An algorithm-assisted automated identification and enumeration system for sensitive hydrogen sulfide sensing under dark field microscopy. Issue 7 (15th March 2022)

• Record Type: Journal Article
• Authors: Xu, Shaohua; Deng, Xiaoyu; Ji, Shuyi; Chen, Lifen; Zhao, Tiesong; Luo, Fang; Qiu, Bin; Lin, Zhenyu; Guo, Longhua
• Is Part Of: Analyst. Volume 147:Issue 7(2022)
• Page Start: 1492
• Page End: 1498
• Publication Date: 2022-03-15
• Subjects: Chemistry, Analytic -- Periodicals; 543
• DOI: 10.1039/d2an00149g
• Languages: English
• ISSNs: 0003-2654

Abstract

Abstract : A sensitive H2 S sensing strategy has been developed based on the automated identification and enumeration algorithm. Abstract : Hydrogen sulfide (H2 S) is an active physiological molecule, and its intracellular level has great significance to life functions. In this study, an effective and sensitive method was developed for H2 S sensing with dark field microscopy (DFM). The proposed method employed AuNPs as the signal source, DFM as the readout system, and an intelligence algorithm as the image processing and output systems, respectively. The AuNP surface was modified with azido and alkynyl in advance, and then added into a tube cap. As the H2 S evaporated from the solution and selectively reduced azido to amino, the click chemistry reaction was inhibited, which resulted in the AuNPs being well dispersed in the solution; otherwise, AuNP aggregation occurred. The scattering colour of single AuNPs could be easily distinguished from that of AuNP aggregations with DFM, and the number or ratio of single AuNPs could also be easily obtained by the custom algorithm. The results showed that the H2 S content could be linearly analyzed in a range from 2–80 μM. Furthermore, the proposed sensing strategy has been applied for H2 S detection in cell lysate. Compared with the traditional colorimetric method, the results showed no significant difference, indicating the good prospects of the algorithm and proposed H2 S sensing method.