Evidence map›Paper›PMID 35645256›Full record

ArticleJournal of functional biomaterials2022

Functionalized Graphene Oxide with Chitosan for Dopamine Biosensing.

Amina Omar, Ahmed M Bayoumy, Ahmed A Aly

Open access · goldAbstract read
In one paragraph

Article in Journal of functional biomaterials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

3 citing papers in PubMed, 29 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 2 institutions in 2 countries.

Amina OmarPhysics Department, Biophysics Branch, Faculty of Science, Ain Shams University, Al Obour 11566, Cairo, Egypt.ORCID 0000-0002-8763-1969
Ahmed M BayoumyPhysics Department, Biophysics Branch, Faculty of Science, Ain Shams University, Al Obour 11566, Cairo, Egypt.ORCID 0000-0003-1052-4281
Ahmed A AlyNeuromodulatory Networks-Neuroplasticity Groups, Leibniz Institute for Neurobiology, 39118 Magdeburg, Germany.ORCID 0000-0001-8843-5807
Ain Shams University · EGLeibniz Institute for Neurobiology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detecting biological structures via a rapid and facile method has become a pronounced point of research. Dopamine (DA) detection is critical for the early diagnosis of a variety of neurological diseases/disorders. A study on the real-time optical detection of DA is described here using graphene oxide (GO) functionalized with chitosan (Cs). Hence, a computational model dependent on a high theoretical level density functional theory (DFT) using the B3LYP/LANL2DZ model is carried out to study the physical as well as electronic properties of the proposed interaction between GO functionalized with Cs and its interaction with DA. GO functionalized with a Cs biopolymer was verified as having much higher stability and reactivity. Moreover, the addition of DA to functionalized GO yields structures with the same stability and reactivity. This ensures that GO-Cs is a stable structure with a strong interaction with DA, which is energetically preferred. Molecular electrostatic potential (MESP) calculation maps indicated that the impact of an interaction between GO and Cs increases the number of electron clouds at the terminals, ensuring the great ability of this composite when interacting with DA. Hence, these calculations and experimental results support the feasibility of using GO functionalized with Cs as a DA biosensor.

Indexed as

biosensorchitosandopaminegraphene oxidemolecular modelingQSAR

Identifiers

PMID35645256
PMCPMC9149961
OpenAlexW4225015865

What OpenQuestion holds

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LicenceCC BY
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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.