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Record W2025887296 · doi:10.1155/2015/520871

A Lipid Mediator Hepoxilin A3 Is a Natural Inducer of Neutrophil Extracellular Traps in Human Neutrophils

2015· article· en· W2025887296 on OpenAlexafffund
David N. Douda, Hartmut Grasemann, C.R. Pace-Asciak, Nades Palaniyar

Bibliographic record

VenueMediators of Inflammation · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health ResearchHospital for Sick ChildrenUniversity of TorontoCanadian HIV Trials Network, Canadian Institutes of Health Research
KeywordsNeutrophil extracellular trapsInducerMediatorExtracellularLipid signalingChemistryNeutrophileBiochemistryImmunologyInflammationBiologyCell biologyEnzymeIn vitroGene

Abstract

fetched live from OpenAlex

Pulmonary exacerbations in cystic fibrosis airways are accompanied by inflammation, neutrophilia, and mucous thickening. Cystic fibrosis sputum contains a large amount of uncleared DNA contributed by neutrophil extracellular trap (NET) formation from neutrophils. The exact mechanisms of the induction of NETosis in cystic fibrosis airways remain unclear, especially in uninfected lungs of patients with early cystic fibrosis lung disease. Here we show that Hepoxilin A3, a proinflammatory eicosanoid, and the synthetic analog of Hepoxilin B3, PBT-3, directly induce NETosis in human neutrophils. Furthermore, we show that Hepoxilin A3-mediated NETosis is NADPH-oxidase-dependent at lower doses of Hepoxilin A3, while it is NADPH-oxidase-independent at higher doses. Together, these results demonstrate that Hepoxilin A3 is a previously unrecognized inducer of NETosis in cystic fibrosis lungs and may represent a new therapeutic target for treating cystic fibrosis and other inflammatory lung diseases.

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 score0.004

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 head0.018
GPT teacher head0.248
Teacher spread0.230 · 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

Citations29
Published2015
Admission routes2
Has abstractyes

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