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Record W2265590678 · doi:10.1111/his.12937

Differential expression of E‐cadherin and catenins in ovarian sex cord stromal tumours

2016· article· en· W2265590678 on OpenAlexaff
Stavroula Stavrinou, Ashleigh Clark, Julie Irving, Cheng‐Han Lee, Esther Oliva, Robert H. Young, Ruethairat Sriraksa, Nesreen Magdy, Susan Van Noorden, W. Glenn McCluggage, Mona El‐Bahrawy

Bibliographic record

VenueHistopathology · 2016
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsRoyal Alexandra HospitalUniversity of AlbertaRoyal Jubilee HospitalUniversity of British Columbia
FundersImperial College London
KeywordsCadherinCateninStromal cellAdherens junctionImmunohistochemistryBiologyPathologyBeta-cateninCancer researchMedicineCell biologyCellWnt signaling pathwayGeneticsSignal transduction

Abstract

fetched live from OpenAlex

AIMS: Sex cord stromal tumours (SCSTs) of the ovary encompass several histological tumour subtypes that are defined by characteristic histological features. Some can show morphological overlap with other subtypes of SCSTs, as well as with non-SCSTs. The E-cadherin/catenin complex constitutes the adherens junction, which is well developed in epithelial tissue, but the constituent molecules are also expressed in several non-epithelial tumours. The aim of this study was to determine whether the expression patterns of E-cadherin and catenins in ovarian SCSTs can be of diagnostic utility. METHODS AND RESULTS: We studied the expression of E-cadherin, α-, β- and γ-catenin in 55 tumours using immunohistochemistry. We found that all tumour subtypes showed nuclear expression of E-cadherin, while only microcystic stromal tumours (MCSTs) displayed a distinct profile, with nuclear localization of all three catenins in almost all cases. CONCLUSIONS: We conclude that the E-cadherin expression profile in SCSTs can assist in distinguishing between SCSTs and non-SCSTs in which there is no nuclear expression of E-cadherin. The nuclear localization of catenins may be of potential use in distinguishing MCST from other subtypes of SCST.

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 score0.316
Threshold uncertainty score0.309

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 head0.015
GPT teacher head0.259
Teacher spread0.244 · 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

Citations9
Published2016
Admission routes1
Has abstractyes

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