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Record W2101410412 · doi:10.1152/ajpgi.00436.2002

Transforming growth factor-β1 downregulation of Smad1 gene expression in rat hepatic stellate cells

2003· article· en· W2101410412 on OpenAlexaff
Hong Shen, Guojiang Huang, Mohammed Hadi, Patrick C. Choy, Manna Zhang, Gerald Y. Minuk, Yongping Chen, Yuewen Gong

Bibliographic record

VenueAmerican Journal of Physiology-Gastrointestinal and Liver Physiology · 2003
Typearticle
Languageen
FieldMedicine
TopicLiver physiology and pathology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSMADHepatic stellate cellDownregulation and upregulationCell biologyTransforming growth factorBone morphogenetic protein 7Bone morphogenetic proteinGene expressionTransforming growth factor betaSmad2 ProteinPhosphorylationBMPR2BiologySignal transductionR-SMADReceptorChemistryBone morphogenetic protein 2Molecular biologyGrowth factorGeneEndocrinologyTGF alphaBiochemistry

Abstract

fetched live from OpenAlex

Smads are intracellular signaling molecules of the transforming growth factor-beta (TGF-beta) superfamily that play an important role in the activation of hepatic stellate cells (HSCs) and hepatic fibrosis. Excepting the regulation of Smad7, receptor-regulated Smad gene expression is still unclear. We employed rat HSCs to investigate the expression and regulation of the Smad1 gene, which is a bone morphogenetic protein (BMP) receptor-regulated Smad. We found that the expression and phosphorylation of Smad1 are increased during the activation of HSCs. Moreover, TGF-beta significantly inhibits Smad1 gene expression in HSCs in a time- and dose-dependent manner. Furthermore, although both TGF-beta1 and BMP2 stimulate the activation of HSCs, they have different effects on HSC proliferation. In conclusion, Smad1 expression and phosphorylation are increased during the activation of HSCs and TGF-beta1 significantly inhibits the expression of the Smad1 gene.

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 categoriesMeta-epidemiology (narrow)
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 score0.478
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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.

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

Citations49
Published2003
Admission routes1
Has abstractyes

Explore more

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