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Record W1996110378 · doi:10.1186/1710-1492-10-s1-a40

Regulation of Proteinase Activated Receptor-2 on airway epithelium

2014· article· en· W1996110378 on OpenAlexaffvenue
Vivek Gandhi, Harissios Vliagoftis

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2014
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRespiratory epitheliumImmunologyEpitheliumAsthmaAllergenInflammationReceptorAirwayBiologyAtopyMedicineAllergyPathology

Abstract

fetched live from OpenAlex

The prevalence of allergic asthma has increased dramatically over the last 20 years. Environmental allergens such as house dust mites (HDM), cockroach, fungi and pollens are major asthma triggers. Recent studies indicate that the serine proteinase activity of these allergens is an important factor contributing to their ability to induce airway inflammation. Allergen serine proteinases can activate Proteinase Activated Receptor -2 (PAR-2), a G protein coupled receptor, which is upregulated on the airway epithelium of asthmatics. PAR-2 activation is pro-inflammatory in many biological systems. PAR-2 polymorphisms are associated with the development of atopy. We have shown that allergic sensitization and inflammation in mouse models of asthma is PAR-2 dependent. We have proposed that PAR-2 on the airway epithelium is a sensor for environmental allergens and leads to allergic inflammation. However, the regulation of PAR-2 expression on airway epithelium is poorly studied. As asthmatic airways are under various types of cellular stress, we hypothesized that cellular stress regulates PAR-2 on airway epithelium. To study the effect of cellular stress on PAR-2 expression, Normal Human Bronchial Epithelial (NHBE) cells were exposed to various stressors such as inflammatory mediators, hypoxia, growth factor deprivation, ROS (Reactive Oxygen Species) and RNS (Reactive Nitrogen Species) for various time periods and PAR-2 mRNA levels were studied by real time PCR. PAR-2 function in stressed cells was assessed by measuring IL-8 release following activation with PAR-2 specific activating peptide (PAR-2 AP). Growth factor deprivation significantly upregulated PAR-2 mRNA (2.25 +/- 0.2 fold), while all the other studied cellular stress stimuli did not modulate PAR-2 expression on airway epithelial cells. Growth factor deprived cells showed significantly upregulated PAR-2 mediated IL-8 release (2.1 +/- 0.2 fold) compared to cells grown with growth factors. Addition of epinephrine, a growth medium supplement used for airway epithelial cells, prevented the effects of growth factors deprivation on PAR-2 expression. Cellular stress could be the driving force for increased PAR-2 expression in asthmatic airways. Further activation of this upregulated PAR-2 can perpetuate inflammation by releasing higher levels of inflammatory mediators. Epinephrine, an adrenergic agonist, neutralizes stress effect on PAR-2 expression. Understanding the mechanisms of these effects could lead to the development of more specific treatments for preventing PAR-2 mediated airway inflammation.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.301
Teacher spread0.278 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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