Biocompatible graphene-zirconia nanocomposite as a cyto-safe immunosensor for the rapid detection of carcinoembryonic antigen

Lin, Lih Poh; Tham, Shiau Ying; Loh, Hwei-San; Tan, Michelle T.T.

doi:10.1038/s41598-021-99498-0

Cited by 13 publications

(15 citation statements)

References 73 publications

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“…The relative R ct (r R ct )with the number of electrodes for the magnetic field up (Figure a) and down direction (Figure b) is presented. The sensor response is represented by r R ct , which is the relative R ct difference between SAMs of ds-DNA and the bare Au/Ni thin film . The corresponding mathematical expression used can be expressed as …”

Section: Resultsmentioning

confidence: 99%

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CISS-Based Label-Free Novel Electrochemical Impedimetric Detection of UVC-Induced DNA Damage

2022

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In this work, we demonstrate chiral-induced spin selectivity (CISS)-based label-free electrochemical impedimetric detection of radiation-induced DNA damage using the electrons’ spin as a novel tool of sensing. For this, self-assembled monolayers (SAMs) of short ds-DNA (of length 7.14 nm) are prepared on arrays of multilayer thin film devices comprising a gold overlay (500 μm diameter with 10 nm thickness) on a nickel thin film (100 nm) fabricated by the physical vapor deposition technique. Subsequently, the SAMs of ds-DNA are exposed to ultraviolet C (UVC) radiation for a prolonged period of 8 h to induce structural perturbations in DNA. The susceptibility of DNA to radiation-induced damage was probed by recording the spin-dependent electrochemical impedimetric spectra, wherein a continuous sinusoidal wave of the amplitude of 10 mV was superimposed on DC bias in the frequency range of 100–105 Hz, with simultaneous spin injection through the attached DNA. The inherent correlation between the charge-transfer resistance (R ct) and the spin selectivity of electrons through DNA was taken into account for the detection of DNA damage for the first time with a limit of detection achieved up to 10 picomolar concentrations of DNA. As the spin-polarized electrons directly probe the structural symmetry, it is robust against perturbation from electronic signals usually found in conventional electrochemical biosensors.

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Section: Resultsmentioning

confidence: 99%

“…The sensor response is represented by r R ct , which is the relative R ct difference between SAMs of ds-DNA and the bare Au/Ni thin film. 45 The corresponding mathematical expression used can be expressed as …”

Section: Resultsmentioning

confidence: 99%

CISS-Based Label-Free Novel Electrochemical Impedimetric Detection of UVC-Induced DNA Damage

2022

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“…Apparatus and software.-All data collected were measured using Metrohm Autolab PGSTAT302N 19,20 and data pre-processing was performed using NOVA 1.11 from Metrohm Autolab and Scikit-learn 1.2.2. The machine models were trained using Python 3.10.12, Scikit-learn 1.2.…”

Section: Methodsmentioning

confidence: 99%

Method—An Investigation Into Post-Hoc Analysis Methods for Electrochemical Biosensor Data

Teo,

Maul,

Tan

2024

J. Electrochem. Soc.

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Recently, researchers are exploring machine learning (ML) algorithms as post-hoc analysis tools to improve performances of electrochemical biosensors. Reported results are promising, yet comprehensive study on optimal methods for model development is still lacking. For improved efficiency, accuracy, and robustness, it is essential to optimise the relationships between feature extraction techniques and choice of training algorithms. Herein, this paper presents a comparative study between different feature extractions methods, namely principal component analysis (PCA), linear discriminative analysis (LDA), fast Fourier transform (FFT) ,and discrete wavelet transform (DWT), to compress and extract significant components from differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS) datasets. Support vector regression (SVR) and multilayer perceptron (MLP) models were developed, and their performances were compared with conventional post-analysis methods. The best performing combination for DPV dataset was MLP with DWT, achieving an R2 of 0.995, and for EIS dataset was MLP with PCA, achieving an R2 of 0.960, on test set, respectively. The developed models had achieved an average of 0.61% improvement for real sample recovery tests. The presented approaches demonstrated the capabilities of optimised ML models to automate post hoc analysis for more robust outcomes, while eliminating tedium of post-analysis for end users.

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“…For a more rapid detection of CEA, Lin and co-workers [41] constructed a special disposable label-free immunosensor which exhibited a limit of detection of 4.25 pg/mL and a limit of quantification of 12.89 pg/mL with a concentration linear range from 0.01 to 10 ng/mL. The fabrication was based on modifying screen-printed carbon electrode (PE) with graphene-zirconia (GZ) nanocomposite functionalized with 1-Pyrenebutyric-Acid-N-hydroxysuccinimide-ester (PYSE) which served as a crosslinker for the immobilization of anti-CEA (Ab).…”

Section: Label-free Ec Immunosensors For Oc Biomarkers Detectionmentioning

confidence: 99%

Electrochemical and Photoelectrochemical Immunosensors for the Detection of Ovarian Cancer Biomarkers

Ekwujuru

Olatunde

Klink

et al. 2023

Sensors

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Photoelectrochemical (PEC) sensing is an emerging technological innovation for monitoring small substances/molecules in biological or non–biological systems. In particular, there has been a surge of interest in developing PEC devices for determining molecules of clinical significance. This is especially the case for molecules that are markers for serious and deadly medical conditions. The increased interest in PEC sensors to monitor such biomarkers can be attributed to the many apparent advantages of the PEC system, including an enhanced measurable signal, high potential for miniaturization, rapid testing, and low cost, amongst others. The growing number of published research reports on the subject calls for a comprehensive review of the various findings. This article is a review of studies on electrochemical (EC) and PEC sensors for ovarian cancer biomarkers in the last seven years (2016–2022). EC sensors were included because PEC is an improved EC; and a comparison of both systems has, expectedly, been carried out in many studies. Specific attention was given to the different markers of ovarian cancer and the EC/PEC sensing platforms developed for their detection/quantification. Relevant articles were sourced from the following databases: Scopus, PubMed Central, Web of Science, Science Direct, Academic Search Complete, EBSCO, CORE, Directory of open Access Journals (DOAJ), Public Library of Science (PLOS), BioMed Central (BMC), Semantic Scholar, Research Gate, SciELO, Wiley Online Library, Elsevier and SpringerLink.

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Biocompatible graphene-zirconia nanocomposite as a cyto-safe immunosensor for the rapid detection of carcinoembryonic antigen

Cited by 13 publications

References 73 publications

CISS-Based Label-Free Novel Electrochemical Impedimetric Detection of UVC-Induced DNA Damage

CISS-Based Label-Free Novel Electrochemical Impedimetric Detection of UVC-Induced DNA Damage

Method—An Investigation Into Post-Hoc Analysis Methods for Electrochemical Biosensor Data

Electrochemical and Photoelectrochemical Immunosensors for the Detection of Ovarian Cancer Biomarkers

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