Beloborodova N.V.,Negovsky Research Institute of General Reanimatology |
Moroz V.V.,Negovsky Research Institute of General Reanimatology |
Osipov A.A.,Negovsky Research Institute of General Reanimatology |
Bedova A.Y.,Negovsky Research Institute of General Reanimatology |
And 3 more authors.
Biochemistry (Moscow) | Year: 2015
Previous studies showed that large amounts of phenylcarboxylic acids (PhCAs) are accumulated in a septic patient's blood due to increased endogenous and microbial phenylalanine and tyrosine biotransformation. Frequently, biochemical aromatic amino acid transformation into PhCAs is considered functionally insignificant for people without monogenetic hereditary diseases. The blood of healthy people contains the same PhCAs that are typical for septic patients as shown in this paper. The overall serum PhCAs level was 6 μM on average as measured by gas chromatography with flame ionization detection. This level is a stable biochemical parameter indicating the normal metabolism of aromatic amino acids. The concentrations of PhCAs in the metabolic profile of healthy people are distributed as follows: phenylacetic ≈ p-hydroxyphenyllactic > p-hydroxyphenylacetic > phenyllactic ≈ phenylpropionic > benzoic. We conclude that maintaining of stable PhCAs level in the serum is provided as the result of integration of human endogenous metabolic pathways and microbiota. © 2015 Pleiades Publishing, Ltd.
Demchenko P.F.,Russian Academy of Sciences |
Ginzburg A.S.,Russian Academy of Sciences |
Aleksandrov G.G.,Russian Academy of Sciences |
Vereskov A.I.,All Russian Research Institute of Metrological Service |
And 5 more authors.
Russian Meteorology and Hydrology | Year: 2015
Presented are the results of the construction of statistical models of the time series of air pollutants (particulate matter with the size of less than 10µm (PM10), CO, and NO2) for the network of automatic stations of air pollution control over Moscow megalopolis. The multiple nonlinear regression of pollutant concentration to external factors (meteorological and other) and values of concentration on previous days are taken as the statistical model of the time series of the average daily concentration of a certain pollutant. The nonlinear nature of the models of the time series can be caused with the dependence of pollutant concentration on wind speed and with other factors. Nonlinear regression based on the relatively short learning samples was used for simulating the series of average daily concentration of pollutants. The computations demonstrated that this gives much higher correlation between the computed and observed values of concentration and smaller standard deviation as compared with the model of inertial forecasting. © 2015, Allerton Press, Inc.
Golubev S.S.,All Russian Research Institute of Metrological Service |
Kudeyarov Y.A.,All Russian Research Institute of Metrological Service |
Malyuchenko V.M.,All Russian Research Institute of Metrological Service |
Zherdev A.V.,Bakh Institute of Biochemistry |
And 2 more authors.
Nanotechnologies in Russia | Year: 2013
In this paper the metrological complex developed for the certification of immunoassay test systems is described. This complex allows measuring the calibration curves, the probabilities of false results, and the parameters of immunoassay test-system components. The use of this complex offers metrological support for the results of immunoassay analysis. Also in this paper the algorithm of plotting and measuring the calibration curves for immunoassay test systems is described in detail. This algorithm is described in the measurement guideline included in the metrological complex. The calibration curves for benzodiazepines and tuberculosis markers, measured by the developed algorithm, are used as an experimental base for the described method. © 2013 Pleiades Publishing, Ltd.