Evidence map›Paper›PMID 32405448›Full record

ReviewChemistryOpen2020

Protein Assays on Organic Electronics: Rational Device and Material Designs for Organic Transistor-Based Sensors.

Tsukuru Minamiki, Riku Kubota, Yui Sasaki, Koichiro Asano, Tsuyoshi Minami

Abstract readReview
In one paragraph

Review in ChemistryOpen, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Tsukuru MinamikiInstitute of Industrial Science The University of Tokyo 4-6-1 Komaba, Meguro-ku Tokyo 153-8505 Japan.
Riku KubotaInstitute of Industrial Science The University of Tokyo 4-6-1 Komaba, Meguro-ku Tokyo 153-8505 Japan.
Yui SasakiInstitute of Industrial Science The University of Tokyo 4-6-1 Komaba, Meguro-ku Tokyo 153-8505 Japan.
Koichiro AsanoInstitute of Industrial Science The University of Tokyo 4-6-1 Komaba, Meguro-ku Tokyo 153-8505 Japan.
Tsuyoshi MinamiInstitute of Industrial Science The University of Tokyo 4-6-1 Komaba, Meguro-ku Tokyo 153-8505 Japan.ORCID 0000-0001-8331-378X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial receptor-based protein assays have various attractive features such as a long-term stability, a low-cost production process, and the ease of tuning the target specificity. However, such protein sensors are still immature compared with conventional immunoassays. To enhance the application potential of synthetic sensing materials, organic field-effect transistors (OFETs) are some of the suitable platforms for protein assays because of their solution processability, durability, and compact integration. Importantly, OFETs enable the electrical readout of the protein recognition phenomena of artificial receptors on sensing electrodes. Thus, we believe that OFETs functionalized with artificial protein receptors will be a powerful tool for the on-site analyses of target proteins. In this Minireview, we summarize the recent progress of the OFET-based protein assays including the rational design strategies for devices and sensing materials.

Indexed as

Aptamers, PeptideBiosensing TechniquesElectrochemical TechniquesElectrodesHumansImmobilized ProteinsNickelNitrilotriacetic AcidOrganic ChemicalsReceptors, ArtificialSurface PropertiesTransistors, ElectronicAptamers, PeptideImmobilized ProteinsNickelNitrilotriacetic AcidOrganic ChemicalsReceptors, Artificialartificial receptorshost-guest chemistryorganic transistorsprotein assaysself-assembled monolayers

Identifiers

PMID32405448
PMCPMC7216454

What OpenQuestion holds

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LicenceCC BY-NC
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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.