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Intelligent Screening of Prostate Cancer Individuals Using an Enzyme-Assisted Multicolor Visualization Platform. | LitMetric

Intelligent Screening of Prostate Cancer Individuals Using an Enzyme-Assisted Multicolor Visualization Platform.

Adv Sci (Weinh)

College of Material, Chemistry and Chemical Engineering, Key Laboratory of Organosilicon Chemistry and Material Technology, Ministry of Education, Department of Orthopedics, Hangzhou Normal University Affiliated Hospital, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, China.

Published: January 2025


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Article Abstract

Rapid and intelligent identification of prostate cancer (PCa) is critical for early diagnosis. Herein, a convenient, reliable, and intelligent strategy is proposed to screen PCa individuals through indirectly quantifying sarcosine (Sar), an early indicator of PCa, in clinical urine samples. Success is achieved by integrating sarcosine oxidase (SOX) as a specific recognition unit; nanozyme-assisted multicolor intelligent visualization platform as a signal reporter. With the Fe-MOFs and peroxidase, the synergetic action of SOX and response gold nanorods (Au NRs) is controlled etched to exhibit a multicolored signal. The sensor exhibits excellent linearity with Sar within 1-60 × 10 m, boasting a remarkable detection limit of 0.12 × 10 m. The RGB value of the display color can be directly extracted using a mobile phone camera. PCa diagnosis can be swiftly made (within 15 min) and directly by identifying two RGB colors (R < 175 or B > 135). The enzyme-assisted multicolor intelligent visualization platform is adept at detecting minute differences in Sar concentration in urine samples between PCa patients and healthy individuals. The concept of enzyme-assisted multicolor sensing can be further expanded by modifying the type of immobilized enzymes, providing a valuable guideline for the rational design of multiple probes to measure specific biomarkers in biological samples.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11714164PMC
http://dx.doi.org/10.1002/advs.202408825DOI Listing

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