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Record W2747144209 · doi:10.1002/em.22117

DNA damage in kidney transplant patients. Role of organ origin

2017· article· en· W2747144209 on OpenAlexfundno aff
Zuray Corredor, Lara Rodríguez‐Ribera, Elisabet Coll, Irene Silva, Juan Manuel Díaz, José Ballarín, Ricard Marcos, Susana Pastor

Bibliographic record

VenueEnvironmental and Molecular Mutagenesis · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsnot available
FundersInstitute of Infection and ImmunityAgència de Gestió d'Ajuts Universitaris i de RecercaUniversitat de Barcelona
KeywordsDNA damageDNAKidneyOrgan transplantationBiologyGeneticsMedicineTransplantationInternal medicine

Abstract

fetched live from OpenAlex

Chronic kidney disease (CKD) patients are characterized by elevated levels of genomic damage. This damage increases when kidney function decreases being maximum in hemodialysis patients. As kidney transplantation improves renal function, and it is related with better survival, the aim of our study was to evaluate potential changes in DNA damage levels after kidney transplantation, and comparing living donor recipients with cadaveric donor recipients. The alkaline comet assay was used to determine DNA breaks and oxidative damaged DNA; and the micronucleus assay was used to determine chromosomal breakage and/or aneuploidy. Fifty CKD patients were followed up after 6 and 12 months of their kidney transplantation. All patients increased their genomic damage levels after 6 and 12 months of renal transplantation, compared with those observed before transplantation, despite of the improvement of their metabolic functions. Donor advanced age correlated positively with higher DNA damage. Genomic damage was lower in living donor transplants with respect to cadaveric donor transplants. Our conclusion is that DNA damage increased in kidney transplantation patients, whereas their renal function improved. Higher levels of DNA damage were found in cadaveric donor transplants when compared to living donor transplants. Environ. Mol. Mutagen. 58:712-718, 2017. © 2017 Wiley Periodicals, Inc.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.233
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.003
GPT teacher head0.189
Teacher spread0.186 · 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 teacher head, 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".

Quick stats

Citations5
Published2017
Admission routes1
Has abstractyes

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