Activation of Lipoprotein Lipase by Glucose-dependent Insulinotropic Polypeptide in Adipocytes
Bibliographic record
Abstract
Glucose-dependent insulinotropic polypeptide (GIP) has been mainly studied because of its glucose-dependent insulinotropic action and its ability to regulate beta-cell proliferation and survival. Considerably less is known about the effects of GIP on fat metabolism, and the present study was directed at identifying the mechanisms underlying its stimulatory action on lipoprotein lipase (LPL). In differentiated 3T3-L1 adipocytes, GIP, in the presence of insulin, increased LPL activity and triglyceride accumulation through a pathway involving increased phosphorylation of protein kinase B (PKB) and reductions in phosphorylated LKB1 and AMP-activated protein kinase (AMPK). Knockdown of AMPK using RNA interference and application of the AMPK inhibitor, Compound C, supported this conclusion. In contrast, the other major incretin hormone, glucagon-like peptide-1, exhibited no significant effects on LPL activity or PKB, LKB1, or AMPK phosphorylation. Cultured subcutaneous human adipocytes showed similar responses to GIP but with greater sensitivity. Chronic elevation of circulating GIP levels in the Vancouver diabetic fatty Zucker rat in vivo resulted in increased LPL activity and elevated triglyceride accumulation in epididymal fat tissue, combined with a modulation of PKB, LKB1, and AMPK phosphorylation similar to that observed in vitro. This appears to be the first demonstration of a GIP-stimulated signal transduction pathway involved in increasing fat storage in adipocytes.
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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 | 0.001 |
| 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".