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The Epstein–Barr virus and post‐transplant lymphoproliferative disease: interplay of immunosuppression, EBV, and the immune system in disease pathogenesis

2001· review· en· W2059776126 on OpenAlexaff
Jerome E. Tanner, Caroline Alfieri

Bibliographic record

VenueTransplant Infectious Disease · 2001
Typereview
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsUniversité de MontréalChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsImmunosuppressionPathogenesisMedicineImmunologyLytic cycleTacrolimusEpstein–Barr virusDiseaseVirusImmune systemLymphoproliferative diseaseLymphoproliferative disordersAntibodyTransplantationVirologyLymphomaPathology

Abstract

fetched live from OpenAlex

Transplant patients are at particular risk for developing post-transplant lymphoproliferative disease (PTLD) following administration of immunosuppressive therapy. In many cases the PTLD lesions express Epstein-Barr virus (EBV) latent and lytic genes as well as elevated levels of host cytokines. An outline of the potential contributions of EBV, host cytokines and T cells, and the immunosuppressive cyclosporine A, tacrolimus, and anti-CD3 antibody in the mechanism and pathogenesis of this disease is presented and discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.007
GPT teacher head0.260
Teacher spread0.252 · 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

Citations125
Published2001
Admission routes1
Has abstractyes

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