PNA-functionalized magnetic microbeads as substrates for enzyme-labelled voltammetric genoassay for DNA sensing applied to identification of GMO in food

Rapid Quantification of SARS-Cov-2 Spike Protein Enhanced with a Machine Learning Technique Integrated in a Smart and Portable Immunosensor

An IoT-WiFi smart and portable electrochemical immunosensor for the quantification of SARS-CoV-2 spike protein was developed with integrated machine learning features. The immunoenzymatic sensor is based on the immobilization of monoclonal antibodies directed at the SARS-CoV-2 S1 subunit on Screen-Printed Electrodes functionalized with gold nanoparticles. The analytical protocol involves a single-step sample incubation. Immunosensor performance was validated in a viral transfer medium which is commonly used for the desorption of nasopharyngeal swabs. Remarkable specificity of the response was demonstrated by testing H1N1 Hemagglutinin from swine-origin influenza A virus and Spike Protein S1 from Middle East respiratory syndrome coronavirus. Machine learning was successfully used for data processing and analysis. Different support vector machine classifiers were evaluated, proving that algorithms affect the classifier accuracy. The test accuracy of the best classification model in terms of true positive/true negative sample classification was 97.3%. In addition, the ML algorithm can be easily integrated into cloud-based portable Wi-Fi devices. Finally, the immunosensor was successfully tested using a third generation replicating incompetent lentiviral vector pseudotyped with SARS-CoV-2 spike glycoprotein, thus proving the applicability of the immunosensor to whole virus detection.

Advances in Electrochemical Techniques for the Detection and Analysis of Genetically Modified Organisms: An Analysis Based on Bibliometrics

Since the first successful transgenic plants obtained in 1983, dozens of plants have been tested. On the one hand, genetically modified plants solve the problems of agricultural production. However, due to exogenous genes of transgenic plants, such as its seeds or pollen drift, diffusion between populations will likely lead to superweeds or affect the original traits. The detection technology of transgenic plants and their products have received considerable attention. Electrochemical sensing technology is a fast, low-cost, and portable analysis technology. This review interprets the application of electrochemical technology in the analysis and detection of transgenic products through bibliometrics. A total of 83 research articles were analyzed, spanning 2001 to 2021. We described the different stages in the development history of the subject and the contributions of countries and institutions to the topic. Although there were more annual publications in some years, there was no explosive growth in any period. The lack of breakthroughs in this technology is a significant factor in the lack of experts from other fields cross-examining the subject. Through keyword co-occurrence analysis, different research directions on this topic were discussed. The use of nanomaterials with excellent electrical conductivity allows for more sensitive detection of GM crops by electrochemical sensors. Furthermore, co-citation analysis was used to interpret the most popular reports on the topic. In the end, we predict the future development of this topic according to the analysis results.