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Record W2092543420 · doi:10.1007/s12079-012-0161-7

CCN3 modulates bone turnover and is a novel regulator of skeletal metastasis

2012· article· en· W2092543420 on OpenAlexafffund
Véronique Ouellet, Peter M. Siegel

Bibliographic record

VenueJournal of Cell Communication and Signaling · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective Tissue Growth Factor Research
Canadian institutionsMcGill University
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchCancer Research Society
KeywordsMatricellular proteinOsteosarcomaWnt signaling pathwayChondrosarcomaCancer researchBiologyChondrocyteBone remodelingCell biologyOsteoblastCancerDKK1MetastasisRegulatorSignal transductionMedicineCartilagePathologyExtracellular matrixEndocrinologyAnatomyGeneticsGene

Abstract

fetched live from OpenAlex

The CCN family of proteins is composed of six secreted proteins (CCN1-6), which are grouped together based on their structural similarity. These matricellular proteins are involved in a large spectrum of biological processes, ranging from development to disease. In this review, we focus on CCN3, a founding member of this family, and its role in regulating cells within the bone microenvironment. CCN3 impairs normal osteoblast differentiation through multiple mechanisms, which include the neutralization of pro-osteoblastogenic stimuli such as BMP and Wnt family signals or the activation of pathways that suppress osteoblastogenesis, such as Notch. In contrast, CCN3 is known to promote chondrocyte differentiation. Given these functions, it is not surprising that CCN3 has been implicated in the progression of primary bone cancers such as osteosarcoma, Ewing's sarcoma and chondrosarcoma. More recently, emerging evidence suggests that CCN3 may also influence the ability of metastatic cancers to colonize and grow in bone.

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 score0.002
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 integrity0.0000.000
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 head0.025
GPT teacher head0.287
Teacher spread0.262 · 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

Citations38
Published2012
Admission routes2
Has abstractyes

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