MétaCan
Menu
Back to cohort
Record W2102075349 · doi:10.1530/rep-12-0199

Differential actions of fibroblast growth factors on intracellular pathways and target gene expression in bovine ovarian granulosa cells

2012· article· en· W2102075349 on OpenAlexaff
Zhongliang Jiang, Christopher A. Price

Bibliographic record

VenueReproduction · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFibroblast Growth Factor Research
Canadian institutionsUniversité de MontréalCegep de Saint Hyacinthe
Fundersnot available
KeywordsCell biologyIntracellularGene expressionGeneFibroblast growth factorSignal transductionBiologyGeneticsReceptor

Abstract

fetched live from OpenAlex

Several fibroblast growth factors (FGFs), including FGF1, FGF4 and FGF10, alter ovarian granulosa cell function. These ligands exhibit different patterns of receptor activation, and their mechanisms of action on granulosa cells remain unknown. The objective of this study was to identify the major pathways and target genes activated by FGF1, FGF4 and FGF10 in primary oestrogenic granulosa cells cultured under serum-free conditions. FGF1 and FGF4 increased levels of mRNA encoding Sprouty family members, SPRY2 and SPRY4, and the orphan nuclear receptors NR4A1 and NR4A3. Both FGF1 and FGF4 decreased levels of mRNA encoding SPRY3 and the pro-apoptotic factor BAX. FGF1 but not FGF4 stimulated expression of the cell cycle regulator, GADD45B. In contrast, FGF10 altered the expression of none of these genes. Western blot demonstrated that FGF4 activated ERK1/2 and Akt signalling rapidly and transiently, whereas FGF10 elicited a modest and delayed activation of ERK1/2. These data show that FGF1 and FGF4 activate typical FGF signalling pathways in granulosa cells, whereas FGF10 activates atypical pathways.

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 score0.031
Threshold uncertainty score0.612

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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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

Citations29
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueReproductionSame topicFibroblast Growth Factor ResearchFrench-language works237,207