Role of arginase in the pathophysiology of preeclampsia
Bibliographic record
Abstract
Preeclampsia (PE), a hypertensive disorder of pregnancy, is characterized by vascular endothelial cell dysfunction resulting in increased levels of superoxide (O 2 .− ) and reduced nitric oxide (NO) bioavailability. Also, increased peroxynitrite (ONOO − ) has been observed in PE. Arginase competes with NO synthase (NOS) for the substrate L‐arginine. Upregulation of arginase can reduce L‐arginine availability for NOS, resulting in NOS uncoupling and more (O 2 .− ) generation. We therefore hypothesize that upregulation of arginase occurs in PE resulting in increased O 2 .− and subsequently ONOO − formation. Immunohistochemical staining of arteries obtained from PE women show increased arginase expression when compared to arteries from normotensive pregnant (NP) women. In order to address mechanisms, HUVECs were treated with 2% plasma from NP and PE women for 24h. PE plasma significantly increased arginase expression (∼35%), increased O 2 .− (∼200%) and ONOO − (10 fold) generation. Plasma from either group did not affect eNOS expression. Inhibition of arginase by BEC reduced O 2 .− by 50%, P<0.05 but not ONOO − in response to PE plasma. Inhibition of NOS by L‐NAME also reduced O 2 .− by 50%. Therefore, in PE there is evidence of elevated arginase expression resulting in uncoupling of NOS leading to excess O 2 .− generation. However, inhibition of arginase did not ultimately reduce ONOO − . Funded by CIHR.
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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 | 0.001 | 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".