MétaCan
Menu
Back to cohort
Record W1969447019 · doi:10.1002/art.23595

Role of Rac1 in a bleomycin‐induced scleroderma model using fibroblast‐specific Rac1‐knockout mice

2008· article· en· W1969447019 on OpenAlexaff
Shangxi Liu, Mohit Kapoor, Shiwen Xu, Laura Kennedy, Christopher P. Denton, Michael Glogauer, David Abraham, Andrew Leask

Bibliographic record

VenueArthritis & Rheumatism · 2008
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsUniversity of TorontoWestern University
FundersVersus Arthritis
KeywordsBleomycinRAC1InflammationFibroblastFibrosisMyofibroblastScleroderma (fungus)MedicineScarsHydroxyprolineCancer researchPathologyImmunologyChemistryBiologySignal transductionInternal medicineCell biologyBiochemistryChemotherapyIn vitro

Abstract

fetched live from OpenAlex

OBJECTIVE: Activated adhesive signaling is a hallmark of fibroblasts isolated from the scars of scleroderma (systemic sclerosis [SSc]) lesions. Rac1 plays a key role in adhesive signaling. The aim of the present study was to examine the role of Rac1 in bleomycin-induced scleroderma, using mice with a fibroblast-specific deletion of Rac1. METHODS: Cutaneous sclerosis was induced by subcutaneous injection of bleomycin. Control groups were treated with phosphate buffered saline. Mice with a fibroblast-specific deletion of Rac1 and control mice were investigated. Dermal thickness, inflammation, collagen production, and the number of alpha-smooth muscle actin-positive cells were determined. The quantity of the collagen-specific amino acid hydroxyproline was also measured. RESULTS: Bleomycin treatment induced marked cutaneous thickening, inflammation, and fibrosis in control mice. Conversely, deletion of Rac1 resulted in resistance to bleomycin-induced fibrosis and inflammation. CONCLUSION: Rac1 expression by fibroblasts is required for fibrogenesis. Inhibition of Rac1 may be a viable method to alleviate the development of cutaneous sclerosis.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.035
GPT teacher head0.245
Teacher spread0.210 · 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.

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

Citations36
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueArthritis & RheumatismSame topicSystemic Sclerosis and Related DiseasesFrench-language works237,207