenosine was performed to increase myocardial perfusion. RESULTS: The perfusion values (mean +/- SD) for the various experimental conditions were as follows: propofol/dobutamine, 7.8 +/- 2.4 mL/g/min (rest, 3.7 +/- 0.8 mL/g/min; mean +/- SD); isoflurane/dobutamine, 9.3 +/- 3.1 mL/g/min (rest, 4.3 +/- 1.0 mL/g/min); propofol/adenosine, 6.8 +/- 1.7 mL/g/min (rest, 3.2 +/- 0.4 mL/g/min); and isoflurane/adenosine, 5.2 +/- 1.3 mL/g/min (rest, 3.7 +/- 0.7 mL/g/min). All perfusion data showed a significant increase after pharmacologic stimulation relative to baseline (P < 0.05). The coronary reserve (mean +/- SD) measured by PET was slightly lower with the combination of isoflurane and adenosine (1.4 +/- 0.5) than with propofol and adenosine (2.1 +/- 0.5). CONCLUSION: Noninvasive quantitative measurements of myocardial perfusion in small animals at rest and during stress are feasible using PET. Evaluation of the coronary reserve must take into account the initial state of the anesthetized animal. The coronary reserve could be measured with both anesthetic agents using either dobutamine or adenosine stimulation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".