Intelligent Screening of Prostate Cancer Individuals Using an Enzyme‐Assisted Multicolor Visualization Platform
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....
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Advanced Science |
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| Online Access: | https://doi.org/10.1002/advs.202408825 |
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| author | Ruomei Teng Ming Li Zikang Chen Jianli Lin Yuhan Zhang Hang Li Zejun Yan Dingyuan Zhang Caiping Ding Youju Huang |
| author_facet | Ruomei Teng Ming Li Zikang Chen Jianli Lin Yuhan Zhang Hang Li Zejun Yan Dingyuan Zhang Caiping Ding Youju Huang |
| author_sort | Ruomei Teng |
| collection | DOAJ |
| description | 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 × 10−6 m, boasting a remarkable detection limit of 0.12 × 10−6 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. |
| format | Article |
| id | doaj-art-4038162a69ee4e9894f6ced2d88b789b |
| institution | Kabale University |
| issn | 2198-3844 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Science |
| spelling | doaj-art-4038162a69ee4e9894f6ced2d88b789b2025-01-09T11:44:45ZengWileyAdvanced Science2198-38442025-01-01121n/an/a10.1002/advs.202408825Intelligent Screening of Prostate Cancer Individuals Using an Enzyme‐Assisted Multicolor Visualization PlatformRuomei Teng0Ming Li1Zikang Chen2Jianli Lin3Yuhan Zhang4Hang Li5Zejun Yan6Dingyuan Zhang7Caiping Ding8Youju Huang9College 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 ChinaCollege 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 ChinaCollege 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 ChinaCollege 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 ChinaCollege 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 ChinaCollege 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 ChinaDepartment of Urology & Nephrology The First Affiliated Hospital of Ningbo University 59, Liuting Street Ningbo Zhejiang 315010 ChinaCollege 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 ChinaCollege 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 ChinaCollege 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 ChinaAbstract 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 × 10−6 m, boasting a remarkable detection limit of 0.12 × 10−6 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.https://doi.org/10.1002/advs.202408825intelligent diagnosismulticolor visualizationprostate cancerRGB colorsurine sample |
| spellingShingle | Ruomei Teng Ming Li Zikang Chen Jianli Lin Yuhan Zhang Hang Li Zejun Yan Dingyuan Zhang Caiping Ding Youju Huang Intelligent Screening of Prostate Cancer Individuals Using an Enzyme‐Assisted Multicolor Visualization Platform Advanced Science intelligent diagnosis multicolor visualization prostate cancer RGB colors urine sample |
| title | Intelligent Screening of Prostate Cancer Individuals Using an Enzyme‐Assisted Multicolor Visualization Platform |
| title_full | Intelligent Screening of Prostate Cancer Individuals Using an Enzyme‐Assisted Multicolor Visualization Platform |
| title_fullStr | Intelligent Screening of Prostate Cancer Individuals Using an Enzyme‐Assisted Multicolor Visualization Platform |
| title_full_unstemmed | Intelligent Screening of Prostate Cancer Individuals Using an Enzyme‐Assisted Multicolor Visualization Platform |
| title_short | Intelligent Screening of Prostate Cancer Individuals Using an Enzyme‐Assisted Multicolor Visualization Platform |
| title_sort | intelligent screening of prostate cancer individuals using an enzyme assisted multicolor visualization platform |
| topic | intelligent diagnosis multicolor visualization prostate cancer RGB colors urine sample |
| url | https://doi.org/10.1002/advs.202408825 |
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