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Record W2165416416 · doi:10.1002/hed.22942

Significant overexpression of the Merkel cell polyomavirus (MCPyV) large T antigen in Merkel cell carcinoma

2012· article· en· W2165416416 on OpenAlexaff
Boban M. Erović, Ayman Al Habeeb, Luke Harris, David P. Goldstein, Danny Ghazarian, Jonathan C. Irish

Bibliographic record

VenueHead & Neck · 2012
Typearticle
Languageen
FieldMedicine
TopicPolyomavirus and related diseases
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMerkel cell polyomavirusMerkel cell carcinomaImmunohistochemistryMerkel cellTissue microarrayPathologyBiologyAntigenPolyomavirus InfectionsPathologicalCarcinomaCancer researchMedicineImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: The purpose of this study was to determine the expression pattern of the Merkel cell polyomavirus (MCPyV) large T-protein antigen in patients with Merkel cell carcinoma. METHODS: A tissue microarray (TMA) containing 30 specimens was constructed and stained for the MCPyV large T protein. Immunohistochemical expression was determined semiquantitively and was compared to patients' outcome. RESULTS: Nuclear expression of MCPyV large T protein was detected in 29 of 30 specimens (97%). In particular, 60% to 100%, 30% to 60%, and 10% to 30% of tumor cells were positive in 27 specimens (90%), 1 (3%), and 1 (3%), respectively. There was no difference in positivity between primary and metastatic lesions. Clinical data could not be correlated to MCPyV large T-protein expression. CONCLUSION: MCPyV large T protein was significantly overexpressed in 97% of all specimens. Although we could not demonstrate a predictive effect, MCPyV large T protein may represent a molecular marker with utility in pathological diagnosis as well as a potential new therapeutic target in patients with Merkel cell carcinoma.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.669

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 head0.016
GPT teacher head0.267
Teacher spread0.251 · 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 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

Citations35
Published2012
Admission routes1
Has abstractyes

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