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Wnt3a/beta‐catenin increases proliferation in valve interstitial cells

2011· article· en· W3175222641 on OpenAlexaffabout
Songyi Xu, Avrum I. Gotlieb

Bibliographic record

VenueThe FASEB Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsWNT3AWnt signaling pathwayCell growthWestern blotChemistryBeta-cateninInterstitial cellAndrologyCell biologyBiologyMedicineEndocrinologySignal transductionBiochemistry

Abstract

fetched live from OpenAlex

Background Valve interstitial cells (VICs) mediate valve function in health and disease. It is suggested that valve repair processes are regulated by developmental pathways. We hypothesize that Wnt3a increases the amount of stabilized β‐catenin present in VICs, which then results in its nuclear translocation and subsequent increase in proliferation. Methods Porcine VIC cultures were maintained in standard media in 10% fetal bovine serum. Cultures were plated, grown to 4–6% confluence, then incubated with 100 ng/ml of exogenous Wnt3a for 3 days, and counted to measure proliferation. VICs were stained with antibody against β‐catenin. Whole cell, cytoplasmic and nuclear levels of β‐catenin were determined using Western blot. Results VICs treated with Wnt3a show increased cell number compared to control and vehicle‐treated cultures. Immunofluorescent images of Wnt3a‐treated VICs show slightly increased β‐catenin staining compare to control and vehicle‐treated cultures. Whole cell, cytoplasmic, and nuclear lysates of Wnt3a‐treated VICs show increased levels of β‐catenin compared to control and vehicle‐treated cultures. Conclusion Wnt3a may increase VIC proliferation through an increase in β‐catenin. Supported by the Heart and Stroke Foundation of Ontario (grant NA6204) and Canadian Institute of Health Research (grant 84228).

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 score0.003
Threshold uncertainty score0.009

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)0.0030.000

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 head0.027
GPT teacher head0.295
Teacher spread0.269 · 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

Citations0
Published2011
Admission routes2
Has abstractyes

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