MétaCan
Menu
Back to cohort
Record W1987812048 · doi:10.1007/s12079-009-0082-2

Thrombin-induced CCN2 expression as a target for anti-fibrotic therapy in scleroderma

2009· article· en· W1987812048 on OpenAlexaff
Andrew Leask

Bibliographic record

VenueJournal of Cell Communication and Signaling · 2009
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsWestern University
Fundersnot available
KeywordsCTGFScleroderma (fungus)MedicineConnective tissueFibrosisThrombinPathologyConnective tissue diseaseGrowth factorImmunologyDiseaseAutoimmune diseaseInternal medicineReceptorPlatelet

Abstract

fetched live from OpenAlex

Scleroderma (systemic sclerosis, SSc) is a fibrotic disease for which there is no therapy. CCN2 (connective tissue growth factor, CTGF) is a marker and mediator of fibrosis. Previously, it has been shown that thrombin induces CCN2 expression in fibroblasts. In a recent fascinating report, Bogatkevich et al. (Arthritis Rheum 60:3455-3464, 2009) show that dabigatran, an inhibitor of thrombin action, blocks the overexpression of CCN2 by scleroderma fibroblasts and reverses the contractile phenotype of these cells. These results strongly suggest that dabigatran may be a potential antifibrotic drug for the treatment of fibrosing diseases such as scleroderma.

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 score0.002
Threshold uncertainty score0.005

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.302
Teacher spread0.262 · 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

Citations5
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cell Communication and SignalingSame topicSystemic Sclerosis and Related DiseasesFrench-language works237,207