Journal
BIOSENSORS & BIOELECTRONICS
Volume 223, Issue -, Pages -Publisher
ELSEVIER ADVANCED TECHNOLOGY
DOI: 10.1016/j.bios.2022.115028
Keywords
Self -powered photoelectrochemical; immunoassay; Artificial neural network; Micro-electro-mechanical system; Cardiac troponin I; Bi 2 O 2 S nanosheets
Ask authors/readers for more resources
Considering the increasing occurrence of acute myocardial infarction at a younger age and its impact on public health, the development of rapid screening tools is crucial. In this study, we developed an artificial neural network-assisted solar-powered photoelectrochemical sensing platform for the rapid screening of cardiac troponin I protein in patients with acute myocardial infarction. By integrating a self-powered photoelectric signal output system with low-cost screen-printed paper electrodes functionalized with ultrathin Bi2O2S nanosheets, we created a solar-powered PEC immunoassay without the need for an excitation light source.
Considering the fact that acute myocardial infarction has shown a trend towards younger age and has become a major health problem, it is necessary to develop rapid screening devices to meet the needs of community health care. Herein, we developed an artificial neural network-assisted solar-powered photoelectrochemical (SP-PEC) sensing platform for rapid screening of cardiac troponin I (cTnI) protein in the prognosis of patients with acute myocardial infarction (AMI) by integrating a self-powered photoelectric signal output system with low-cost screen-printed paper electrodes functionalized with ultrathin Bi2O2S (BOS) nanosheets. An integrated solarpowered PEC immunoassay with micro-electro-mechanical system (MEMS) was constructed without an excitation light source. The quantification of cTnI protein was obtained by the electrical signal changes caused by the electro-oxidation process of H2O2, generated by the classical split immune reaction, on the electrode surface. The test electrodes were developed as dual working electrodes, one for target cTnI testing and the other for evaluating light intensity, to reduce the temporal inconsistency of sunlight. The photoelectrodes were discovered to exhibit satisfactory negative response to target concentrations in the dynamic range of 2.0 pg mL-1-10 ng mL-1 since being regressed in an improved artificial neural network (ANN) model using the pooled dataset of target signals affected by the light source. The difference of hot electron and hole transfer behavior in different thickness of nano-materials was determined by finite element analysis (FEA), which provided a theoretical basis for the development of efficient PEC sensors. This work presents a unique perspective for the design of a revolutionary low-cost bioassay platform by inventively illuminating the PEC biosensor's component process without the use of light.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available