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Record W2799884370 · doi:10.3389/fimmu.2018.01130

Endothelial Dysfunction in Kidney Transplantation

2018· review· en· W2799884370 on OpenAlexafffund
Héloïse Cardinal, Mélanie Dieudé, Marie‐Josée Hébert

Bibliographic record

VenueFrontiers in Immunology · 2018
Typereview
Languageen
FieldMedicine
TopicRenal and Vascular Pathologies
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersCanadian Institutes of Health ResearchUniversité de MontréalKidney Foundation of Canada
KeywordsEndothelial dysfunctionMedicineTransplantationKidney transplantationImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Kidney transplantation entails a high likelihood of endothelial injury. The endothelium is a target of choice for injury by ischemia-reperfusion, alloantibodies, and autoantibodies. A certain degree of ischemia-reperfusion injury inevitably occurs in the immediate posttransplant setting and can manifest as delayed graft function. Acute rejection episodes, whether T-cell or antibody-mediated, can involve the graft micro- and macrovasculature, leading to endothelial injury and adverse long-term consequences on graft function and survival. In turn, caspase-3 activation in injured and dying endothelial cells favors the release of extracellular vesicles (apoptotic bodies and apoptotic exosome-like vesicles) that further enhance autoantibody production, complement deposition, and microvascular rarefaction. In this review, we present the evidence for endothelial injury, its causes and long-term consequences on graft outcomes in the field of kidney transplantation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.026
GPT teacher head0.289
Teacher spread0.263 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations77
Published2018
Admission routes2
Has abstractyes

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