Interleukin‐6 blockade, a potential adjunct therapy for post‐burn hypermetabolism
Bibliographic record
Abstract
Severe burns remain a leading cause of death and disability worldwide. Despite advances in patient care, the excessive and uncontrolled hypermetabolic stress response induced by this trauma inevitably affects every organ system causing substantial morbidity and mortality. Recent evidence suggests interleukin-6 (IL-6) is a major culprit underlying post-burn hypermetabolism. Indeed, genetic deletion of IL-6 alleviates various complications associated with poor clinical outcomes including the adverse remodeling of adipose tissue, cachexia and hepatic steatosis. Thus, pharmacological blockade of IL-6 may be a more favorable treatment option to fully restore metabolic function after injury. To test this, we investigated the safety and effectiveness of blocking IL-6 for post-burn hypermetabolism using a validated anti-IL-6 monoclonal antibody (mAb) in our experimental murine model. Here, we show daily anti-IL-6 mAb administration protects against burn-induced weight loss (P < .0001) without any adverse effect on mortality. At the organ level, post-burn treatment with the IL-6 blocker suppressed the thermogenic activation of adipose tissue (P < .01) and its associated wasting (P < .05). The reduction of browning-induced lipolysis (P < .0001) indirectly decreased hepatic lipotoxicity (P < .01) which improved liver dysfunction (P < .05). Importantly, the beneficial effects of this anti-IL-6 agent extended to the skin, reflected by the decrease in excessive collagen deposition (P < .001) and genes involved in pathologic fibrosis and scarring (P < .05). Together, our results indicate that post-burn IL-6 blockade leads to significant improvements in systemic hypermetabolism by inhibiting pathological alterations in key immunometabolic organs. These findings support the therapeutic potential of anti-IL-6 interventions to improve care, quality of life, and survival in burned patients.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".