Evidence map›Paper›PMID 31628541›Full record

ArticleMikrochimica acta2019

Ultrasensitive electrochemical sensing of dopamine by using dihydroxylatopillar[5]arene-modified gold nanoparticles and anionic pillar[5]arene-functionalized graphitic carbon nitride.

Xiaoping Tan, Shuhua He, Xi Liu, Genfu Zhao, Ting Huang, Long Yang

Abstract read
PubMed Publisher
In one paragraph

Article in Mikrochimica acta, 2019. 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. Review
  2. Article
  3. Review
  4. Article
  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

6 authors.

Xiaoping TanChongqing Key Laboratory of Inorganic Special Functional Materials, College of Chemistry and Chemical Engineering, Yangtze Normal University, Fuling, 408100, China.
Shuhua HeChongqing Key Laboratory of Inorganic Special Functional Materials, College of Chemistry and Chemical Engineering, Yangtze Normal University, Fuling, 408100, China.
Xi LiuChongqing Key Laboratory of Inorganic Special Functional Materials, College of Chemistry and Chemical Engineering, Yangtze Normal University, Fuling, 408100, China.
Genfu ZhaoChongqing Key Laboratory of Inorganic Special Functional Materials, College of Chemistry and Chemical Engineering, Yangtze Normal University, Fuling, 408100, China. fu1165158114@126.com.
Ting HuangChongqing Key Laboratory of Inorganic Special Functional Materials, College of Chemistry and Chemical Engineering, Yangtze Normal University, Fuling, 408100, China.
Long YangChongqing Key Laboratory of Inorganic Special Functional Materials, College of Chemistry and Chemical Engineering, Yangtze Normal University, Fuling, 408100, China. long133109070@126.com.ORCID http://orcid.org/0000-0002-0286-1803

Funding

Basic Research Project of Science and Technology Commission of Chongqing cstc2017jcyjA0656Basic Research Project of Science and Technology Commission of Chongqing cstc2017jcyjAX0031
6 · The paper itself

Abstract

An ultrasensitive and highly selective electrochemical method is described for the determination of dopamine (DA). It is based on the use of a multi-functional nanomaterial composed of water-soluble pillar[5]arene (WP5), dihydroxylatopillar[5]arene (2HP5)-modified gold nanoparticles (GNPs), and graphitic carbon nitride (g-C

Indexed as

Electrochemical detectionFunctionalized pillar[5]areneHost-guest interactionHybrid materialsMacrocyclic hostsMolecular recognitionMulticomponent nanomaterialNanomaterials synthesisSensing platformSupramolecular sensor

Identifiers

PMID31628541

What OpenQuestion holds

Textmetadata
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.