Evidence map›Paper›PMID 28299957›Full record

ArticleJournal of diabetes science and technology2017

Enhancing Glycemic Control via Detection of Insulin Using Electrochemical Impedance Spectroscopy.

Aldin Malkoc, David Probst, Chi Lin, Mukund Khanwalker, Connor Beck, Curtiss B Cook, Jeffrey T La Belle

Abstract read
In one paragraph

Article in Journal of diabetes science and technology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Smart Pens Will Improve Insulin Therapy.Journal of diabetes science and technology · 2018
    Article
  4. Article
  5. 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.

Aldin Malkoc1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
David Probst1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Chi Lin1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Mukund Khanwalker1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Connor Beck1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Curtiss B Cook2 Mayo Clinic Arizona, Scottsdale, AZ, USA.
Jeffrey T La Belle1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrently, glycemic management for individuals with diabetes mellitus involves monitoring glucose only, which is insufficient as glucose metabolism involves other biomarkers such as insulin. Monitoring additional biomarkers alongside glucose has been proposed to improve glycemic control. In this work, the development of a rapid and label-free insulin biosensor with high sensitivity and accuracy is presented. The insulin sensor prototype also serves as a prior study for a multimarker sensing platform technology that can further improve glycemic control in the future.

methodsElectrochemical impedance spectroscopy was used to identify an optimal frequency specific to insulin detection on a gold disk electrode with insulin antibody immobilized, which was accomplished by conjugating the primary amines of insulin antibody to the carboxylic bond of the self-assembling monolayer on the gold surface. After blocking with ethanolamine, the insulin physiological concentration gradient was tested. The imaginary impedance was correlated to insulin concentration and the results were compared with standard equivalent circuit analysis and correlation of charge transfer resistance to target concentration.

resultsThe optimal frequency of insulin is 810.5 Hz, which is characterized by having the highest sensitivity and sufficient specificity. The lower limit of detection was 2.26 [Formula: see text] which is comparable to a standard and better than traditional approaches.

conclusionAn insulin biosensor prototype capable of detecting insulin in physiological range without complex data normalization was developed. This prototype will be the ground works of a multimarker platform sensor technology for future all-in-one glycemic management sensors.

Indexed as

BiomarkersBiosensing TechniquesDielectric SpectroscopyHumansInsulinBiomarkersInsulindiabetes mellituselectrochemical impedance spectroscopyimaginary impedanceinsulinlabel freepoint-of-care

Identifiers

PMID28299957
PMCPMC5950988

What Socratic 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 Socratic graph.