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Record W4386592467 · doi:10.1111/his.15007

New developments in mesothelial pathology

2023· review· en· W4386592467 on OpenAlexaff
Andrew Churg

Bibliographic record

VenueHistopathology · 2023
Typereview
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMesotheliomaBAP1PathologyMesothelial CellMedicineImmunohistochemistryAsbestosPeritoneal mesotheliomaDifferential diagnosisStainLung cancerStaining

Abstract

fetched live from OpenAlex

This review article examines some new and some problem areas in mesothelial pathology, four of which are discussed, as follows. (1) The concept of mesothelioma in situ: this lesion is defined as a single layer of bland mesothelial cells without evidence of invasion, but that have lost BAP1 and/or MTAP by immunohistochemistry. Benign reactions can exactly mimic mesothelioma in situ, but a hint to the correct diagnosis is a story of recurrent pleural effusions/ascites of unknown aetiology without radiological or direct visual evidence of tumour. (2) The nature of well-differentiated papillary mesothelial tumour (WDPMT): WDPMT has a long history of arguments regarding its behaviour, and this uncertainty can now be seen to arise, in part, from the observation that some forms of mesothelioma in situ microscopically look exactly like WDPMT. Hence, it is recommended to always run at least a BAP1 stain on any lesion that looks like WDPMT. Both flat and WDPMT-like mesothelioma in situ are strongly associated with eventual development of invasive mesothelioma, but this process is relatively slow. (3) New immunostains for separating mesothelioma from other tumours: here, it is proposed that in most cases, and particularly when the differential is epithelioid mesothelioma versus non-small cell lung cancer, one can make this separation with extremely high sensitivity and specificity using just two stains: HEG1 and claudin-4. (4) Markers for separating benign from malignant mesothelial proliferations: this topic is briefly reviewed, with an indication of which markers are generally accepted and the best utilisation and possible limitations of each marker.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score1.000

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)0.0000.004

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 head0.080
GPT teacher head0.370
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

Citations19
Published2023
Admission routes1
Has abstractyes

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