Evidence map›Paper›PMID 27807499›Full record

ArticleCancer biology & medicine2016

Nanomaterials incorporated ultrasound contrast agents for cancer theranostics.

Lei Fu, Heng-Te Ke

Open access · goldAbstract read
In one paragraph

Article in Cancer biology & medicine, 2016. 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
1.8field-weighted citation impact, top 16% 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, 26 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

2 authors at 2 institutions in 1 country.

Lei FuCenter of Systems Medicine, Chinese Academy of Medical Sciences, Suzhou Institute of Systems Medicine, Suzhou 215123, China.
Heng-Te KeCollege of Pharmaceutical Sciences, Soochow University, Suzhou 215123, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNSoochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanotechnology provides various nanomaterials with tremendous functionalities for cancer diagnostics and therapeutics. Recently, theranostics has been developed as an alternative strategy for efficient cancer treatment through combination of imaging diagnosis and therapeutic interventions under the guidance of diagnostic results. Ultrasound (US) imaging shows unique advantages with excellent features of real-time imaging, low cost, high safety and portability, making US contrast agents (UCAs) an ideal platform for construction of cancer theranostic agents. This review focuses on the development of nanomaterials incorporated multifunctional UCAs serving as theranostic agents for cancer diagnostics and therapeutics, via conjugation of superparamagnetic iron oxide nanoparticles (SPIOs), CuS nanoparticles, DNA, siRNA, gold nanoparticles (GNPs), gold nanorods (GNRs), gold nanoshell (GNS), graphene oxides (GOs), polypyrrole (PPy) nanocapsules, Prussian blue (PB) nanoparticles and so on to different types of UCAs. The cancer treatment could be more effectively and accurately carried out under the guidance and monitoring with the help of the achieved theranostic agents. Furthermore, nanomaterials incorporated theranostic agents based on UCAs can be designed and constructed by demand for personalized and accurate treatment of cancer, demonstrating their great potential to address the challenges of cancer heterogeneity and adaptation, which can provide alternative strategies for cancer diagnosis and therapeutics.

Indexed as

cancernanomaterialsnanomedicinetheranosticsultrasound contrast agents

Identifiers

PMID27807499
PMCPMC5069833
OpenAlexW2529180147

What OpenQuestion holds

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LicenceCC BY-NC-SA
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.