MITOCHONDRIAL METABOLISM IS PRESERVED FOLLOWING NORMOTHERMIC EX-VIVO KIDNEY PERFUSION OF GRAFTS PROCURED FOLLOWING CARDIAC DEATH
Bibliographic record
Abstract
Background: Normothermic ex-vivo kidney perfusion (NEVKP) preservation has demonstrated superior graft outcomes for kidneys procured following donation-after-cardiac death (DCD) over static cold storage (SCS). To determine the mechanisms for this advantage, we compared the transcriptome from both groups through an unbiased genome-wide microarray analysis. Methods: Kidneys from 30kg Yorkshire pigs were subjected to 30min of warm ischemia and then 8hrs of pressure-controlled NEVKP or SCS prior to heterotopic autotransplantation. Renal biopsies were collected on POD3 and RNA transcript expression was determined utilizing the Affymetrix GeneChip® Porcine Gene 1.0 ST Array platform examining over 23,000 transcripts. Gene set enrichment analysis (GSEA) was completed using the Hallmark gene sets and Gene Ontology (GO) pathways. Results: NEVKP-stored grafts demonstrated parameters associated with improved post-transplant graft function including lactate clearance (0hr:10.29+/-0.48mmol/L vs 8hr:1.67+/-0.67mmol/L,n=5,p<0.01), decreasing intra-renal resistance (0hr:1.63+/-0.20mmHg/mL/min vs 8hr:0.41+/-0.13 mmHg/mL/min,n=5,p<0.01), and continuous urine production. Graft function was significantly improved with NEVKP compared to SCS following transplantation with lower peak serum creatinine (POD1:4.0+/-1.15mg/dL vs POD3:12.0+/-0.78mg/dL,n=5,p<0.01) and higher creatinine clearance on POD3 (39.6+/-11.8mL/min vs 2.6+/-0.9ml/min,n=5,p<0.01). GSEA demonstrated 11 Hallmark Gene Sets enriched in NEVKP compared to SCS including sets associated with fatty-acid metabolism and oxidative phosphorylation, while 7 Gene Sets were enriched in SCS compared to NEVKP (FDR-value<0.25,p<0.05). GO analysis demonstrated pathways associated with lipid oxidation/metabolism, the Krebs cycle, and pyruvate metabolism enriched in NEVKP vs SCS (FDR-value<0.05) Conclusions: NEVKP maintained or enriched transcripts of key mitochondrial metabolic pathways compared to SCS in grafts procured following DCD, likely accounting for the improved post-transplant graft function.
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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 | 0.000 |
| 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 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".