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Role of proteinase‐activated receptor‐2 in anti‐bacterial and immunomodulatory effects of interferon‐γ on human neutrophils and monocytes

2011· article· en· W1567728895 on OpenAlexaff
Victoria Shpacovitch, M Feld, Dirk Holzinger, M. Kido, Morley D. Hollenberg, Francesca Levi‐Schaffer, Nathalie Vergnolle, Stephan Ludwig, Johannes Roth, Thomas A. Luger, Martin Steinhoff

Bibliographic record

VenueImmunology · 2011
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsCanadian Institutes of Health ResearchUniversity of Calgary
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsAgonistInnate immune systemSecretionPhagocytosisChemotaxisBiologyInterferonMonocyteMicrobiologyReceptorPhagocyteImmune systemImmunologyCell biologyBiochemistry

Abstract

fetched live from OpenAlex

Recent studies show that proteinase-activated receptor-2 (PAR(2)) contributes to the development of inflammatory responses. However, investigations into the precise role of PAR(2) activation in the anti-microbial defence of human leucocytes are just beginning. We therefore evaluated the contribution of PAR(2) to the anti-microbial response of isolated human innate immune cells. We found that PAR(2) agonist, acting alone, enhances phagocytosis of Staphylococcus aureus and killing of Escherichia coli by human leucocytes, and that the magnitude of the effect is similar to that of interferon-γ (IFN-γ). However, co-application of PAR(2) -cAP and IFN-γ did not enhance the phagocytic and bacteria-killing activity of leucocytes beyond that triggered by either agonist alone. On the other hand, IFN-γ enhances PAR(2) agonist-induced monocyte chemoattractant protein 1 (MCP-1) secretion by human neutrophils and monocytes. Furthermore, phosphoinositide-3 kinase and janus kinase molecules are involved in the synergistic effect of PAR(2) agonist and IFN-γ on MCP-1 secretion. Our findings suggest a potentially protective role of PAR(2) agonists in the anti-microbial defence established by human monocytes and neutrophils.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.448

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 head0.022
GPT teacher head0.255
Teacher spread0.233 · 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 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

Citations13
Published2011
Admission routes1
Has abstractyes

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