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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 OpenAlex
Andrew Leask

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.001
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 score0.042
Threshold uncertainty score0.261

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.040
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