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Record W2033079101 · doi:10.3892/or.19.4.933

Myeloid leukemia-1 expression in benign and malignant melanocytic lesions

2008· article· en· W2033079101 on OpenAlexafffund
Ronald P.C. Wong, Shahram Khosravi, Magdalena Martinka, Gang Li

Bibliographic record

VenueOncology Reports · 2008
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsVancouver Coastal Health Research InstituteUniversity of British ColumbiaSKiN Health
FundersCanadian Dermatology Foundation
KeywordsMelanomaOncogeneImmunohistochemistryMedicineCancer researchPathologyTissue microarrayMyeloid leukemiaCancerMolecular medicineCell cycleInternal medicine

Abstract

fetched live from OpenAlex

Myeloid leukemia-1 (Mcl-1) is an anti-apoptotic protein implicated in tumor progression. Its expression was found to be elevated in many types of human cancers and is correlated with tumor progression. The expression of Mcl-1 in melanoma is not fully understood. We investigated the expression of Mcl-1 in normal nevi, dysplastic nevi, primary melanoma and melanoma metastases by tissue microarray and immunohistochemistry. We found that Mcl-1 expression was significantly increased in dysplastic nevi, primary melanoma and melanoma metastases when compared to normal nevi, though the expression of Mcl-1 was decreased in metastatic melanoma when compared to dysplastic nevi. We did not find any correlation between Mcl-1 expression and melanoma patient survival. Our data suggest that Mcl-1 may play a critical role in the initiation of melanoma development.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.328
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 source (direct Gemma or distilled Codex), 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

Citations20
Published2008
Admission routes2
Has abstractyes

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