Cortisol detection using a Long Period Fiber Grating Immunosensor coated with Graphene Oxide

resumo

Recirculating Aquaculture Systems (RAS) have revolutionized the protein production sector in aquaculture, leading to significant growth and expansion of the industry. Despite the success of RAS in aquaculture, there are challenges related to stress in fish raised in these systems, which can impact their food intake, growth, and overall well-being. One of the major limitations in the aquaculture industry is the lack of smart sensors for realtime detection of stress hormones like cortisol, hindering our ability to understand and effectively manage the welfare of fish in these systems. In this work, a graphene oxide (GO) coated long period grating (LPG) was fabricated into a double-clad optical fiber (DCF) with W-shaped refractive index profile. The working point of the device was tuned to the mode transition region to enhance its sensitivity against outer medium changes. It was further integrated into a microfluidic system and the fiber surface was functionalized with specific anti-cortisol antibodies for the detection of cortisol. Finally, the performance of this immunosensor was evaluated for a cortisol concentration range of 0.01 ng/mL to 100 ng/mL, a wide working range of concentrations of relevant interest, achieving a limit of detection (LOD) of 0.06 ng/mL. Moreover, a selectivity test using testosterone and glucose as interfering substances was carried out.

palavras-chave

MODE TRANSITION; SENSITIVITY

categoria

Biotechnology & Applied Microbiology; Chemistry; Electrochemistry; Science & Technology - Other Topics; Instruments & Instrumentation

autores

Soares, S; Giannetti, A; Esposito, F; Sansone, L; Srivastava, A; Campopiano, S; Giordano, M; Facao, M; Santos, NF; Iadicicco, A; Marques, C; Chiavaioli, F

nossos autores

agradecimentos

This work was performed within the project "Monitoring of Honey- bee Immunomodulation and Resilience to Stress Factors by Fiber Optic Technology" (MoBeeFO) CUP I53D23000390006 under PRIN 2022 grant financed by the European Union - Next Generation EU, Mission 4 Component 1 and Italian Ministry of University and Research. The research was co-funded by the financial support of the European Union under the REFRESH - Research Excellence For REgion Sustainability and High-tech Industries project number CZ.10.03.01/00/22003/0000048 via the Operational Programme Just Transition. This work was also supported by the Ministry of Education, Youth, and Sports of the Czech Republic conducted by the VSB-Technical University of Ostrava, under grant no SP2024/081. This work was developed within the scope of the projects CICECO (LA/P/0006/2020, UIDB/50011/2020 & UIDP/50011/2020) and DigiAqua (PTDC/EEI-EEE/0415/2021), financed by national funds through the Portuguese Science and Technology Foundation/MCTES (FCT I.P.). Simone Soares acknowledges FCT/MCTES for the PhD fellowship grant UI/BD/153066/2022. N. F. Santos acknowledges FCT I.P. for the research action 2022.04595.CEECIND (GraFi- berSens project).

Partilhe este projeto

Publicações similares

Usamos cookies para atividades de marketing e para lhe oferecer uma melhor experiência de navegação. Ao clicar em “Aceitar Cookies” você concorda com nossa política de cookies. Leia sobre como usamos cookies clicando em "Política de Privacidade e Cookies".