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Record W2801002328 · doi:10.1002/lary.27207

Human papillomavirus: An unlikely etiologic factor in sinonasal inverted papilloma

2018· article· en· W2801002328 on OpenAlexaff
Sepideh Mohajeri, Chi Lai, Bibianna Purgina, Dakheelallah Almutairi, Tabassom Baghai, Jim Dimitroulakos, Shaun Kilty

Bibliographic record

VenueThe Laryngoscope · 2018
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Surgical Oncology
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineInverted papillomaHuman papillomavirusImmunohistochemistryPapillomaBasal cellHPV infectionEtiologyPolymerase chain reactionBiomarkerPathologyHuman papilloma virusCarcinomaOncologyCancer researchInternal medicineCancerCervical cancerBiologyGene

Abstract

fetched live from OpenAlex

OBJECTIVES/HYPOTHESIS: Tenuous evidence has supported the hypothesis that sinonasal inverted papilloma (SNIP) arise from human papillomavirus (HPV) infection. To clarify the role of HPV in SNIP, all known HPV sub-types were evaluated by employing a robust polymerase chain reaction-based method in a wide variety of SNIPs from a single institution. STUDY DESIGN: Retrospective surgical specimen tumor sample analysis. METHODS: HPV positivity among SNIP samples and those with squamous cell carcinoma (SCC) were compared. Immunohistochemistry was used to quantify p16 (over)expression among tumors as a surrogate marker for HPV. RESULTS: HPV was detected in 10/76 (13%) SNIP specimens. Identified HPV subtypes included nononcogenic 6 and 11 (6/76, 8%) and oncogenic 16, 18, 45, 56 (4/76, 5%). There was no HPV positivity among SCC samples. Only 4/10 (40%) HPV + samples had > 75% p16 cell staining. CONCLUSION: HPV is not supported as an etiological driver of SNIP development or progression to SCC. The p16 biomarker is not a sensitive indicator of HPV positivity in SNIP. LEVEL OF EVIDENCE: NA Laryngoscope, 2443-2447, 2018.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.001

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 head0.057
GPT teacher head0.359
Teacher spread0.302 · 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 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

Citations36
Published2018
Admission routes1
Has abstractyes

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