Abstract 36: Changes in HDL Particle Traits in Response to Regular Exercise: Results from the HERITAGE Family Study
Bibliographic record
Abstract
Given the controversy around HDL-C as a therapeutic target, there is a need to investigate other features of HDL and how they respond to various preventive interventions. We tested the hypothesis that regular exercise would have beneficial effects on HDL particle (HDL-P) traits in sedentary adults. Methods: The following HDL-P traits were measured via NMR (Liposcience Inc.) before and after completion of a 20-week exercise program in the HERITAGE Family Study (N=715): concentration of total, large, medium, and small HDL-P and mean HDL-P size. ANCOVA was used to test for aggregation of HDL-P trait responses in families controlling for age, sex, and baseline BMI and trait value. Results: The concentration of large HDL-P significantly increased in response to regular exercise in both Black and White participants, while the increase was significantly larger in females compared to males (Table 1). In general, regular exercise decreased the concentration of medium and small HDL-P. Together, these responses contributed to a significant increase in the average cholesterol content of HDL particles. Exercise-induced changes in large HDL-P were inversely correlated with changes in fat mass and systolic blood pressure. Moreover, changes in BMI were significantly associated with changes in all of the HDL-P traits, but not with HDL-C. We found significant evidence of familial aggregation for the exercise-induced changes in HDL-P traits in both races, as there was 1.4 to 1.6 times more variance between than within families for the changes in total (p=0.02 in Whites) and large HDL-P (p=0.004 in Whites, p=0.02 in Blacks) and HDL-P size (p=0.0009 in Whites, p=0.009 in Blacks). Conclusion: The HDL-P subclass profile favorably responded to regular exercise in sedentary Black and White adults, highlighted by increases in the concentration of large HDL-P, and may be influenced by a significant genetic component. We provide evidence that regular exercise could potentially be used as an HDL-based therapy designed to target beneficial subfractions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".