Volume 21, Issue 9 2410638
Research Article

Cross-Referencing Multifluid Metabolic Profiles on Hollow Dodecahedral Nanocages for Enhanced Disease Status Identification

Fangying Shi

Fangying Shi

School of Materials Science and Chemical Engineering, Ningbo University, Ningbo, 315211 China

Department of Gastroenterology and Hepatology, Zhongshan Hospital, Department of Chemistry, Department of Institutes of Biomedical Sciences, Fudan University, Shanghai, 200433 China

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Lingli Chen

Lingli Chen

Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032 China

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Yiming Qiao

Yiming Qiao

Department of Gastroenterology and Hepatology, Zhongshan Hospital, Department of Chemistry, Department of Institutes of Biomedical Sciences, Fudan University, Shanghai, 200433 China

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Chunhui Deng

Corresponding Author

Chunhui Deng

Department of Gastroenterology and Hepatology, Zhongshan Hospital, Department of Chemistry, Department of Institutes of Biomedical Sciences, Fudan University, Shanghai, 200433 China

School of Chemistry and Chemical Engineering, Nanchang University, Nanchang, 330031 China

E-mail: [email protected]; [email protected]; [email protected]

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Qunyan Yao

Corresponding Author

Qunyan Yao

Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai, 200032 China

Department of Gastroenterology and hepatology, Zhongshan hospital (Xiamen), Fudan University, Xiamen, 361015 China

Shanghai institute of liver diseases, Shanghai, 200032 China

Shanghai Geriatric Medical center, Shanghai, 201104 China

E-mail: [email protected]; [email protected]; [email protected]

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Nianrong Sun

Corresponding Author

Nianrong Sun

Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai, 200032 China

Shanghai institute of liver diseases, Shanghai, 200032 China

E-mail: [email protected]; [email protected]; [email protected]

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First published: 05 February 2025
Citations: 2

Abstract

The development of matrices has shown great potential for fluid metabolic analysis in disease detection. However, single-fluid metabolomic analysis has been recognized as insufficient to fully capture the complexities of diseases such as liver disease, which limits detection accuracy. To this end, the hollow dodecahedral nanocages-based analytical tool is developed, featuring four-high characteristics of speed, throughput, efficiency, and patient compliance, to enhance extraction of multifluid metabolic profiles. The cross-referencing of these profiles among different liver diseases, including hepatocellular carcinoma (HCC), chronic liver disease (CLD), and healthy controls, enhances the diagnosis of liver diseases, particularly achieving near-perfect discrimination for HCC with an AUC value of 0.990, significantly outperforming any single fluid analysis. Additionally, the dynamic changes in expression levels of the key biomarkers throughout disease progression are explored, providing insights into their temporal evolution, and highlighting their role in monitoring disease status. This work highlights that multifluid metabolic analysis can comprehensively and sensitively reflect the disease status, enabling precise identification of complex diseases and facilitating personalized treatment.

Conflict of Interest

The authors declare no conflict of interest.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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