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Record W2048673492 · doi:10.1371/journal.pone.0093946

IgE Regulates the Expression of smMLCK in Human Airway Smooth Muscle Cells

2014· article· en· W2048673492 on OpenAlexafffund
Jyoti Balhara, Naresh Singh Redhu, Lianyu Shan, Abdelilah S. Gounni

Bibliographic record

VenuePLoS ONE · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMast cells and histamine
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health ResearchCanadian Thoracic SocietyManitoba Health Research Council
KeywordsImmunoglobulin EDownregulation and upregulationSykCD23p38 mitogen-activated protein kinasesKinaseCell biologyMyosin light-chain kinaseMAPK/ERK pathwayMyosinProtein kinase AChemistryImmunologyBiologySignal transductionTyrosine kinaseAntibodyBiochemistry

Abstract

fetched live from OpenAlex

Previous studies have shown that enhanced accumulation of contractile proteins such as smooth muscle myosin light chain kinase (smMLCK) plays a major role in human airway smooth muscle cells (HASM) cell hypercontractility and hypertrophy. Furthermore, serum IgE levels play an important role in smooth muscle hyperreactivity. However, the effect of IgE on smMLCK expression has not been investigated. In this study, we demonstrate that IgE increases the expression of smMLCK at mRNA and protein levels. This effect was inhibited significantly with neutralizing abs directed against FcεRI but not with anti-FcεRII/CD23. Furthermore, Syk knock down and pharmacological inhibition of mitogen activated protein kinases (MAPK) (ERK1/2, p38, and JNK) and phosphatidylinositol 3-kinase (PI3K) significantly diminished the IgE-mediated upregulation of smMLCK expression in HASM cells. Taken together, our data suggest a role of IgE in regulating smMLCK in HASM cells. Therefore, targeting the FcεRI activation on HASM cells may offer a novel approach in controlling the bronchomotor tone in allergic asthma.

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 score0.001
Threshold uncertainty score0.005

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 integrity0.0000.000
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 head0.017
GPT teacher head0.196
Teacher spread0.179 · 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

Citations7
Published2014
Admission routes2
Has abstractyes

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Same venuePLoS ONESame topicMast cells and histamineFrench-language works237,207