Evidence map›Paper›PMID 37366944›Full record

ReviewBiosensors2023

Graphene-Based Sensors for the Detection of Microorganisms in Food: A Review.

Jingrong Gao, Aniket Chakraborthy, Shan He, Song Yang, Nasrin Afsarimanesh, Anindya Nag, Shanggui Deng

Abstract readReview
In one paragraph

Review in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Jingrong GaoSchool of Food and Pharmacy, Zhejiang Ocean University, Zhoushan 316022, China.
Aniket ChakraborthyFaculty of Electrical and Computer Engineering, Technische Universität Dresden, 01062 Dresden, Germany.ORCID 0000-0002-3553-522X
Shan HeSchool of Food and Pharmacy, Zhejiang Ocean University, Zhoushan 316022, China.
Song YangYihai Food Technology Co., Ltd., Ma'anshan 243000, China.
Nasrin AfsarimaneshSchool of Civil and Mechanical Engineering, Curtin University, Perth, WA 2605, Australia.
Anindya NagFaculty of Electrical and Computer Engineering, Technische Universität Dresden, 01062 Dresden, Germany.ORCID 0000-0002-3760-1470
Shanggui DengSchool of Food and Pharmacy, Zhejiang Ocean University, Zhoushan 316022, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a constant need to maintain the quality of consumed food. In retrospect to the recent pandemic and other food-related problems, scientists have focused on the numbers of microorganisms that are present in different food items. As a result of changes in certain environmental factors such as temperature and humidity, there is a constant risk for the growth of harmful microorganisms, such as bacteria and fungi, in consumed food. This questions the edibility of the food items, and constant monitoring to avoid food poisoning-related diseases is required. Among the different nanomaterials used to develop sensors to detect microorganisms, graphene has been one of the primary materials due to its exceptional electromechanical properties. Graphene sensors are able to detect microorganisms in both a composite and non-composite manner, due to their excellent electrochemical characteristics such as their high aspect ratios, excellent charge transfer capacity and high electron mobility. The paper depicts the fabrication of some of these graphene-based sensors, and their utilization to detect bacteria, fungi and other microorganisms that are present in very small amounts in different food items. In addition to the classified manner of the graphene-based sensors, this paper also depicts some of the challenges that exist in current scenarios, and their possible remedies.

Indexed as

Biosensing TechniquesGraphiteNanostructuresGraphitecompositesE. coligraphenemicroorganismssensors

Identifiers

PMID37366944
PMCPMC10296147

What OpenQuestion holds

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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.