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Record W2191692978 · doi:10.1097/der.0000000000000143

Epidermal Expression of Filaggrin/Profilaggrin Is Decreased in Atopic Dermatitis: Reverse Association With Mast Cell Tryptase and IL-6 but Not With Clinical Severity

2015· article· en· W2191692978 on OpenAlexvenueno aff
Tiina Ilves, Virpi Tiitu, Mireille‐Maria Suttle, J. V. Saarinen, Ilkka Tapani Harvima

Bibliographic record

VenueDermatitis · 2015
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsFilaggrinAtopic dermatitisMedicineDermatology

Abstract

fetched live from OpenAlex

BACKGROUND: A decrease in filaggrin expression contributes to the pathogenesis of atopic dermatitis (AD) and can be modified by inflammatory factors. OBJECTIVES: The aim of this study was to determine the correlation of (pro)filaggrin (filaggrin and profilaggrin) expression with clinical severity in AD and with mast cell (MC) tryptase, chymase, and IL-6. METHODS: Punch biopsies were collected from 17 patients with moderate-to-severe AD and from 10 psoriatic patients. Atopic dermatitis severity was measured using different clinical parameters. (Pro)filaggrin, MC tryptase, chymase, and IL-6 were stained using immunohistochemical, enzymehistochemical, and sequential double-staining methods. RESULTS: (Pro)filaggrin expression was lower in the lesional than in the nonlesional granular layer in AD and was correlated negatively with itch severity but not with other severity parameters. (Pro)filaggrin expression was also decreased in the psoriatic lesions. In AD, (pro)filaggrin expression correlated negatively with the number of tryptase MCs in the nonlesional granular layer and with IL-6 MCs in both the nonlesional and lesional granular layers. CONCLUSION: (Pro)filaggrin expression is decreased in AD and is reversely associated with MC tryptase and IL-6. However, it does not associate with disease severity, and it was also decreased in psoriasis.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.783

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 head0.022
GPT teacher head0.275
Teacher spread0.254 · 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

Citations17
Published2015
Admission routes1
Has abstractyes

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