ABSTRACT
This work presents an opto-electrical method that measures the viral nucleocapsid protein and anti-N antibody interactions to differentiate between SARS-CoV-2 negative and positive nasal swab samples. Upon light exposure of the patient nasal swab sample mixed with the anti-N antibody, charge transfer (CT) transitions within the altered protein folds are initiated between the charged amino acids side chain moieties and the peptide backbone that play the role of donor and acceptor groups. A Figure of Merit (FOM) was introduced to correlate the relative variations of the samples with and without antibody at two different voltages. Empirically, SARS-CoV-2 in patient nasal swab samples was detected within two minutes, if an extracted FOM threshold of >1 was achieved; otherwise, the sample wasconsidered negative.
ABSTRACT
Accurately classifying the innate immune players is essential to comprehensively and quantitatively evaluate the interactions between the innate and the adaptive immune systems. In addition, accurate classification enables the development of models to predict behavior and to improve prospects for therapeutic manipulation of inflammatory diseases and cancer. Rapid development in technologies that provide an accurate definition of the type of cell in action, allows the field of innate immunity to the lead in therapy developments. This article presents a novel immunophenotyping technique using electrical characterization to differentiate between the two most important cell types of the innate immune system: dendritic cells (DCs) and macrophages (MACs). The electrical characterization is based on capacitance measurements, which is a reliable marker for cell surface area and hence cell size. We differentiated THP-1 cells into DCs and MACs in vitro and conducted electrical measurements on the three cell types. The results showed average capacitance readings of 0.83 µF, 0.93 µF, and 1.01 µF for THP-1, DCs, and MACs, respectively. This corresponds to increasing cell size since capacitance is directly proportional to area. The results were verified with image processing. Image processing was used for verification because unlike conventional techniques, especially flow cytometry, it avoids cross referencing and by-passes the limitation of a lack of specificity of markers used to detect the different cell types.
