Metoprolol impairs resistance artery function in mice
Bibliographic record
Abstract
Acute β-blockade with metoprolol has been associated with increased mortality by undefined mechanisms. Since metoprolol is a relatively high affinity blocker of β(2)-adrenoreceptors, we hypothesized that some of the increased mortality associated with its use may be due to its abrogation of β(2)-adrenoreceptor-mediated vasodilation of microvessels in different vascular beds. Cardiac output (CO; pressure volume loops), mean arterial pressure (MAP), relative cerebral blood flow (rCBF; laser Doppler), and microvascular brain tissue Po(2) (G2 oxyphor) were measured in anesthetized mice before and after acute treatment with metoprolol (3 mg/kg iv). The vasodilatory dose responses to β-adrenergic agonists (isoproterenol and clenbuterol), and the myogenic response, were assessed in isolated mesenteric resistance arteries (MRAs; ∼200-μm diameter) and posterior cerebral arteries (PCAs ∼150-μm diameter). Data are presented as means ± SE with statistical significance applied at P < 0.05. Metoprolol treatment did not effect MAP but reduced heart rate and stroke volume, CO, rCBF, and brain microvascular Po(2), while concurrently increasing systemic vascular resistance (P < 0.05 for all). In isolated MRAs, metoprolol did not affect basal artery tone or the myogenic response, but it did cause a dose-dependent impairment of isoproterenol- and clenbuterol-induced vasodilation. In isolated PCAs, metoprolol (50 μM) impaired maximal vasodilation in response to isoproterenol. These data support the hypothesis that acute administration of metoprolol can reduce tissue oxygen delivery by impairing the vasodilatory response to β(2)-adrenergic agonists. This mechanism may contribute to the observed increase in mortality associated with acute administration of metoprolol in perioperative patients.
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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 | 0.001 |
| 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".