A. M. Vervald

Optical imaging of fluorescent carbon biomarkers using artificial neural networks

Abstract. The principle possibility of extraction of fluorescence of nanoparticles in the presence of background autofluorescence of a biological environment using neural network algorithms is demonstrated. It is shown that the methods used allow detection of carbon nanoparticles fluorescence against the background of the autofluorescence of egg white with a sufficiently low concentration detection threshold (not more than 2  μg/ml for carbon dots and 3  μg/ml for nanodiamonds). It was also shown that the use of the input data compression can further improve the accuracy of solving the inverse problem by 1.5 times.

Use of neural network algorithms for elaboration of fluorescent biosensors on the base of nanoparticles

In this paper, the results of application of artificial neural networks for extraction of fluorescence contribution of nanoparticles used in biomedicine as biomarkers and drug carriers against the fluorescence background of inherent fluorophores of biological objects are presented. Principle possibility of solving this problem is shown. The used architectures of ANN allow detecting fluorescence of carbon dots against the background of proper fluorescence of egg protein with reasonably high accuracy-not worse than 0.002 mg/mL.

Influence of hydrogen bonds on the colloidal and fluorescent properties of detonation nanodiamonds in water, methanol and ethanol

ABSTRACT This paper presents the results of research of influence of hydrogen bonds with different strength on fluorescence and colloidal properties of detonation nanodiamonds with surface carboxylic groups in the solvents. It is established that the colloidal properties of detonation nanodiamonds are almost independent on hydrogen bonds strength in water, methanol and ethanol. The fluorescent properties of detonation nanodiamonds are dependent on the type of solvent: the more intensive fluorescent properties correspond to weaker hydrogen bonds in solvents.

Joint Application of Group Determination of Parameters and of Training with Noise Addition to Improve the Resilience of the Neural Network Solution of the Inverse Problem in Spectroscopy to Noise in Data

In most cases, inverse problems are ill-posed or ill-conditioned, which is the reason for high sensitivity of their solution to noise in the input data. Despite the fact that neural networks have the ability to work with noisy data, in the case of inverse problems, this is not enough, because the incorrectness of the problem “outweighs” the ability of the neural network. In previous studies, the authors have shown that separate use of methods of group determination of parameters and of noise addition during training of neural networks can improve the resilience of the solution to noise in the input data. This study is devoted to the investigation of joint application of these methods. The study is performed at the example of an inverse problem in laser Raman spectroscopy - determination of concentrations of ions in a solution of inorganic salts by Raman spectrum of the solution.

Interactions of nanodiamonds and surfactants in aqueous suspensions

One of the features for nanodiamonds (NDs) is their complex chemically active surface, due to which NDs can be widely used in biomedicine as drugs carriers, adsorbents, or as the basis for various bioconjugates [1, 2]. Alternatively, the chemical activity of the surface groups leads to the formation of ND’s aggregates [3]. To improve the NDs’ dispersibility, surfactants are often added in suspensions [4]. However, physical picture of the interactions between these nanoparticles and molecules of surfactants is not fully understood. It is known that in suspensions, surfactants [5], as well as NDs [3, 6, 7], substantially change the structure of solvent and, primarily, the strength of hydrogen bonds. The authors [6, 7] showed that in aqueous suspensions the detonation nanodiamonds (DNDs) weaken the hydrogen bonds in bulk water and such changes depend on the type of ND’s surface groups. In this study, we investigated the interactions of hydrophilic (DND–COOH) and hydrophobic (DND–H) surface groups of DNDs with the surfactant sodium octanoate in water using dynamic light scattering and Raman spectroscopy techniques.

Fluorescent properties of nanodiamonds in result of interactions of nanodiamonds with biomacromolecules in water

In the present work an influence of interactions between detonation nanodiamonds and biomacromolecules (DNA and lysozyme) on fluorescent properties of nanodiamonds was studied. Formation mechanisms of complexes of nanodiamonds with DNA and lysozyme molecules were investigated. It was found that fluorescent intensity of detonation nanodiamonds changes in different ways for nanoparticles with different surface composition. It was established that fluorescent intensity of nanodiamonds increases in case of the interaction with a sufficient number of biomacromolecules.

The influence of boron doped nanodiamonds on hydrogen bonds in suspensions of protic solvents

This work presents the results of study of the influence of BDND on hydrogen bonds of protonic solvents. In addition, the comparative analysis of the interactions of BDND and DND-COOH with solvents molecules was carried out. The analysis of temperature dependences of the quantitative characteristics of the stretching bands of OH groups of the solvents and the suspensions of NDs has shown that the BDND and DND differently weaken the hydrogen bonds in water and in water-ethanol solution with 70 vol. % ethanol content. In water-ethanol solution with 20 vol. % of ethanol the both NDs practically does not change the network of hydrogen bonds.