Evidence map›Paper›PMID 20729136›Full record

ArticleOral oncology2010

Dendrimer-triglycine-EGF nanoparticles for tumor imaging and targeted nucleic acid and drug delivery.

Quan Yuan, Eunmee Lee, W Andrew Yeudall, Hu Yang

Abstract read
In one paragraph

Article in Oral oncology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

27 citing papers in PubMed, 57 citations in OpenAlex.

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  13. Targeted nanosystems: Advances in targeted dendrimers for cancer therapy.Nanomedicine : nanotechnology, biology, and medicine · 2016
    Review
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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

4 authors at 1 institution in 1 country.

Quan YuanDepartment of Biomedical Engineering, School of Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA.
Eunmee Lee
W Andrew Yeudall
Hu Yang
Virginia Commonwealth University · US

Funding

Brain-targeted nanomedicine via buccal administrationR21NS063200 · NINDS · VIRGINIA COMMONWEALTH UNIVERSITY · PI YANG, HU · 2009 to 2010
$395k
NINDS NIH HHS R21 NS063200NINDS NIH HHS R21NS063200
6 · The paper itself

Abstract

We designed an epidermal growth factor (EGF)-containing polyamidoamine (PAMAM) Generation 4 dendrimer vector labeled with quantum dots for targeted imaging and nucleic acid delivery. (1)H NMR, SDS-PAGE, and Western blotting were applied to characterize the synthesized G4.0-GGG-EGF nanoparticles. Targeting efficiency, cell viability, proliferation, and intracellular signal transduction were evaluated using HN12, NIH3T3, and NIH3T3/EGFR cells. We found that EGF-conjugated dendrimers did not stimulate growth of EGFR-expressing cells at the selected concentration. Consistent with this, minimal stimulation of post-receptor signaling pathways was observed. These nanoparticles can localize within cells that express the EGFR in a receptor-dependent manner, whereas uptake into cells lacking the receptor was low. A well characterized vimentin shRNA (shVIM) and yellow fluorescent protein (YFP) siRNA were used to test the delivery and transfection efficiency of the constructed targeted vector. Significant knockdown of expression was observed, indicating that this vector is useful for introduction of nucleic acids or drugs into cells by a receptor-targeted mechanism.

Indexed as

NanoparticlesAnimalsDendrimersEpidermal Growth FactorErbB ReceptorsHumansMagnetic Resonance ImagingMiceMouth NeoplasmsNIH 3T3 CellsNucleic AcidsSignal TransductionDendrimersEpidermal Growth FactorErbB ReceptorsNucleic Acids

Identifiers

PMID20729136
PMCPMC2938769
OpenAlexW2138048554

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.