Effect of Alcohol on Lipoprotein Metabolism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The mechanism by which alcohol increases plasma total high density lipoproteins (HDLs) and HDL-cholesterol is unknown, but it may involve modulation of the lipolytic enzymes, hepatic triglyceride lipase (HTGL) and/or lipoprotein lipase (LPL) in hepatic and extrahepatic tissues. The modulation of HDL metabolism by alcohol may also be related to its potential to induce mixed function oxidases in liver microsomes. These possibilities were examined by a pair-feeding protocol in which rats were fed diets with 35% of the caloric content as ethanol; control groups received a diet with an isocaloric amount of sucrose or were fed chow ad libitum. Alcohol caused a significant decrease in HTGL activity of liver microsomes, but there was no significant effect of alcohol upon the activities of LPL in adipose tissue and heart muscle. The relative rates of mixed function oxidases, assayed in control liver microsomes using ethoxy-,pentoxy- and benzyloxy-resorufin as substrates, were benzyloxy greater than ethoxy greater than pentoxy. This order was not affected by alcohol, but the oxidation of ethoxy- and pentoxyresorufin was reduced in liver microsomes from the ethanol-fed group. HTGL synthesis and secretion were also measured using primary rat hepatocyte cultures isolated from animals on the above dietary regimes and maintained for up to 3 days in basal medium alone or supplemented with 10 mmol/l ethanol. In basal media the order of activity of extracellular HTGL, released by the addition of heparin, was sucrose-fed greater than chow-fed greater than ethanol-fed. The rate of HTGL secretion from hepatocytes was stimulated in ethanol-containing medium, and was greater in hepatocytes from the sucrose-fed controls.(ABSTRACT TRUNCATED AT 250 WORDS)
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 it