Remote Ischemic Preconditioning by Hindlimb Occlusion Prevents Liver Ischemic/Reperfusion Injury
Bibliographic record
Abstract
INTRODUCTION: Hepatocellular injury caused by ischemia-reperfusion of the liver occurs in a number of clinical situations including major trauma, elective surgery of the liver, and liver transplantation. Several strategies have been used to prevent liver injury following ischemia-reperfusion (I/R). Among these, ischemic preconditioning has shown promise as a preventative approach. In this manuscript, we hypothesized that use of remote ischemic preconditioning by brief hindlimb ischemia might prevent liver dysfunction in a mouse model of liver I/R. METHODS: C57/B mice were subjected to 60 minutes of partial liver ischemia with or without antecedent hindlimb vascular I/R. Blood was drawn for serum alanine aminotransferase levels at times following liver reperfusion. Liver inflammation was assessed by measuring serum and liver tumor necrosis factor (TNF)-alpha protein and mRNA. The role of toll-like receptor 4 (TLR4) in mediating protection was determined using the mouse strain HeJ, which has a mutated TLR4. RESULTS: Antecedent hindlimb ischemia (10 minutes) lessened I/R-induced elevation of serum alanine aminotransferase compared with untreated I/R animals. This protection correlated with a reduction in serum TNF-alpha protein levels as well as liver TNF-alpha mRNA and apoptosis. High Mobility Group-Box 1 (HMG-B1) levels in the blood were elevated after hindlimb ischemia and injection of HMG-B1 prior to liver recapitulated the protective effect of hindlimb occlusion. TLR4-mutant HeJ mice did not demonstrate protection with hindlimb preconditioning. CONCLUSIONS: Brief hindlimb occlusion prevents liver I/R injury. This effect appears to be related to release of HMG-B1 and is dependent on the presence of a functional TLR4. Remote ischemia preconditioning represents a novel approach to preventing distant organ injury.
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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".