AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (12.9 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article

Rapid and sensitive detection of urinary KIM-1 using fully printed photonic crystal microarrays

Yang Liu1,§Xuwei He1,2,§Zewei Lian3,§Qian Guo4Jimei Chi3Xiaoxue Lin2Liyue Zhang2Zheng Liu2Yingyuan Liu2Meng Su3Keyu Wang5( )Qiangguo Ao1( )Qingli Cheng1( )
Department of Nephrology, The Second Medical Center of Chinese PLA General Hospital, National Clinical Research Centre for Geriatric Diseases, Beijing 100853, China
Chinese PLA Medical School, Beijing 100853, China
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences, Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS), Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing 100190, China
Department of Rheumatology and Immunology, Peking University International Hospital, Beijing 102206, China
Department of Clinical Laboratory, The Second Medical Center of Chinese PLA General Hospital, National Clinical Research Centre for Geriatric Diseases, Beijing 100853, China

§ Yang Liu, Xuwei He, and Zewei Lian contributed equally to this work.

Show Author Information

Abstract

Urinary kidney injury molecule 1 (uKIM-1) serves as a reliable marker for the early diagnosis of acute kidney injury (AKI). The rapid and facile detection of changes in uKIM-1 is essential for early AKI diagnosis, ultimately improving the prognosis of patients. In this study, we developed a fully printed photonic crystal-integrated microarray with photonic crystal-enhanced fluorescence properties, which can detect uKIM-1 levels at the point-of-care. We confirmed its efficacy in the early diagnosis of AKI using clinical urine specimens. Direct quantitative detection of uKIM-1 was achieved within 10 min. The lowest limit of detection is 8.75 pg·mL−1 with an accuracy of 94.2%. The diagnostic efficacy was validated using 86 clinical urine samples, highlighting the high sensitivity and stability of the photonic crystal microarray. Consequently, a facile and reliable immunoassay was designed and prepared for the rapid quantitative detection of uKIM-1, which is crucial for the early identification and convenient detection of AKI in hospital or community settings. Rapid, convenient, cost-effective, and long-term monitoring of changes in uKIM-1 levels can assist clinicians in making timely adjustments to treatment regimens, preventing the transition from AKI to chronic kidney disease (CKD), improving the quality of life of patients with AKI, and reducing healthcare costs. It highlights the advantages of utilizing urine samples as a noninvasive and easily accessible medium for early detection and monitoring of kidney-related conditions.

Graphical Abstract

Acute kidney injury (AKI) is a serious disease prevalent in all clinical departments. A rapid quantitative measurement of urinary kidney injury molecule 1 (KIM-1) based on photonic crystal (PC) microarrays and portable testing devices can help to diagnose AKI early, prevent its further progression to chronic kidney disease, save lives, and maintain health.

Electronic Supplementary Material

Download File(s)
12274_2023_6335_MOESM1_ESM.pdf (1.5 MB)

References

【1】
【1】
 
 
Nano Research
Pages 4329-4337

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Liu Y, He X, Lian Z, et al. Rapid and sensitive detection of urinary KIM-1 using fully printed photonic crystal microarrays. Nano Research, 2024, 17(5): 4329-4337. https://doi.org/10.1007/s12274-023-6335-1
Topics:

1691

Views

133

Downloads

7

Crossref

8

Web of Science

7

Scopus

2

CSCD

Received: 26 September 2023
Revised: 08 November 2023
Accepted: 13 November 2023
Published: 04 December 2023
© Tsinghua University Press 2023