MétaCan
Menu
Back to cohort
Record W3161926612 · doi:10.1183/23120541.00984-2020

Upregulation of interleukin-19 in severe asthma: a potential saliva biomarker for asthma severity

2021· article· en· W3161926612 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueERJ Open Research · 2021
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcGill University Health Centre
FundersKing Saud UniversityAl Jalila Foundation
KeywordsMedicineAsthmaBiomarkerSalivaRheumatoid arthritisImmunologyDownregulation and upregulationInterleukinCOPDAllergyCytokineInternal medicineGene

Abstract

fetched live from OpenAlex

Interleukin (IL)-19, a designated IL-20 subfamily cytokine, has been implicated in inflammatory disorders including rheumatoid arthritis, psoriasis and, lately, asthma. Here, through the analysis of transcriptomic datasets of lung tissue of large asthma cohorts, we report that IL-19 expression is upregulated in asthma and correlates with disease severity. The gene expression of IL-19 was significantly higher in lung tissue from patients with severe and mild/moderate asthma compared to healthy controls. IL-19 protein level, however, was significantly higher in the blood and saliva of patients with severe asthma compared to mild/moderate subgroups as measured by ELISA assay. IL-19 protein level was not affected by corticosteroid treatment in plasma. Our data provide insights into the potential use of IL-19 as a saliva marker for asthma severity and a potential therapeutic target.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.688
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.093
GPT teacher head0.427
Teacher spread0.333 · 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