Inhibition of Lipolysis With Acipimox Attenuates Postburn White Adipose Tissue Browning and Hepatic Fat Infiltration
Why this work is in the frame
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Bibliographic record
Abstract
Extensive burn injuries promote an increase in the lipolysis of white adipose tissue (WAT), a complication that enhances postburn hypermetabolism contributing to hyperlipidemia and hepatic steatosis. The systemic increase of free fatty acids (FFAs) due to burn-induced lipolysis and subsequent organ fatty infiltration may culminate in multiple organ dysfunction and, ultimately, death. Thus, reducing WAT lipolysis to diminish the mobilization of FFAs may render an effective means to improve outcomes postburn. Here, we investigated the metabolic effects of Acipimox, a clinically approved drug that suppresses lipolysis via inhibition of hormone-sensitive lipase (HSL). Using a murine model of thermal injury, we show that specific inhibition of HSL with Acipimox effectively suppresses burn-induced lipolysis in the inguinal WAT leading to lower levels of circulating FFAs at 7 days postburn (P < 0.05). The FFA substrate shortage indirectly repressed the thermogenic activation of adipose tissue after injury, reflected by the decrease in protein expression of key browning markers, UCP-1 (P < 0.001) and PGC-1α (P < 0.01). Importantly, reduction of FFA mobilization by Acipimox significantly decreased liver weight and intracellular fat accumulation (P < 0.05), suggesting that it may also improve organ function postburn. Our data validate the pharmacological inhibition of lipolysis as a potentially powerful therapeutic strategy to counteract the detrimental metabolic effects induced by burn.
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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) | 0.000 | 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) | 0.000 | 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