Hematopoietic AMPK β1 reduces mouse adipose tissue macrophage inflammation and insulin resistance in obesity
Bibliographic record
Abstract
Individuals who are obese are frequently insulin resistant, putting them at increased risk of developing type 2 diabetes and its associated adverse health conditions. The accumulation in adipose tissue of macrophages in an inflammatory state is a hallmark of obesity-induced insulin resistance. Here, we reveal a role for AMPK β1 in protecting macrophages from inflammation under high lipid exposure. Genetic deletion of the AMPK β1 subunit in mice (referred to herein as β1(-/-) mice) reduced macrophage AMPK activity, acetyl-CoA carboxylase phosphorylation, and mitochondrial content, resulting in reduced rates of fatty acid oxidation. β1(-/-) macrophages displayed increased levels of diacylglycerol and markers of inflammation, effects that were reproduced in WT macrophages by inhibiting fatty acid oxidation and, conversely, prevented by pharmacological activation of AMPK β1-containing complexes. The effect of AMPK β1 loss in macrophages was tested in vivo by transplantation of bone marrow from WT or β1(-/-) mice into WT recipients. When challenged with a high-fat diet, mice that received β1(-/-) bone marrow displayed enhanced adipose tissue macrophage inflammation and liver insulin resistance compared with animals that received WT bone marrow. Thus, activation of AMPK β1 and increasing fatty acid oxidation in macrophages may represent a new therapeutic approach for the treatment of insulin resistance.
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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 | 0.001 | 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) | 0.002 | 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".