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Record W2146244138 · doi:10.1083/jcb.200711044

CHIP promotes Runx2 degradation and negatively regulates osteoblast differentiation

2008· article· en· W2146244138 on OpenAlexaff
Xueni Li, Mei Huang, Huiling Zheng, Yinyin Wang, Fangli Ren, Yu Shang, Yonggong Zhai, David M. Irwin, Yuguang Shi, Di Chen, Zhijie Chang

Bibliographic record

VenueThe Journal of Cell Biology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBone Metabolism and Diseases
Canadian institutionsUniversity of Toronto
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Natural Science Foundation of China
KeywordsRUNX2OsteoblastTransactivationBiologyCell biologyUbiquitinCellular differentiationProtein degradationTranscription factorBiochemistryIn vitroGene

Abstract

fetched live from OpenAlex

Runx2, an essential transactivator for osteoblast differentiation, is tightly regulated at both the transcriptional and posttranslational levels. In this paper, we report that CHIP (C terminus of Hsc70-interacting protein)/STUB1 regulates Runx2 protein stability via a ubiquitination-degradation mechanism. CHIP interacts with Runx2 in vitro and in vivo. In the presence of increased Runx2 protein levels, CHIP expression decreases, whereas the expression of other E3 ligases involved in Runx2 degradation, such as Smurf1 or WWP1, remains constant or increases during osteoblast differentiation. Depletion of CHIP results in the stabilization of Runx2, enhances Runx2-mediated transcriptional activation, and promotes osteoblast differentiation in primary calvarial cells. In contrast, CHIP overexpression in preosteoblasts causes Runx2 degradation, inhibits osteoblast differentiation, and instead enhances adipogenesis. Our data suggest that negative regulation of the Runx2 protein by CHIP is critical in the commitment of precursor cells to differentiate into the osteoblast lineage.

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 score0.126
Threshold uncertainty score0.195

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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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

Citations115
Published2008
Admission routes1
Has abstractyes

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