DEFECTIVE GLYCOSYLATION OF CHOLESTERYL ESTER TRANSFER PROTEIN IN PLASMA FROM ALCOHOL ABUSERS
Bibliographic record
Abstract
AIMS: Alcohol consumption reduces the carbohydrate content of some glycoproteins, e.g. carbohydrate-deficient transferrin. The aim of this study was to investigate if there is such an alcohol-induced glycosylation defect in plasma cholesteryl ester transfer protein (CETP). A defect in the posttranslational glycosylation of CETP may affect its structure and electrical charge and may therefore affect its function. CETP activity is low in alcohol abusers. METHODS: We studied the effect of alcohol consumption on CETP properties in 10 alcohol abusers and 10 control subjects. CETP was partially purified from lipoprotein-free plasma by FPLC using a Phenyl-Sepharose column. Isoelectric focusing, polyacrylamide gel electrophoresis, and western blotting were performed for partially purified CETP. RESULTS: CETP had a lower molecular weight in the alcohol abusers than in the controls (range 50.6-84.0 kDa in the alcohol abusers vs 51.3-85.0 kDa in the controls). CETP purified from alcohol abusers had a higher isoelectric point, indicating a lower negative charge on the surface of the protein than in the controls' CETP. A similar effect was observed when control CETP was incubated with neuraminidase, an enzyme which is known to remove sialic acid from glycoproteins. CONCLUSIONS: We conclude that CETP from alcohol abusers may have a glycosylation defect due to defective sialylation caused posttranslationally by alcohol itself or its metabolite acetaldehyde. The defective glycosylation of CETP associated with altered binding to lipoproteins may lead to the low CETP activity observed previously in alcoholic subjects.
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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 | 0.001 | 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".