Evidence map›Paper›PMID 33324612›Full record

ArticleFrontiers in chemistry2020

Preparation of Electrochemical Sensor Based on Zinc Oxide Nanoparticles for Simultaneous Determination of AA, DA, and UA.

Yuanzhi Pan, Junli Zuo, Zhongyu Hou, Yizhong Huang, Cancan Huang

Abstract read
In one paragraph

Article in Frontiers in chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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  13. Bioinorganic chemistry and applications · 2022
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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

5 authors.

Yuanzhi PanNational Key Laboratory of Science and Technology on Micro/Nano Fabrication, Key Laboratory for Thin Film and Microfabrication of Ministry of Education, Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Junli ZuoDepartment of Geriatrics, Ruijin Hospital, Shanghai Jiao Tong School of Medicine, Shanghai, China.
Zhongyu HouNational Key Laboratory of Science and Technology on Micro/Nano Fabrication, Key Laboratory for Thin Film and Microfabrication of Ministry of Education, Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Yizhong HuangSchool of Materials Science and Engineering, Nanyang Technological University, Singapore, Singapore.
Cancan HuangBeijing Kanghong Biomedical Co., Ltd., Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ZnO nanoparticles (NPs) were synthesized using a hydrothermal method. Scanning electron microscope (SEM) and X-ray diffraction have been used for characterizing the synthesized ZnO NPs. An electrochemical sensor was fabricated using ZnO NPs-modified glassy carbon electrode for simultaneous determination of ascorbic acid (AA), dopamine (DA), and uric acid (UA). The proposed electrochemical sensor exhibited excellent detection performance toward three analytes, demonstrating that it can potentially be applied in clinical applications. The results indicated the ZnO NPs-modified electrode can detect AA in the concentrations range between 50 and 1,000 μM. The ZnO NPs-modified electrode can detect DA in the concentrations range between 2 and 150 μM. The ZnO NPs-modified electrode can detect UA in the concentrations range between 0.2 and 150 μM. The limits of detections of AA, DA, and UA using ZnO NPs-modified electrode were calculated to be 18.4, 0.75, and 0.11 μM, respectively.

Indexed as

ascorbic aciddopamineelectrochemical sensoruric acidzinc oxide

Identifiers

PMID33324612
PMCPMC7723903

What OpenQuestion holds

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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.