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Record W1428851925

Abstract 11102: Fibroblast Growth Factor-2 Attenuates Human Cardiac Fibroblast-Mediated Extracellular Matrix Remodeling

2014· article· en· W1428851925 on OpenAlexaff
Daniyil A. Svystonyuk, Janet M.C. Ngu, H.E. Mewhort, David G. Guzzardi, Brodie D Lipon, Daniel Park, Darrell D. Belke, Guoqi Teng, Paul W.M. Fedak

Bibliographic record

VenueCirculation · 2014
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsLibin Cardiovascular Institute of Alberta
Fundersnot available
KeywordsMyofibroblastFibroblastExtracellular matrixMedicineTransforming growth factorCardiac fibrosisFibroblast growth factorFibrosisInternal medicineCell biologyEndocrinologyBiologyIn vitroBiochemistryReceptor
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: After MI, elevation of profibrotic transforming growth factor-β1 (TGF-β1) results in myofibroblast-mediated matrix remodeling and progression of heart failure. In this study, we examined the effects of fibroblast growth factor (FGF-2) on human cardiac fibroblast (CF) mediated extracellular matrix (ECM) remodeling. METHOD/RESULTS: Human CF from atrial or ventricular heart biopsies were seeded into 3D collagen matrices. Myofibroblast activation was functionally assessed by the extent of matrix contraction. As compared to baseline myofibroblast activity, FGF-2 attenuated TGF-β1 mediated myofibroblast activation in both atrial (1.06±0.09 versus 1.17±0.09, P<0.0001) and ventricular fibroblasts (1.12±0.04 vs. 1.51±0.27, P<0.05). New collagen synthesis was assessed by 3H-proline incorporation. Fibroblasts treated with TGF-β1 had increased collagen synthesis while FGF-2 reduced collagen synthesis (P<0.05). ECM dysregulation was investigated by in situ zymography. TGF-β1 increased total protease activi...

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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.262
Teacher spread0.244 · 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
Published2014
Admission routes1
Has abstractyes

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