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Record W1549214740 · doi:10.1186/1471-2482-4-9

Graft calcifications and dysfunction following liver transplantation

2004· article· en· W1549214740 on OpenAlexafffund
G. Tzimas, Mohammad Afshar, Éric Chevet, Anouk Emadali, Hojatollah Vali, Peter Metrakos

Bibliographic record

VenueBMC Surgery · 2004
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsMcGill UniversityRoyal Victoria HospitalRoyal Victoria Regional Health Centre
FundersCanadian Institutes of Health ResearchMcGill University Health CentreNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsMedicineCalcificationLiver transplantationLiver dysfunctionIschemiaTransplantationSurgeryCalcinosisHepatocytePathologyReperfusion injuryOrgan dysfunctionInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The molecular events, following ischemia and reperfusion (I/R) of the liver during transplantation are largely unknown. There is evidence that apoptotic and necrotic events may take place, and occasionally result in primary graft dysfunction. We herein report two cases, where significant I/R injury correlated with the development of liver calcification and primary liver dysfunction. CASE PRESENTATION: Both patients with clinical and biochemical evidence of primary graft dysfunction demonstrated calcification at light and electron microscopy levels. In addition, one patient had macroscopic evidence of calcification on cross-sectional imaging. Both patients died secondary to the sequelae of the graft dysfunction. CONCLUSIONS: Severe I/R-induced injury to the liver, clinically leads to graft dysfunction. This is due to advanced apoptotic and/or necrotic events at the hepatocyte level that may, on the most severe form, lead to calcification. The study of microcalcification at the early posttransplant period could provide insight in the events taking place following significant ischemia/reperfusion-induced injury to the graft.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.032
GPT teacher head0.271
Teacher spread0.238 · 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

Citations11
Published2004
Admission routes2
Has abstractyes

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