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Record W2152098567 · doi:10.1093/rheumatology/kep371

Rosiglitazone alleviates the persistent fibrotic phenotype of lesional skin scleroderma fibroblasts

2009· article· en· W2152098567 on OpenAlexafffund
Shiwen Xu, Mark Eastwood, Richard Stratton, C.P. Denton, Andrew Leask, David Abraham

Bibliographic record

VenueLara D. Veeken · 2009
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsCanadian Institutes of Health ResearchWestern University
FundersCanadian Institutes of Health Research
KeywordsRosiglitazonePeroxisome proliferator-activated receptorMedicineAgonistWestern blotFibrosisPhenotypePPAR agonistScleroderma (fungus)EndocrinologyInternal medicineReceptorFibroblastPathologyBiologyCell cultureGene

Abstract

fetched live from OpenAlex

OBJECTIVE: The transcription factor peroxisome proliferator-activated receptor (PPAR)-gamma plays an important role in controlling cell differentiation. The aim of the present study was to examine whether PPAR-gamma expression was reduced in skin scleroderma fibroblasts and whether PPAR-gamma agonists could suppress the persistent fibrotic phenotype of skin scleroderma fibroblasts. METHODS: Dermal fibroblasts were isolated from site-, age- and sex-matched healthy individuals and lesional areas of individuals with dcSSc. Western blot and collagen gel contraction analyses were used to detect protein expression in the presence or absence of the PPAR-gamma agonist rosiglitazone. RESULTS: PPAR-gamma expression was reduced in dcSSc fibroblasts. The PPAR-gamma agonist rosiglitazone alleviated the persistent fibrotic phenotype of dcSSc fibroblasts. CONCLUSION: Rosiglitazone may alleviate the extent of fibrosis in dcSSc.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.021
GPT teacher head0.245
Teacher spread0.224 · 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

Citations59
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueLara D. VeekenSame topicSystemic Sclerosis and Related DiseasesFrench-language works237,207