Stanisław Masiuk

The expression and intranuclear distribution of nucleolin in HL-60 and K-562 cells after repeated, short-term exposition to rotating magnetic fields

Purpose: The aim of the study was to analyze the influence of rotating magnetic fields (RMF) on the expression and intranuclear distribution of nucleolin, protein involved in ribosome biosynthesis, in HL-60 (acute promyelocytic leukemia) and K-562 (chronic myelogenous leukemia) established human cell lines. Materials and methods: Cells were exposed to RMF for two chosen states of the magnetic field induction: B = 10 mT and B = 20 mT in experimental set-up for 30 min with 24-h intervals for four days. Cytospin slides were prepared and expression of nucleolin was detected using monoclonal antibodies. Parameters of fluorescence related to nucleolin were measured in at least 2000 tumor cells in each slide by a laser scanning cytometer with an argon laser. Percentages of cells in different phases of cell cycle were also analyzed. Results: The repeated exposition of cells to RMF caused significant increase in nucleolin expression in the whole nucleus and in the nucleolin aggregates (NUA). The redistribution of nucleolin measured by changes in number of NUA was also observed. The exposition of both cell lines studied to RMF did not alter the cell cycle. Conclusion: The nucleolin is responsive to RMF in HL-60 and K-562. The increase of its expression may indicate a reaction of cells to RMF and it may influence their other biological properties.

Entropy criterion of random states for granular material in a mixing process

Mathematical assessment of homogenisation progress of the granular material mixing process is presented. The mixing process was realised using a vessel in the form of two partly penetrating horizontal cylinders equipped with two multi-ribbon agitators. The experimental system consisted of three sets of particles of different colour. Random states of the mixed granular material were characterised by the sampling procedure at different moments of the mixing process. Informational entropy as well as the flow of quantum of information were applied to describe the progress of the homogenisation process. Analysis of this process was based on experimental investigations in the form of informational entropy patterns and described by means of the average informational entropy or the quantum of information.

Informational analysis of the grinding process of granular material using a multi-ribbon blender

A new concept of investigation on granular material grinding process using a multi-ribbon blender is demonstrated. A new approach of mathematical description of this process is presented using the Shannon’s entropy definition for random processes. The analysis of experiments was carried out employing the probability size distribution variation with the time of grinding process. The investigations reported in this work provide useful insight into the granular material grinding process. Moreover, the proposed informational description may be used to quantify the progress of this process whose importance in plant design and process optimisation, according to other experimental works, appears to be underestimated.

Experimental study of temperature gradient on solid dissolution process exposed to transverse rotating magnetic field

The main purpose of this work is to study the effect of transverse rotating magnetic field (TRMF) on the dissolution process of rock-salt sample. Moreover, the experimental study of the influence of the temperature gradient between the surface of sample and the solvent temperature on this process is presented in this paper. The results of investigations are worked out by means of the novel type dimensionless equations including standard and magnetic numbers. The obtained results are compared with previous data given in literature.

Forced Convection Mass-Transfer Enhancement in Mixing Systems

The design, scale-up and optimization of industrial processes conducted in agitated systems require, among other, precise knowledge of the hydrodynamics, mass and heat transfer parameters and reaction kinetics. Literature data available indicate that the mass-transfer process is generally the rate-limiting step in many industrial applications. Because of the tremendous importance of mass-transfer in engineering practice, a very large number of studies have determined mass-transfer coefficients both empirically and theoretically. Agitated vessels find their use in a considerable number of mass-transfer operations. They are usually employed to dissolve granular or powdered solids into a liquid solvent in preparation for a reaction of other subsequent operations (Basmadjian, 2004). Agitation is commonly used in leaching operations or process of precipitation, crystallization and liquid extraction. Transfer of the solute into the main body of the fluid occurs in the three ways, dependent upon the conditions. For an infinite stagnant fluid, transfer will be by the molecular diffusion augmented by the gradients of temperature and pressure. The natural convection currents are set up owing to the difference in density between the pure solvent and the solution. This difference in inducted flow helps to carry solute away from the interface. The third mode of transport is depended on the external effects. In this way, the forced convection closely resembles natural convection expect that the liquid flow is involved by using the external force. Mass-transfer process in the mixing systems is very complicated and may be described by the non-dimensional Sherwood number, as a rule is a function of the Schmidt number and the dimensionless numbers describing the influence of hydrodynamic conditions on the realized process. In chemical engineering operations the experimental investigations are usually concerned with establishing the mass-transfer coefficients that define the rate of transport to the continuous phase. One of the key aspects in the dynamic behaviour of the mass-transfer processes is the role of hydrodynamics. On a macroscopic scale, the improvement of hydrodynamic conditions can be achieved by using various techniques of mixing, vibration, rotation, pulsation and oscillation in addition to other techniques like the use of fluidization, turbulence promotes or magnetic and electric fields etc.

Analysis of Thermal Transient Processes by Means of Neural Network Technique

Particularly in the past decade, a very large effort has been expended in developing numerical methods for solving complex multidimensional problems in area of engineering processes. In the last few years the complex behaviour of biological, chemical and industrial systems has been explained in terms of dynamic analysis and many techniques to obtain predictions have been developed. The dynamic investigations of a various processes have focused attention on the problem of the mathematical description. In principle, this knowledge may be obtained by many computational modelling. As an easier alternative, the experimental data may be used to find out a black-box model or an empirical correlation defining the system behaviour. The limitation of this approach is that it requires assumption of the functional form of the proposed correlation. The popular approach to analyse the unsteady and steady heat transfer problems is associated with the availability of non-linear empirical modelling methodologies, such as neural networks, inspired by the biological network of neurons in the brain (Hussain, 1999; Ou & Achenie, 2005). Authors (Liau & Chen, 2006) proposed this methodology to model optimal concentrations of reactants for preparing sub-micron silica particles. Different sets of the reactant concentrations were selected within an operating range and were designed to evaluate the PSD data. The relationship between the reactant concentration and resultant PSD can be evaluated by means of the ANN modelling approach. The neural network models can be successfully used to compute PSD of particles with different shapes in highly concentred suspensions from laser diffraction measurements (Nascimento et al., 1997; Guardani et al. 2002). The ANN pattern recognition (ANNPR) approach has also been proposed for fed-batch cultivation processes of Escherichia coli (Duan et al., 2006). A novel data mining macro-kinetic approach based on ANN was proposed to develop the macrokinetic model of oxidation of p-xylene to terephthalic acid in a industrial type of continuous stirred tank reactor (Yan, 2007). Authors (Liu & Kim, 2008) used the purely mathematic and mechanical model with ANN to model membrane filtration process. As a tool of modelling, neural network technique has been used by (Jones et al., 1999) to magnetic inverse problem of determining the anisotropy field distribution from experimental transverse susceptibility data. Approximation models such as artificial neural networks (ANNs) are powerful and reliable in predicting the complex conditions such as nonlinear and time-variant biological