Metformin prevents the pathological browning of subcutaneous white adipose tissue
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Browning, the conversion of white adipose tissue (WAT) to a beige phenotype, has gained interest as a strategy to induce weight loss and improve insulin resistance in metabolic disorders. However, for hypermetabolic conditions stemming from burn trauma or cancer cachexia, browning is thought to contribute to energy wasting and supraphysiological nutritional requirements. Metformin's impact on this phenomenon and underlying mechanisms have not been explored. METHODS: We used both a murine burn model and human ex vivo adipose explants to assess metformin and 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR)'s effects on the development of subcutaneous beige adipose. Enzymes involved in fat homeostasis and browning, as well as mitochondrial dynamics, were assessed to determine metformin's effects. RESULTS: Treatment with the biguanide metformin lowers lipolysis in beige fat by inducing protein phosphatase 2A (PP2A) independently of adenosine monophosphate kinase (AMPK) activation. Increased PP2A activity catalyzes the dephosphorylation of acetyl-CoA carboxylase (Ser 79) and hormone sensitive lipase (Ser 660), thus promoting fat storage and the "whitening" of otherwise lipolytic beige adipocytes. Moreover, co-incubation of metformin with the PP2A inhibitor okadaic acid countered the anti-lipolytic effects of this biguanide in human adipose. Additionally, we show that metformin does not activate this pathway in the WAT of control mice and that AICAR sustains the browning of white adipose, offering further evidence that metformin acts independently of this cellular energy sensor. CONCLUSIONS: This work provides novel insights into the mechanistic underpinnings of metformin's therapeutic benefits and potential as an agent to reduce the lipotoxicity associated with hypermetabolism and adipose browning.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it