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Biomedical And Clinical Sciences
Oncology And Carcinogenesis
Predictive And Prognostic Markers
Intelligent Screening Of Prostate Cancer Individuals Using An Enzyme-assisted Multicolor Visualization Platform.

Home
Research Domains
Biomedical And Clinical Sciences
Oncology And Carcinogenesis
Predictive And Prognostic Markers
Intelligent Screening Of Prostate Cancer Individuals Using An Enzyme-assisted Multicolor Visualization Platform.

Related Experiment Video

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Published on: April 8, 2016

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

Ruomei Teng¹, Ming Li^1,2, Zikang Chen¹

¹College 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.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)

|November 8, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

A new method uses sarcosine oxidase and a multicolor platform to detect prostate cancer (PCa) biomarkers in urine. This rapid, intelligent approach offers a convenient and reliable tool for early PCa screening.

Keywords:

RGB colors intelligent diagnosis multicolor visualization prostate cancer

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Area of Science:

Biomarker Detection
Nanotechnology
Point-of-Care Diagnostics

Background:

Early identification of prostate cancer (PCa) is crucial for effective treatment.
Sarcosine (Sar) is a key early indicator of PCa, but its quantification in clinical samples is challenging.

Purpose of the Study:

To develop a convenient, reliable, and intelligent strategy for screening PCa by quantifying sarcosine in urine.
To create a nanozyme-assisted multicolor intelligent visualization platform for signal reporting.

Main Methods:

Integrated sarcosine oxidase (SOX) for specific recognition of sarcosine.
Utilized a nanozyme-assisted multicolor platform with Fe-MOFs and gold nanorods (Au NRs) for signal generation.
Employed a mobile phone camera to extract RGB values from the multicolor signal for analysis.

Main Results:

The sensor demonstrated excellent linearity with sarcosine concentration (1-60 × 10^-6 m) and a low detection limit (0.12 × 10^-6 m).
PCa diagnosis was achieved within 15 minutes by analyzing specific RGB color values.
The platform effectively detected subtle differences in sarcosine levels between PCa patients and healthy individuals.

Conclusions:

The developed enzyme-assisted multicolor intelligent visualization platform provides a rapid and accurate method for PCa screening.
This approach offers a valuable guideline for designing novel probes for biomarker detection in biological samples.