Apolipoprotein A-II regulates HDL stability and affects hepatic lipase association and activity
Bibliographic record
Abstract
The effect of apolipoprotein A-II (apoA-II) on the structure and stability of HDL has been investigated in reconstituted HDL particles. Purified human apoA-II was incorporated into sonicated, spherical LpA-I particles containing apoA-I, phospholipids, and various amounts of triacylglycerol (TG), diacylglycerol (DG), and/or free cholesterol. Although the addition of PC to apoA-I reduces the thermodynamic stability (free energy of denaturation) of its alpha-helices, PC has the opposite effect on apoA-II and significantly increases its helical stability. Similarly, substitution of apoA-I with various amounts of apoA-II significantly increases the thermodynamic stability of the particle alpha-helical structure. ApoA-II also increases the size and net negative charge of the lipoprotein particles. ApoA-II directly affects apoA-I conformation and increases the immunoreactivity of epitopes in the N and C termini of apoA-I but decreases the exposure of central domains in the molecule (residues 98-186). ApoA-II appears to increase HL association with HDL and inhibits lipid hydrolysis. ApoA-II mildly inhibits PC hydrolysis in TG-enriched particles but significantly inhibits DG hydrolysis in DG-rich LpA-I. In addition, apoA-II enhances the ability of reconstituted LpA-I particles to inhibit VLDL-TG hydrolysis by HL. Therefore, apoA-II affects both the structure and the dynamic behavior of HDL particles and selectively modifies lipid metabolism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".