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Record W2147682199 · doi:10.1096/fj.13-248930

Epac1 and Epac2 are differentially involved in inflammatory and remodeling processes induced by cigarette smoke

2014· article· en· W2147682199 on OpenAlexaff
Anouk Oldenburger, Wim Timens, Sophie Bos, Marieke Smit, Alan V. Smrcka, Anne‐Coline Laurent, Junjun Cao, Machteld N. Hylkema, Herman Meurs, Harm Maarsingh, Frank Lezoualc’h, Martina Schmidt

Bibliographic record

VenueThe FASEB Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNational Institute of General Medical SciencesNational Institutes of Health
KeywordsInflammationIn vivoChemistryCell biologyCytokineExtracellular matrixImmunologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

Cigarette smoke (CS) induces inflammatory responses characterized by increase of immune cells and cytokine release. Remodeling processes, such as mucus hypersecretion and extracellular matrix protein production, are also directly or indirectly induced by CS. Recently, we showed that activation of the exchange protein directly activated by cAMP (Epac) attenuates CS extract‐induced interleukin (IL)‐8 release from cultured airway smooth muscle cells. Using an acute, short‐term model of CS exposure, we now studied the role of Epac1, Epac2, and the Epac effector phospholipase‐Cε (PLCε) in airway inflammation and remodeling in vivo. Compared to wild‐type mice exposed to CS, the number of total inflammatory cells, macrophages, and neutrophils and total IL‐6 release was lower in Epac2 ‐/‐ mice, which was also the case for neutrophils and IL‐6 in PLCε ‐/‐ mice. Taken together, Epac2, acting partly via PLCε, but not Epac1, enhances CS‐induced airway inflammation in vivo. In total lung homogenates of Epac1 ‐/‐ mice, MUC5AC and matrix remodeling parameters (transforming growth factor‐β1, collagen I, and fibronectin) were increased at baseline. Our findings suggest that Epac1 primarily is capable of inhibiting remodeling processes, whereas Epac2 primarily increases inflammatory processes in vivo. —Oldenburger, A., Timens, W., Bos, S., Smit, M., Smrcka, A. V., Laurent, A‐C., Cao, J., Hylkema, M., Meurs, H., Maarsingh, H., Lezoualc'h, F., and Schmidt, M., Epac1 and Epac2 are differentially involved in inflammatory and remodeling processes induced by cigarette smoke. FASEB J. 28, 4617–4628 (2014). www.fasebj.org

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.222
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.019
GPT teacher head0.248
Teacher spread0.228 · 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 teacher head, 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

Citations29
Published2014
Admission routes1
Has abstractyes

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