Evidence map›Paper›PMID 29286384›Full record

ArticleJournal of visualized experiments : JoVE2017

Synthesis of Monocyte-targeting Peptide Amphiphile Micelles for Imaging of Atherosclerosis.

Christopher Poon, Manjima Sarkar, Eun Ji Chung

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In one paragraph

Article in Journal of visualized experiments : JoVE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 11 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Christopher PoonDepartment of Biomedical Engineering, University of Southern California.
Manjima SarkarDepartment of Biomedical Engineering, University of Southern California.
Eun Ji ChungDepartment of Biomedical Engineering, University of Southern California; eunchung@usc.edu.
University of Southern California · US

Funding

Multimodal Peptide Amphiphile Micelles for AtherosclerosisR00HL124279 · NHLBI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHUNG, EUN JI PAIGE · 2016 to 2018
$747k
NHLBI NIH HHS R00 HL124279
6 · The paper itself

Abstract

Atherosclerosis is a major contributor to cardiovascular disease, the leading cause of death worldwide, which claims 17.3 million lives annually. Atherosclerosis is also the leading cause of sudden death and myocardial infarction, instigated by unstable plaques that rupture and occlude the blood vessel without warning. Current imaging modalities cannot differentiate between stable and unstable plaques that rupture. Peptide amphiphiles micelles (PAMs) can overcome this drawback as they can be modified with a variety of targeting moieties that bind specifically to diseased tissue. Monocytes have been shown to be early markers of atherosclerosis, while large accumulation of monocytes is associated with plaques prone to rupture. Hence, nanoparticles that can target monocytes can be used to discriminate different stages of atherosclerosis. To that end, here, we describe a protocol for the preparation of monocyte-targeting PAMs (monocyte chemoattractant protein-1 (MCP-1) PAMs). MCP-1 PAMs are self-assembled through synthesis under mild conditions to form nanoparticles of 15 nm in diameter with near neutral surface charge. In vitro, PAMs were found to be biocompatible and had a high binding affinity for monocytes. The methods described herein show promise for a wide range of applications in atherosclerosis as well as other inflammatory diseases.

Indexed as

AtherosclerosisHumansMicellesMonocytesNanoparticlesPeptidesMicellesPeptides

Identifiers

PMID29286384
PMCPMC5755426
OpenAlexW2768358024

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.