Intestinal Lipoprotein Overproduction, a Newly Recognized Component of Insulin Resistance, Is Ameliorated by the Insulin Sensitizer Rosiglitazone: Studies in the Fructose-Fed Syrian Golden Hamster
Bibliographic record
Abstract
We investigated whether intestinal lipoprotein overproduction in a fructose-fed, insulin-resistant hamster model is prevented with insulin sensitization. Syrian Golden hamsters were fed either chow, 60% fructose for 5 wk, chow for 5 wk with the insulin sensitizer rosiglitazone added for the last 3 wk, or 60% fructose plus rosiglitazone. In vivo Triton studies showed a 2- to 3-fold increase in the large (Svedberg unit > 400) and smaller (Sf 100-400) triglyceride-rich lipoprotein particle apolipoprotein B48 (apoB48) but not triglyceride secretion with fructose feeding in the fasted state (P < 0.01) and partial normalization with rosiglitazone in fructose-fed hamsters. Ex vivo pulse-chase labeling of enterocytes confirmed the oversecretion of apoB48 lipoproteins with fructose feeding. Intestinal lipoprotein oversecretion was associated with increased expression of microsomal triglyceride transfer protein expression. With rosiglitazone treatment of fructose-fed hamsters, there was approximately 50% reduction in apoB48 secretion from primary cultured enterocytes and amelioration of the elevated microsomal triglyceride transfer protein mass and activity in fructose-fed hamsters. In contrast, in the postprandial state, the major differences between nutritional and drug intervention protocols were evident in triglyceride-rich lipoprotein triglyceride and not apoB48 secretion rates. The data suggest that intestinal lipoprotein overproduction can be ameliorated with the insulin sensitizer rosiglitazone.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".