MétaCan
Menu
Back to cohort

FIAT, the factor‐inhibiting ATF4‐mediated transcription, also represses the transcriptional activity of the bZIP factor FRA‐1

2010· article· en· W2111002047 on OpenAlexaff
René St‐Arnaud, Vice Mandic, Bilal Elchaarani

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2010
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsMcGill UniversityShriners Hospitals for Children - Canada
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institutes of Health
KeywordsLeucine zipperATF4ATF3Transcription factorbZIP domainRepressorActivating transcription factor 2Cell biologyBasic helix-loop-helix leucine zipper transcription factorsBiologyActivating transcription factorTranscription (linguistics)ChemistryDNA-binding proteinBiochemistryPromoterGeneGene expression

Abstract

fetched live from OpenAlex

FIAT is a leucine zipper protein whose name was coined for its interaction with ATF4 and subsequent blockage of ATF4-directed osteocalcin gene transcription. FIAT lacks a basic DNA-binding domain but contains three leucine zippers; it heterodimerizes with ATF4 to prohibit binding to DNA. FIAT could also potentially interact with additional basic domain-leucine zipper transcriptional regulators of osteoblast activity, such as FRA-1. We have found that FIAT inhibits transcriptional activation by a FRA-1/c-JUN heterodimer without affecting transcription mediated by a c-JUN homodimer. The repressor effect of FIAT on FRA-1-dependent transcription was measured using reporter constructs for the natural FRA-1 targets, Mmp-9 and Mgp. The FIAT-FRA-1 interaction is mediated through the second leucine zipper of FIAT. These data confirm an additional target of the FIAT transcriptional repressor activity and suggest that FIAT can both modulate early osteoblast activity by interacting with ATF4 and regulate later osteoblast function through inhibition of FRA-1.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.247
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.103
GPT teacher head0.342
Teacher spread0.239 · 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

Citations4
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of the New York Academy of SciencesSame topicPeptidase Inhibition and AnalysisFrench-language works237,207