β2-adrenergic stress evaluation of coronary endothelial-dependent vasodilator function in mice using 11C-acetate micro-PET imaging of myocardial blood flow and oxidative metabolism
Bibliographic record
Abstract
BACKGROUND: Endothelial dysfunction is associated with vascular risk factors such as dyslipidemia, hypertension, and diabetes, leading to coronary atherosclerosis. Sympathetic stress using cold-pressor testing (CPT) has been used to measure coronary endothelial function in humans with positron emission tomography (PET) myocardial blood flow (MBF) imaging, but is not practical in small animal models. This study characterized coronary vasomotor function in mice with [(11)C]acetate micro-PET measurements of nitric-oxide-mediated endothelial flow reserve (EFRNOM) (adrenergic-stress/rest MBF) and myocardial oxygen consumption (MVO2) using salbutamol β2-adrenergic-activation. METHODS: [(11)C]acetate PET MBF was performed at rest + salbutamol (SB 0.2, 1.0 μg/kg/min) and norepinephrine (NE 3.2 μg/kg/min) stress to measure an index of MBF response. β-adrenergic specificity of NE was evaluated by pretreatment with α-adrenergic-antagonist phentolamine (PHE), and β2-selectivity was assessed using SB. RESULTS: Adjusting for changes in heart rate × systolic blood pressure product (RPP), the same stress/rest MBF ratio of 1.4 was measured using low-dose SB and NE in normal mice (equivalent to human CPT response). The MBF response was correlated with changes in MVO2 (p = 0.02). Nitric oxide synthase (NOS)-inhibited mice (N(g)-nitro-L-arginine methyl ester (L-NAME) pretreatment and endothelial nitric oxide synthase (eNOS) knockout) were used to assess the EFRNOM, in which the low-dose SB- and NE-stress MBF responses were completely blocked (p = 0.02). With high-dose SB-stress, the MBF ratio was reduced by 0.4 following NOS inhibition (p = 0.03). CONCLUSIONS: Low-dose salbutamol β2-adrenergic-stress [(11)C]acetate micro-PET imaging can be used to measure coronary-specific EFRNOM in mice and may be suitable for assessment of endothelial dysfunction in small animal models of disease and evaluation of new therapies.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".