Evidence map›Paper›PMID 40463338›Full record

ArticleRSC advances2025

Innovative sensors with selectivity enhancement by molecularly imprinted polymers for the concurrent quantification of donepezil and memantine.

Eman M Moaaz, Ahmed S Fayed, Ezzat M Abdel-Moety, Mamdouh R Rezk

Abstract read
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Article in RSC advances, 2025. 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.

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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.

Eman M MoaazPharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Cairo University Kasr El-Aini Street ET-11562 Cairo Egypt eman.moaaz@pharma.cu.edu.eg.ORCID https://orcid.org/0000-0001-8380-1169
Ahmed S FayedPharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Cairo University Kasr El-Aini Street ET-11562 Cairo Egypt eman.moaaz@pharma.cu.edu.eg.
Ezzat M Abdel-MoetyPharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Cairo University Kasr El-Aini Street ET-11562 Cairo Egypt eman.moaaz@pharma.cu.edu.eg.
Mamdouh R RezkPharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Cairo University Kasr El-Aini Street ET-11562 Cairo Egypt eman.moaaz@pharma.cu.edu.eg.ORCID https://orcid.org/0000-0002-4425-4390

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ion-selective sensors are widely employed in various pharmaceutical, environmental, and biological analytical applications due to their simplicity, cost-effectiveness, and rapid response times. They suffer from some challenges though. These challenges may arise from the selective sensing process that can be hindered by interference from ions with similar charges or suitable lipophilicity. Solid contact type due to water layer formation between the sensing surfaces may also appear as an obstacle. This work is dedicated to overcoming the selectivity issue using the molecularly imprinted polymer (MIP) approach to determine Donepezil (DON) and Memantine (MEM) in their combined pharmaceutical formulation. Precipitation polymerization approach was employed for the preparation of the MIP for each drug. The resulting MIPs were thoroughly examined using various characterization methods. The potential response of the proposed sensors was stabilized by applying graphene nanoplatelets as an ion-to-electron transducer layer. This layer prevented the formation of the water layer, improved the responses, and enhanced charge transfer. Two sensors featuring different cationic exchangers were designed for the selective determination of donepezil, for which one sensor was developed for memantine analysis by adding the corresponding MIPs to the membrane components. The achieved detection limits were 5.01 × 10

Identifiers

PMID40463338
PMCPMC12132094

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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.