Evidence map›Paper›PMID 29019959›Full record

ReviewSensors (Basel, Switzerland)2017

Recent Advances in Nanoparticle Concentration and Their Application in Viral Detection Using Integrated Sensors.

Brian M Dincau, Yongkuk Lee, Jong-Hoon Kim, Woon-Hong Yeo

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Challenges in Direct Detection of Flaviviruses: A Review.Pathogens (Basel, Switzerland) · 2023
    Review
  3. Review
  4. Review
  5. Article
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.

Brian M DincauSchool of Engineering and Computer Science, Washington State University, Vancouver, WA 98686, USA. brian.dincau@wsu.edu.
Yongkuk LeeGeorge W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30313, USA. yklee@gatech.edu.
Jong-Hoon KimSchool of Engineering and Computer Science, Washington State University, Vancouver, WA 98686, USA. jh.kim@wsu.edu.
Woon-Hong YeoGeorge W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA 30313, USA. whyeo@gatech.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early disease diagnostics require rapid, sensitive, and selective detection methods for target analytes. Specifically, early viral detection in a point-of-care setting is critical in preventing epidemics and the spread of disease. However, conventional methods such as enzyme-linked immunosorbent assays or cell cultures are cumbersome and difficult for field use due to the requirements of extensive lab equipment and highly trained personnel, as well as limited sensitivity. Recent advances in nanoparticle concentration have given rise to many novel detection methodologies, which address the shortcomings in modern clinical assays. Here, we review the primary, well-characterized methods for nanoparticle concentration in the context of viral detection via diffusion, centrifugation and microfiltration, electric and magnetic fields, and nano-microfluidics. Details of the concentration mechanisms and examples of related applications provide valuable information to design portable, integrated sensors. This study reviews a wide range of concentration techniques and compares their advantages and disadvantages with respect to viral particle detection. We conclude by highlighting selected concentration methods and devices for next-generation biosensing systems.

Indexed as

biosensorsnanoparticle concentrationselectivitysensitivityviral detection

Identifiers

PMID29019959
PMCPMC5677234

What OpenQuestion holds

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LicenceCC BY
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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.