Portable and intelligent ratio fluorometry and colorimetry for dual-mode detection of dopamine based on B, N-codoped carbon dots and machine learning.

Journal: Talanta
Published Date:

Abstract

A dual-mode approach was developed for dopamine (DA) assay based on boron (B) and nitrogen (N) co-doped carbon dots (B, N-CDs). This platform enabled highly sensitive and specific detection of DA in biological samples through collaborative ratio fluorometry and colorimetry. B, N-CDs were synthesized via a one-pot hydrothermal method using 3-aminobenzylboric acid (3-APBA) and proline (Pro) as precursors. B, N-CDs exhibited dark blue fluorescence under ultraviolet (UV) light excitation with a quantum yield (QY) of 0.05. In the presence of DA, the fluorescence of B, N-CDs displayed bright blue with the QY at 0.22. The original fluorescence peak intensity at 420 nm of B, N-CDs decreased, while a new peak at 465 nm increased significantly with the increasing concentration of DA. In this case, a ratio fluorometry for DA detection was constructed using B, N-CDs as fluorescence probes. On the other way, the color of B, N-CDs solution changed from colorless to brown with the addition of DA. A colorimetry for DA sensing was established based on the absorbance enhancement of B, N-CDs. There is excellent linear relationship within the concentration range of 2.5-500 μM for DA sensing with limit of detection (LOD) at 0.22 μM (ratio fluorometry) and 1.04 μM (colorimetry) and the relative standard deviations (RSD%) are 0.2170 and 0.02131, respectively. To enable the real-time visual and portable quantification of DA, two intelligent methods were explored by a program named RGB color analysis in a smartphone and machine learning. This dual-mode sensing strategy combined high sensitivity, wide linear range and ease of operation, offering a novel solution for rapid analysis of DA in complex biological substrates.

Authors

  • Xiaoshuang Wang
    School of Chemistry and Chemical Engineering, Liaocheng University, Liaocheng, 252059, China.
  • Lijun Wang
    Department of Stomatology, The Third Medical Center Chinese PLA General Hospital Beijing China.
  • Mengnan Wu
    School of Chemistry and Chemical Engineering, Liaocheng University, Liaocheng, 252059, China.
  • Yihao Zheng
    School of Chemistry and Chemical Engineering, Liaocheng University, Liaocheng, 252059, China.
  • Ruirui Wang
    School of Chemistry and Chemical Engineering, Liaocheng University, Liaocheng, 252059, China.
  • Tong Shao
    School of Chemistry and Chemical Engineering, Liaocheng University, Liaocheng, 252059, China.
  • Suyuan Zeng
    School of Chemistry and Chemical Engineering, Liaocheng University, Liaocheng, 252059, China.
  • Aifeng Li
    School of Chemistry and Chemical Engineering, Liaocheng University, Liaocheng, 252059, China.
  • Rui Li
    Department of Oncology, Xiyuan Hospital, China Academy of Chinese Medical Science, Beijing, China.
  • Qiaoli Yue
    School of Chemistry and Chemical Engineering, Liaocheng University, Liaocheng, 252059, China. Electronic address: yueqiaoli@lcu.edu.cn.