48 Metformin Rescues the Aging-induced Failure of Post-burn White Adipose Browning
Bibliographic record
Abstract
Abstract Introduction Severe burns are responsible for an estimated 300,000 deaths per year worldwide. While modern burn care has markedly improved survival for pediatric and adult patients, this is sadly not the case for one population: the elderly. Despite being the fastest-growing demographic in North America, burn patients over the age of 60 years have the highest mortality and morbidity rates. Recent evidence suggests that progressive aging induces several structural and functional alterations which impair the capacity of older trauma patients to adequately respond to stress. Indeed, it was discovered that reduced survival in elderly burn patients is associated with the failure to initiate the browning of white adipose tissue (WAT) —a hallmark of the systemic response to injury commonly observed in adults. Interestingly, the widely used hypoglycemic drug metformin has been found to protect against aging-induced metabolic decline in various pathological conditions. Thus, we investigated the anti-aging effects of metformin on the metabolic deterioration of post-burn WAT responses in elderly patients and mice after injury. Methods Human WAT was obtained from elderly patients admitted to our burn center. Elderly (75-week) mice received a full-thickness scald burn and/or daily intraperitoneal injections of metformin (100 mg/kg) for 7 days. The inguinal WAT was harvested for histological analyses. Mitochondrial respiration was measured via Seahorse XF96. Gene and protein expression was assessed via RT-PCR and western blot, respectively. Results Post-burn metformin treatment restores the thermogenic activation of WAT in elderly patients and mice, reflected by the increased expression of key browning markers, UCP-1 and PGC-1α (p< 0.05). This was accompanied by higher mitochondrial respiration, improved lipolysis (p< 0.05) and increased fat wasting (p< 0.01) relative to control counterparts. The anti-aging effects of metformin appeared to be mediated by AMPK, which consequently increased [NAD+] (p< 0.01), thereby promoting activation of the longevity-specific enzyme Sirt-1 (p< 0.05). Conclusions Here, we show that post-burn metformin treatment effectively rejuvenates adaptive metabolic responses in elderly WAT by targeting key longevity pathways which rescue the age-dependent loss of being back to youthful levels. Our findings support the potential of anti-aging modalities to improve care and outcomes in elderly burned patients.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".