Evidence map›Paper›PMID 35458591›Full record

ArticleMolecules (Basel, Switzerland)2022

The Facile Preparation of PBA-GO-CuO-Modified Electrochemical Biosensor Used for the Measurement of α-Amylase Inhibitors' Activity.

Min Li, Xiaoying Yin, Hongli Shan, Chenting Meng, Shengxue Chen, Yinan Yan

Open access · goldAbstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2022. 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
0.3field-weighted citation impact, top 48% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

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

6 authors at 2 institutions in 1 country.

Min LiCollege of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China.
Xiaoying YinCollege of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China.
Hongli ShanCollege of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China.
Chenting MengCollege of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China.
Shengxue ChenCollege of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China.
Yinan YanCollege of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China.
Shanghai University of Engineering Science · CNNational Engineering Research Center for Nanotechnology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Element doping and nanoparticle decoration of graphene is an effective strategy to fabricate biosensor electrodes for specific biomedical signal detections. In this study, a novel nonenzymatic glucose sensor electrode was developed with copper oxide (CuO) and boron-doped graphene oxide (B-GO), which was firstly used to reveal rhubarb extraction's inhibitive activity toward α-amylase. The 1-pyreneboronic acid (PBA)-GO-CuO nanocomposite was prepared by a hydrothermal method, and its successful boron doping was confirmed by transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS), in which the boron doping rate is unprecedentedly up to 9.6%. The CuO load reaches ~12.5 wt.%. Further electrochemical results showed that in the enlarged cyclic voltammograms diagram, the electron-deficient boron doping sites made it easier for the electron transfer in graphene, promoting the valence transition from CuO to the electrode surface. Moreover, the sensor platform was ultrasensitive to glucose with a detection limit of 0.7 μM and high sensitivity of 906 μA mM

Indexed as

Biosensing TechniquesGraphitealpha-AmylasesBoronCopperElectrochemical TechniquesElectrodesGlucosealpha-AmylasesBoronCoppercupric oxideGlucoseGraphiteboron-dopedcopper oxidegraphenenonenzymatic glucose sensor

Identifiers

PMID35458591
PMCPMC9030138
OpenAlexW4224301331

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.