Evidence map›Paper›PMID 29667855›Full record

ArticleJournal of diabetes science and technology2018

A Disposable Tear Glucose Biosensor-Part 5: Improvements in Reagents and Tear Sampling Component.

Chi En Lin, Yuka Ito, Anna Deng, Jared Johns, Daniel Matloff, Curtiss B Cook, Koji Sode, Jeffrey T La Belle

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of diabetes science and technology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 4 institutions in 2 countries.

Chi En Lin1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Yuka Ito2 Department of Biotechnology and Life Science, Graduate School of Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, Japan.
Anna Deng1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Jared Johns1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Daniel Matloff1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Curtiss B Cook3 School of Medicine, Mayo Clinic Arizona, Scottsdale, AZ, USA.
Koji Sode2 Department of Biotechnology and Life Science, Graduate School of Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, Japan.
Jeffrey T La Belle1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Arizona State University · USMayo Clinic in Arizona · USTokyo University of Agriculture and Technology · JPUniversity of North Carolina at Chapel Hill · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A tear glucose (TG) sensor with an integrated tear sampler can provide a noninvasive method for calibrating the continuous TG contact lens and monitoring glucose. Expanding from previous work, an improved TG sensor that implements dried reagents, genetically modified glucose dehydrogenase (GDH), and a tear sampler was developed and compared against the TG sensor prepared with commercial GDH. It was found that neither sensor was affected by the tear interferents: ascorbic acid, acetaminophen, and uric acid. The sensor prepared with commercial GDH generated higher current. This suggests that using enzymes with lower K

Indexed as

Biosensing TechniquesContact LensesBlood GlucoseGlucose 1-DehydrogenaseHumansIndicators and ReagentsTearsBlood GlucoseGlucose 1-DehydrogenaseIndicators and Reagentsdiabetes mellitusglucose dehydrogenaseintegrated tear glucose sensornoninvasive glucose monitoringSchirmer’s test strip

Identifiers

PMID29667855
PMCPMC6134317
OpenAlexW2801532544

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.