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Record W2926710375 · doi:10.3390/ijms20071670

Infiltration of T Cells into a Three-Dimensional Psoriatic Skin Model Mimics Pathological Key Features

2019· article· en· W2926710375 on OpenAlexafffund
Isabelle Lorthois, Mélissa Simard, Sophie Morin, Roxane Pouliot

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsUniversité Laval
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsPsoriasisProinflammatory cytokineInfiltration (HVAC)InflammationPathologicalPhenotypePathologyImmunologyBiologyMedicine

Abstract

fetched live from OpenAlex

Psoriasis is an autoimmune chronic dermatosis that is T cell-mediated, characterized by epidermal thickening, aberrant epidermal differentiation and inflammatory infiltrates, with a dominant Th1 and Th17 profile. Additional in vitro models are required to study the complex interactions between activated T cells and skin cells, and to develop new, more effective treatments. We have therefore sought to model this psoriatic inflammation by the generation of tissue-engineered immunocompetent tissues, and we have investigated the response of activated T-cell infiltration in models produced with lesional psoriatic skin cells on major hallmarks of psoriasis. The immunocompetent lesional skin model displayed a delayed onset of epidermal differentiation, an hyperproliferation of the basal keratinocytes, a drastic increase in the secretion of proinflammatory cytokines, and a disturbed expression of key transcription factors, as observed in lesional plaques, suggesting a crucial importance of combining the pathological phenotype of cutaneous cells to T cells in order to generate a relevant model for psoriasis. Finally, we found this skin model to be responsive to methotrexate treatment, making it a valuable tool for drug development.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

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 science0.0010.000
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 head0.253
Teacher spread0.241 · 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 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

Citations46
Published2019
Admission routes2
Has abstractyes

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