AIEgen‐Based and Smartphone‐Assisted On‐Site Quantitation of Cystatin C for Monitoring of Chronic Kidney Disease

ABSTRACT The development of affordable and user‐friendly diagnostic tools for early warning and monitoring progression of chronic kidney disease (CKD) is crucial to reducing CKD‐related morbidity and mortality. This study reports on (1) a protein‐templated AIEgen, Ir@BSA, which emits intense green phosphorescence with a quantum yield up to 69.40% and a lifetime up to 1839.40 ns in aqueous solution; (2) a straightforward protocol for Cys C quantitation, which employs Ir@BSA as the phosphorescent signal indicator and papain as the biomolecular recognition element, respectively; and (3) a smartphone‐based portable phosphorescence reader (termed as SAPD), which can stably excite and accurately collect phosphorescence signals from the paper‐based arrays. Quantitation of Cys C in clinical serum samples using SAPD integrated with the paper‐based arrays highlights its remarkable advantages including high sensitivity (0.36 µg mL −1 ) and specificity, cost‐effectiveness (∼$67.5 per set), portability (∼450 g), good precision (RSD ≤ 8.25 %), good accuracy (comparable to clinical standard latex immune‐turbidimetric method), and high throughput (16 samples per experiment). More importantly, this study reveals the significant potential of Cys C as an early warning marker of CKD progression. The reported method enables Cys C quantitation anywhere, anytime, by anyone, and is ideally suited for mass screening for CKD and home monitoring of CKD progression, facilitating early diagnosis and proactive management of CKD.

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Aggregate
Published
2025-08-09
DOI
https://doi.org/10.1002/agt2.70127
Citations
3
Primary Topic
Biosensors and Analytical Detection
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article
Field-Weighted Citation Impact
2.02

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article

AIEgen‐Based and Smartphone‐Assisted On‐Site Quantitation of Cystatin C for Monitoring of Chronic Kidney Disease

Changqing Yi, Mei‐Jin Li, Shuqi Xia, Wanqing Zhang et al.
3 citations
Aggregate
Biosensors and Analytical Detection
2.02
article

AIEgen‐Based and Smartphone‐Assisted On‐Site Quantitation of Cystatin C for Monitoring of Chronic Kidney Disease

Changqing Yi, Mei‐Jin Li, Shuqi Xia, Wanqing Zhang, Zhaofan Luo, Shiqiong Niu, Jie Gong, Xue Zhu
article en
3 citations

Abstract

ABSTRACT The development of affordable and user‐friendly diagnostic tools for early warning and monitoring progression of chronic kidney disease (CKD) is crucial to reducing CKD‐related morbidity and mortality. This study reports on (1) a protein‐templated AIEgen, Ir@BSA, which emits intense green phosphorescence with a quantum yield up to 69.40% and a lifetime up to 1839.40 ns in aqueous solution; (2) a straightforward protocol for Cys C quantitation, which employs Ir@BSA as the phosphorescent signal indicator and papain as the biomolecular recognition element, respectively; and (3) a smartphone‐based portable phosphorescence reader (termed as SAPD), which can stably excite and accurately collect phosphorescence signals from the paper‐based arrays. Quantitation of Cys C in clinical serum samples using SAPD integrated with the paper‐based arrays highlights its remarkable advantages including high sensitivity (0.36 µg mL −1 ) and specificity, cost‐effectiveness (∼$67.5 per set), portability (∼450 g), good precision (RSD ≤ 8.25 %), good accuracy (comparable to clinical standard latex immune‐turbidimetric method), and high throughput (16 samples per experiment). More importantly, this study reveals the significant potential of Cys C as an early warning marker of CKD progression. The reported method enables Cys C quantitation anywhere, anytime, by anyone, and is ideally suited for mass screening for CKD and home monitoring of CKD progression, facilitating early diagnosis and proactive management of CKD.

AggregateVol. 6(10)
Sun Yat-sen University (CN), The Seventh Affiliated Hospital of Sun Yat-sen University (CN), Shenzhen Technology University (CN), Fuzhou University (CN), Ube (Japan) (JP)
Sun Yat-sen University, Natural Science Foundation of Guangdong Province, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities, Shenzhen Science and Technology Innovation Program
Good health and well-being
Openalex Percentile: Top 13%
Biosensors and Analytical Detection
2.02
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