Evidence map›Paper›PMID 30613300›Full record

ReviewTheranostics2018

Dendrimer- and copolymer-based nanoparticles for magnetic resonance cancer theranostics.

Sayoni Ray, Zhao Li, Chao-Hsiung Hsu, Lian-Pin Hwang, Ying-Chih Lin, Pi-Tai Chou, Yung-Ya Lin

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Theranostics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
–field-weighted citation impact
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

44 citing papers in PubMed.

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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

7 authors.

Sayoni RayDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA.
Zhao LiDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA.
Chao-Hsiung HsuDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA.
Lian-Pin HwangDepartment of Chemistry, National Taiwan University, Taipei 10617, Taiwan.
Ying-Chih LinDepartment of Chemistry, National Taiwan University, Taipei 10617, Taiwan.
Pi-Tai ChouDepartment of Chemistry, National Taiwan University, Taipei 10617, Taiwan.
Yung-Ya LinDepartment of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer theranostics is one of the most important approaches for detecting and treating patients at an early stage. To develop such a technique, accurate detection, specific targeting, and controlled delivery are the key components. Various kinds of nanoparticles have been proposed and demonstrated as potential nanovehicles for cancer theranostics. Among them, polymer-like dendrimers and copolymer-based core-shell nanoparticles could potentially be the best possible choices. At present, magnetic resonance imaging (MRI) is widely used for clinical purposes and is generally considered the most convenient and noninvasive imaging modality. Superparamagnetic iron oxide (SPIO) and gadolinium (Gd)-based dendrimers are the major nanostructures that are currently being investigated as nanovehicles for cancer theranostics using MRI. These structures are capable of specific targeting of tumors as well as controlled drug or gene delivery to tumor sites using pH, temperature, or alternating magnetic field (AMF)-controlled mechanisms. Recently, Gd-based pseudo-porous polymer-dendrimer supramolecular nanoparticles have shown 4-fold higher T

Indexed as

AnimalsDendrimersDrug Delivery SystemsHumansMagnetic Resonance ImagingNanoparticlesNeoplasmsPolymersTheranostic NanomedicineDendrimersPolymerscancer theranosticscopolymer nanoparticledendrimer nanoparticlemagnetic resonance

Identifiers

PMID30613300
PMCPMC6299700

What OpenQuestion holds

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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.