Evidence map›Paper›PMID 42850410›Full record

ArticleAnalytical and bioanalytical chemistry2026

Colorimetric discrimination of chrysanthemum polyphenols via tunable MOF-818 nanozyme sensor array.

Rui Dong, Li Jin, Jili Hu, Jianhua Shu, Chun Ma, Chengle Li, Hongxing Kan, Liping Sun

Abstract read
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Article in Analytical and bioanalytical chemistry, 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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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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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.

Rui DongSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, 230012, Anhui, China.
Li JinSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, 230012, Anhui, China.
Jili HuSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, 230012, Anhui, China.
Jianhua ShuSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, 230012, Anhui, China.
Chun MaSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, 230012, Anhui, China.
Chengle LiSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, 230012, Anhui, China.
Hongxing KanSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, 230012, Anhui, China. ffdkhx@ahtcm.edu.cn.
Liping SunSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, 230012, Anhui, China. sunliping@ahtcm.edu.cn.

Funding

Anhui Province's Project for Cultivating Outstanding Young Teachers in Colleges and Universities YQYB2025006Major Natural Science Research Projects of Anhui Provincial Department of Education 2024AH040143The Anhui Province Traditional Chinese Medicine Inheritance and Innovation Research Project 2025CCCX072the Natural Science Key Project of Anhui Provincial Department of Education 2023AH050846The Open Fund of Functional Activity and Resource Utilization of Edible and Medicinal Fungi Anhui Provincial Joint Key Laboratory AHSYYJ2025008
6 · The paper itself

Abstract

Chrysanthemum is an important botanical resource with medicinal and dietary value, whose quality and therapeutic efficacy are closely related to its polyphenolic composition. However, conventional polyphenol analysis is limited by high cost, time consumption, and operational complexity. To address these challenges, a colorimetric sensor array was constructed using two metal-organic framework nanozymes (MOF-818-1 and MOF-818-2). Although derived from identical precursors, modulated solvothermal synthesis endowed the nanozymes with distinct catecholase-like catalytic activities, enabling the oxidation of o-diphenols into colored o-quinones. Differential responses toward chlorogenic acid (CGA), quercetin (QR), and dicaffeoylquinic acid (DCQA) generated characteristic two-dimensional fingerprints. Combined with multivariate pattern recognition methods, including principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLS-DA), and hierarchical cluster analysis (HCA), the sensor array enabled proof-of-concept discrimination and concentration estimation of target polyphenols. The method was successfully applied to real chrysanthemum extracts, providing a rapid, simple, cost-effective strategy for herbal quality control.

Indexed as

ChrysanthemumColorimetric sensor arrayMOFNanozymesPolyphenols

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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.