Mitochondrial Transplantation Reduces Injury and Improves Liver Function in a Porcine Model of Hemi-hepatic Ischemia/Reperfusion
Bibliographic record
Abstract
OBJECTIVE: To assess mitochondrial transplantation (MitoTx) via portal vein infusion to reduce liver ischemia-reperfusion injury (I/R) in a survival porcine model. SUMMARY BACKGROUND DATA: MitoTx has been shown to alleviate I/R injury in various organs. METHODS: Male Yorkshire pigs (38±1 kg) were subjected to 2 hours of ischemia in the left hemi-liver (left portal-triad clamping), and at the beginning of reperfusion (marked as t=0 h), animals received a 1-hour infusion of autologous mitochondria (MT, 7×10^9/kg) or saline (controls) via the portal vein. Liver tissue oxygen saturation (sO 2 ) was assessed by photoacoustic imaging. RESULTS: Twelve pigs (6 MitoTx vs. 6 controls) underwent 2-hour left hemi-liver I/R. All pigs recovered and were ambulatory at t=6 hours. MitoTx reduced peak AST levels at t=2 hours compared with controls (299.83±46.62 vs. 878.83±255.09 UI/L; P =0.049). At t=24 hours, MitoTx pigs had lowered necrosis area percentage (8.01±4.12 vs. 23.40±7.33 %; P =0.08) in left livers-all right lobes had 0% necrotic area. MitoTx pigs had shorter prothrombin time, plateauing around t=8 hours (12.9±0.3 vs. 14.1±0.1 s; P =0.003), faster lactate clearance (<2 mmol/L) from the blood [HR: 1.3, (1.1, 1.7); P =0.003] and from the bile [HR: 1.4, (1.1, 1.7); P =0.009] compared with controls. At t=6 hours, MitoTx pigs had decreased IL-6 (304±71 vs. 686±87 pg/mL; P =0.007). Photoacoustic imaging showed that MitoTx pigs had a better recovery of sO 2 from baseline in left livers compared with controls (at t=30 min; -3.05±2.72 vs. -15.19±2.92 %; P =0.016). CONCLUSION: MitoTx reduces injury and improves liver function after prolonged liver I/R, showing promise for liver transplantation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".