Increased Plasma Acylation‐Stimulating Protein Correlates with Hyperlipidemia at Late Gestation
Bibliographic record
Abstract
OBJECTIVES: Obesity is often associated with negative consequences, including hyperlipidemia and insulin resistance. Weight gain during pregnancy is also associated with major lipid alterations. Fat storage is enhanced in early pregnancy. At late gestation, hyperlipidemia becomes a major manifestation. The acylation-stimulating protein (ASP) is a potent lipogenic adipocytokine that correlates with postprandial triglyceride (TG) clearance in vivo and has been linked to hyperlipidemic disorders. The role of ASP during a normal pregnancy is unknown. The objective of this study was to investigate plasma ASP levels in correlation with the lipid profile during late gestation. RESEARCH METHODS AND PROCEDURES: Seventy healthy women at late gestation and 60 non-pregnant controls of similar age and prepregnancy BMI were included in a cross-sectional study. Fasting plasma ASP levels and the lipid profile of all of the women were measured. RESULTS: ASP levels were markedly elevated in the pregnant women (66%, p < 0.001). ASP levels correlated strongly with the elevated levels of TGs (r = 0.608, p < 0.000), apolipoprotein B (0.519, p < 0.000), and low-density lipoprotein-cholesterol (r = 0.405, p < 0.000). Multivariate analysis adjusting for BMI and age showed that changes in ASP levels at late gestation were best predicted by TG and apoB levels, accounting for 53.8% of plasma ASP variation. For the controls, ASP strongly correlated with BMI, which was the only significant predictor of ASP levels. DISCUSSION: Gestational hormone alterations during pregnancy may affect ASP function as a lipogenic factor. Increased plasma ASP levels at late gestation and their strong correlation with parameters reflecting very low-density lipoprotein accumulation are suggestive of ASP resistance, which may further contribute to the hyperlipidemic state, shifting energy in the form of TGs to the rapidly growing fetus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".