Rapid pattern recognition of different types of sulphur-containing species as well as serum and bacteria discrimination using Au NCs-Cu2+ complexes |
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| Institution: | 1. Key Laboratory of Optic-electric Sensing and Analytical Chemistry for Life Science, MOE, College of Chemistry and Molecular Engineering, Qingdao University of Science and Technology, Qingdao 266042, China;2. The Affiliated Hospital of Qingdao University, Qingdao 266003, China;1. Institute of Analytical Technology and Smart Instruments, College of Environment and Public Health, XiamenHuaxia University, Xiamen 361024, China;2. State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361005, China;3. College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, China;1. Faculty of Materials Science and Engineering, Kunming University of Science and Technology, Kunming 650093, China;2. Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences, Ningbo 315201, China;3. Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, Shenzhen 518055, China;4. Center of Material Science and Optoelectronic Technology, University of Chinese Academy of Sciences, Beijing 100049, China;5. Laboratory of Environmental Biotechnology, School of Environmental and Civil Engineering, Jiangnan University, Wuxi 214122, China;6. College of Science, Henan University of Technology, Zhengzhou 10463, China;7. College of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou 310018, China;8. Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences, Ningbo 315201, China;1. Department of Materials Science and Engineering, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul 120-749, South Korea;2. Department of Biomedical Engineering, Gachon University, South Korea;3. Korea Institute of Science and Technology (KIST), Seoul, South Korea |
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| Abstract: | Discrimination of different types of sulfur-containing species not only helps us to deeply understand how sulfur affects cellular signaling, but also contribute to the early diagnosis of diseases. However, the current investigation about sulfur-containing species discrimination is mainly concentrated in biothiols, which is relatively limited for practical application. Toward circumventing this limitation, herein, a convenient sensor array consisting of three kinds of Au NCs-Cu2+ for simultaneous and rapid identification of different types of sulfur-containing species is reported. Based on the fingerprint-like fluorescence responses generated by competitive binding between Au NCs-Cu2+ and different sulfur-containing species, not only ten different types of sulfur-containing species separately but also their binary or ternary randomly selected mixtures can be well discriminated even in human urine and serum samples. It is worth noting that it only takes 2 min to obtain the best response signals for sulfur-containing species discrimination. Most importantly, serums from cancer patients (such as liver cancer and breast cancer) and healthy people as well as sulfur-oxidizing bacteria (SOB) and sulfur-free bacteria can be both effectively and rapidly identified within 2 min, respectively, making it a promising approach for point-of-care disease diagnostic. |
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| Keywords: | Sulfur-containing species Gold nanoclusters Sensor array Fluorescence Bacteria discrimination Serum discrimination |
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