Lecithin:cholesterol acyltransferase: symposium on 50 years of biomedical research from its discovery to latest findings
Bibliographic record
Abstract
LCAT converts free cholesterol to cholesteryl esters in the process of reverse cholesterol transport. Familial LCAT deficiency (FLD) is a genetic disease that was first described by Kaare R. Norum and Egil Gjone in 1967. This report is a summary from a 2017 symposium where Dr. Norum recounted the history of FLD and leading experts on LCAT shared their results. The Tesmer laboratory shared structural findings on LCAT and the close homolog, lysosomal phospholipase A2. Results from studies of FLD patients in Finland, Brazil, Norway, and Italy were presented, as well as the status of a patient registry. Drs. Kuivenhoven and Calabresi presented data from carriers of genetic mutations suggesting that FLD does not necessarily accelerate atherosclerosis. Dr. Ng shared that LCAT-null mice were protected from diet-induced obesity, insulin resistance, and nonalcoholic fatty liver disease. Dr. Zhou presented multiple innovations for increasing LCAT activity for therapeutic purposes, whereas Dr. Remaley showed results from treatment of an FLD patient with recombinant human LCAT (rhLCAT). Dr. Karathanasis showed that rhLCAT infusion in mice stimulates cholesterol efflux and suggested that it could also enhance cholesterol efflux from macrophages. While the role of LCAT in atherosclerosis remains elusive, the consensus is that a continued study of both the enzyme and disease will lead toward better treatments for patients with heart disease and FLD.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".