resumo
This paper designs a biophotonic sensor that utilizes the localized surface plasmon resonance (LSPR) effect to detect Shigella sonnei (S. sonnei) with high sensitivity, featuring a novel crayfish-type optical fiber structure. Diseases and food safety caused by S. sonnei have become a public health issue of common concern around the world. This sensor is specifically designed for the detection of S. sonnei. This sensor has the advantage of being easy to operate, requires no labeling, and has high specificity. Excite the LSPR effect using gold nanoparticles (AuNPs). To enhance the LSPR effect, a fusion structure of multimode fiber and seven-core fiber was utilized, as was a crayfish-type optical fiber structure. Using Rsoft to simulate the crayfish-type optical fiber structure, it is concluded that the structure has excellent evanescent field. S. sonnei antibodies were used to improve the specificity of the sensor. Tungsten disulfide thin layer (WS2-thin layer) and zinc oxide nanowires were used to increase the surface area for antibody attachment. The linear range of the sensor was 1 x 10(0)-1 x 10(7) CFU/ml, the sensitivity was 0.378 nm/lg (CFU/ml), and the limit of detection was 4.78 CFU/ml. The reproducibility, reusability, selectivity, and stability of the sensor were tested. The test results showed that the sensor had excellent performance. In addition, the sensor was tested with real food samples. This research has far-reaching significance for biophotonic sensors and human health. (c) 2024 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution-NonCommercial 4.0International (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/).https://doi.org/10.1063/5.0242975
palavras-chave
ESCHERICHIA-COLI; NANOPARTICLES
categoria
Optics; Physics
autores
Zhang, Q; Singh, R; Nedoma, J; Min, R; Marques, C; Zhang, BY; Kumar, S
nossos autores
Carlos Marques
Professor AuxiliarProjectos
Associated Laboratory CICECO-Aveiro Institute of Materials (LA/P/0006/2020)
agradecimentos
This work was supported by the Double-Hundred Talent Plan of Shandong Province, China; the Special Construction Project Fund for Shandong Province Taishan Mountain Scholars; Liaocheng University (Grant No. 318052341); and the Science and Technology Support Plan for Youth Innovation of Colleges and Universities of Shandong Province of China (Grant No. 2022KJ107). S. Kumar would like to acknowledge the Koneru Lakshmaiah Education Foundation, India, for their funding support for this work. This work was developed within the scope of the projects CICECO (Grant Nos. LA/P/0006/2020, UIDB/50011/2020, and UIDP/50011/2020), financed by National funds through the Portuguese Science and Technology Foundation/MCTES (FCT I.P). The research was co-funded by the European Union under the REFRESH (Research Excellence for Region Sustainability and High-Tech Industries) Project (No. CZ.10.03.01/00/22_003/0000048) via the Operational Program Just Transition. This work was also supported by the Ministry of Education, Youth, and Sports of the Czech Republic and conducted by the VSB-Technical University of Ostrava under Grant Nos. SP2024/081 and SP2024/05.