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Apo D in Soft Tissue Tumors

2004· article· en· W2131505559 on OpenAlexaff
Robert B. West, Jeff D. Harvell, Sabine C. Linn, Chih Long Lui, Wijan Prapong, Tina Hernandez‐Boussard, Kelli Montgomery, Torsten O. Nielsen, Brian P. Rubin, Rajiv M. Patel, John R. Goldblum, Patrick O. Brown, Matt van de Rijn

Bibliographic record

VenueThe American Journal of Surgical Pathology · 2004
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsUniversity of British ColumbiaVancouver General Hospital
FundersNational Cancer Institute
KeywordsPathologyTissue microarrayImmunohistochemistryImmunostainingDermatofibrosarcoma protuberansCD34NeurofibromaBiologySoft tissueMedicine

Abstract

fetched live from OpenAlex

Using gene microarray expression profiling, we previously found that apolipoprotein D (Apo D) was highly expressed in dermatofibrosarcoma protuberans (DFSP). In this study, we confirm that Apo D is highly and relatively specifically expressed in DFSP using immunohistochemistry. A tissue microarray containing 421 soft tissue tumors was constructed and stained with antibodies against Apo D and CD34. Cytoplasmic immunostaining for Apo D was found in 9 of 10 typical DFSPs. In addition, 3 of 3 Bednar tumors and 2 of 3 giant cell fibroblastomas stained in conventional sections. In contrast, Apo D was immunoreactive in only a very small subset of a diverse collection of other soft tissue tumors, including Malignant Fibrous Histiocytoma (MFH), glomus tumor, neurofibroma, and malignant peripheral nerve sheath tumors. Immunostains for Apo D were negative in conventional sections of 16 fibrous histiocytomas, and an additional 12 variants of fibrous histiocytoma. Digital images of all immunohistochemical and hematoxylin and eosin tissue microarray stains are available at the accompanying website (http://microarray-pubs.stanford.edu/tma_portal/apod/). We conclude that Apo D is strongly expressed in DFSPs and neural lesions and may be useful in differentiating DFSP from fibrous histiocytoma.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.209

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)0.0000.000

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 head0.299
Teacher spread0.284 · 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

Citations85
Published2004
Admission routes1
Has abstractyes

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