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Record W2153857286 · doi:10.1073/pnas.1101544108

Transcription cofactors TRIM24, TRIM28, and TRIM33 associate to form regulatory complexes that suppress murine hepatocellular carcinoma

2011· article· en· W2153857286 on OpenAlexaff
Benjamin Herquel, Khalid Ouararhni, Konstantin Khetchoumian, Mihaela Ignat, Marius Teletin, Manuel Mark, Guillaume Béchade, Alain Van Dorsselaer, Sarah Cianférani, Ali Hamiche, Florence Cammas, Irwin Davidson, Régine Losson

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsMontreal Clinical Research Institute
FundersUniversité de StrasbourgInstitut National de la Santé et de la Recherche MédicaleInstitut National Du CancerCentre National de la Recherche ScientifiqueAssociation pour la Recherche sur le Cancer
KeywordsTranscription factorBiologySubfamilyCell biologySomatic cellGeneGenetics

Abstract

fetched live from OpenAlex

TRIM24 (TIF1α), TRIM28 (TIF1β), and TRIM33 (TIF1γ) are three related cofactors belonging to the tripartite motif superfamily that interact with distinct transcription factors. TRIM24 interacts with the liganded retinoic acid (RA) receptor to repress its transcriptional activity. Germ line inactivation of TRIM24 in mice deregulates RA-signaling in hepatocytes leading to the development of hepatocellular carcinoma (HCC). Here we show that TRIM24 can be purified as at least two macromolecular complexes comprising either TRIM33 or TRIM33 and TRIM28. Somatic hepatocyte-specific inactivation of TRIM24, TRIM28, or TRIM33 all promote HCC in a cell-autonomous manner in mice. Moreover, HCC formation upon TRIM24 inactivation is strongly potentiated by further loss of TRIM33. These results demonstrate that the TIF1-related subfamily of TRIM proteins interact both physically and functionally to modulate HCC formation in mice.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.075
GPT teacher head0.272
Teacher spread0.197 · 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 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

Citations217
Published2011
Admission routes1
Has abstractyes

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Same venueProceedings of the National Academy of SciencesSame topicinterferon and immune responsesFrench-language works237,207