Metabolic dysfunction in mice with adipocyte-specific ablation of the adenosine A2A receptor
Bibliographic record
Abstract
It has been well established that adenosine plays a key role in the control of inflammation through G protein coupled receptors and recently shown that it can regulate thermogenesis. Here we investigated the specific requirements of the adenosine A2A receptor (A2AR) in mature adipocytes for thermogenic functionality and metabolic homeostasis. We generated fat tissue-specific adenosine A2AR KO mice to assess the influence of signaling through this receptor on brown and beige fat functionality, obesity, insulin sensitivity, inflammation, and liver function. Fat-specific A2AR KO and WT littermate mice were compared for potential differences in cold tolerance and energy metabolism. In addition, we measured glucose metabolism, AT inflammation, and liver phenotypes in mice of the two genotypes after exposure to a diet rich in fat. Our results provide novel evidence indicating that loss of the adenosine A2AR specifically in adipocytes is associated with cold intolerance and decreased oxygen consumption. Furthermore, mice with fat specific ablation of the A2AR exposed to a diet rich in fat showed increased propensity to obesity, decreased insulin sensitivity, elevated adipose tissue inflammation, and hepato-steatosis and hepato-steatitis. Overall, our data provide novel evidence that A2AR in mature adipocytes safeguards metabolic homeostasis, suggesting the possibility of targeting this receptor selectively in fat for the treatment of metabolic disease.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".