Evidence map›Paper›PMID 29200502›Full record

ArticleMikrochimica acta2017

Lateral flow assay for carbohydrate antigen 19-9 in whole blood by using magnetized carbon nanotubes.

Yan Huang, Yongqiang Wen, Kwaku Baryeh, Sunitha Takalkar, Michelle Lund, Xueji Zhang, Guodong Liu

Open access · greenAbstract read
In one paragraph

Article in Mikrochimica acta, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

13 citing papers in PubMed, 46 citations in OpenAlex.

  1. Article
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  3. A Wearable In-Pad Diagnostic for the Detection of Disease Biomarkers in Menstruation Blood.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
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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

7 authors at 2 institutions in 2 countries.

Yan HuangResearch Center for Bioengineering and Sensing Technology, University of Science & Technology Beijing, Beijing 100083, PR China.
Yongqiang WenResearch Center for Bioengineering and Sensing Technology, University of Science & Technology Beijing, Beijing 100083, PR China.
Kwaku BaryehDepartment of Chemistry and Biochemistry, North Dakota State University, Fargo, North Dakota 58105, United States.
Sunitha TakalkarDepartment of Chemistry and Biochemistry, North Dakota State University, Fargo, North Dakota 58105, United States.
Michelle LundDepartment of Chemistry and Biochemistry, North Dakota State University, Fargo, North Dakota 58105, United States.
Xueji ZhangResearch Center for Bioengineering and Sensing Technology, University of Science & Technology Beijing, Beijing 100083, PR China.
Guodong LiuDepartment of Chemistry and Biochemistry, North Dakota State University, Fargo, North Dakota 58105, United States.
North Dakota State University · USUniversity of Science and Technology Beijing · CN

Funding

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

Abstract

The authors describe a rapid, low-cost and sensitive approach for the determination of carbohydrate antigen 19-9 (CA 19-9) in whole blood by using magnetized carbon nanotube (MCNT) and lateral flow strip biosensor (LFSB). MCNTs were synthesized by depositing magnetite (Fe

Indexed as

Biosensing TechniquesBlood Chemical AnalysisCA-19-9 AntigenHumansLimit of DetectionMagnetsNanotubes, CarbonCA-19-9 AntigenNanotubes, CarbonCA 19-9lateral flow assaymagnetized carbon nanotubevisual detection

Identifiers

PMID29200502
PMCPMC5708549
OpenAlexW2747967006

What OpenQuestion holds

Textmetadata
LicenceTDM
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.