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Record W1968835093 · doi:10.1016/j.febslet.2010.04.074

Transforming growth factor‐β inhibits nephronectin‐induced osteoblast differentiation

2010· article· en· W1968835093 on OpenAlexafffund
Ling Fang, Shireen Kahai, Weining Yang, Chengyan He, Arun Seth, Chun Peng, Burton B. Yang

Bibliographic record

VenueFEBS Letters · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTGF-β signaling in diseases
Canadian institutionsHealth Sciences CentreYork UniversityUniversity of TorontoSunnybrook Health Science Centre
FundersChina Scholarship CouncilHeart and Stroke Foundation of Canada
KeywordsOsteoblastTransforming growth factor betaCellular differentiationCell biologyTGF beta signaling pathwayTransforming growth factorTransforming growth factor, beta 3ChemistryBETA (programming language)TransfectionCell growthBiologyEndocrinologyMolecular biologyGrowth factorGeneBiochemistryIn vitroTGF alphaReceptor

Abstract

fetched live from OpenAlex

We used cDNA microarray to identify transforming growth factor beta (TGF-beta) responsive target genes during osteoblast development and found that nephronectin (Npnt) is one such gene that is significantly down-regulated. Here we report the role of TGF-beta in regulating Npnt-mediated osteoblast differentiation. We found that the effect of TGF-beta on Npnt expression is associated with a change in cell morphology in a dose-dependent manner. Npnt-induced osteoblast differentiation was also inhibited by TGF-beta, which changed cell morphology from cuboidal to fibroblastic, an indication that osteoblast differentiation was disrupted. Furthermore, TGF-beta inhibited differentiation of osteoblasts transfected with various truncated Npnt constructs, suggesting that TGF-beta can exert a down-stream effect on Npnt function. Our results suggest that TGF-beta can inhibit osteoblast differentiation through various mechanisms.

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 score0.018
Threshold uncertainty score0.718

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 head0.008
GPT teacher head0.221
Teacher spread0.213 · 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

Citations23
Published2010
Admission routes2
Has abstractyes

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