Effects of enalaprilat on venoconstriction to norepinephrine: role of prostaglandins
Bibliographic record
Abstract
OBJECTIVE: Most patients with cardiovascular disease continue to receive both aspirin and an angiotensin-converting enzyme (ACE) inhibitor. This is despite the fact that ACE inhibition also inhibits the enzyme kininase II and leads to accumulation of bradykinin which increases prostaglandins. We hypothesized that in normal veins, vasodilator prostaglandins contribute significantly to ACE inhibitor dilation of norepinephrine-induced venoconstriction, and this would be blocked by cyclooxygenase inhibition. METHODS: The study was performed using the in vivo dorsal hand vein technique for measuring vascular responses directly. Venoconstriction to norepinephrine infusions (0.5-1024 ng/min) was assessed in eight normal subjects (46+/-5 years, mean+/-S.E.M.) during coinfusion of saline in one hand (control) and enalaprilat (1000 microg/min) in the contralateral hand. On a second morning (7+/-1 days apart, mean+/-S.E.M., random order), the same procedure was repeated with indomethacin (3 microg/min) coinfusion in both hands. RESULTS: Enalaprilat shifted the norepinephrine dose-response curve to the right (P=0.024) and increased the norepinephrine log ED(50) (dose required to cause 50% venoconstriction) from 1.70+/-0.08 to 2.31+/-0.11 log ng/min (P=0.001). Indomethacin shifted the norepinephrine dose-response curve to the left (P=0.018) and decreased the norepinephrine log ED(50) from 1.70+/-0.08 to 1.09+/-0.18 log ng/min (P=0.002). In the presence of indomethacin, enalaprilat caused only a small but significant increase in the norepinephrine log ED(50), from 1.09+/-0.18 to 1.29+/-0.18 log ng/min (P=0.041). CONCLUSIONS: The results suggest that vasodilator prostaglandins contribute significantly to the attenuation of sympathetic venoconstriction by enalaprilat. This may have clinical relevance in patients receiving aspirin and ACE inhibitors in the setting of increased sympathetic activity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".