Increased methionine sulfoxide content of apoA-I in type 1 diabetes
Bibliographic record
Abstract
Cardiovascular disease is a major cause of morbidity and premature mortality in diabetes. HDL plays an important role in limiting vascular damage by removing cholesterol and cholesteryl ester hydroperoxides from oxidized low density lipoprotein and foam cells. Methionine (Met) residues in apolipoprotein A-I (apoA-I), the major apolipoprotein of HDL, reduce peroxides in HDL lipids, forming methionine sulfoxide [Met(O)]. We examined the extent and sites of Met(O) formation in apoA-I of HDL isolated from plasma of healthy control and type 1 diabetic subjects to assess apoA-I exposure to lipid peroxides and the status of oxidative stress in the vascular compartment in diabetes. Three tryptic peptides of apoA-I contain Met residues: Q(84)-M(86)-K(88), W(108)-M(112)-R(116), and L(144)-M(148)-R(149). These peptides and their Met(O) analogs were identified and quantified by mass spectrometry. Relative to controls, Met(O) formation was significantly increased at all three locations (Met(86), Met(112), and Met(148)) in diabetic patients. The increase in Met(O) in the diabetic group did not correlate with other biomarkers of oxidative stress, such as N(epsilon)-malondialdehyde-lysine or N(epsilon)-(carboxymethyl)lysine, in plasma or lipoproteins. The higher Met(O) content in apoA-I from diabetic patients is consistent with increased levels of lipid peroxidation products in plasma in diabetes. Using the methods developed here, future studies can address the relationship between Met(O) in apoA-I and the risk, development, or progression of the vascular complications of diabetes.
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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".