MétaCan
Menu
Back to cohort
Record W2127124250 · doi:10.1101/gad.1453406

E4F1: a novel candidate factor for mediating BMI1 function in primitive hematopoietic cells

2006· article· en· W2127124250 on OpenAlexafffund
Jalila Chagraoui, Sherry L. Niessen, Julie Lessard, Simon Girard, Philippe Coulombe, Martin Sauvageau, Sylvain Meloche, Guy Sauvageau

Bibliographic record

VenueGenes & Development · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsHôpital Maisonneuve-RosemontUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersCanadian Institutes of Health ResearchNational Institutes of HealthCanada Research Chairs
KeywordsBMI1BiologyHaematopoiesisGene knockdownRNA interferenceCell biologyStem cellCancer researchPhenotypeClonogenic assayHematopoietic stem cellCell cultureGeneticsGeneRNA

Abstract

fetched live from OpenAlex

The Polycomb group gene Bmi1 is essential for the proliferation of neural and hematopoietic stem cells. Much remains to be learned about the pathways involved in the severe hematopoietic phenotype observed in Bmi1 homozygous mutant mice except for the fact that loss of p53 or concomitant loss of p16(Ink4a) and p19(Arf) functions achieves only a partial rescue. Here we report the identification of E4F1, an inhibitor of cellular proliferation, as a novel BMI1-interacting partner in hematopoietic cells. We provide evidence that Bmi1 and E4f1 genetically interact in the hematopoietic compartment to regulate cellular proliferation. Most importantly, we demonstrate that reduction of E4f1 levels through RNA interference mediated knockdown is sufficient to rescue the clonogenic and repopulating ability of Bmi1(-/-) hematopoietic cells up to 3 mo post-transplantation. Using cell lines and MEF, we also demonstrate that INK4A/ARF and p53 are not essential for functional interaction between Bmi1 and E4f1. Together, these findings identify E4F1 as a key modulator of BMI1 activity in primitive hematopoietic cells.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.011
GPT teacher head0.236
Teacher spread0.224 · 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 designBench or experimental
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

Citations57
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueGenes & DevelopmentSame topicEpigenetics and DNA MethylationFrench-language works237,207