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Record W2159665984 · doi:10.1186/1546-0096-5-22

Increased serum levels of TGFβ1 in children with localized scleroderma

2007· article· en· W2159665984 on OpenAlexaff
Yosef Uziel, Brian M. Feldman, Bernice R. Krafchik, Ronald M. Laxer, Rae S. M. Yeung

Bibliographic record

VenuePediatric Rheumatology · 2007
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoSickKids Foundation
Fundersnot available
KeywordsScleroderma (fungus)Transforming growth factorMedicineInternal medicineImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: There are neither sensitive nor specific laboratory tests for measuring disease activity in localized scleroderma (LS). Monitoring is done almost exclusively by clinical assessment. Our aim was to determine whether serum concentrations of TGFbeta1 are a good biomarker of disease activity in children with LS. METHODS: 55 pediatric patients with LS were divided into sub-types according to their main lesion; morphea, generalized morphea, linear scleoderma affecting a limb or the face. The lesions were further categorized by overall clinical assessment into active, inactive, and indeterminate groups according to disease activity. Serum TGFbeta1 concentration levels were measured by enzyme linked immunosorbent assay (ELISA), analyzed and correlated with disease subtypes and disease activity. RESULTS: The mean TGFbeta1 concentration were significantly higher in the patient group (51393 +/- 33953 pg/ml) than in the control group (9825 +/- 5287 pg/ml) (P < 0.001). The mean concentration were elevated in all the disease subtypes, and did not correlate with disease duration or activity. CONCLUSION: Serum concentration of TGFbeta1 were elevated in patients with all subtypes of LS irrespective of clinical disease activity. Although TGFbeta1 may play an important role in the pathogenesis of local skin fibrosis, circulating blood levels of molecules known to act locally may not be useful biomarkers of disease activity.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.246
Teacher spread0.233 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations22
Published2007
Admission routes1
Has abstractyes

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