Effect of two phenanthrene alkaloids on angiotensin II‐induced leukocyte–endothelial cell interactions <i>in vivo</i>
Bibliographic record
Abstract
1. The present study has evaluated the effect of two phenanthrene alkaloids, uvariopsine and stephenanthrine, on angiotensin II (Ang-II)-induced leukocyte-endothelial cell interactions in vivo and the mechanisms involved in their activity. Intravital microscopy within the rat mesenteric microcirculation was used. 2. A 60 min superfusion with 1 nm Ang-II induced a significant increase in the leukocyte-endothelial cell interactions that were completely inhibited by 1 microm uvariopsine cosuperfusion. A lower dose of 0.1 microm significantly reduced Ang-II-induced leukocyte adhesion by 75%. 3. When Ang-II was cosuperfused with 1 and 0.1 microm stephenanthrine, Ang-II-induced leukocyte responses were significantly diminished. A lower dose of 0.01 microm only affected Ang-II-induced leukocyte adhesion. 4. Both alkaloids inhibited Ang-II-induced endothelial P-selectin upregulation and the generation of reactive oxygen species (ROS) in endothelial cells stimulated with Ang-II, in fMLP-stimulated human neutrophils (PMNs) and in the hypoxanthine-xanthine oxidase system. However, cyclic AMP levels in PMNs stimulated with fMLP were not affected. 5. Uvariopsine and stephenanthrine inhibited PAF-induced elevations in intracellular calcium levels in PMNs (IC50 values: 15.1 and 6.1 microm respectively) and blocked the binding of [3H]PAF to these leukocytes. They also reduced PAF-induced increases in intracellular levels of superoxide anion and hydrogen peroxide. 6. In conclusion, stephenanthrine and uvariopsine are potent inhibitors of Ang-II-induced leukocyte accumulation in vivo. This effect appears to be mediated through ROS scavenging activity and blockade of PAF receptor. Thus, they have potential therapeutic interest for the control of leukocyte recruitment that occurs in cardiovascular disease states in which Ang-II is involved.
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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".