The goal of the present paper was to find effective biochemical markers of chronic narcotization. Materials and methods. The results of biochemical research of biological liquids in human organism and chromatographic methods of drug substances identification in cadaveric urine were analyzed. Research of 197 samples of different biologic liquids of 10 persons was carried out. Control was fulfilled on the basis of 135 samples of biological liquids took of 12 persons. Methods of identification of drug substances are presented, chromatographic and spectral characteristics of drug substances are described. Interrelations of biochemical indices at positive study of drug substances identification were conducted. The increased urea metabolic concentration in cadaveric blood of drug addicts was revealed in comparison with control specimens. Results. (Numeral results are given in Table 3). Correct correlation of biochemical markers was not established. Conclusion. The present results suppose continued study of informative reliable biochemical markers of chronic drug intoxication
Bychkov E.N., Serkova S.A., Arsentieva L.A., Frantsuzova T.S., Bluvshtein G.A., Borodulin V.B. General methods of identification of narcotic substances in cadaveric urine and biochemical indices in blood at positive identification of drug substances // Saratov Journal of Medical Scientific Research, Vol. 7, Issue 3, 2011, pp. 642-646

Laser-induced luminescence of multilayer structures based on the solids of CdSe and CdSe/ZnS nanocrystals, different organic semiconductors and on the layers of organic semiconductors with embedded nanocrystals has been investigated. Drastic decrease of luminescence quantum yield is observed in the films of CdSe nanocrystals on organic semiconductors compared to those on optical glasses. The luminescence of the nanocrystals in the matrices of organic semiconductors and in multilayer structures is shown to be suppressed. The effects observed are explained by the transfer of photogenerated carriers from the nanocrystals to the molecules of organic semiconductors. The presence of the charge transfer is confirmed by a drastic increase in the conductivity (by 2 - 4 orders of magnitude) and in photo-voltaic effect at the presence of CdSe and CdSe/ZnS nanocrystals in the structures under investigation. The prospects of using the multilayer structures for development new materials for solar cells are discussed.

We discuss semiempirical approaches and parametric methods developed for modeling molecular vibronic spectra. These methods, together with databases of molecular fragments, have proved efficient and flexible for solving various problems ranging from detailed interpretation of conventional vibronic spectra and calculation of radiative transition probabilities to direct simulations of dynamical (time-resolved) spectra and spectrochemical analysis of individual substances and mixtures. A number of specific examples and applications presented here show the potential of the semiempirical approach for predictive calculations of spectra and solution of inverse spectral problems. It is noteworthy that these advances provide computational insights into developing theories of photoinduced isomer transformations and nonradiative transitions in polyatomic molecules and molecular ensembles, theory of new methods for standardless quantitative spectral analysis.
Nova Science Publishers, New York, 2008

A recently proposed mutual information based algorithm for decomposing data into least dependent components (MILCA) is applied to spectral analysis, namely to blind recovery of concentrations and pure spectra from their linear mixtures. The algorithm is based on precise estimates of mutual information between measured spectra, which allows to assess and make use of actual statistical dependencies between them. We show that linear filtering performed by taking second derivatives effectively reduces the dependencies caused by overlapping spectral bands and, thereby, assists resolving pure spectra. In combination with second derivative preprocessing and alternating least squares postprocessing, MILCA shows decomposition performance comparable with or superior to specialized chemometrics algorithms. The results are illustrated on a number of simulated and experimental (infrared and Raman) mixture problems, including spectroscopy of complex biological materials.