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Record W2945659966 · doi:10.1021/acsnano.8b09679

Delivery of MicroRNAs by Chitosan Nanoparticles to Functionally Alter Macrophage Cholesterol Efflux <i>in Vitro</i> and <i>in Vivo</i>

2019· article· en· W2945659966 on OpenAlexafffund
My-Anh Nguyen, Hailey Wyatt, Leah C. Susser, Michèle Geoffrion, Adil Rasheed, Anne‐Claire Duchez, Mary Lynn Cottee, Esther Afolayan, Eliya Farah, Zaina Kahiel, Marceline Côté, Suresh Gadde, Katey J. Rayner

Bibliographic record

VenueACS Nano · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity of Ottawa
FundersNational Heart, Lung, and Blood InstituteNational Institutes of HealthCanada Research ChairsHeart and Stroke Foundation of Canada
KeywordsIn vivomicroRNAABCA1CholesterolEffluxChitosanIn vitroCell biologyMacrophageGene deliveryIntracellularChemistryTransfectionBiologyBiochemistryGeneTransporterGenetics

Abstract

fetched live from OpenAlex

The prevention and treatment of cardiovascular diseases (CVD) has largely focused on lowering circulating LDL cholesterol, yet a significant burden of atherosclerotic disease remains even when LDL is low. Recently, microRNAs (miRNAs) have emerged as exciting therapeutic targets for cardiovascular disease. miRNAs are small noncoding RNAs that post-transcriptionally regulate gene expression by degradation or translational inhibition of target mRNAs. A number of miRNAs have been found to modulate all stages of atherosclerosis, particularly those that promote the efflux of excess cholesterol from lipid-laden macrophages in the vessel wall to the liver. However, one of the major challenges of miRNA-based therapy is to achieve tissue-specific, efficient, and safe delivery of miRNAs in vivo. We sought to develop chitosan nanoparticles (chNPs) that can deliver functional miRNA mimics to macrophages and to determine if these nanoparticles can alter cholesterol efflux and reverse cholesterol transport in vivo. We developed chNPs with a size range of 150-200 nm via the ionic gelation method using tripolyphosphate (TPP) as a cross-linker. In this method, negatively charged miRNAs were encapsulated in the nanoparticles by ionic interactions with polymeric components. We then optimized the efficiency of intracellular delivery of different formulations of chitosan/TPP/miRNA to mouse macrophages. Using a well-defined miRNA with roles in macrophage cholesterol metabolism, we tested whether chNPs could deliver functional miRNAs to macrophages. We find chNPs can transfer exogenous miR-33 to naïve macrophages and reduce the expression of ABCA1, a potent miR-33 target gene, both in vitro and in vivo, confirming that miRNAs delivered via nanoparticles can escape the endosomal system and function in the RISC complex. Because miR-33 and ABCA1 play a key role in regulating the efflux of cholesterol from macrophages, we also confirmed that macrophages treated with miR-33-loaded chNPs exhibited reduced cholesterol efflux to apolipoprotein A1, further confirming functional delivery of the miRNA. In vivo, mice treated with miR33-chNPs showed decreased reverse cholesterol transport (RCT) to the plasma, liver, and feces. In contrast, when efflux-promoting miRNAs were delivered via chNPs, ABCA1 expression and cholesterol efflux into the RCT pathway were improved. Over all, miRNAs can be efficiently delivered to macrophages via nanoparticles, where they can function to regulate ABCA1 expression and cholesterol efflux, suggesting that these miRNA nanoparticles can be used in vivo to target atherosclerotic lesions.

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 score0.007
Threshold uncertainty score0.566

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 head0.003
GPT teacher head0.199
Teacher spread0.196 · 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

Citations152
Published2019
Admission routes2
Has abstractyes

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