Evaluation of serum and urine biomarkers for severe COVID-19.

Introduction: The new coronavirus disease, COVID-19, poses complex challenges exacerbated by several factors, with respiratory tissue lesions being notably significant among them. Consequently, there is a pressing need to identify informative biological markers that can indicate the severity of the disease. Several studies have highlighted the involvement of proteins such as APOA1, XPNPEP2, ORP150, CUBN, HCII, and CREB3L3 in these respiratory tissue lesions. However, there is a lack of information regarding antibodies to these proteins in the human body, which could potentially serve as valuable diagnostic markers for COVID-19. Simultaneously, it is relevant to select biological fluids that can be obtained without invasive procedures. Urine is one such fluid, but its effect on clinical laboratory analysis is not yet fully understood due to lack of study on its composition. Methods: Methods used in this study are as follows: total serum protein analysis; ELISA on moderate and severe COVID-19 patients' serum and urine; bioinformatic methods: ROC analysis, PCA, SVM. Results and discussion: The levels of antiAPOA1, antiXPNPEP2, antiORP150, antiCUBN, antiHCII, and antiCREB3L3 exhibit gradual fluctuations ranging from moderate to severe in both the serum and urine of COVID-19 patients. However, the diagnostic value of individual anti-protein antibodies is low, in both blood serum and urine. On the contrary, joint detection of these antibodies in patients' serum significantly increases the diagnostic value as demonstrated by the results of principal component analysis (PCA) and support vector machine (SVM). The non-linear regression model achieved an accuracy of 0.833. Furthermore, PCA aided in identifying serum protein markers that have the greatest impact on patient group discrimination. The study revealed that serum serves as a superior analyte for describing protein quantification due to its consistent composition and lack of organic salts and drug residues, which can otherwise affect protein stability.

Detection of electric-quadrupole transitions in water vapour near 5.4 and 2.5 µm.

Nowadays, the spectroscopic databases used for the modeling of Earth and planetary atmospheres provide only electric-dipole transitions for polyatomic molecules (H2O, CO2, N2O, CH4, O3…). Very recently, electric-quadrupole transitions have been detected in the high sensitivity cavity ring down spectrum (CRDS) of water vapour near 1.3 µm [A. Campargue et al., Phys. Rev. Res., 2020, 2, 023091, DOI: 10.1103/PhysRevResearch.2.023091]. This discovery paved the way to systematic searches of quadrupole transitions in water vapor and other polyatomic molecules. In the present work, on the basis of high accuracy ab initio predictions, H216O quadrupole lines are detected for the first time in the 5.4 µm and 2.5 µm regions where they are predicted to have their largest intensities (up to 10-26 cm per molecule). A total of twelve quadrupole lines are identified in two high sensitivity Fourier transform spectra recorded with a 1064 m path length. Ten lines in the 4030-4150 cm-1 region are assigned to the ν3 band while the lines near 1820 and 1926 cm-1 belong to the ν2 band. The derived line intensities which are largely above the dipole intensity cut-off of the standard spectroscopic databases, agree nicely with the theoretical predictions. We thus conclude that the calculated line list of quadrupole transitions, validated by the present measurements, should be incorporated in the spectroscopic databases.

Developing a Methodology for Determination of Elemental Composition of Shielding Materials.

Radiation transport simulation models can provide estimations of radiation effects such as detector response and detection capabilities. The objective of this research was to develop a methodology for quick, efficient, and effective determination of the composition of shielding materials to be used in radiation transport models. A C++ code, MatFit, was developed that used the concept of densitometry and the iterative method developed for the Spectrum Analysis by Neutron Detectors II (SAND II) computer program to estimate the elemental composition of shielding materials. These results were compared to previous neutron activation analysis (NAA) on the same samples. It was determined that densitometry provided an elemental approximation that yielded an attenuation rate within 10% of that found through NAA but requires much fewer resources, as well as less time. From this research, it is recommended that the developed method and C++ program be used when constructing models for detector response.