Evidence map›Paper›PMID 28025540›Full record

ArticleSensors (Basel, Switzerland)2016

Nanostructured Tip-Shaped Biosensors: Application of Six Sigma Approach for Enhanced Manufacturing.

Seong-Joong Kahng, Jong-Hoon Kim, Jae-Hyun Chung

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Seong-Joong KahngDepartment of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA. sjkahng@uw.edu.
Jong-Hoon KimSchool of Engineering and Computer Science, Washington State University, Vancouver, WA 98686, USA. jh.kim@wsu.edu.
Jae-Hyun ChungDepartment of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA. jae71@uw.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanostructured tip-shaped biosensors have drawn attention for biomolecule detection as they are promising for highly sensitive and specific detection of a target analyte. Using a nanostructured tip, the sensitivity is increased to identify individual molecules because of the high aspect ratio structure. Various detection methods, such as electrochemistry, fluorescence microcopy, and Raman spectroscopy, have been attempted to enhance the sensitivity and the specificity. Due to the confined path of electrons, electrochemical measurement using a nanotip enables the detection of single molecules. When an electric field is combined with capillary action and fluid flow, target molecules can be effectively concentrated onto a nanotip surface for detection. To enhance the concentration efficacy, a dendritic nanotip rather than a single tip could be used to detect target analytes, such as nanoparticles, cells, and DNA. However, reproducible fabrication with relation to specific detection remains a challenge due to the instability of a manufacturing method, resulting in inconsistent shape. In this paper, nanostructured biosensors are reviewed with our experimental results using dendritic nanotips for sequence specific detection of DNA. By the aid of the Six Sigma approach, the fabrication yield of dendritic nanotips increases from 20.0% to 86.6%. Using the nanotips, DNA is concentrated and detected in a sequence specific way with the detection limit equivalent to 1000 CFU/mL. The pros and cons of a nanotip biosensor are evaluated in conjunction with future prospects.

Indexed as

Biosensing TechniquesDNALimit of DetectionNanostructuresNanotechnologySpectrum Analysis, RamanDNAbiosensornanofabricationnanotipsensitivitysix-sigma approachspecificity

Identifiers

PMID28025540
PMCPMC5298590

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Registered trials

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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.