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Record W2113192334 · doi:10.1084/jem.20111790

The microtubule-associated protein DCAMKL1 regulates osteoblast function via repression of Runx2

2013· article· en· W2113192334 on OpenAlexaff
Weiguo Zou, Matthew B. Greenblatt, Nicholas J. Brady, Sutada Lotinun, Bo Zhai, Heather de Rivera, Anju Singh, Jun Sun, Steven P. Gygi, Roland Baron, Laurie H. Glimcher, Dallas C. Jones

Bibliographic record

VenueThe Journal of Experimental Medicine · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBone Metabolism and Diseases
Canadian institutionsInstitute of Infection and Immunity
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institutes of HealthNational Institute of General Medical SciencesBroad Institute
KeywordsRUNX2Psychological repressionCell biologyMicrotubuleOsteoblastBiologyFunction (biology)ChemistryGeneticsGeneGene expression

Abstract

fetched live from OpenAlex

Osteoblasts are responsible for the formation and mineralization of the skeleton. To identify novel regulators of osteoblast differentiation, we conducted an unbiased forward genetic screen using a lentiviral-based shRNA library. This functional genomics analysis led to the identification of the microtubule-associated protein DCAMKL1 (Doublecortin-like and CAM kinase-like 1) as a novel regulator of osteogenesis. Mice with a targeted disruption of Dcamkl1 displayed elevated bone mass secondary to increased bone formation by osteoblasts. Molecular experiments demonstrated that DCAMKL1 represses osteoblast activation by antagonizing Runx2, the master transcription factor in osteoblasts. Key elements of the cleidocranial dysplasia phenotype observed in Runx2(+/-) mice are reversed by the introduction of a Dcamkl1-null allele. Our results establish a genetic linkage between these two proteins in vivo and demonstrate that DCAMKL1 is a physiologically relevant regulator of anabolic bone formation.

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 score0.024
Threshold uncertainty score0.198

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 head0.005
GPT teacher head0.230
Teacher spread0.225 · 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

Citations63
Published2013
Admission routes1
Has abstractyes

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