Evidence map›Paper›PMID 29899282›Full record

ReviewSensors (Basel, Switzerland)2018

Recent Developments in Enzyme, DNA and Immuno-Based Biosensors.

Melis Asal, Özlem Özen, Mert Şahinler, İlker Polatoğlu

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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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

4 authors.

Melis AsalDepartment of Molecular Biology and Genetics, İzmir International Biomedicine and Genome Institute, Dokuz Eylül University, Balçova, 35340 İzmir, Turkey. melis.asal@ogr.deu.edu.tr.ORCID 0000-0002-2761-0920
Özlem ÖzenDepartment of Pharmacology, Ege University, Institute of Health Sciences, Bornova, 35040 İzmir, Turkey. zlemozen@gmail.com.ORCID 0000-0003-1522-1271
Mert ŞahinlerDepartment of Bioengineering, Graduate School of Natural and Applied Sciences, Ege University, Bornova, 35040 İzmir, Turkey. mertsahinler@hotmail.com.ORCID 0000-0001-7632-1466
İlker PolatoğluBioengineering Department, Manisa Celal Bayar University, Yunusemre, 45140 Manisa, Turkey. ilker.polatoglu@cbu.edu.tr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Novel sensitive, rapid and economical biosensors are being developed in a wide range of medical environmental and food applications. In this paper, we review some of the main advances in the field over the past few years by discussing recent studies from literature. A biosensor, which is defined as an analytical device consisting of a biomolecule, a transducer and an output system, can be categorized according to the type of the incorporated biomolecule. The biomolecules can be enzymes, antibodies, ssDNA, organelles, cells etc. The main biosensor categories classified according to the biomolecules are enzymatic biosensors, immunosensors and DNA-based biosensors. These sensors can measure analytes produced or reduced during reactions at lower costs compared to the conventional detection techniques. Numerous types of biosensor studies conducted over the last decade have been explored here to reveal their key applications in medical, environmental and food industries which provide comprehensive perspective to the readers. Overviews of the working principles and applications of the reviewed sensors are also summarized.

Indexed as

AntibodiesBiological ProductsBiosensing TechniquesDNAEnzymesAntibodiesBiological ProductsDNAEnzymesbiosensorDNAenvironmental analysisenzymefood analysisimmunosensormedical analysisnanotechnology

Identifiers

PMID29899282
PMCPMC6021829

What OpenQuestion holds

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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.