Study on chemical equilibrium in nucleus-nucleus collisions at relativistic energies

We present a detailed study of chemical freeze-out in nucleus-nucleus collisions at beam energies of 11.6, 30, 40, 80 and 158A GeV. By analyzing hadronic multiplicities within the statistical hadronization approach, we have studied the chemical equilibration of the system as a function of center of mass energy and of the parameters of the source. Additionally, we have tested and compared different versions of the statistical model, with special emphasis on possible explanations of the observed strangeness hadronic phase space under-saturation.Comment: 6 pages, 4 figues, proceedings for '20th Winter Workshop on Nuclear Dynamics

On transverse momentum event–by–event fluctuations in string hadronic models

Transverse momentum event-by-event fluctuations are studied within the string-hadronic model of high energy nuclear collisions, LUCIAE. Data on non-statistical pT fluctuations in p+p interactions are reproduced. Fluctuations of similar magnitude are predicted for nucleus-nucleus collisions, in contradiction to the preliminary NA49 results. The introduction of a string clustering mechanism (Firecracker Model) leads to a further, significant increase of pT fluctuations for nucleus-nucleus collisions. Secondary hadronic interactions, as implemented in LUCIAE, cause only a small reduction of pT fluctuations

Chemical equilibrium study in nucleus-nucleus collisions at relativistic energies

We present a detailed study of chemical freeze-out in nucleus-nucleus collisions at beam energies of 11.6, 30, 40, 80 and 158A GeV. By analyzing hadronic multiplicities within the statistical hadronization approach, we have studied the strangeness production as a function of centre of mass energy and of the parameters of the source. We have tested and compared different versions of the statistical model, with special emphasis on possible explanations of the observed strangeness hadronic phase space under-saturation. We show that, in this energy range, the use of hadron yields at midrapidity instead of in full phase space artificially enhances strangeness production and could lead to incorrect conclusions as far as the occurrence of full chemical equilibrium is concerned. In addition to the basic model with an extra strange quark non-equilibrium parameter, we have tested three more schemes: a two-component model superimposing hadrons coming out of single nucleon-nucleon interactions to those emerging from large fireballs at equilibrium, a model with local strangeness neutrality and a model with strange and light quark non-equilibrium parameters. The behaviour of the source parameters as a function of colliding system and collision energy is studied. The description of strangeness production entails a non-monotonic energy dependence of strangeness saturation parameter gamma_S with a maximum around 30A GeV. We also present predictions of the production rates of still unmeasured hadrons including the newly discovered Theta^+(1540) pentaquark baryon

Equilibria of oligomeric proteins under high pressure – A theoretical description

High pressure methods have become a useful tool for studying protein structure and stability. Using them, various physico-chemical processes including protein unfolding, aggregation, oligomer dissociation or enzyme-activity decrease were studied on many different proteins. Oligomeric protein dissociation is a process that can perfectly utilize the potential of high-pressure techniques, as the high pressure shifts the equilibria to higher concentrations making them better observable by spectroscopic methods. This can be especially useful when the oligomeric form is highly stable at atmospheric pressure. These applications may be, however, hindered by less intensive experimental response as well as interference of the oligomerization equilibria with unfolding or aggregation of the subunits, but also by more complex theoretical description. In this study we develop mathematical models describing different kinds of oligomerization equilibria, both closed (equilibrium of monomer and the highest possible oligomer without any intermediates) and consecutive. Closed homooligomer equilibria are discussed for any oligomerization degree, while the more complex heterooligomer equilibria and the consecutive equilibria in both homo- and heterooligomers are taken into account only for dimers and trimers. In all the cases, fractions of all the relevant forms are evaluated as functions of pressure and concentration. Significant points (inflection points and extremes) of the resulting transition curves, that can be determined experimentally, are evaluated as functions of pressure and/or concentration. These functions can be further used in order to evaluate the thermodynamic parameters of the system, i.e. atmospheric-pressure equilibrium constants and volume changes of the individual steps of the oligomer-dissociation processes. © 2016 Elsevier LtdP208-12-G016, GACR, Grant Agency of the Czech RepublicGrant Agency of the Czech Republic [P208-12-G016

Comparison of defect detection limits in Lorentz force eddy current testing and classical eddy current testing

Lorentz force eddy current testing (LET) is a motion-induced eddy current testing method in the framework of nondestructive testing. In this study, we address the question of how this method is classified in comparison with a commercial eddy current testing (ECT) measurement device ELOTEST N300 in combination with the probe PKA48 from Rohmann GmbH. Therefore, measurements using both methods are performed and evaluated. Based on the measurement results, the corresponding defect detection limits, i.e., up to which depth the defect can be detected, are determined and discussed. For that reason, the excitation frequency spectrum of the induced eddy currents in the case of LET is considered

Optimization ACE inhibition activity in hypertension based on random vector functional link and sine-cosine algorithm

Bioactive peptides from protein hydrolysates with antihypertensive properties have a great effect in health, which warrants their pharmaceutical use. Nevertheless, the process of their production may affect their efficacy. In this study, we investigate the inhibitory activities of various hydrolysates on angiotensin-converting enzyme (ACE) in relation to the chemical diversity of corresponding bioactive peptides. This depends on the enzyme specificity and process conditions used for the production of hydrolysates. In order to mitigate the uncontrolled chemical alteration in bioactive peptides, we propose a computational approach using the random vector functional link (RVFL) network based on the sine-cosine algorithm (SCA) to find optimal processing parameters, and to predict the ACE inhibition activity. The SCA is used to determine the optimal configuration of RVFL, improving the prediction performance. The experimental results show that the performance measures of the proposed model are better than the state-of-the-art methods

Applications of Boolean modeling to study the dynamics of a complex disease and therapeutics responses.

peer reviewedComputational modeling has emerged as a critical tool in investigating the complex molecular processes involved in biological systems and diseases. In this study, we apply Boolean modeling to uncover the molecular mechanisms underlying Parkinson's disease (PD), one of the most prevalent neurodegenerative disorders. Our approach is based on the PD-map, a comprehensive molecular interaction diagram that captures the key mechanisms involved in the initiation and progression of PD. Using Boolean modeling, we aim to gain a deeper understanding of the disease dynamics, identify potential drug targets, and simulate the response to treatments. Our analysis demonstrates the effectiveness of this approach in uncovering the intricacies of PD. Our results confirm existing knowledge about the disease and provide valuable insights into the underlying mechanisms, ultimately suggesting potential targets for therapeutic intervention. Moreover, our approach allows us to parametrize the models based on omics data for further disease stratification. Our study highlights the value of computational modeling in advancing our understanding of complex biological systems and diseases, emphasizing the importance of continued research in this field. Furthermore, our findings have potential implications for the development of novel therapies for PD, which is a pressing public health concern. Overall, this study represents a significant step forward in the application of computational modeling to the investigation of neurodegenerative diseases, and underscores the power of interdisciplinary approaches in tackling challenging biomedical problems

Enhancement of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) accumulation in Arxula adeninivorans by stabilization of production

Background: In recent years the production of biobased biodegradable plastics has been of interest of researchers partly due to the accumulation of non-biodegradable plastics in the environment and to the opportunity for new applications. Commonly investigated are the polyhydroxyalkanoates (PHAs) poly(hydroxybutyrate) and poly(hydroxybutyrate-co-hydroxyvalerate) (PHB-V). The latter has the advantage of being tougher and less brittle. The production of these polymers in bacteria is well established but production in yeast may have some advantages, e.g. the ability to use a broad spectrum of industrial by-products as a carbon sources. Results: In this study we increased the synthesis of PHB-V in the non-conventional yeast Arxula adeninivorans by stabilization of polymer accumulation via genetic modification and optimization of culture conditions. An A. adeninivorans strain with overexpressed PHA pathway genes for β-ketothiolase, acetoacetyl-CoA reductase, PHAs synthase and the phasin gene was able to accumulate an unexpectedly high level of polymer. It was found that an optimized strain cultivated in a shaking incubator is able to produce up to 52.1% of the DCW of PHB-V (10.8gL-1) with 12.3%mol of PHV fraction. Although further optimization of cultivation conditions in a fed-batch bioreactor led to lower polymer content (15.3% of the DCW of PHB-V), the PHV fraction and total polymer level increased to 23.1%mol and 11.6gL-1 respectively. Additionally, analysis of the product revealed that the polymer has a very low average molecular mass and unexpected melting and glass transition temperatures. Conclusions: This study indicates a potential of use for the non-conventional yeast, A. adeninivorans, as an efficient producer of polyhydroxyalkanoates

MolArt: a molecular structure annotation and visualization tool

Summary MolArt fills the gap between sequence and structure visualization by providing a light-weight, interactive environment enabling exploration of sequence annotations in the context of available experimental or predicted protein structures. Provided a UniProt ID, MolArt downloads and displays sequence annotations, sequence-structure mapping and relevant structures. The sequence and structure views are interlinked, enabling sequence annotations being color overlaid over the mapped structures, thus providing an enhanced understanding and interpretation of the available molecular data. Availability and implementation MolArt is released under the Apache 2 license and is available at https://github.com/davidhoksza/MolArt. The project web page https://davidhoksza.github.io/MolArt/ features examples and applications of the tool

Exploration and comparison of molecular mechanisms across diseases using MINERVA Net.

peer reviewedProtein function is often interpreted using molecular interaction diagrams, encoding roles a given protein plays in various molecular mechanisms. Information about disease-related mechanisms can be inferred from disease maps, knowledge repositories containing manually constructed systems biology diagrams. Disease maps hosted on the Molecular Interaction Network VisuAlization (MINERVA) Platform are individually accessible through a REST API interface of each instance, making it challenging to systematically explore their contents. To address this challenge, we introduce the MINERVA Net web service, a repository of open-access disease maps allowing users to publicly share minimal information about their maps. The MINERVA Net repository provides REST API endpoints of particular disease maps, which then can be individually queried for content. In this article, we describe the concept of MINERVA Net and illustrate its use by comparing proteins and their interactions in three different disease maps