abstract
The level of protein aggregates can be used as an indicator of some diseases, including neurodegenerative disorders such as Alzheimer's disease, and may be closely related to the efficacy of anti-cancer treatments. Moreover, strict control over protein aggregate levels is essential in pharmaceutical manufacturing to prevent potential side effects in the human body. In this study, we present a low-cost solution to evaluate protein aggregate levels in liquid samples using a smartphone-based fluorescence detection device. Initially, protein aggregate levels were assessed in bovine serum albumin samples. Then, this analysis was conducted using total protein extracts from breast cancer cells. The results obtained with the device were consistent with commercial spectrometer measurements, resulting in mean absolute errors of 0.098 for bovine serum albumin samples and 0.152 for the proteins extracted from cancer cells, corresponding to differences of 9.8 % and 15.2 % between the commercial spectrometer and the developed device in the considered scales.
keywords
MECHANISMS
subject category
Engineering; Instruments & Instrumentation
authors
Sousa, C; Helguero, L; Direito, I; Andre, P; Guieu, S; Domingue, MF; Alberto, N
our authors
Samuel Jacques André Guieu
Junior ResearcherProjects
CICECO - Aveiro Institute of Materials (UIDB/50011/2020)
Associated Laboratory CICECO-Aveiro Institute of Materials (LA/P/0006/2020)
Collaboratory for Emerging Technologies, CoLab (EMERGING TECHNOLOGIES)
acknowledgements
This work is funded by FCT/MCTES through national funds and when applicable co-funded EU funds under the project UIDB/50008/2020-UIDP/50008/2020. This work was also developed within the scope of the projects CICECO-Aveiro Institute of Materials (UIDB/50011/2020, IDP/50011/2020 & LA/P/0006/2020) and LAQV-REQUIMTE (UIDB/50006/2020) , financed by National funds through the FCT/MCTES (PIDDAC) . I. Direito thanks FCT for her PhD fellowship SFRH/BD/117818/2016 and COVID/BD/151716/2021. L. Helguero thanks UIDB/04501/2020 and UIDP/04501/2020, MEDISIS (CENTRO-01-0246-FEDER-000018) supported by Comissao de Coordenacao e Desenvolvimento Regional do Centro. M. Domingues acknowledges the scientific action REACT, funded by FCT/MEC through national funds and when applicable co-funded by FEDER - PT2020 partnership agreement under the project UID/EEA/50008/2019, and the Khalifa University FSU grant 8474000469. N. Alberto acknowledges the Scientific Employment Stimulus 2022.00250.CEECIND/CP1716/CT0002,