Interaction of Lecithin:Cholesterol Acyltransferase (LCAT)·α2-Macroglobulin Complex with Low Density Lipoprotein Receptor-related Protein (LRP)
Bibliographic record
Abstract
The reaction of lecithin:cholesterol acyltransferase (LCAT) with high density lipoproteins (HDL) is of critical importance in reverse cholesterol transport, but the structural and functional pathways involved in the regulation of LCAT have not been established. We present evidence for the direct binding of LCAT to alpha(2)-macroglobulin (alpha(2)M) in human plasma to form a complex 18.5 nm in diameter. Forty percent of plasma LCAT-HDL was associated with alpha(2)M; moreover, most of the LCAT in cerebrospinal fluid and in the medium of cultured human hepatoma cell line was associated with alpha(2)M. Purified recombinant human LCAT (rLCAT) labeled with (125)I bound to native and methylamine-activated alpha(2)M (alpha(2)M-MA) in vitro in a time- and concentration-dependent manner, and this binding did not depend on the presence of lipid. rLCAT bound to alpha(2)M-MA with greater affinity than to alpha(2)M. Furthermore, rLCAT did not activate alpha(2)M as phosphatidylcholine-specific phospholipase C does. Reconstituted HDL particles (LpA-I) inhibited the binding of rLCAT to alpha(2)M more efficiently than native HDL(3) did. LCAT associated with alpha(2)M was enzymatically inactive under both endogenous and exogenous assay conditions. Purified rLCAT alone did not bind to low density lipoprotein receptor-related protein (LRP) as lipoprotein lipase (LPL) does; however, when rLCAT was combined with alpha(2)M-MA to form a complex, binding, internalization, and degradation of rLCAT took place in LRP-expressing cells (LRP (+/+)) but not in cells deficient in LRP (LRP (-/-)). It is concluded that the binding of LCAT to alpha(2)M inhibits its enzymatic activity. Furthermore, the finding supports the possibility that the LRP receptor can act in vivo to mediate clearance of the LCAT-alpha(2)M complex and may significantly influence the bioavailability of LCAT.
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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 | 0.000 |
| 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".