Evidence map›Paper›PMID 35200351›Full record

ArticleBiosensors2022

Ion-Imprinted Polymer-on-a-Sensor for Copper Detection.

Zeynep Gerdan, Yeşeren Saylan, Mukden Uğur, Adil Denizli

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2022. 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
5.4field-weighted citation impact, top 3% 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, 40 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

4 authors at 3 institutions in 1 country.

Zeynep GerdanGraduate School of Biomedical Engineering, Istanbul University-Cerrahpaşa, Istanbul 34320, Turkey.
Yeşeren SaylanDepartment of Chemistry, Hacettepe University, Ankara 06800, Turkey.ORCID 0000-0001-5173-1522
Mukden UğurDepartment of Robotics and Intelligent Systems, Institute of Science, Turkish German University, Istanbul 34820, Turkey.
Adil DenizliDepartment of Chemistry, Hacettepe University, Ankara 06800, Turkey.ORCID 0000-0001-7548-5741
Hacettepe University · TRIstanbul University-Cerrahpaşa · TRTürkisch-Deutsche Universität · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accumulation of metal ions in the body is caused by human activities and industrial uses. Among these metal ions, copper is the third most abundant ion found in the human body and is indispensable for health because it works as a catalyst in the iron absorption processes. However, high doses of copper ions have been reported to generate various diseases. Different types of sensors are used to detect metal ions for several applications. To design selective and specific recognition sites on the sensor surfaces, molecular imprinting is one of the most used alteration methods to detect targets by mimicking natural recognition molecules. In this study, an ion-imprinted polymer-integrated plasmonic sensor was prepared to selectively detect copper (Cu(II)) ions in real-time. Following different characterization experiments, the Cu(II)-imprinted plasmonic sensor was employed for kinetic, selectivity, and reusability studies. According to the results, it was observed that this sensor can measure with 96% accuracy in the Cu(II) concentration range of 0.04-5 μM in buffer solution. The limit of detection and limit of quantification values were computed as 0.027 µM and 0.089 µM. The results also showed that this plasmonic sensor works successfully not only in a buffer solution but also in complex media such as plasma and urine.

Indexed as

CopperMolecular ImprintingHumansIonsMetalsPolymersCopperIonsMetalsPolymerscopper detectionion detectionion-imprinted polymerplasmonic sensor

Identifiers

PMID35200351
PMCPMC8869677
OpenAlexW4210420355

What OpenQuestion holds

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LicenceCC BY
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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.