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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 OpenAlexaff
Fatemeh Saheb Sharif‐Askari, Narjes Saheb Sharif‐Askari, Swati Goel, Bassam Mahboub, Abdul W. Ansari, Mohamad‐Hani Temsah, Adel M. Zakri, Elaref Ratemi, Rifat Hamoudi, Qutayba Hamid, Rabih Halwani

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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

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 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

Citations15
Published2021
Admission routes1
Has abstractyes

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