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Record W2760887315 · doi:10.4049/jimmunol.1700985

Mechanisms of the Innate Defense Regulator Peptide-1002 Anti-Inflammatory Activity in a Sterile Inflammation Mouse Model

2017· article· en· W2760887315 on OpenAlexafffund
Bing Wu, Amy Huei‐Yi Lee, Robert E. W. Hancock

Bibliographic record

VenueThe Journal of Immunology · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsInflammationRegulatorInnate immune systemInflammatory responseCell biologyPeptideBiologyImmunologyBiochemistryImmune systemGene

Abstract

fetched live from OpenAlex

Innate defense regulator (IDR) peptide-1002 is a synthetic host defense peptide derivative with strong anti-inflammatory properties. Extending previous data, IDR-1002 suppressed in vitro inflammatory responses in RAW 264.7 murine monocyte/macrophage cells challenged with the TLR4 agonist LPS and TLR2 agonists lipoteichoic acid and zymosan. To investigate the anti-inflammatory mechanisms of IDR-1002 in vivo, the PMA-induced mouse ear inflammation model was used. Topical IDR-1002 treatment successfully dampened PMA-induced ear edema, proinflammatory cytokine production, reactive oxygen and nitrogen species release, and neutrophil recruitment in the ears of CD1 mice. Advanced RNA transcriptomic analysis on the mouse ear transcriptome revealed that IDR-1002 reduced sterile inflammation by suppressing the expression of transmembrane G protein-coupled receptors (class A/1 rhodopsin-like), including receptors for chemokines, PGs, histamine, platelet activating factor, and anaphylatoxin. IDR-1002 also dampened the IFN-γ response and repressed the IFN regulatory factor 8-regulated network that controls central inflammatory pathways. This study demonstrates that IDR-1002 exhibits strong in vitro and in vivo anti-inflammatory activities, informs the underlying anti-inflammatory mechanisms, and reveals its potential as a novel therapeutic for inflammatory 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 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)0.002
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 score0.062
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.231
Teacher spread0.218 · 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

Citations52
Published2017
Admission routes2
Has abstractyes

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