The diversity and the stability of the microbial community are associated with microecological interactions between its members. Antagonism is one type of interaction, which particularly determines the benefits that probiotics bring to host health by suppressing opportunistic pathogens and microbial contaminants in food. Mathematical models allow for quantitatively predicting intrapopulation relationships. The aim of this study was to create predictive models for bacterial contamination outcomes depending on the probiotic antagonism and prebiotic concentration. This should allow an improvement in the screening of synbiotic composition for preventing gut microbial infections. The functional model (fermentation) was based on a three-stage continuous system, and the distal colon section (N₂, pH 6.8, flow rate 0.04 h^–1) was simulated. The strains Bifidobacterium adolescentis ATCC 15703 and Bacillus cereus ATCC 9634 were chosen as the model probiotic and pathogen. Oligofructose Orafti P95 (OF) was used as the prebiotic at concentrations of 2, 5, 7, 10, 12, and 15 g/L of the medium. In the first stage, the system was inoculated with Bifidobacterium, and a dynamic equilibrium (Bifidobacterium count, lactic, and acetic acids) was achieved. Then, the system was contaminated with a 3-day Bacillus suspension (spores). The microbial count, as well as the concentration of acids and residual carbohydrates, was measured. A Bacillus monoculture was studied as a control. The stationary count of Bacillus in monoculture was markedly higher. An increase (up to 8 h) in the lag phase was observed for higher prebiotic concentrations. The specific growth rate in the exponential phase varied at different OF concentrations. Thus, the OF concentration influenced two key events of bacterial infection, which together determine when the maximal pathogen count will be reached. The mathematical models were developed, and their accuracies were acceptable for Bifidobacterium (relative errors ranging from 1.00% to 2.58%) and Bacillus (relative errors ranging from 0.74% to 2.78%) count prediction.

Stirred bioreactors are widely used in the pharmaceutical industry to produce various active substances for the treatment of cancer, heart and vascular diseases, viral and bacterial infections. Despite the widespread use of bioreactors with a stirrer, the optimization of mixing conditions remains an urgent task. In bioreactors of this type, continuous mixing of cells in a medium with a high rotation speed should be carried out. The manuscript considers an example of the use of computational fluid dynamics to study and model the process of cultivation Escherichia coli bacterial cells in a batch bioreactor (NLF, 30 l.). Computational fluid dynamics was used to analyze the hydrodynamic conditions in a bioreactor with a double Rushton turbine stirrer. To describe the movement of flows and evaluate turbulence in a batch bioreactor, the multiphase Euler model and the k-𝜀 turbulence model, respectively, were used, the built-in Ansys Fluent software package. A geometric model was built with the original dimensions of the bioreactor with an NLF 30 stirrer. Based on the geometric model, a computational grid was created for the working volume of the bioreactor and the optimal parameters for constructing the computational grid were selected. As a result of modeling the hydrodynamic regime, the distribution profiles of the turbulence kinetic energy over the volume of the bioreactor were obtained and the velocities of cell movement were found at different speeds of rotation of the stirrer. The obtained results show the possibility and applicability of the Ansys Fluent software package for calculating the hydrodynamic situation in a bioreactor with a stirrer at different stirring rates and at different cell volume fractions.

The application of artificial neural networks (ANNs) to mathematical modelling in microbiology and biotechnology has been a promising and convenient tool for over 30 years because ANNs make it possible to predict complex multiparametric dependencies. This article is devoted to the investigation and justification of ANN choice for modelling the growth of a probiotic strain of Bifidobacterium adolescentis in a continuous monoculture, at low flow rates, under different oligofructose (OF) concentrations, as a preliminary study for a predictive model of the behaviour of intestinal microbiota. We considered the possibility and effectiveness of various classes of ANN. Taking into account the specifics of the experimental data, we proposed two-layer perceptrons as a mathematical modelling tool trained on the basis of the error backpropagation algorithm. We proposed and tested the mechanisms for training, testing and tuning the perceptron on the basis of both the standard ratio between the training and test sample volumes and under the condition of limited training data, due to the high cost, duration and the complexity of the experiments. We developed and tested the specific ANN models (class, structure, training settings, weight coefficients) with new data. The validity of the model was confirmed using RMSE, which was from 4.24 to 980% for different concentrations. The results showed the high efficiency of ANNs in general and bilayer perceptrons in particular in solving modelling tasks in microbiology and biotechnology, making it possible to recommend this tool for further wider applications.

Plant polyphenols are known for their numerous health-promoting properties. This article reviews the current state of research in two related fields, namely beneficial effects of flavonoids for human health, e.g., gut microbiome, and supercritical fluid extraction applied to flavonoids of plant origin. The review covered research articles registered in eLIBRARY.RU, PubMed, and Science Direct in 2005–2025. Polyphenolic compounds obtained from various berries were reported to have a positive impact on gut microbiota, e.g., they stimulated the growth of lactobacilli, bifidobacteria, and other beneficial microorganisms, as well as improved the adhesion of probiotic and pathogenic microbes to intestinal epithelial cells. The review revealed some promising application areas for berry extracts in the functional food industry. Polyphenols can be part of meat formulations due to their strong antioxidant activity. Their antimicrobial effect against a wide range of contaminants renders them good prospects in protecting food products from microbial spoilage. Supercritical extraction is a promising method that isolates biologically active substances from plant materials. The review summarizes its advantages and limitations, as well as the range of prospective co-solvents. Ultrasonication, pulse electric field, and enzymic pretreatment make supercritical extraction more efficient. In general, this extraction method proved to be an excellent means of isolating flavonoids and related compounds from various plants and their parts.

Objectives . The development of technological solutions aimed at increasing the efficiency of supercritical fluid extraction of polar biologically active substances from plant materials is a priority direction due to the demand for such substances in the food and pharmaceutical industries. The aim of this study is to develop an approach for stabilizing extractant composition by continuously feeding a polar cosolvent into a supercritical carbon dioxide flow. Methods . The study was carried out on blackcurrant (R ibes nigrum L.) fruits, which contain polyphenols, one of the most difficultto-extract compounds. Two types of prepared raw materials were used: heat-dried at 50°C for 48 h; freeze-dried at a pressure of 68 Pa and a temperature of up to 25°C for 48 h. Extracts were obtained by supercritical fluid extraction in a 250-mL high-pressure extractor. The process was carried out at a temperature of 50°C and a pressure of 200 bar in different modes: using pure CO2; with the addition of ethanol; with the addition of acetone; and employing different methods for feeding the extractant into the high-pressure extractor. Results . The highest efficiency of polyphenol extraction was achieved using heat drying of the raw materials in combination with a continuous supply of ethanol as a cosolvent, which enabled the highest yields of extract (22.47 wt %) and polyphenols (4.95 wt %). The experiments confirmed that the modes using acetone provide a high yield of extractive substances; however, their use is limited by the toxicity of the solvent, whereas a continuous supply of ethanol is a more promising and safer method for process intensification. Рeat-dried samples consistently demonstrated higher yields of both extract and target polyphenols in comparison with freeze-dried raw materials in all extraction modes studied. Conclusions . The choice of drying method at the stage of raw material preparation is shown to have a significant impact on extraction efficiency: heat drying provides a higher extract yield than freeze drying. The experiments confirmed that the addition of polar cosolvents increased the solubility of polyphenols. While the highest efficiency among single-addition modes was achieved using acetone, ethanol is recommended due to its non-toxicity. By using a continuous flow of a cosolvent instead of its a single addition, the total extract yield is increased by 6.4 times, and the polyphenol content by 17 times. The proposed universal approach can be applied to the extraction of a wide range of polar compounds; even higher efficiency is expected for less polar substances.

Plant polyphenols have recently been recognized as promising new-generation prebiotics. However, the concentrations and profiles of polyphenols vary significantly among different plants, so the effects of their extracts on probiotic strains are also highly variable. This study assessed the effects of ethanol and supercritical fluid extracts of black currant and sea buckthorn on the growth of bifidobacteria and their antagonism against intestinal pathogens. Extracts of black currant and sea buckthorn were obtained using reflux ethanol extraction or supercritical fluid extraction. Total phenols in the extracts were determined by the Folin-Ciocalteu colorimetric method. Individual phenolic compounds were identified by UV-Vis spectroscopy. Effects of the extracts on bifidobacteria and the intestinal pathogens Bacillus cereus and Staphylococcus aureus were evaluated in monoculture. Antagonism of bifidobacteria against the pathogens was evaluated in coculture in the media with various ethanol extracts. Concentrations of organic acids were determined using HPLC. Phenolic components of the berries had stimulated, neutral, or negative effects on probiotic growth and organic acid production, depending on the type of raw material and the extraction method. Bifidobacterium adolescentis and Bifidobacterium longum were the most sensitive to, and strongly inhibited by, the extracts, while no pronounced growth-stimulating effect was observed for any of the studied bifidobacteria strains. Additionally, the effect of total phenolic concentrations in the extracts on the strain growth was evaluated by diluting the native extracts. Minimum inhibitory concentrations in the ethanol extracts for bifidobacteria ranged from 30 to 140 μg GAE/mL, while those in the supercritical fluid extracts were lower (13–32 μg GAE/mL). The sea buckthorn supercritical fluid extract stimulated Bifidobacterium bifidum growth, while the ethanol extract of sea buckthorn and the supercritical fluid extract of black currant stimulated the growth of Bifidobacterium breve and B. longum subsp. infantis. B. cereus was not sensitive to changes in total phenolic concentrations. The minimum inhibitory concentration of total phenols for S. aureus was the lowest (7 μg GAE/mL) in the supercritical fluid extract of sea buckthorn. The extracts had mostly neutral or positive effects on lactic and acetic acids production by bifidobacteria. The greatest increase in acid concentrations was observed for B. breve in the medium with black currant ethanol extract. The greatest suppression of pathogen growth was achieved by a combination of B. breve with either of the ethanol extracts. The results demonstrate that black currant and sea buckthorn extracts are highly selective prebiotics that exert different effects on the antagonism of bifidobacteria against pathogens. The study revealed the most effective combination of the bifidobacteria and berry extracts against the pathogens, as well as the most effective symbiotic composition.