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Record W4392133702 · doi:10.1016/j.heliyon.2024.e27122

Mitochondrial DNA levels in perfusate and bile during ex vivo normothermic machine correspond with donor liver quality

2024· article· en· W4392133702 on OpenAlexafffund
Lauren P. Westhaver, Sarah Nersesian, Riley J. Arseneau, Joshua Hefler, Breanna K.V. Hargreaves, Alexander Edgar, Yara Azizieh, Nerea Cuesta‐Gomez, Dayne L. Izquierdo, A. M. James Shapiro, Boris Gala-López, Jeanette E. Boudreau

Bibliographic record

VenueHeliyon · 2024
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsUniversity of AlbertaBeatrice Hunter Cancer Research InstituteDalhousie University
FundersBreakthrough T1D CanadaCanadian Institutes of Health ResearchAstellas PharmaKillam TrustsDalhousie UniversityBeatrice Hunter Cancer Research InstituteCanadian Liver FoundationUniversity of AlbertaAstellas Pharma CanadaCanadian Blood ServicesDartmouth CollegeResearch Nova ScotiaCancer Research Institute
KeywordsEx vivoIn vivoMitochondrial DNADNAMolecular biologyBiologyChemistryMedicineBiochemistryGeneticsGene

Abstract

fetched live from OpenAlex

normothermic machine perfusion (NMP) preserves donor organs and permits real-time assessment of allograft health, but the most effective indicators of graft viability are uncertain. Mitochondrial DNA (mtDNA), released consequent to traumatic cell injury and death, including the ischemia-reperfusion injury inherent in transplantation, may meet the need for a biomarker in this context. We describe a real time PCR-based approach to assess cell-free mtDNA during NMP as a universal biomarker of allograft quality. Measured in the perfusate fluid of 29 livers, the quantity of mtDNA correlated with metrics of donor liver health including International Normalized Ratio (INR), lactate, and warm ischemia time, and inversely correlated with inferior vena cava (IVC) flow during perfusion. Our findings endorse mtDNA as a simple and rapidly measured feature that can inform donor liver health, opening the possibility to better assess livers acquired from extended criteria donors to improve organ supply.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.287
Teacher spread0.269 · 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 designObservational
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".

Quick stats

Citations9
Published2024
Admission routes2
Has abstractyes

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