Evidence map›Paper›PMID 22234515›Full record

ReviewChemical Society reviews2012

Silica-based nanoprobes for biomedical imaging and theranostic applications.

Juan L Vivero-Escoto, Rachel C Huxford-Phillips, Wenbin Lin

Abstract readReview
In one paragraph

Review in Chemical Society reviews, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed, 1 pooled it
–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

77 citing papers in PubMed, 1 synthesis or guideline pooled it.

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17 more citing papers are in PubMed but not listed here.

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.

Juan L Vivero-EscotoDepartment of Chemistry, University of North Carolina at Chapel Hill, CB#390, Chapel Hill, North Carolina 27599, USA.
Rachel C Huxford-Phillips
Wenbin Lin

Funding

"Smart" Nanoparticles for Cancer Therapy and ImagingU54CA119343 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI VAN DYKE, TERRY A · 2005 to 2009
$18.3M
Translational Nanosystems for Improved Lung Cancer Treatment with Small MoleculesU54CA151652 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DESIMONE, JOSEPH M. · 2010 to 2014
$12.1M
Nanoscale Metal-organic Frameworks for Imaging and Therapy of Pancreatic CancerU01CA151455 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LIN, WENBIN, YEH, JEN JEN · 2010 to 2014
$2.1M
NCI NIH HHS U01 CA151455NCI NIH HHS U01-CA151455NCI NIH HHS U54 CA119343NCI NIH HHS U54 CA151652NCI NIH HHS U54-CA151652
6 · The paper itself

Abstract

Nanoparticle-based contrast agents are attracting a great deal of attention for various biomedical imaging and theranostic applications. Compared to conventional contrast agents, nanoparticles possess several potential advantages to improve in vivo detection and to enhance targeting efficiency. Silica-based nanoprobes can be engineered to achieve longer blood circulation times, specific clearance pathways, and multivalent binding. In this tutorial review, we summarize the latest progress on designing silica-based nanoprobes for imaging and theranostic applications. The synthesis of both solid silica and mesoporous silica nanoparticles is described, along with different approaches used for surface functionalization. Special emphasis is placed on the application of silica-based nanoprobes in optical, magnetic resonance, and multimodal imaging. The latest breakthroughs in the applications of silica nanoparticles as theranostic agents are also highlighted.

Indexed as

AnimalsCell Line, TumorContrast MediaDiagnostic ImagingMiceNanoparticlesPorositySilicon DioxideContrast MediaSilicon Dioxide

Identifiers

PMID22234515
PMCPMC3777230

What OpenQuestion holds

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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.