Burn Plus Lipopolysaccharide Augments Endoplasmic Reticulum Stress and NLRP3 Inflammasome Activation and Reduces PGC-1α in Liver
Bibliographic record
Abstract
Extensively burned patients often suffer from sepsis (especially caused by Pseudomonas aeruginosa), which may prolong metabolic derangement, contribute to multiple organ failure, and increase mortality. The molecular and cellular mechanisms of such infection-related metabolic derangement and organ dysfunction are unclear. We have previously shown that severely burned patients have significant and persisting hepatic endoplasmic reticulum (ER) stress. We hypothesized that ER stress and the unfolded protein response correlate with NOD-like receptor, pyrin domain containing 3 (NLRP3) inflammasome activation in burn. These may trigger profound metabolic changes in the liver, which form the pathological basis of liver damage and liver dysfunction after burn injury. A two-hit rat model was established by a 60% total body surface area scald burn and intraperitoneal injection of P. aeruginosa-derived lipopolysaccharide (LPS) 3 days after burn. One day later, animals were killed, and liver tissue samples were collected for gene expression and protein analysis of NLRP3 inflammasome activation, ER stress, and glucose and lipid metabolism. Liver damage was assessed by plasma markers (alanine aminotransferase and aspartate aminotransferase) and liver immunohistochemical analysis. Our results showed that burn injury and LPS injection induced inflammasome activation in liver and augmented hepatic ER stress and liver damage. Although there was an increased metabolic demand after burn, hepatic NLRP3 inflammasome activation corresponded to inhibition of PGC-1α (peroxisome proliferator-activated receptor γ-coactivator 1α) and its upstream regulators protein kinase A catalyst unit, AMP-activated protein kinase α, and sirtuin-1 may provide a mechanism for the enhanced metabolic derangement after major burn injury plus sepsis. In conclusion, burn + LPS augments inflammasome activation and ER stress in liver, which in turn contribute to postburn metabolic derangement.
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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 | 0.000 | 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) | 0.001 | 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 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".