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Record W2344565165 · doi:10.1111/exd.13059

Galanin 3 receptor‐deficient mice show no alteration in the oxazolone‐induced contact dermatitis phenotype

2016· letter· en· W2344565165 on OpenAlexaff
Bálint Botz, Susanne M. Brunner, Ágnes Kemény, Erika Pintér, Jason J. McDougall, Barbara Kofler, Zsuzsanna Helyes

Bibliographic record

VenueExperimental Dermatology · 2016
Typeletter
Languageen
FieldNeuroscience
TopicNeuropeptides and Animal Physiology
Canadian institutionsDalhousie University
FundersEuropean Social FundÖsterreichische ForschungsförderungsgesellschaftAustrian Science Fund
KeywordsOxazoloneExtravasationGalaninInflammationImmunologyReceptorImmune systemContact dermatitisKnockout mouseChemistryAllergyMedicineNeuropeptideInternal medicine

Abstract

fetched live from OpenAlex

Allergic contact dermatitis (ACD) is an inflammatory skin disease induced by allergen exposure and characterized by erythema, oedema and immune cell infiltration. The sensory peptide galanin (GAL) and its three receptors (GAL1-3 ) are involved in regulating inflammation. As GAL and its receptors are expressed in human and murine skin and GAL expression is increased in oxazolone-induced contact allergy, it could play a role in dermatitis. As GAL reduces neurogenic plasma extravasation in the mouse skin via GAL3 activation, the role of GAL3 in the oxazolone-induced dermatitis model was explored. Following topical challenge with oxazolone, GAL3 gene-deficient mice showed a trend towards reduced ear thickness. Plasma extravasation and neutrophil infiltration increased considerably upon oxazolone challenge in both GAL3 knockout animals and wild-type controls without any observable effect of the gene deletion. We conclude that a lack of GAL3 does not influence oxazolone-induced ACD.

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 score0.003
Threshold uncertainty score0.010

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.033
GPT teacher head0.274
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 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

Citations4
Published2016
Admission routes1
Has abstractyes

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