Peroxynitrite Causes Endoplasmic Reticulum Stress and Apoptosis in Human Vascular Endothelium
Bibliographic record
Abstract
OBJECTIVE: Peroxynitrite, a potent oxidant generated by the reaction of NO with superoxide, has been implicated in the promotion of atherosclerosis. We designed this study to determine whether peroxynitrite induces its proatherogenic effects through induction of endoplasmic reticulum (ER) stress. METHODS AND RESULTS: Human vascular endothelial cells treated with Sin-1, a peroxynitrite generator, induced the expression of the ER chaperones GRP78 and GRP94 and increased eIF2alpha phosphorylation. These effects were inhibited by the peroxynitrite scavenger uric acid. Sin-1 caused the depletion of ER-Ca2+, an effect known to induce ER stress, resulting in the elevation of cytosolic Ca2+ and programmed cell death (PCD). Sin-1 treatment was also found, via 3-nitrotyrosine and GRP78 colocalization, to act directly on the ER. Adenoviral-mediated overexpression of GRP78 in endothelial cells prevented Sin-1-induced PCD. Consistent with these in vitro findings, 3-nitrotyrosine was observed and colocalized with GRP78 in endothelial cells of early atherosclerotic lesions from apolipoprotein E-deficient mice. CONCLUSIONS: Peroxynitrite is an ER stress-inducing agent. Its effects include the depletion of ER-Ca2+, a known mechanism of ER stress induction. The observation that 3-nitrotyrosine-containing proteins colocalize with markers of ER stress within early atherosclerotic lesions suggests that peroxynitrite contributes to atherogenesis through a mechanism involving ER stress.
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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".