313.6: Establishment of a genetic signature of ischemia reperfusion injury in a porcine pancreas transplantation model
Bibliographic record
Abstract
Toronto organ preservation laboratory. Introduction: Despite considerable advancement in surgical and immunological management in pancreas transplantation, graft pancreatitis remains a feared complication, occurring in 17-30% of cases after pancreas transplantation. Identification of molecular mechanisms of underlying ischemia reperfusion (IR) injury in pancreas transplantation could therefore pave the path for targeted therapy to improve surgical outcomes. The aim of the study was to identify the genes differentially expressed in the early period of graft reperfusion in porcine pancreas transplantation models. Methods: A porcine pancreas transplant model was used as outlined in Figure 1. Graft pancreatectomy in the donor and implantation in a recipient pig after 2hr cold storage. The native recipient pancreas was removed. The graft tissues were isolated from each experiment, in-vivo (Control 1), after 2 hours of cold storage (Control 2) and 60 mins after reperfusion (Test) and stored in (Ribonucleic acid) RNA later solution; RNA isolated using the Qiagen RNA lipid Mini easy kit, subjected to bio-analyser (Agilent Tech) and selected for microarray analysis using Porcine Gene1.0ST (Affymetrix). The gene sets were analysed using the Transcriptome analysis console (TAC, ThermoFisher ver 4.0.3.14) and g:Profiler and Cytoscape (ver 3.9.1), for gene otology (GO) and enrichment analysis respectively.Results: Four porcine pancreas transplants were performed. A total of 20 genes were found consistently upregulated and 2 downregulated in the test samples compared to the controls. The genes were mapped to the Mitogen activated protein (MAP) kinase signalling pathways (ATF3, THBS1, DUSP 1,5, 10), apoptotic signalling cascade (IL6, ZFP36, ANKRD1), Kreb’s cycle and oxidative phosphorylation (RFK, HMGCR) and intercellular adhesion and leucocyte activation (SELE, FOS), pathways mostly linked to IR injury (See Figure 2 for details). MIR21 gene, linked to micro-RNA pathway of IR injury (Myocardial ischemia model) was found significantly upregulated in the reperfusion tissues (Fold change 8.48; p<0.05, q <0.05). Messenger RNAs of COX7C (associated with oxidative phosphorylation) and POSTN (wound healing in myocardial ischemia models) were found consistently downregulated in the post-reperfusion and cold stored tissues respectively.Conclusion: The results provide new insights into molecular and biochemical pathways linked to pancreatic IR injury in experimental pancreas transplantation model. Targeting potential genes like HMGCR (linked to cholesterol biosynthesis and downstream isoprenylation pathway of inflammation) and IL6 (Apoptotic signalling cascade) could be promising in alleviating the tissue injury associated with IR and resultant graft pancreatitis after transplantation and offer potential targets for preconditioning grafts using normothermic machine perfusion. Lan He and Xiaolin Wang (The centre for applied genomics, Sick Kids, Toronto). References: 1. Drognitz O, Michel P, Koczan D, Neeff H, Mikami Y, Obermaier R, Thiesen HJ, Hopt UT, Loebler M. Characterization of ischemia/reperfusion-induced gene expression in experimental pancreas transplantation. Transplantation. 2006 May 27;81(10):1428-34. doi: 10.1097/01.tp.0000208619.71264.40. 2. Urbanellis P, McEvoy CM, Škrtić M, Kaths JM, Kollmann D, Linares I, Ganesh S, Oquendo F, Sharma M, Mazilescu L, Goto T, Noguchi Y, John R, Mucsi I, Ghanekar A, Bagli D, Konvalinka A, Selzner M, Robinson LA. Transcriptome Analysis of Kidney Grafts Subjected to Normothermic Ex Vivo Perfusion Demonstrates an Enrichment of Mitochondrial Metabolism Genes. Transplant Direct. 2021 Jul 8;7(8):e719. doi: 10.1097/TXD.0000000000001157. PMID: 34258386
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 0.001 |
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".