Physiological roles of the GIP receptor in murine brown adipose tissue
Bibliographic record
Abstract
Objective Glucose-dependent insulinotropic polypeptide (GIP) is secreted from the gut in response to nutrient ingestion and promotes meal-dependent insulin secretion and lipid metabolism . Loss or attenuation of GIP receptor (GIPR) action leads to resistance to diet-induced obesity through incompletely understood mechanisms. The GIPR is expressed in white adipose tissue ; however, its putative role in brown adipose tissue (BAT) has not been explored. Methods We investigated the role of the GIPR in BAT cells in vitro and in BAT-specific ( Gipr BAT−/− ) knockout mice with selective elimination of the Gipr within the Myf5 + expression domain. We analyzed body weight , adiposity , glucose homeostasis , insulin and lipid tolerance, energy expenditure, food intake , body temperature, and iBAT oxygen consumption ex vivo . High-fat diet (HFD)-fed Gipr BAT−/− mice were studied at room temperature (21 °C), 4 °C, and 30 °C ambient temperatures. Results The mouse Gipr gene is expressed in BAT, and GIP directly increased Il6 mRNA and IL-6 secretion in BAT cells . Additionally, levels of thermogenic, lipid and inflammation mRNA transcripts were altered in BAT cells transfected with Gipr siRNA . Body weight gain , energy expenditure, and glucose and insulin tolerance were normal in HFD-fed Gipr BAT−/− mice housed at room temperature. However, Gipr BAT−/− mice exhibited higher body temperatures during an acute cold challenge and a lower respiratory exchange ratio and impaired lipid tolerance at 21 °C. In contrast, body weight was lower and iBAT oxygen consumption was higher in HFD-fed mice housed at 4 °C but not at 30 °C. Conclusions The BAT GIPR is linked to the control of metabolic gene expression, fuel utilization, and oxygen consumption. However, the selective loss of the GIPR within BAT is insufficient to recapitulate the findings of decreased weight gain and resistance to obesity arising in experimental models with systemic disruption of GIP action.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".