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Normothermic Ex-Vivo Kidney Perfusion Restores the Genetic Profile of Marginal Kidney Grafts Subjected to Warm Ischemia

2018· article· en· W2884038446 on OpenAlexaff
Peter Urbanellis, Mátyás Hamar, Moritz Kaths, Ivan Linares, Dagmar Kollmann, Sujani Ganesh, Rohan John, Paul S. F. Yip, István Mucsi, Anand Ghanekar, Darius Bägli, Ana Konvalinka, David Grant, Lisa A. Robinson, Markus Selzner

Bibliographic record

VenueTransplantation · 2018
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsHospital for Sick ChildrenUniversity Health Network
Fundersnot available
KeywordsEx vivoPerfusionKidneyRenal functionKidney transplantationMedicineUrologyIschemiaTransplantationCreatinineMachine perfusionIn vivoCold storageAndrologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Background Increasing evidence demonstrates the superiority of normothermic ex-vivo kidney perfusion (NEVKP) over cold storage (CS) for grafts sensitive to ischemia-reperfusion injury, including kidneys procured following donation-after-cardiac-death (DCD). To account for this improvement, we investigated whether NEVKP-preservation returns the genetic profiles of DCD grafts to that of unmanipulated naïve kidneys. Methods Kidneys from 30kg Yorkshire pigs were removed following 30 minutes of warm ischemia in a model of DCD. These grafts were then stored in either static cold histidine-tryptophan-ketoglutarate solution (CS) or subjected to pressure-controlled NEVKP for 8 hours prior to heterotopic autotransplantation. Kidney biopsies were collected on POD3 and gene expression was compared with naïve porcine kidneys utilizing the Affymetrix GeneChip® Porcine Gene 1.0 ST Array platform examining over 23,000 transcripts. Validation was performed using quantitative real-time polymerase chain reaction. Results During NEVKP storage, DCD grafts demonstrated favourable perfusion characteristics including progressive lactate clearance (0hr: 10.29 +/-0.48 mmol/L vs 8hr: 1.67+/-0.67 mmol/L, n=5, P<0.01), decreasing intra-renal resistance (0hr:1.63+/-0.20 mmHg/mL/min vs 8hr:0.41+/-0.13 mmHg/mL/min, n=5, p<0.01), and continuous urine production. Post-transplantation graft function significantly improved with NEVKP compared to CS with decreased 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). Genomic comparison of grafts subjected to NEVKP on POD3 showed significant differences in only 27 genes when compared to naïve porcine kidneys (Table 1, >±2-fold changes in expression over naïve, n=3, P<0.05, FDR p-value<0.20). In contrast, 668 genes were significantly differentially expressed between grafts stored with CS on POD3 and naïve kidneys (Table 2, >±2-fold changes in expression over naïve, n=3, P<0.05, FDR p-value<0.20).Conclusions NEVKP restored damaged kidney grafts in a model of DCD with a genomic profile closely resembling naïve kidneys. Conversely, ongoing injury was evident in DCD grafts following CS through increased expression of genes related to inflammation, apoptosis, and repair. Together, these findings support the use of NEVKP for storage of DCD grafts that are more susceptible to ischemia-reperfusion injury.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.267
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2018
Admission routes1
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