Evidence map›Paper›PMID 28668773›Full record

ArticleBiosensors & bioelectronics2017

Fluorescent carbon nanoparticle-based lateral flow biosensor for ultrasensitive detection of DNA.

Sunitha Takalkar, Kwaku Baryeh, Guodong Liu

Abstract read
In one paragraph

Article in Biosensors & bioelectronics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
6.0field-weighted citation impact, top 3% 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

24 citing papers in PubMed, 103 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

3 authors at 1 institution in 1 country.

Sunitha TakalkarDepartment of Chemistry and Biochemistry, North Dakota State University, Fargo, ND 58102, USA.
Kwaku BaryehDepartment of Chemistry and Biochemistry, North Dakota State University, Fargo, ND 58102, USA.
Guodong LiuDepartment of Chemistry and Biochemistry, North Dakota State University, Fargo, ND 58102, USA. Electronic address: guodong.liu@ndsu.edu.
North Dakota State University · US

Funding

Targeting CLEC-2/podoplanin as a therapeutic strategy for pancreatic cancerP20GM109024 · NIGMS · NORTH DAKOTA STATE UNIVERSITY · PI Megan Orr · 2016 to 2026
$20.5M
NIGMS NIH HHS P20 GM109024
6 · The paper itself

Abstract

We report a fluorescent carbon nanoparticle (FCN)-based lateral flow biosensor for ultrasensitive detection of DNA. Fluorescent carbon nanoparticle with a diameter of around 15nm was used as a tag to label a detection DNA probe, which was complementary with the part of target DNA. A capture DNA probe was immobilized on the test zone of the lateral flow biosensor. Sandwich-type hybridization reactions among the FCN-labeled DNA probe, target DNA and capture DNA probe were performed on the lateral flow biosensor. In the presence of target DNA, FCNs were captured on the test zone of the biosensor and the fluorescent intensity of the captured FCNs was measured with a portable fluorescent reader. After systematic optimizations of experimental parameters (the components of running buffers, the concentration of detection DNA probe used in the preparation of FCN-DNA conjugates, the amount of FCN-DNA dispensed on the conjugate pad and the dispensing cycles of the capture DNA probes on the test-zone), the biosensor could detect a minimum concentration of 0.4 fM DNA. This study provides a rapid and low-cost approach for DNA detection with high sensitivity, showing great promise for clinical application and biomedical diagnosis.

Indexed as

Biosensing TechniquesCarbonDNAFluorescenceHumansNanoparticlesCarbonDNADNAFluorescent carbon nanoparticleLateral flow biosensor

Identifiers

PMID28668773
PMCPMC5556692
OpenAlexW2636998246

What OpenQuestion holds

Textmetadata
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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.