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The Cellient System for Cytohistology to Analyze p16 Positive Dyskeratocytes in Paraffin Sections of HPV-Positive Cervical Scrapes

2012· article· en· W2049900846 on OpenAlexaffvenue
Mathilde E. Boon, Joke Dols, Nicodemus L. Butamanya, Gregor Reid

Bibliographic record

VenueJournal of Analytical Oncology · 2012
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsAscus (bryozoa)Papanicolaou stainMedicineSquamous intraepithelial lesionPapanicolaou TestHistologyHPV infectionLesionPathologyCervical cancerCervical intraepithelial neoplasiaInternal medicineCancerBiology

Abstract

fetched live from OpenAlex

The Cellient™ Automated Cell Block System (Hologic) can be used to analyze cells of HPV-positive cervical scrapes staining positive with the biomarker p16. For this study fourteen cervical scrapes of Tanzanian women infected with HIV testing positive for HPV were selected. The paraffin Cellient sections were stained with the Papanicolaou method, with hematoxylin eosin (HE), and with the biomarker p16. This pilot study was limited to cases classified as atypical squamous lesion of unknown significance (ASCUS) and high-grade squamous lesion (HSIL) as diagnosed in the ThinPrep slide. The Cellient paraffin sections (cut from paraffin blocks prepared from the residual cervical sample) were classified into negative, atypical, CIN 1, CIN 2, and CIN 3. Multiple HPV genotypes were encountered in 79% of the scrapes. HPV16 was found in six scrapes and HPV52 in four. In the Papanicolaou sections, it was easy to detect dyskeratotic cells. Eleven of the 14 cases were p16 positive and five contained p16 positive dyskeratocytes. Of the 10 ASCUS scrapes, two contained p16 positive CIN 1 epithelial fragments. All four HSIL cases contained p16 positive CIN 3epithelial fragments. In HIV-positive HPV-positive women, the Cellient system resulted in high quality histology sections with perfect p16 images of dyskeratocytes.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.386
Teacher spread0.356 · 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

Citations2
Published2012
Admission routes2
Has abstractyes

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