This work is devoted to the development of the approach to restoration of the spatial-temporal distribution of electric field in the human brain. This field was estimated from the model derived from the Maxwell’s equations with boundary conditions corresponding to electric potentials at the EEG electrodes, which are located on the surface of the head according to the standard “10-20” scheme. The MRI data were used for calculation of the spatial distribution of the electrical conductivity of biotissues in the human brain. The study of the electric field distribution using our approach was carried out for the healthy child and the child with autism. The research was carried out using the equipment of the Tomsk Regional Common Use Center of Tomsk State University.
In our study we used rank-order filter, the emissions filter on the base of the criteria of Pearson, Gaussian filter and median filterfor improving the is fluorescence lifetime imaging microscopy (FLIM) data. The data obtained with the FLIM technology are the distribution with a pronounced peak, while during measurement the peak value is measured with an error. According to the analysisthe Gaussian filter is more useful to improve quality of FLIM data.Spatial filtering allows to reduce the noise component, obtained in the course of measurements, including reduction the influence of the individual bursts. Filtering in time scale allows to determine a peak value of intensity more accurately.This research was carried out using the equipment of Tomsk Regional Common Use Center of Tomsk State University.
The study of exosomes of saliva and blood plasma by THz laser spectroscopy was carried out. Exosomes were sampled from patients with colorectal cancer (n = 6) and healthy volunteers (n = 5). A substantive examination of the samples absorption spectra was performed using the method of canonical correlation analysis. The presence of Glycine, LAlanine, Mannose was revealed everywhere. The Mannose content was less in exosomes samples corresponding to colorectal cancer in comparison with exosomes samples from healthy volunteers.
Absorption spectra of paraffin-embedded prostate cancer and healthy tissues have been measured in the 0.2-3 THz range. The Principal Component Analysis and the Support Vector Machine (SVM) were applied to analyze experimental data. The SVM classifier was created which allows to distinguish the healthy tissues from tumor tissues, including classification of tumor tissue stage according to the Gleason scale.