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Record W2873991300 · doi:10.1369/0022155418788117

Characterization of Epidermal Lipoxygenase Expression in Normal Human Skin and Tissue-Engineered Skin Substitutes

2018· article· en· W2873991300 on OpenAlexafffund
Carolyne Simard‐Bisson, Lorraine Andrée Parent, Véronique Moulin, Bernard Fruteau de Laclos

Bibliographic record

VenueJournal of Histochemistry & Cytochemistry · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsUniversité Laval
FundersFondation CHU de Québec
KeywordsEpidermis (zoology)Human skinLipoxygenasePsoriasisEnzymeCell biologyFunction (biology)Cancer researchBiologyChemistryBiochemistryImmunologyAnatomyGenetics

Abstract

fetched live from OpenAlex

Lipoxygenases (LOXs) are enzymes likely to be involved in corneocyte lipid envelope formation and skin barrier function. In humans, mutations in epidermis-type lipoxygenase 3 ( eLOX-3) and 12R-lipoxygenase ( 12R-LOX) genes are associated with autosomal recessive congenital ichthyosis (ARCI), whereas deletion of these genes in mice causes epidermal defects. LOXs also represent a matter of interest in psoriasis as well as in cancer research. However, their expression as well as the exact role of these enzymes in normal human skin have not been fully described. Our goal was to characterize the expression of epidermal LOXs in both normal human skin and Tissue-Engineered Skin Substitutes (TESS) and to consider TESS as a potential model for LOX functional studies. Staining for epidermal differentiation markers and LOXs was performed, in parallel, on normal human skin and TESS. Our results showed similar expression profiles in TESS when compared with native skin for e-LOX3, 12R-LOX, 12S-lipoxygenase (12S-LOX), and 15-lipoxygenase 2 (15-LOX-2) but not for 15-lipoxygenase 1 (15-LOX-1). Because of their appropriate epidermal differentiation and LOX expression, TESS represent an alternative model for future studies on LOX function.

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 score0.005
Threshold uncertainty score0.958

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 science0.0000.000
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 head0.008
GPT teacher head0.263
Teacher spread0.255 · 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

Citations16
Published2018
Admission routes2
Has abstractyes

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