Apolipoprotein B, apolipoprotein A-I, insulin resistance and the metabolic syndrome
Bibliographic record
Abstract
PURPOSE OF REVIEW: The goal of identifying subjects with metabolic syndrome is to detect those at higher risk of developing cardiovascular disease. Evidence continues to accumulate as to the superiority of apolipoprotein B and apolipoprotein A-I over the conventional lipoprotein lipids as markers of vascular risk. It would seem reasonable, therefore, to redefine the dyslipidemia of the metabolic syndrome incorporating apolipoproteins. Therefore, our objective is to elucidate how apolipoprotein B and apolipoprotein A-I amplify evidence of the interactions amongst metabolic syndrome, insulin resistance, abdominal obesity, and vascular risk. RECENT FINDINGS: In several large epidemiological studies, including the NHANES III database, apolipoprotein B/apolipoprotein A-I ratio was tightly linked to the metabolic syndrome and each of its components, the descending order being: low HDL cholesterol, high triglyceride, high waist circumference, high glucose, and high blood pressure. Moreover, apolipoprotein B associates more closely with inflammatory markers and insulin resistance than triglyceride and all cholesterol markers. Yet despite close association of the apolipoprotein B/apolipoprotein A-I ratio to metabolic syndrome, both are independent predictors of future myocardial infarction. SUMMARY: We believe that the dyslipidemia of the metabolic syndrome should be redefined to include apolipoprotein B and apolipoprotein A-I.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".