Effects of high-density lipoprotein on endothelium-dependent vasorelaxation
Bibliographic record
Abstract
Studies using cultured endothelial cells have shown that high-density lipoprotein (HDL) positively modulates endothelial nitric oxide synthase (eNOS). The purpose of this study was to test the hypotheses that positive modulation of eNOS by HDL occurs in whole vessels and that it augments endothelium-dependent vasorelaxation. To test these hypotheses, brachial arteries were obtained from swine. Endothelium-dependent and endothelium-independent vasorelaxation were determined in vitro to assess the effects of acute administration of HDL (50 microg.mL-1; n = 8) and chronic exposure to relatively high HDL concentration on vascular function (low HDL, 0.89 +/- 0.02 mmol.L-1, n = 4; high HDL, 1.16 +/- 0.05 mmol.L-1, n = 4; p < 0.005). Acute administration of HDL did not augment maximal endothelium-dependent vasorelaxation to bradykinin (BK) (no HDL, 82.6% +/- 2.2%; HDL, 76.7% +/- 3.5%; not significant (ns)). Similarly, maximal relaxation to BK was not enhanced by chronic exposure to high HDL concentrations. NO synthase (NOS) activity was also similar between groups (low HDL, 129.0 +/- 19.2 counts.h-1.microg-1 protein; high HDL, 113.9 +/- 47.1 counts.h-1.microg-1; ns). Consistent with NOS activity, the extent of eNOS phosphorylation at several sites was similar between low HDL and high HDL. Both apolipoprotein A-I (ApoA-I) and scavenger receptor class B type I (SR-BI) were associated with eNOS. Similar to cultured cell studies, this study demonstrates that both ApoA-I and SR-BI associate with eNOS in the vascular wall. Binding of ApoA-I and SR-BI to eNOS does not, however, result in modulation of either NO formation or endothelial function.
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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 | 0.001 |
| 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".