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Eight single (SGA) and eight multi-population (MGA) genetic algorithms (GA) differing in the sequence of implementation of the main genetic operators’ selection, crossover and mutation, or omitting the mutation operator, have been examined for the purposes of parameter identification of a Saccharomyces cerevisiae fed-batch fermentation process model. The influence of some of the main genetic algorithm parameters, namely number of individuals, maximum number of generations, generation gap, crossover and mutation rates for both SGA and MGA, and insertion and migration probability for MGA only, have been investigated in depth. Almost all applied SGA and MGA led to similar values of the optimization criterion but the SGA with operators’ sequence mutation, crossover and selection, and MGA with operators’ sequence crossover, selection and mutation, are significantly faster than others while keeping the model accuracy. Among the considered GA parameters, generation gap influences most significantly to SGA and MGA convergence time, saving of about 40% of computational time of the algorithms without affecting the model accuracy.

This study aimed to determine the total phenolic content of Oriental tobacco waste seeds, grown under organic production, and to evaluate their antioxidant activity by extraction with different solvents under different conditions. The extraction was performed with H2O, 99.9% CH3OH, 60% CH3OH, and 96% C2H5OH under maceration and ultrasonic extraction at 20°C and 40°C. All solvents were used in a volume of 4 mL, 5 mL, and 6 mL. The total phenolic content varied between 0.89 mg/g GAE (maceration; sample/solvent ratio 0.1g/5mL, C2H5OH) and 5.85 mg/g GAE (maceration; sample/solvent ratio 0.1g/6mL, C2H5OH). Ethanolic and 60% methanolic extracts had the highest antioxidant activity as determined by the DPPH method; 60% methanolic and water extracts had the highest antioxidant activity as determined by the ABTS method; while methanolic and 60% methanolic extracts had the highest antioxidant activity as determined by the FRAP method. In addition, the content of nicotine in tobacco seed extract was not detected.

Extremophiles are of significant scientific interest due to their unique adaptation to harsh environmental conditions and their potential for diverse biotechnological applications. Among these extremophiles, filamentous fungi adapted to high-salt environments represent a new and valuable source of enzymes, biomolecules, and biomaterials. While most studies on halophiles have focused on bacteria, reports on filamentous fungi remain limited. This review compiles information about salt-adapted fungi and details their distribution, adaptation mechanisms, and potential applications in various societal areas. Understanding the adaptive mechanisms of halophilic fungi not only sheds light on the biology of extremophilic fungi but also leads to promising biotechnological applications, including the development of salt-tolerant enzymes and strategies for bioremediation of saline habitats. To fully realize this potential, a comprehensive understanding of their ecology, diversity and physiology is crucial. In addition, understanding their survival mechanisms in saline environments is important for the development of astrobiology. The significant potential of applications of halophilic fungi is highlighted.

In order to meet the ever-growing needs of society, modern agriculture must develop sustainable farming and livestock production. Crops need phosphorus, a macronutrient found in soils, but they are only able to utilize small quantities of it. Chemical phosphate fertilizers are ineffective and environmentally harmful. The use of microorganisms (bacteria, yeast, filamentous fungi, and microalgae) that synthesize phytases is a promising and environmentally friendly alternative to chemical fertilizers. Phytases are also needed as feed additives in animal husbandry to overcome phosphorus deficiency for animal growth and development. Phytases are phosphatases that catalyze the release of phosphorus from phytate by stepwise hydrolysis. The broad substrate specificity, optimal pH range, higher thermal stability, and specific efficiency of fungal phytases make them interesting enzymes for agricultural applications. They improve and stimulate the growth and development of plants and animals by releasing inorganic phosphorus and producing siderophores, organic acids, hydrogen cyanide, ammonia, and phytohormones. Phytases are crucial for enhancing phosphorus use in farming and decreasing phosphorus waste’s environmental effects. This paper addresses key challenges in modern farming, such as the inefficient utilization of phosphorus from soil and the environmental harm caused by chemical fertilizers, and provides a comprehensive overview of recent advances in the research of fungal phytases. Available scientific data have been synthesized to highlight the potential of phytase use in agriculture. This review outlines key areas for future research, including the development of phytase variants with improved functionality. The potential integration of fungal phytases into sustainable agricultural practices is underlined, in contrast to previously published work focused primarily on their biochemical properties. The review offers new insight into the possible applications of micromycete phytases as a critical factor for sustainable agriculture in the future.

The Asteraceae family is a large plant family, with over 1600 genera and 25,000 species, most of which are generally herbaceous plants. This family’s members are widely used in the human diet and medicine. One of the most popular representatives is Centaurea benedicta L., known as ‘Blessed Thistle’. It is a famous plant in the herbal world with some medical benefits, such as strong antioxidant and antidepressant effects, with antibacterial and antiseptic properties, a stimulant of appetite, with a good effect on the liver and the secretion of bile juices, etc. Therefore, this work aimed to fully characterize the chemical composition of the seeds of C. benedicta introduced in Bulgaria, some of the physicochemical characteristics, as well as the biologically active compounds. The main nutrient in the chemical composition was carbohydrates (68.5%), and half of their quantity was occupied by fibers (32.2%). Total proteins accounted for 16.4%, and the glyceride oil content was rather low—about 11.0%. The main fatty acids identified in the seed oil were linoleic (72.1%) and oleic acids (18.1%), and the amount of the polyunsaturated ones predominated (73.0%). The main lipid-soluble bioactive components were sterols (0.9%), phospholipids (1.9%), and tocopherols (492 mg/kg). β-Sitosterol (59.5%) and stigmasterol (19.4%) were the main sterols, and α-tocopherol (472 mg/kg) predominated in the tocopherol fraction. The major phospholipids were phosphatidylethanolamine (45.4%), followed by phosphatidylinositol (37.1%) and phosphatidylcholine (6.1%).

InterCriteria analysis (ICrA) and two kinds of correlation analyses, Pearson (PCA) and Spearman (SCA), were applied to surface electromyography (sEMG) signals obtained from human arm movements in the horizontal plane. Ten healthy participants performed ten movements, eight of which were cyclic. Each cyclic movement (CM) consisted of flexion and extension phases with equal duration (10 s, 6 s, 2 s, and 1 s) and two 5 s rest poses between them. The CMs were performed with and without an added load of 0.5 kg on the wrists of the participants. The sEMG signals from six different muscles or separate muscle heads (m. deltoideus pars clavicularis, m. deltoideus pars spinata, m. brachialis, m. anconeus, m. biceps brachii, and m. triceps brachii long head) were recorded and used to compare the results of the ICrA, PCA, and SCA. All three methods found identical consonance pairs for the flexion and extension CM phases. Additionally, PCA detected two more consonance pairs in the extension phases. In this investigation, ICrA, PCA, and SCA were proven to be reliable tools when applied separately or in combination for sEMG data. These three methods are appropriate for researching arm movements in the horizontal plane and experimental protocol revision.

The fungal strain, Penicillium griseofulvum P29, isolated from a soil sample taken from Terra Nova Bay, Antarctica, was found to be a good producer of sialidase (P29). The present study was focused on the purification and structural characterization of the enzyme. P29 enzyme was purified using a Q-Sepharose column and fast performance liquid chromatography separation on a Mono Q column. The determined molecular mass of the purified enzyme of 40 kDa by SDS-PAGE and 39924.40 Da by matrix desorption/ionization mass spectrometry (MALDI-TOF/MS) analysis correlated well with the calculated mass (39903.75 kDa) from the amino acid sequence of the enzyme. P29 sialidase shows a temperature optimum of 37 °C and low-temperature stability, confirming its cold-active nature. The enzyme is more active towards α(2 → 3) sialyl linkages than those containing α(2 → 6) linkages.Based on the determined amino acid sequence and 3D structural modeling, a 3D model of P29 sialidase was presented, and the properties of the enzyme were explained. The conformational stability of the enzyme was followed by fluorescence spectroscopy, and the new enzyme was found to be conformationally stable in the neutral pH range of pH 6 to pH 9. In addition, the enzyme was more stable in an alkaline environment than in an acidic environment. The purified cold-active enzyme is the only sialidase produced and characterized from Antarctic fungi to date.

Centaurea thracica (Janka) Hayek is a plant common in southern Bulgaria. The inflorescences were collected during June and September 2021, while their seeds were obtained in September 2021. The chemical and lipid composition of the inflorescences during the vegetation process of the plant were established. A significant decrease in total proteins (from 8.7 to 7.4%), glyceride oils (2.0–1.7%), and ash (4.5–4.2%) content was observed, while the amount of carbohydrates (72.3–77.2%) and fibers (28.7–35.8%) increased. During the vegetation of the plant, the content of oleic and linoleic acids increased up to 2–3 times, while the level of palmitic acid decreased. The lipids from the seeds were rich in oleic (53.0%) and palmitic (36.2%) acids. The tocopherol content in the oils of the inflorescences during vegetation increased from 58 to 110 mg/kg, and the content in the oil from the seeds was 260 mg/kg. The phospholipid content decreased during vegetation, and differences were observed in the composition between the inflorescences and the seeds. The high content of oleic acid, linoleic acid, tocopherols, and phospholipids determine the nutritional and biological value of the oils isolated from Centaurea thracica, and contribute to their potential use in various directions.

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The InterCriteria decision-making approach, known as InterCriteria analysis (ICrA), was applied here to optimize the experimental protocol when the surface electromyography (EMG) signals of upper arm human muscles are recorded. Ten healthy subjects performed cycling movements in the sagittal plane with and without added weight for ten, six, two, and one second, respectively, for each active phase. The EMG signals from six muscles or parts of muscles, namely m. deltoideus pars clavicularis and pars spinata, m. brachialis, m. anconeus, m. biceps brachii, and m. triceps brachii caput longum, were recorded. ICrA was used on the obtained data to find correlations between the sixteen different phases, eight for elbow flexion and eight for elbow extension. Based on the obtained results, we proposed an optimized experimental protocol (OEP) that omits slower and more difficult tasks while saving crucial data. The optimized protocol consists of seven, instead of ten, tasks and takes three minutes less than the time taken for the full experimental protocol (FEP). The lower number of movements in the OEP could prevent physical and psychical fatigue, discomfort, or even pain in the investigated subjects. In addition, the time to train subjects, as well as the time to process the surface EMG data, can be significantly reduced.

Sialidases (neuraminidases) catalyze the removal of terminal sialic acid residues from glycoproteins. Novel enzymes from non-clinical isolates are of increasing interest regarding their application in the food and pharmaceutical industry. The present study aimed to evaluate the participation of carbon catabolite repression (CCR) in the regulation of cold-active sialidase biosynthesis by the psychrotolerant fungal strain Penicillium griseofulvum P29, isolated from Antarctica. The presence of glucose inhibited sialidase activity in growing and non-growing fungal mycelia in a dose- and time-dependent manner. The same response was demonstrated with maltose and sucrose. The replacement of glucose with glucose-6-phosphate also exerted CCR. The addition of cAMP resulted in the partial de-repression of sialidase synthesis. The CCR in the psychrotolerant strain P. griseofulvum P29 did not depend on temperature. Sialidase might be subject to glucose repression by both at 10 and 25 °C. The fluorescent assay using 4MU-Neu5Ac for enzyme activity determination under increasing glucose concentrations evidenced that CCR may have a regulatory role in sialidase production. The real-time RT-PCR experiments revealed that the sialidase gene was subject to glucose repression. To our knowledge, this is the first report that has studied the effect of CCR on cold-active sialidase, produced by an Antarctic strain.

Catalase (CAT) is an enzyme involved in the first line of cellular antioxidant defense. It plays a key role in the protection of a wide range of Antarctic organisms against cold stress. Extracellular catalase is very rare and data on it are extremely scarce. The aim of the present study was to select an efficient producer of extracellular catalase from amongst Antarctic filamentous fungi. Sixty-two Antarctic filamentous fungal strains were investigated for their potential ability to synthesize intracellular and extracellular CAT. The Antarctic strain Penicillium rubens III11-2 was selected as the best producer of extracellular catalase. New information on the involvement of the extracellular antioxidant enzymes superoxide dismutase and CAT in the response of filamentous fungi against low-temperature stress was obtained. An efficient scheme for the purification of CAT from culture fluid was developed. An enzyme preparation with high specific activity (513 U/mg protein) was obtained with a yield of 19.97% and a purification rate of 98.4-fold. The purified enzyme exhibited maximal enzymatic activity in the temperature range of 5–40 °C and temperature stability between 0 and 30 °C, therefore being characterized as temperature sensitive. To our knowledge, this is the first purified extracellular cold active catalase preparation from Antarctic filamentous fungi.

Electromyography (EMG) is a widely used method for estimating muscle activity and could help in understanding how muscles interact with each other and affect human movement control. To detect muscle interactions during elbow flexion and extension, a recently developed InterCriteria Analysis (ICrA) based on the mathematical formalisms of index matrices and intuitionistic fuzzy sets is applied. ICrA has had numerous implementations in different fields, including biomedicine and quality of life; however, this is the first time the approach has been used for establishing muscle interactions. Six human upper arm large surface muscles or parts of muscles responsible for flexion and extension in shoulder and elbow joints were selected. Surface EMG signals were recorded from four one-joint (pars clavicularis and pars spinata of m. deltoideus [DELcla and DELspi, respectively], m. brachialis [BRA], and m. anconeus [ANC]) and two two-joint (m. biceps brachii [BIC] and m. triceps brachii-caput longum [TRI]) muscles. The outcomes from ten healthy subjects performing flexion and extension movements in the sagittal plane at four speeds with and without additional load are implemented in this study. When ICrA was applied to examine the two different movements, the BIC–BRA muscle interaction was distinguished during flexion. On the other hand, when the ten subjects were observed, four interacting muscle pairs, namely DELcla-DELspi, BIC-TRI, BIC-BRA, and TRI-BRA, were detected. The results obtained after the ICrA application confirmed the expectations that the investigated muscles contribute differently to the human upper arm movements when the flexion and extension velocities are changed, or a load is added.

Hypnum cupressiforme Hedw. is the main species for Moss surveys (ICP Vegetation programme) in Southeastern Europe and is widely distributed in the region. In addition to their biomonitoring role, mosses are applied in some countries as a traditional medicine for the treatment of eczema, cuts, burns, eye diseases, etc. Therefore, the chemical and lipid composition of the moss H. cupressiforme is of interest to establish their possible application in different fields. The chemical composition of the moss was examined regarding total lipids, proteins, carbohydrates (i.e., fibres), ash, and moisture content. The main lipid-soluble bioactive components were determined as sterols, tocopherols, phospholipids and fatty acids. The major fatty acids were linoleic (14.9%), oleic (13.8%), palmitic (12.5%) and α-linolenic (11.3%) acids. Unsaturated fatty acids (56.4%) prevailed in the glyceride oil, in which the polyunsaturated ones constituted 32.5%. The lipid indices (atherogenicity, thrombogenicity, hypocholesterolemic/hypercholesterolemic ratio, peroxidability, and oxidation stability index) were also theoretically calculated based on the fatty acid composition of the moss lipids to establish their health benefits and the rate of oxidation. The primary results of this study revealed H. cupressiforme to be a promising alternative source of bioactive compounds that could be implemented in supplements with health-promoting effects.

Sialic acids (Sia) represent a set of derivatives of nine-carbon sugar neuraminic acid that occupy a terminal position in oligosaccharide chains located on the surface of cells. They are very important for several physiological and pathological processes, including bacterial and viral infections. Until recently, Sia had been described mostly in animals, viruses, bacteria and protozoan species. In the last years, information on sialic acids existence in filamentous fungi has been published, but these data are very scarce. The same is valid for the enzymes that are involved in the synthesis, transport and degradation of Sia in fungi. So far, most data known regarding fungal sialidases are a result of published complete fungal genomes. However, based on the accumulated data, it appears that the kingdom of fungi probably harbours hitherto unknown mechanisms and enzymes of sialic acid metabolism. This review attempts to present the state of knowledge on sialic acids in fungi with respect to their structure, diversity and biological role, as well as Sia metabolism and enzymes involved in their conversion. The summary is presented at the background of the respective metabolic mechanisms possessed by eukaryotes and prokaryotes. The possible role of sialome and sialometabolism in fungi are also discussed.

This paper presents a hybrid scheme based on two population-based metaheuristic techniques, namely genetic algorithm (GA) and cuckoo search (CS). In particular, the hybrid is formed by the application of standard simple genetic algorithms (SGA) and CS, specifically adapted and for first time applied by the authors for the purposes of parameter identification of yeast fed-batch fermentation process model. The parameters of the hybrid technique SGA-CS have been thoroughly explored and tuned to meet the specific peculiarities of the considered here optimization problem. A comparison of SGA, CS and developed hybrid SGA-CS has been performed, outlining the advantages and disadvantages of each algorithm. Additionally, a new modification of SGA-CS hybrid technique, inspired by proven as very effective modification of SGA, working with implementation of main genetic operators in order crossover, mutation and selection, has been here elaborated. Presented modified hybrid technique has been tested, aiming at verification of the obtained promising results of developed SGA-CS technique.

The experimental procedures of drug design, proven to be time-consuming and costly, are successfully complemented with computer-aided (in silico) approaches nowadays. Virtual ligand screening (VLS) is one of the most promising approaches when searching for new hit compounds. The efficiency of VLS procedures might be improved via post-docking optimization. In the focus of this investigation is AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening) developed as multi-step structure-based procedure for efficient computational refinement of protein-ligand complexes at different levels of protein flexibility. Their performance has been assessed by the recently developed InterCriteria Analysis (ICrA), elaborated as multi-criterion decision-making approach to reveal possible relations in the behavior of pairs of criteria when multiple objects are considered. The capacity of ICrA as a supporting tool to assess the effect of applying different levels of protein flexibility in the post-docking optimization via AMMOS has been investigated and analyzed.

(1) Background: In silico approaches to rational drug design are among the fastest evolving ones. Depending on the available structural information for the biomacromolecule and the small molecule, the in silico methods are classified as ligand- and structure-based. The latter predict ligand–receptor binding using 3D structures of both molecules, whose computational simulation is referred to as molecular docking. It aims at estimating the binding affinity (approximated by scoring function) and the ligand binding pose in the receptor’s active site, which postulates a key role of the scoring functions in molecular docking algorithms. This study focuses on the performance of different types of scoring functions implemented in molecular modelling software packages. (2) Methods: An InterCriteria analysis (ICrA) was applied to assess the performance of the scoring functions available in MOE, GOLD, SeeSAR, and AutoDock Vina software platforms. The InterCriteria analysis was developed to distinguish possible relations between pairs of criteria when multiple objects are considered. All 12 investigated scoring functions were tested by docking a set of protease inhibitors in the binding sites of two protein targets. The dataset consisted of 88 benzamidine-type compounds with experimentally measured inhibitory constants for thrombin and trypsin, which allows for the objective assessment of the scoring functions performance. The results generated by the molecular docking were subjected to ICrA in order to analyze both docking energies as approximations of the binding affinities and RMSDs (root-mean-square deviation) as measures of the experimental binding pose proximity between the compounds and the co-crystalized ligand, based on the atoms in the common scaffold. (3) Results: The results obtained for the best poses, the average of the best 5 or 30 poses retained after docking, were analyzed. A comparison with the experimentally observed inhibitory effects was also performed. The InterCriteria analysis application confirms that the performance of the scoring functions for the same dataset of ligands depends on the studied protein. The analysis reveals that none of the studied scoring functions is a good predictor of the compounds’ binding affinities for the considered protein targets. (4) Conclusion: In terms of this analysis, the investigated scoring functions do not produce equivalent results, which suggests the necessity for their combined use in consensus docking studies.

Intuitionistic fuzzy logic is the main tool in the recently developed step-wise “cross-evaluation” procedure that aims at the assessment of different optimization algorithms. In this investigation, the procedure previously applied to compare the effectiveness of two or three algorithms has been significantly upgraded to evaluate the performance of a set of four algorithms. For the first time, the procedure applied here has been tested in the evaluation of the effectiveness of genetic algorithms (GAs), which are proven as very promising and successful optimization techniques for solving hard non-linear optimization tasks. As a case study exemplified with the parameter identification of a S. cerevisiae fed-batch fermentation process model, the cross-evaluation procedure has been executed to compare four different types of GAs, and more specifically, multi-population genetic algorithms (MGAs), which differ in the order of application of the three genetic operators: Selection, crossover and mutation. The results obtained from the implementation of the upgraded intuitionistic fuzzy logic-based procedure for MGA performance assessment have been analyzed, and the standard MGA has been outlined as the fastest and most reliable one among the four investigated algorithms.

Fermentation processes by nature are complex, time-varying, and highly nonlinear. As dynamic systems their modeling and further high-quality control are a serious challenge. The conventional optimization methods cannot overcome the fermentation processes peculiarities and do not lead to a satisfying solution. As an alternative, genetic algorithms as a stochastic global optimization method can be applied. For the purpose of parameter identification of a fed-batch cultivation of S. cerevisiae altogether four kinds of simple and four kinds of multipopulation genetic algorithms have been considered. Each of them is characterized with a different sequence of implementation of main genetic operators, namely, selection, crossover, and mutation. The influence of the most important genetic algorithm parameters—generation gap, crossover, and mutation rates has—been investigated too. Among the considered genetic algorithm parameters, generation gap influences most significantly the algorithm convergence time, saving up to 40% of time without affecting the model accuracy.