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Updated: Jul 19, 2026

Detection of Nitric Oxide and Superoxide Radical Anion by Electron Paramagnetic Resonance Spectroscopy from Cells using Spin Traps
Published on: August 18, 2012
Multimodal sensing platform based on MnO2 nanozyme and carbon dots for colorimetric and fluorescent detection of
Man Du1, Shuang Hou1, Xinyue Yang1
1College of Chemical and Pharmaceutical Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, P. R. China.
Abstract:
Peroxynitrite (ONOO-), as a crucial bioactive molecule, is closely associated with various diseases when present at abnormal levels, making reliable and accurate detection urgently needed. This study developed a colorimetric and fluorometric multi-mode sensing platform based on manganese dioxide nanosheets (MnO2 NSs) and carbon dots (CDs) for the quantitative detection of ONOO-. Under acidic conditions, MnO2 NSs oxidized 3,3',5,5'-tetramethylbenzidine (TMB) to a blue oxidized product (TMB+), which was subsequently further oxidized by ONOO- to the diimine form (oxTMB). The resulting oxTMB effectively quenched the fluorescence of CDs via a fluorescence resonance energy transfer (FRET) mechanism. Additionally, ONOO- can directly quench the fluorescence of CDs through a FRET effect. The developed multi-mode sensing strategy exhibited excellent sensitivity for ONOO- detection. For the colorimetric mode based on TMB + MnO2 NSs, the detection limit (LOD) was 28.73 nM in the range 1-70 µM. In the fluorescence mode based on TMB + MnO2 NSs + CDs, the LOD was 40.17 nM in the range 0.3-45 µM. The LOD of the fluorescence mode based on CDs was 25.47 nM in the range 0.3-55 µM. By integrating a portable smartphone with a color recognition application, visual and on-site detection of ONOO- was achieved. The proposed method was successfully applied to detect ONOO- in human serum samples, yielding satisfactory recoveries ranging from 95.5% to 104.7%. Furthermore, CDs were successfully utilized for fluorescence imaging of ONOO- in living cells. This multimodal sensing platform overcomes the limitations of single-mode detection and provided an economical, efficient, and convenient method for ONOO- detection.
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