Identification of Oxidized Phosphatidylinositols Present in OxLDL and Human Atherosclerotic Plaque
Bibliographic record
Abstract
Oxidized low-density lipoprotein (OxLDL) plays an important role in initiation and progression of atherosclerosis. Proatherogenic effects of OxLDL have been attributed to bioactive phospholipids generated during LDL oxidation. It is unknown what effect oxidation has on the phosphatidylinositol (PtdIns) molecules in LDL, even though PtdIns is 6% of the total LDL phospholipid pool. We sought to identify and quantitate oxidized phosphatidylinositol (OxPtdIns) species in OxLDL and human atherosclerotic plaque. Bovine liver PtdIns was subjected to non-enzymatic and lipoxygenase-catalyzed oxidation. Reversed-phase liquid chromatography with negative ESI-MS identified and confirmed compounds by fragmentation pattern analysis from which an OxPtdIns library was generated. Twenty-three OxPtdIns molecules were identified in copper-oxidized human LDL at 0, 6, 12, 24, 30, and 48 h, and in human atherosclerotic plaque. In OxLDL, OxPtdIns species containing aldehydes and carboxylates comprised 17.3 ± 0.1 and 0.9 ± 0.2%, respectively, of total OxPtdIns in OxLDL at 48 h. Hydroperoxides and isoprostanes at 24 h (68.5 ± 0.2 and 22.8 ± 0.2%) were significantly greater than 12 h (P < 0.01) without additional changes thereafter. Hydroxides decreased with increased oxidation achieving a minimum at 24 h (5.2 ± 0.3%). Human atherosclerotic plaques contained OxPtdIns species including aldehydes, carboxylates, hydroxides, hydroperoxides and isoprostanes, comprising 18.6 ± 4.7, 1.5 ± 0.7, 16.5 ± 7.4, 33.3 ± 1.1 and 30.2 ± 3.3% of total OxPtdIns compounds. This is the first identification of OxPtdIns molecules in human OxLDL and atherosclerotic plaque. With these novel molecules identified we can now investigate their potential role in atherosclerosis.
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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 | 0.001 | 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".