Human recombinant erythropoietin alters the flow-dependent vasodilatation of in vitro perfused rat mesenteric arteries with unbalanced endothelial endothelin-1 / nitric oxide ratio
Bibliographic record
Abstract
Chronic use of human recombinant erythropoietin (r-HuEPO) is accompanied by serious vascular side effects related to the rise in blood viscosity and shear stress. We investigated the direct effects of r-HuEPO on endothelium and nitric oxide (NO)-dependent vasodilatation induced by shear stress of cannulated and pressurized rat mesenteric resistance arteries. Intravascular flow was increased in the presence or absence of the NO synthase inhibitor N(G)-nitro-l-arginine methyl ester (L-NAME; 10(-4) mol/L). In the presence of r-HuEPO, the flow-dependent vasodilatation was attenuated, while L-NAME completely inhibited it. The association of r-HuEPO and L-NAME caused a vasoconstriction in response to the rise in intravascular flow. Bosentan (10(-5) mol/L), an inhibitor of endothelin-1 (ET-1) receptors, corrected the attenuated vasodilatation observed with r-HuEPO and inhibited the vasoconstriction induced by flow in the presence of r-HuEPO and L-NAME. r-HuEPO and L-NAME exacerbated ET-1 vasoconstriction. At shear stress values of 2 and 14 dyn/cm(2) (1 dyn = 10(-5) N), cultured EA.hy926 endothelial cells incubated with r-HuEPO, L-NAME, or both released greater ET-1 than untreated cells. In conclusion, r-HuEPO diminishes flow-induced vasodilatation. This inhibitory effect seems to implicate ET-1 release. NO withdrawal exacerbates the vascular effects of ET-1 in the presence of r-HuEPO. These findings support the importance of a balanced endothelial ET-1:NO ratio to avoid the vasopressor effects of r-HuEPO.
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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".