Evidence map›Paper›PMID 29747414›Full record

ArticleSensors (Basel, Switzerland)2018

Rapid Iodine Sensing on Mechanically Treated Carbon Nanofibers.

Eunbyul Cho, Alexandra Perebikovsky, Olivia Benice, Sunshine Holmberg, Marc Madou, Maziar Ghazinejad

Open access · goldAbstract read
In one paragraph

Article 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

6 citing papers in PubMed, 34 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Eunbyul ChoDepartment of Biomedical Engineering, University of California, Irvine, CA 92697, USA. eunbyuc@uci.edu.
Alexandra PerebikovskyDepartment of Physics and Astronomy, University of California, Irvine, CA 92697, USA. aperebik@uci.edu.
Olivia BeniceDepartment of Chemistry, University of California, Irvine, CA 92697, USA. obenice@uci.edu.
Sunshine HolmbergDepartment of Mechanical and Aerospace Engineering, University of California, Irvine, CA 92697, USA. sholmber@uci.edu.
Marc MadouDepartment of Mechanical and Aerospace Engineering, University of California, Irvine, CA 92697, USA. mmadou@uci.edu.
Maziar GhazinejadDepartment of Mechanical and Aerospace Engineering, University of California, Irvine, CA 92697, USA. mghazinejad@csufresno.edu.
University of California, Irvine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, we report on a rapid, efficient electrochemical iodine sensor based on mechanically treated carbon nanofiber (MCNF) electrodes. The electrode’s highly graphitic content, unique microstructure, and the presence of nitrogen heteroatoms in its atomic lattice contribute to increased heterogeneous electron transfer and improved kinetics compared to conventional pyrolytic carbons. The electrode demonstrates selectivity for iodide ions in the presence of both interfering agents and high salt concentrations. The sensor exhibits clinically relevant limits of detection of 0.59 µM and 1.41 µM, in 1X PBS and synthetic urine, respectively, and a wide dynamic range between 5 µM and 700 µM. These results illustrate the advantages of the material’s unique electrochemical properties for iodide sensing, in addition to its simple, inexpensive fabrication. The reported iodine sensor eliminates the need for specimen processing, revealing its aptitude for applications in point-of-care diagnostics.

Indexed as

carbon microstructurecarbon nanofiberelectrochemical sensoriodine deficiencypoint-of-care

Identifiers

PMID29747414
PMCPMC5982240
OpenAlexW2802448478

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.