High-density lipoprotein cholesterol and paraoxonase 1 (PON1) genetics and serum PON1 activity in prepubertal children in Spain
Bibliographic record
Abstract
BACKGROUND: Oxidative stress plays an important role in atherosclerosis. Paraoxonase 1 (PON1) is a high-density lipoprotein (HDL)-associated enzyme that inhibits low-density lipoprotein (LDL) oxidation and may play a protective role against coronary heart disease. The aim of this study was to analyze the relationship between HDL-cholesterol (HDL-C) and PON1 in a Spanish prepubertal population with high plasma HDL-C levels. METHODS: The study population included 1,266 children between the ages of 6 and 8 years. Serum PON1 activity was measured by the hydrolysis of paraoxon. PON1 192Q/R and PON1 55L/M polymorphisms were analyzed by PCR and restriction analysis. RESULTS: The prevalence of the less common PON1 192R and PON 55M alleles in this population was 30% and 38%, respectively. No significant correlations between serum PON1 activity and lipid profile were observed. Multiple linear regression analysis showed that the PON1 192Q/R polymorphism accounts for 69% of PON1 activity in the children in the study, with the PON1 55L/M polymorphism accounting for an additional 5% of this variation in boys, and for an additional 3% together with HDL-C concentration in girls. CONCLUSIONS: PON1 192Q/R polymorphism is the main determinant of PON1 activity in the prepubertal population in this study, accounting for around 70% of serum PON1 activity. HDL-C concentration has a small contribution to serum PON1 activity in girls.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".