Mathematical models describing oxygen binding by hemoglobin.

Despite the fact that the investigation of the structural and functional properties of hemoglobin dates back more than 150 years, the topic has not lost its relevance today. The most important component of these studies is the development of mathematical models that formalize and generalize the mechanisms determining the cooperative binding of ligands based on data on the structural and functional state of the protein. In this work, we review the mathematical relationships describing oxygen binding by hemoglobin, ranging from the classical Hüfner, Hill, and Adair equations to the Szabo-Karplus and tertiary two-state mathematical models based on the Monod-Wyman-Changeux and Koshland-Némethy-Filmer concepts. The generality of the considered equations as mathematical functions, bearing in their basis a power dependence, is demonstrated. The problems and possible solutions related to approximation of experimental data by the oxygenation equations with correlated fitting parameters are noted. Attention is paid to empirical equations, extended versions of the Hill equation, where the coefficient of cooperation is modulated by Gauss and Lorentz distributions as functions of partial oxygen pressure.

A New Model of Hemoglobin Oxygenation.

The study of hemoglobin oxygenation, starting from the classical works of Hill, has laid the foundation for molecular biophysics. The cooperative nature of oxygen binding to hemoglobin has been variously described in different models. In the Adair model, which better fits the experimental data, the constants of oxygen binding at various stages differ. However, the physical meaning of the parameters in this model remains unclear. In this work, we applied Hill's approach, extending its interpretation; we obtained a good agreement between the theory and the experiment. The equation in which the Hill coefficient is modulated by the Lorentz distribution for oxygen partial pressure approximates the experimental data better than not only the classical Hill equation, but also the Adair equation.

Analysis and classification of peanuts with fungal diseases based on real-time spectral processing.

The study presents an approach to the analysis and classification of peanuts performed in order to detect kernels with fungi diseases, i.e. kernels prone to contamination with mycotoxigenic Aspergillus flavus (Aspergillus parasiticus). The aim of this study was to evaluate the effectiveness of luminescent spectroscopy with a violet laser (405 nm wavelength) as the excitation source of the fluorescence when applied for real-time detection of mould in peanuts performed by means of multispectral processing based on machine learning methods. We suggest a laboratory unit used to form, register, and process the luminescence spectra of peanuts in visible and near-infrared wavelength ranges in the real-time mode. The study demonstrated that contaminated peanuts have increased luminous intensity and show a redshift in the fluorescence peaks of the contaminated samples as compared to the pure ones. The difference in the fluorescence spectra of pure and contaminated kernels is compatible with the results obtained when traditional UV-light sources are used (365 nm). To classify peanuts by their spectral characteristics, neural network algorithms were used combined with dimensionality reduction methods. The paper presents the probabilities of incorrect recognition of the peanuts' type depending on the number of relevant secondary features determined when reducing the dimensionality of the initial data. When 10 spectral components were used, the error ratios were 0.7% or 0.3% depending on the method of reducing the dimensionality of the initial data.

The Role of Acidosis in the Pathogenesis of Severe Forms of COVID-19.

COVID-19 has specific characteristics that distinguish this disease from many other infections. We suggest that the pathogenesis of severe forms of COVID-19 can be associated with acidosis. This review article discusses several mechanisms potentially linking the damaging effects of COVID-19 with acidosis and shows the existence of a vicious cycle between the development of hypoxia and acidosis in COVID-19 patients. At the early stages of the disease, inflammation, difficulty in gas exchange in the lungs and thrombosis collectively contribute to the onset of acidosis. In accordance with the Verigo-Bohr effect, a decrease in blood pH leads to a decrease in oxygen saturation, which contributes to the exacerbation of acidosis and results in a deterioration of the patient's condition. A decrease in pH can also cause conformational changes in the S-protein of the virus and thus lead to a decrease in the affinity and avidity of protective antibodies. Hypoxia and acidosis lead to dysregulation of the immune system and multidirectional pro- and anti-inflammatory reactions, resulting in the development of a "cytokine storm". In this review, we highlight the potential importance of supporting normal blood pH as an approach to COVID-19 therapy.

Second derivative analysis of synthesized spectra for resolution and identification of overlapped absorption bands of amino acid residues in proteins: Bromelain and ficin spectra in the 240-320 nm range.

We establish the origin and formation of peaks in UV absorption spectra of proteins by applying the second derivative analysis to (i) spectra of the native protein, (ii) to its model spectra "synthesized" as a sum of partial free amino acid spectra and (iii) to absorption spectra of the free amino acids. We show that the bromelain peaks at 248.2, 253.2, 258.4 and 264.2 nm are due to phenylalanine maxima; the predictable peak at 279.6 nm (which is almost coincident with the extremum of the zero-order spectrum at 279.4 nm) is mainly due to tyrosine maximum, while the peaks at 274.6 and 290.6 nm are due to tryptophan maximum; 268.0 nm peak to the superposition of tyrosine and phenylalanine maxima, and 283.4 nm peak to the superposition of tyrosine and tryptophan maxima. Similar results are obtained for ficin: the peaks at 248.4, 253.0 and 258.8 nm are formed by the phenylalanine maxima, the predictable peak at 264.4 nm accords with the corresponding bromelain 264.2 nm peak; the 279.4 nm peak almost coincides with the zero order spectrum peak (279.6 nm), but it is expressed stronger than that of bromelain due to a different ratio of tyrosine to tryptophan side groups. The peaks at 273.4 and 290.6 nm are associated with tryptophan, the 268.0 nm peak being mainly due to tyrosine (and fractionally to phenylalanine); and the 283.8 nm peak belongs to tyrosine and, to a greater extent, to tryptophan. We demonstrate that the amino acid residues of tryptophan, tyrosine and phenylalanine undergo correspondingly the largest, intermediate and the lowest positive (red) wavelength shift in the zero-order protein absorption spectrum with respect to the model (synthesized) spectrum. The difference appearing in the positions of the bromelain and ficin absorption band peaks is determined by superposition of relative contributions from amino acid residues. This superposition is resulted from (i) linear combination of amino acid residues spectra and (ii) their different (non-uniform) wavelength shifts as functions of microenvironment of these residues' chromophores. The proposed approach to the analysis of the protein absorption spectra with the help of "synthesized" spectra can be transferred to other objects studied in analytical and organic chemistry of high molecular compounds containing monomer units with various chromophores.