Macrophage-specific expression of group IIA sPLA2 results in accelerated atherogenesis by increasing oxidative stress
Bibliographic record
Abstract
Group IIA secretory phospholipase A2 (sPLA2) is an acute-phase protein mediating decreased plasma HDL cholesterol and increased atherosclerosis. This study investigated the impact of macrophage-specific sPLA2 overexpression on lipoprotein metabolism and atherogenesis. Macrophages from sPLA2 transgenic mice have 2.5 times increased rates of LDL oxidation (thiobarbituric acid-reactive substances formation) in vitro (59 +/- 5 vs. 24 +/- 4 nmol malondialdehyde/mg protein; P < 0.001) dependent on functional 12/15-lipoxygenase (12/15-LO). Low density lipoprotein receptor-deficient (LDLR-/-) mice were transplanted with bone marrow from either sPLA2 transgenic mice (sPLA2--> LDLR-/-; n = 19) or wild-type C57BL/6 littermates (C57 BL/6-->LDLR-/-; n = 19) and maintained for 8 weeks on chow and then for 9 weeks on a Western-type diet. Plasma sPLA2 activity and plasma lipoprotein profiles were not significantly different between sPLA2-->LDLR-/- and C57BL/6-->LDLR-/- mice. Aortic root atherosclerosis was increased by 57% in sPLA2-->LDLR-/- mice compared with C57BL/6-->LDLR-/- controls (P < 0.05). Foam cell formation in vitro and in vivo was increased significantly. Urinary, plasma, and aortic levels of the isoprostane 8,12-iso-iPF2alpha-VI and aortic levels of 12/15-LO reaction products were each significantly higher (P < 0.001) in sPLA2-->LDLR-/- compared with C57BL/6-->LDLR-/- mice, indicating significantly increased in vivo oxidative stress in sPLA2--> LDLR-/-. These data demonstrate that macrophage-specific overexpression of human sPLA2 increases atherogenesis by directly modulating foam cell formation and in vivo oxidative stress without any effect on systemic sPLA2 activity and lipoprotein metabolism.
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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) | 0.001 | 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".