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Record W1970086542 · doi:10.1621/nrs.05006

Steroid Receptor RNA Activator (SRA1): Unusual Bifaceted Gene Products with Suspected Relevance to Breast Cancer

2007· review· en· W1970086542 on OpenAlexafffund
Etienne Leygue

Bibliographic record

VenueNuclear Receptor Signaling · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health ResearchCanadian Breast Cancer Research AllianceCancerCare Manitoba Foundation
KeywordsBiologyRNAGeneCarcinogenesisBreast cancerGene isoformComputational biologyAndrogen receptorEstrogen receptorGeneticsActivator (genetics)Cancer researchBioinformaticsCancerProstate cancer

Abstract

fetched live from OpenAlex

The steroid receptor RNA activator (SRA) is a unique modulator of steroid receptor transcriptional activity, as it is able to mediate its coregulatory effects as a RNA molecule. Recent findings, however, have painted a more complex picture of the SRA gene (SRA1) products. Indeed, even though SRA was initially thought to be noncoding, several RNA isoforms have now been found to encode an endogenous protein (SRAP), which is well conserved among Chordata. Although the function of SRAP remains largely unknown, it has been proposed that, much like its corresponding RNA, the protein itself might regulate estrogen and androgen receptor signaling pathways. As such, data suggest that both SRA and SRAP might participate in the mechanisms underlying breast, as well as prostate tumorigenesis. This review summarizes the published literature dealing with these two faces of the SRA gene products and underscores the relevance of this bifaceted system to breast cancer 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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.316
Teacher spread0.286 · 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 designNot applicable
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

Citations129
Published2007
Admission routes2
Has abstractyes

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