Evidence map›Paper›PMID 35884273›Full record

ReviewBiosensors2022

Transcription Factor-Based Biosensors for Detecting Pathogens.

Yangwon Jeon, Yejin Lee, Keugtae Kim, Geupil Jang, Youngdae Yoon

Open access · goldAbstract readReview
In one paragraph

Review in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 27% 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

9 citing papers in PubMed, 11 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

5 authors at 3 institutions in 1 country.

Yangwon JeonDepartment of Environmental Health Science, Konkuk University, Seoul 05029, Korea.
Yejin LeeDepartment of Environmental Health Science, Konkuk University, Seoul 05029, Korea.
Keugtae KimDepartment of Environmental & Energy Engineering, University of Suwon, Hwaseong 18323, Korea.ORCID 0000-0003-3036-6217
Geupil JangSchool of Biological Sciences and Technology, Chonnam National University, Gwangju 61186, Korea.
Youngdae YoonDepartment of Environmental Health Science, Konkuk University, Seoul 05029, Korea.
Konkuk University · KRChonnam National University · KRUniversity of Suwon · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microorganisms are omnipresent and inseparable from our life. Many of them are beneficial to humans, while some are not. Importantly, foods and beverages are susceptible to microbial contamination, with their toxins causing illnesses and even death in some cases. Therefore, monitoring and detecting harmful microorganisms are critical to ensuring human health and safety. For several decades, many methods have been developed to detect and monitor microorganisms and their toxicants. Conventionally, nucleic acid analysis and antibody-based analysis were used to detect pathogens. Additionally, diverse chromatographic methods were employed to detect toxins based on their chemical and structural properties. However, conventional techniques have several disadvantages concerning analysis time, sensitivity, and expense. With the advances in biotechnology, new approaches to detect pathogens and toxins have been reported to compensate for the disadvantages of conventional analysis from different research fields, including electrochemistry, nanotechnology, and molecular biology. Among them, we focused on the recent studies of transcription factor (TF)-based biosensors to detect microorganisms and discuss their perspectives and applications. Additionally, the other biosensors for detecting microorganisms reported in recent studies were also introduced in this review.

Indexed as

Biosensing TechniquesToxins, BiologicalElectrochemistryFood ContaminationHumansNanotechnologyTranscription FactorsToxins, BiologicalTranscription Factorsbiodetectionbiosensorscell-based biosensorscell-free biosensorspathogensTF-based biosensors

Identifiers

PMID35884273
PMCPMC9312912
OpenAlexW4283726619

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.