The interplay of glucose-dependent insulinotropic polypeptide in adipose tissue
Bibliographic record
Abstract
Adipose tissue was once known as a reservoir for energy storage but is now considered a crucial organ for hormone and energy flux with important effects on health and disease. Glucose-dependent insulinotropic polypeptide (GIP) is an incretin hormone secreted from the small intestinal K cells, responsible for augmenting insulin release, and has gained attention for its independent and amicable effects with glucagon-like peptide 1 (GLP-1), another incretin hormone secreted from the small intestinal L cells. The GIP receptor (GIPR) is found in whole adipose tissue, whereas the GLP-1 receptor (GLP-1R) is not, and some studies suggest that GIPR action lowers body weight and plays a role in lipolysis, glucose/lipid uptake/disposal, adipose tissue blood flow, lipid oxidation, and free-fatty acid (FFA) re-esterification, which may or may not be influenced by other hormones such as insulin. This review summarizes the research on the effects of GIP in adipose tissue (distinct depots of white and brown) using cellular, rodent, and human models. In doing so, we explore the mechanisms of GIPR-based medications for treating metabolic disorders, such as type 2 diabetes and obesity, and how GIPR agonism and antagonism contribute to improvements in metabolic health outcomes, potentially through actions in adipose tissues.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".