MétaCan
Menu
Back to cohort
Record W2410814784 · doi:10.1621/nrs.14001

Regulation of Steroid Hormone Receptors and Coregulators during the Cell Cycle Highlights Potential Novel Function in Addition to Roles as Transcription Factors

2016· review· en· W2410814784 on OpenAlexafffund
Yingfeng Zheng, Leigh C. Murphy

Bibliographic record

VenueNuclear Receptor Signaling · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
FundersCancerCare Manitoba Foundation
KeywordsBiologyCell cycleSteroid hormone receptorCell biologyTranscription factorSteroid hormoneKinasePELP-1Cyclin-dependent kinaseReceptorNuclear receptorCellGeneticsGeneEstrogen receptorCancer

Abstract

fetched live from OpenAlex

Cell cycle progression is tightly controlled by several kinase families including Cyclin-Dependent Kinases, Polo-Like Kinases, and Aurora Kinases. A large amount of data show that steroid hormone receptors and various components of the cell cycle, including cell cycle regulated kinases, interact, and this often results in altered transcriptional activity of the receptor. Furthermore, steroid hormones, through their receptors, can also regulate the transcriptional expression of genes that are required for cell cycle regulation. However, emerging data suggest that steroid hormone receptors may have roles in cell cycle progression independent of their transcriptional activity. The following is a review of how steroid receptors and their coregulators can regulate or be regulated by the cell cycle machinery, with a particular focus on roles independent of transcription in G2/M.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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

Citations20
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueNuclear Receptor SignalingSame topicMicrotubule and mitosis dynamicsFrench-language works237,207