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Record W2473960746 · doi:10.5858/arpa.2015-0120-rs

Epstein-Barr Virus–Associated Smooth Muscle Tumor

2016· review· en· W2473960746 on OpenAlexaff
Jyoti Dekate, Runjan Chetty

Bibliographic record

VenueArchives of Pathology & Laboratory Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsVirusSmooth Muscle TumorEpstein–Barr virusBiologyPathologyGammaherpesvirinaeVirologySarcomaNeoplasmMalignant transformationEpstein–Barr virus infectionImmunologyHerpesviridaeViral diseaseCancer researchMedicineImmunohistochemistry

Abstract

fetched live from OpenAlex

Immunodeficient individuals are prone to develop a number of opportunistic infections and unique neoplasms. Epstein-Barr virus-associated smooth muscle tumor is an uncommon neoplasm associated with immunodeficiency. It has been described in patients infected with human immunodeficiency virus, in the posttransplant setting, and in those with congenital immunodeficiency. Different anatomic sites can be involved by Epstein-Barr virus-associated smooth muscle tumor, and even multiple locations can contain these unique lesions within the same patient. The presence of variable numbers of intratumoral lymphocytes and primitive round cell areas are the unique defining features for this tumor. Histopathologic features may vary considerably in terms of cellular atypia, mitotic activity, and necrosis, with no correlation to the clinical behavior. Demonstration of Epstein-Barr virus infection by in situ hybridization within tumor cell remains critical for the diagnosis. The mechanism for Epstein-Barr virus infection of progenitor cells and neoplastic transformation has been an area of interest and conjecture. Different treatment strategies are proposed according to underlying disease status. This paper reviews the clinicopathologic features of this uncommon neoplasm with detailed discussion of the role of Epstein-Barr virus in the pathogenesis.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.309
Teacher spread0.289 · 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.

Study designOther design
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

Citations73
Published2016
Admission routes1
Has abstractyes

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