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Abstract 16413: MicroRNAs Mediate Cardiac RNA-induced Inflammatory Response <i>via</i> Toll-like Receptor 7

2015· article· en· W4242066172 on OpenAlexaff
Yan Feng, Hongliang Chen, Lin Zou, Dan Yan, Ganqiong Xu, Wei Chao

Bibliographic record

VenueCirculation · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsMedicineCytokineRNAFlow cytometrymicroRNAInflammationMolecular biologyImmune systemTumor necrosis factor alphaTLR3Toll-like receptorPharmacologyImmunologyBiologyInnate immune systemBiochemistryGene

Abstract

fetched live from OpenAlex

Introduction: We have reported that RNA released from necrotic cells induces cytokine production and may contribute to myocardial ischemia/reperfusion (I/R) injury. Our previous study has also demonstrated that RNA isolated from the heart elicits a robust cytokine response in both cardiomyocytes (CMs) and immune cells, but the type of RNA responsible for the inflammatory effect is unknown. We hypothesize that extracellular microRNAs (miRs) mediate the inflammatory effects. Methods: I/R model: mice were subjected to sham procedure or coronary occlusion for 45 min followed by reperfusion. miR array : 68 miRs in the plasma were quantified. Cytokine detection : CMs and macrophages (Mф) were treated with synthetic miRs for 18 h. Cytokines in media were measured by ELISA. miR uptake : Uptake of fluorescent-labeled miR in Mфs was detected by fluorescent microscopy and flow cytometry. miR inhibition : Locked nucleic acid-based inhibitors complementary to 6 target miRs were mixed as anti-miRs-combo. Results: Compared to the sham procedure, 31 out of 68 miRs were significantly increased by > 2-fold at 4 h following I/R. To test whether miR induces inflammatory response, we treated CMs and Mфs with selected 8 miR mimics (0.5 - 1500 nM) and found that 6 of them (miR-34a, -122, -133a, 142a, -146a, -208a) induced cytokine response in a dose-dependent manner. The effects were abolished by pre-treatment of RNase (but not DNase) and by mutations (U→A). Similar to cardiac total RNA, miR-induced cytokines was completely diminished in TLR7 -/- or MyD88 -/- , but not in TLR3 -/- or Trif -/- Mфs, and significantly inhibited by a specific TLR7 inhibitor in CMs. After incubation with fluorescent miR-133a, TLR7 -/- Mфs had similar cellular fluorescence as WT Mфs. Importantly, anti-miRs-combo significantly decreased cardiac RNA-induced cytokine production in both Mфs and CMs. Conclusions: Our data demonstrate that 1) Multiple cellular miRs are released to circulation during I/R; 2) Six miR mimics induce cytokine production specifically via TLR7-MyD88 signaling. 3) Endogenous miRs mediate in part cardiac RNA-induced cytokine response. These data suggest that cellular miRs are potent proinflammatory ligands that act through TLR7-MyD88 signaling.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.245
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2015
Admission routes1
Has abstractyes

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