Glucose-dependent insulinotropic polypeptide directly induces glucose transport in rat skeletal muscle
Bibliographic record
Abstract
Several gastrointestinal proteins have been identified to have insulinotropic effects, including glucose-dependent insulinotropic polypeptide (GIP); however, the direct effects of incretins on skeletal muscle glucose transport remain largely unknown. Therefore, the purpose of the current study was to examine the role of GIP on skeletal muscle glucose transport and insulin signaling in rats. Relative to a glucose challenge, a mixed glucose+lipid oral challenge increased circulating GIP concentrations, skeletal muscle Akt phosphorylation, and improved glucose clearance by ∼35% (P < 0.05). These responses occurred without alterations in serum insulin concentrations. In an incubated soleus muscle preparation, GIP directly stimulated glucose transport and increased GLUT4 accumulation on the plasma membrane in the absence of insulin. Moreover, the ability of GIP to stimulate glucose transport was mitigated by the addition of the PI 3-kinase (PI3K) inhibitor wortmannin, suggesting that signaling through PI3K is required for these responses. We also provide evidence that the combined stimulatory effects of GIP and insulin on soleus muscle glucose transport are additive. However, the specific GIP receptor antagonist (Pro(3))GIP did not attenuate GIP-stimulated glucose transport, suggesting that GIP is not signaling through its classical receptor. Together, the current data provide evidence that GIP regulates skeletal muscle glucose transport; however, the exact signaling mechanism(s) remain unknown.
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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 | 0.000 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".