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SWI/SNF Complex Mutations in Gynecologic Cancers: Molecular Mechanisms and Models

2020· review· en· W3002554121 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnnual Review of Pathology Mechanisms of Disease · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChromatin Remodeling and Cancer
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchNational Institutes of HealthNational Cancer InstituteBC Cancer Foundation
KeywordsSWI/SNFSMARCA4BiologySMARCB1ChromatinChromatin remodelingGeneticsHistoneTranscription factorGeneCancer researchContext (archaeology)

Abstract

fetched live from OpenAlex

ch/Sucrose NonFermentable) chromatin remodeling complexes interact with histones and transcription factors to modulate chromatin structure and control gene expression. These evolutionarily conserved multisubunit protein complexes are involved in regulating many biological functions, such as differentiation and cell proliferation. Genomic studies have revealed frequent mutations of genes encoding multiple subunits of the SWI/SNF complexes in a wide spectrum of cancer types, including gynecologic cancers. These SWI/SNF mutations occur at different stages of tumor development and are restricted to unique histologic types of gynecologic cancers. Thus, SWI/SNF mutations have to function in the appropriate tissue and cell context to promote gynecologic cancer initiation and progression. In this review, we summarize the current knowledge of SWI/SNF mutations in the development of gynecologic cancers to provide insights into both molecular pathogenesis and possible treatment implications for these diseases.

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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.676
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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 head0.029
GPT teacher head0.330
Teacher spread0.301 · 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