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Record W2032084074 · doi:10.1210/en.2003-0185

Identification of a Putative Autocrine Bone Morphogenetic Protein-Signaling Pathway in Human Ovarian Surface Epithelium and Ovarian Cancer Cells

2003· article· en· W2032084074 on OpenAlexaff
Trevor G. Shepherd, Mark W. Nachtigal

Bibliographic record

VenueEndocrinology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTGF-β signaling in diseases
Canadian institutionsDalhousie University
FundersLudwig Institute for Cancer Research
KeywordsAutocrine signallingBone morphogenetic protein 4Bone morphogenetic proteinBiologyBMPR2EndocrinologyCell biologyInternal medicineSignal transductionCell cultureGeneGeneticsMedicine

Abstract

fetched live from OpenAlex

Bone morphogenetic proteins (BMPs) are members of the TGFbeta superfamily of cytokines that are involved in development, differentiation, and disease. In an analysis of normal ovarian surface epithelium (OSE) and ovarian cancer (OC) cells, we observed BMP4 mRNA expression and found that primary OC cells produce mature BMP4. In addition, each member of the downstream signaling pathway was expressed in primary OSE and OC cells. Smad1 was phosphorylated and underwent nuclear translocation in normal OSE and OC cells upon treatment with BMP4. Interestingly, the BMP target genes ID1 and ID3 were up-regulated 10- to 15-fold in primary OC cells, compared with a 2- to 3-fold increase in normal OSE. The growth of several primary OC cells was relatively unaltered by BMP4 treatment; however, long-term BMP4 treatment of primary OC cells resulted in decreased cell density as well as increased cell spreading and adherence. These data demonstrate the existence and putative function of BMP signaling in normal OSE and OC cells, and thus the continued examination of BMP4 signaling in the regulation of these two processes will be critical to further our current understanding of the role of BMP biology in OC pathogenesis.

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 score0.002
Threshold uncertainty score0.861

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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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

Citations55
Published2003
Admission routes1
Has abstractyes

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