Impact of uric acid on liver injury and intestinal permeability following resuscitated hemorrhagic shock in rats
Bibliographic record
Abstract
BACKGROUND: Multiorgan failure is a consequence of severe ischemia-reperfusion injury after traumatic hemorrhagic shock (HS), a major cause of mortality in trauma patients. Circulating uric acid (UA), released from cell lysis, is known to activate proinflammatory and proapoptotic pathways and has been associated with poor clinical outcomes among critically ill patients. Our group has recently shown a mediator role for UA in kidney and lung injury, but its role in liver and enteric damage after HS remains undefined. Therefore, the objective of this study was to evaluate the role of UA on liver and enteric injury after resuscitated HS. METHODS: A murine model of resuscitated HS was treated during resuscitation with a recombinant uricase, a urate oxidase enzyme (rasburicase; Sanofi-Aventis, Canada Inc, Laval, Canada), to metabolize and reduce circulating UA. Biochemical analyses (liver enzymes, liver apoptotic, and inflammatory markers) were performed at 24 hours and 72 hours after HS. Physiological testing for enteric permeability and gut bacterial product translocation measurement (plasma endotoxin) were performed 72 hours after HS. In vitro, HT-29 cells were exposed to UA, and the expression of intercellular adhesion proteins (ZO-1, E-cadherin) was measured to evaluate the influence of UA on enteric permeability. RESULTS: The addition of uricase to resuscitation significantly reduced circulating and liver UA levels after HS. It also prevented HS-induced hepatolysis and liver apoptotic/inflammatory mediators at 24 hours and 72 hours. Hemorrhagic shock-induced enteric hyperpermeability and endotoxemia were prevented with uricase. CONCLUSIONS: After resuscitated HS, UA is an important mediator in liver and enteric injury. Uric acid represents a therapeutic target to minimize organ damage in polytrauma patients sustaining HS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".