Evidence map›Paper›PMID 25627465›Full record

ReviewJournal of diabetes science and technology2015

Advancing the development of glycated protein biosensing technology: next-generation sensing molecules.

Miho Kameya, Akane Sakaguchi-Mikami, Stefano Ferri, Wakako Tsugawa, Koji Sode

Abstract readReview
In one paragraph

Review in Journal of diabetes science and technology, 2015. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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.

Miho KameyaDepartment of Biotechnology & Life Science, Graduate School of Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan.
Akane Sakaguchi-MikamiDepartment of Medical Technology, School of Health Sciences, Graduate School of Bionics, Computer and Media Sciences, Tokyo University of Technology, Tokyo, Japan.
Stefano FerriDepartment of Biotechnology & Life Science, Graduate School of Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan.
Wakako TsugawaDepartment of Biotechnology & Life Science, Graduate School of Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan.
Koji SodeDepartment of Biotechnology & Life Science, Graduate School of Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan Ultizyme International Ltd, Tokyo, Japan sode@cc.tuat.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Research advances in biochemical molecules have led to the development of convenient and reproducible biosensing molecules for glycated proteins, such as those based on the enzymes fructosyl amino acid oxidase (FAOX) or fructosyl peptide oxidase (FPOX). Recently, more attractive biosensing molecules with potential applications in next-generation biosensing of glycated proteins have been aggressively reported. We review 2 such molecules, fructosamine 6-kinase (FN6K) and fructosyl amino acid-binding protein, as well as their recent applications in the development of glycated protein biosensing systems. Research on FN6K and fructosyl amino acid-binding protein has been opening up new possibilities for the development of highly sensitive and proteolytic-digestion-free biosensing systems for glycated proteins.

Indexed as

Amino Acid OxidoreductasesBiomarkersBiosensing TechniquesFructosamineHumansamadoriaseAmino Acid OxidoreductasesBiomarkersFructosaminefructosyl-peptide oxidasebiosensingfructosamine 6-kinasefructosyl amino acid-binding proteinglycated albuminglycated proteinhemoglobin A1c

Identifiers

PMID25627465
PMCPMC4604589

What OpenQuestion holds

Textmetadata
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.