RESUMO
The COVID-19 pandemic has caused major disturbances to human health and economy on a global scale. Although vaccination campaigns and important advances in treatments have been developed, an early diagnosis is still crucial. While PCR is the golden standard for diagnosing SARS-CoV-2 infection, rapid and low-cost techniques such as ATR-FTIR followed by multivariate analyses, where dimensions are reduced for obtaining valuable information from highly complex data sets, have been investigated. Most dimensionality reduction techniques attempt to discriminate and create new combinations of attributes prior to the classification stage; thus, the user needs to optimize a wealth of parameters before reaching reliable and valid outcomes. In this work, we developed a method for evaluating SARS-CoV-2 infection and COVID-19 disease severity on infrared spectra of sera, based on a rather simple feature selection technique (correlation-based feature subset selection). Dengue infection was also evaluated for assessing whether selectivity toward a different virus was possible with the same algorithm, although independent models were built for both viruses. High sensitivity (94.55%) and high specificity (98.44%) were obtained for assessing SARS-CoV-2 infection with our model; for severe COVID-19 disease classification, sensitivity is 70.97% and specificity is 94.95%; for mild disease classification, sensitivity is 33.33% and specificity is 94.64%; and for dengue infection assessment, sensitivity is 84.27% and specificity is 94.64%.
RESUMO
The coronavirus disease 2019 (COVID-19) pandemic has reached an unprecedented level. There is a strong demand for diagnostic and serological supplies worldwide, making it necessary for countries to establish their own technologies to produce high-quality biomolecules. The two main viral antigens used for the diagnostics for severe acute respiratory syndrome coronavirus (SARS-CoV-2) are the structural proteins spike (S) protein and nucleocapsid (N) protein. The spike protein of SARS-CoV-2 is cleaved into S1 and S2, in which the S1 subunit has the receptor-binding domain (RBD), which induces the production of neutralizing antibodies, whereas nucleocapsid is an ideal target for viral antigen-based detection. In this study, we designed plasmids, pcDNA3.1/S1 and pcDNA3.1/N, and optimized their expression of the recombinant S1 and N proteins from SARS-CoV-2 in a mammalian system. The RBD was used as a control. The antigens were successfully purified from Expi293 cells, with high yields of the S1, N, and RBD proteins. The immunogenic abilities of these proteins were demonstrated in a mouse model. Further, enzyme-linked immunosorbent assays with human serum samples showed that the SARS-CoV-2 antigens are a suitable alternative for serological assays to identify patients infected with COVID-19.
RESUMO
We report a comprehensive comparative study of ferroelectric and piezoelectric properties of BNT-BKT-BT ceramics through the MPB (morphotropic phase boundary) zone, from the rhombohedral to the tetragonal phases in the system (97.5-x)(Bi0.5Na0.5)TiO3 + x(Bi0.5K0.5)TiO3 + 2.5(BaTiO3), where x = 0 to 24.5 mol %. The structural transitions were studied by XRD patterns and Raman spectra. The MPB was confirmed between x = 10 and 12.5 mol % BKT. The dielectric/ferroelectric/piezoelectric properties of the BNT-BKT-BT system are maximized in the MPB region exhibiting a dielectric constant of 1506, a remanent polarization of 34.4 µC/cm², a coercive field = 36.9 kV/cm, and piezoelectric values of d33 = 109 pC/N, kt = 0.52, and kp = 0.24. Changes in microstructure as a function of BKT content are also presented and discussed.