Human Serum PCSK9 Is Elevated at Parturition in Comparison to Nonpregnant Subjects While Serum PCSK9 from Umbilical Cord Blood is Lower Compared to Maternal Blood
Bibliographic record
Abstract
Background. Serum lipids including total cholesterol (TC), triglycerides (TG), and low density lipoprotein cholesterol (LDL-C) are increased in pregnancy. Serum proprotein convertase subtilisin kexin 9 (PCSK9) is a significant player in lipoprotein metabolism. Circulating PCSK9 downregulates the LDL receptor on the surface of the liver, inhibiting clearance of LDL-C. Therefore, our study assessed serum PCSK9 concentrations at parturition (Maternal) compared to a nonpregnant (Control) cohort, as well as between mother and newborn (Maternal and Newborn). Methods. Blood was collected from women at parturition and from umbilical cords. Serum lipids and PCSK9 were measured and data were analysed for significance by Mann-Whitney U test at P < 0.05 and presented as median levels. Spearman's correlations were made at a 95% confidence interval. Results. Serum PCSK9 was significantly higher in Maternal versus Control cohorts (493.1 versus 289.7 ng/mL; P < 0.001, resp.), while the Newborn cohort was significantly lower than Maternal (278.2 versus 493.1 ng/mL; P < 0.0001, resp.). PCSK9 was significantly correlated with TC and HDL-C in Maternal and with TC, LDL-C, and HDL-C in Newborn cohorts. Conclusions. Our study provides the first quantitative report on PCSK9 in pregnancy (at parturition) and in umbilical cord blood. Further research will determine how these changes may affect lipoprotein levels during this physiological state.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".