Evidence map›Paper›PMID 41953584›Full record

ArticleACS applied nano materials2026

Anthracene-Modified Nanoporous Silica Nanoparticles for ATP Detection and Salivary Diagnostics in Parkinson's Disease.

Elcin Ezgi Ahi, Estela Climent, Cansu Beyret, Mehmet Gokhan Caglayan, Burak Coban, Rezzak Yilmaz, Vicente Martí-Centelles, Ramón Martínez-Máñez, Mahmut Durmuş

Abstract read
In one paragraph

Article in ACS applied nano materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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.

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

9 authors.

Elcin Ezgi AhiDepartment of Chemistry, Gebze Technical University, Gebze, Kocaeli 41400, Türkiye.ORCID https://orcid.org/0000-0003-3311-4517
Estela ClimentInstituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València, Universitat de València, Camino de Vera s/n, Valencia 46022, Spain.ORCID https://orcid.org/0000-0002-6128-1235
Cansu BeyretDepartment of Analytical Chemistry, Faculty of Pharmacy, Ankara University, Yenimahalle, Ankara 06560, Türkiye.
Mehmet Gokhan CaglayanDepartment of Analytical Chemistry, Faculty of Pharmacy, Ankara University, Yenimahalle, Ankara 06560, Türkiye.ORCID https://orcid.org/0000-0002-4212-3549
Burak CobanDepartment of Neurology, School of Medicine, Ankara University, Ankara 06100, Türkiye.
Rezzak YilmazDepartment of Neurology, School of Medicine, Ankara University, Ankara 06100, Türkiye.
Vicente Martí-CentellesInstituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València, Universitat de València, Camino de Vera s/n, Valencia 46022, Spain.ORCID https://orcid.org/0000-0002-9142-9392
Ramón Martínez-MáñezInstituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València, Universitat de València, Camino de Vera s/n, Valencia 46022, Spain.ORCID https://orcid.org/0000-0001-5873-9674
Mahmut DurmuşDepartment of Chemistry, Gebze Technical University, Gebze, Kocaeli 41400, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ATP is an essential biological molecule, and abnormal levels are linked to various diseases. In this study, we developed an optical sensor array consisting of an anthracene-modified MCM-41 mesoporous nanoparticle-based hybrid organic-inorganic material to detect ATP in a TRIS-HCl buffer (pH 7). To create the sensor, we synthesized MCM-41 silica nanoparticles and functionalized them with aminoanthracene and imidazolium-anthracene groups. The fluorescence responses of the optical sensor array were recorded and analyzed by using a pattern recognition protocol, specifically linear discriminant analysis, to distinguish between ATP, ADP, AMP, and potential interferents. Quantitative regression analysis of ATP in TRIS-HCl was performed using artificial neural networks, which yielded an acceptable error rate of 7.8%. The sensor array was also evaluated for discrimination of Parkinson's disease (PD) from healthy controls, based on pattern recognition of ATP-related analytes in saliva samples from 24 patients with PD and 23 healthy controls. The results showed that the MCM-41 mesoporous silica nanoparticle-based sensor array can discriminate PD by pattern recognition with 73.7% sensitivity and 83.3% specificity.

Indexed as

anthracenesatpLDA analysisMCM-41optic array sensorsParkinson’s disease

Identifiers

PMID41953584
PMCPMC13054783

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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.