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Synchronization is a phenomenon observed in neuronal networks involved in diverse brain activities. Neural mass models such as Wilson-Cowan (WC) and Jansen-Rit (JR) manifest synchronized states. Despite extensive research on these models over the past several decades, their potential of manifesting second-order phase transitions (SOPT) and criticality has not been sufficiently acknowledged. In this study, two networks of coupled WC and JR nodes with small-world topologies were constructed and Kuramoto order parameter (KOP) was used to quantify the amount of synchronization. In addition, we investigated the presence of SOPT using the synchronization coefficient of variation. Both networks reached high synchrony by changing the coupling weight between their nodes. Moreover, they exhibited abrupt changes in the synchronization at certain values of the control parameter not necessarily related to a phase transition. While SOPT was observed only in JR model, neither WC nor JR model showed power-law behavior. Our study further investigated the global synchronization phenomenon that is known to exist in pathological brain states, such as seizure. JR model showed global synchronization, while WC model seemed to be more suitable in producing partially synchronized patterns. [ABSTRACT FROM AUTHOR]

The rapid spread and evolving nature of COVID-19 variants have raised concerns regarding their competitive dynamics and coinfection scenarios. In this study, we assess the competitive interactions between the Omicron variant and other prominent variants (Alpha, Beta and Delta) on a social network, considering both single infection and coinfection states. Using the SIRS model, we simulate the progression of these variants and analyze their impact on infection rates, mortality and overall disease burden. Our findings demonstrate that the Alpha and Beta strains exhibit comparable contagion levels, with the Alpha strain displaying higher infection and mortality rates. Moreover, the Delta strain emerges as the most prevalent and virulent strain, surpassing the other variants. When introduced alongside the less virulent Omicron strain, the Delta strain results in higher infection and mortality rates. However, the Omicron strain's dominance leads to an overall increase in disease statistics. Remarkably, our study highlights the efficacy of the Omicron variant in supplanting more virulent strains and its potential role in mitigating the spread of infectious diseases. The Omicron strain demonstrates a competitive advantage over the other variants, suggesting its potential to reduce the severity of the disease and alleviate the burden on healthcare systems. These findings underscore the importance of monitoring and understanding the dynamics of COVID-19 variants, as they can inform effective prevention and mitigation strategies, particularly with the emergence of variants that possess a relative advantage in controlling disease transmission. [ABSTRACT FROM AUTHOR]

In visual arts, painting is deeply reliant on the colour combination for its impact, depth and emotion. Recently, many studies have focused on image processing, regarding identification and classification of images, using some colour features such as saturation, hue, luminance and so forth. This study aims to delve into some of the painting styles from the perspective of graph theory and network science. We compared a number of famous paintings to find out the likely pattern that an artist uses for colour combination and juxtaposition. To achieve this aim, the digital image of a painting is converted to a graph where each vertex represents one of the painting's colours. In this graph, two vertices would be adjacent if and only if the two relative colours could be found in at least two adjacent pixels in the digital image. Among the several tools for network analysis, clustering, node centrality and degree distribution are used. Outcomes showed that artists unconsciously are following subtle mathematical rules to reach harmony and coordination in their work. [ABSTRACT FROM AUTHOR]

Abstract: CaV channels are transmembrane proteins that mediate and regulate ion fluxes across cell membranes, and they are activated in response to action potentials to allow Ca2+ influx. Since ion channels are composed of charge or polar groups, an external alternating electric field may affect the ion‐selective membrane transport and the performance of the channel. In this article, we have investigated the effect of an external GHz electric field on the dynamics of calcium ions in the selectivity filter of the CaVAb channel. Molecular dynamics (MD) simulations and the potential of mean force (PMF) calculations were carried out, via the umbrella sampling method, to determine the free energy profile of Ca2+ ions in the CaVAb channels in presence and absence of an external field. Exposing CaVAb channel to 1, 2, 3, 4, and 5 GHz electric fields increases the depth of the potential energy well and this may result in an increase in the affinity and strength of Ca2+ ions to binding sites in the selectivity filter the channel. This increase of strength of Ca2+ ions binding in the selectivity filter may interrupt the mechanism of Ca2+ ion conduction, and leads to a reduction of Ca2+ ion permeation through the CaVAb channel. [ABSTRACT FROM AUTHOR]

Dopamine as a neurotransmitter plays a critical role in the functioning of the central nervous system. The structure of D3 receptor as a member of class A G-protein coupled receptors (GPCRs) has been reported. We used MD simulation to investigate the effect of an oscillating electric field, with frequencies in the range 0.6–800 GHz applied along the z-direction, on the dopamine-D3R complex. The simulations showed that at some frequencies, the application of an external oscillating electric field along the z-direction has a considerable effect on the dopamine-D3R. However, there is no enough evidence for prediction of changes in specific frequency, implying that there is no order in changes. Computing the correlation coefficient parameter showed that increasing the field frequency can weaken the interaction between dopamine and D3R and may decrease the Arg128{3.50}-Glu324{6.30} distance. Because of high stability of α helices along the z-direction, applying an oscillating electric field in this direction with an amplitude 10-time higher did not have a considerable effect. However, applying the oscillating field at the frequency of 0.6 GHz along other directions, such as X-Y and Y-Z planes, could change the energy between the dopamine and the D3R, and the number of internal hydrogen bonds of the protein. This can be due to the effect of the direction of the electric field vis-à-vis the ligands orientation and the interaction of the oscillating electric field with the dipole moment of the protein. [ABSTRACT FROM AUTHOR]

The hydrophobic mismatch between the lipid bilayer and integral membrane proteins has well-defined effect on mechanosensitive (MS) ion channels. Also, membrane local bending is suggested to modulate MS channel activity. Although a number of studies have already shown the significance of each individual factor, the combined effect of these physical factors on MS channel activity have not been investigated. Here using finite element simulation, we study the combined effect of hydrophobic mismatch and local bending on the archetypal mechanosensitive channel MscL. First we show how the local curvature direction impacts on MS channel modulation. In the case of MscL, we show inward (cytoplasmic) bending can more effectively gate the channel compared to outward bending. Then we indicate that in response to a specific local curvature, MscL inserted in a bilayer with the same hydrophobic length is more expanded in the constriction pore region compared to when there is a protein-lipid hydrophobic mismatch. Interestingly in the presence of a negative mismatch (thicker lipids), MscL constriction pore is more expanded than in the presence of positive mismatch (thinner lipids) in response to an identical membrane curvature. These results were confirmed by a parametric energetic calculation provided for MscL gating. These findings have several biophysical consequences for understanding the function of MS channels in response to two major physical stimuli in mechanobiology, namely hydrophobic mismatch and local membrane curvature. [ABSTRACT FROM AUTHOR]

Mechanosensitive (MS) channels are ubiquitous molecular force sensors that respond to a number of different mechanical stimuli including tensile, compressive and shear stress. MS channels are also proposed to be molecular curvature sensors gating in response to bending in their local environment. One of the main mechanisms to functionally study these channels is the patch clamp technique. However, the patch of membrane surveyed using this methodology is far from physiological. Here we use continuum mechanics to probe the question of how curvature, in a standard patch clamp experiment, at different length scales (global and local) affects a model MS channel. Firstly, to increase the accuracy of the Laplace's equation in tension estimation in a patch membrane and to be able to more precisely describe the transient phenomena happening during patch clamping, we propose a modified Laplace's equation. Most importantly, we unambiguously show that the global curvature of a patch, which is visible under the microscope during patch clamp experiments, is of negligible energetic consequence for activation of an MS channel in a model membrane. However, the local curvature (RL < 50) and the direction of bending are able to cause considerable changes in the stress distribution through the thickness of the membrane. Not only does local bending, in the order of physiologically relevant curvatures, cause a substantial change in the pressure profile but it also significantly modifies the stress distribution in response to force application. Understanding these stress variations in regions of high local bending is essential for a complete understanding of the effects of curvature on MS channels. [ABSTRACT FROM AUTHOR]

Protein complexes are aggregates of protein molecules that play important roles in biological processes. Detecting protein complexes from protein-protein interaction (PPI) networks is one of the most challenging problems in computational biology, and many computational methods have been developed to solve this problem. Generally, these methods yield high false positive rates. In this article, a semantic similarity measure between proteins, based on Gene Ontology (GO) structure, is applied to weigh PPI networks. Consequently, one of the well-known methods, COACH, has been improved to be compatible with weighted PPI networks for protein complex detection. The new method, WCOACH, is compared to the COACH, ClusterOne, IPCA, CORE, OH-PIN, HC-PIN and MCODE methods on several PPI networks such as DIP, Krogan, Gavin 2002 and MIPS. WCOACH can be applied as a fast and high-performance algorithm to predict protein complexes in weighted PPI networks. All data and programs are freely available at http://bioinformatics. aut.ac.ir/wcoach. [ABSTRACT FROM AUTHOR]

Diffusion plays a key role in many biochemical reaction systems seen in nature. Scenarios where diffusion behavior is critical can be seen in the cell and subcellular compartments where molecular crowding limits the interaction between particles. We investigate the application of a computational method for modeling the diffusion of molecules and macromolecules in three-dimensional solutions using agent based modeling. This method allows for realistic modeling of a system of particles with different properties such as size, diffusion coefficients, and affinity as well as the environment properties such as viscosity and geometry. Simulations using these movement probabilities yield behavior that mimics natural diffusion. Using this modeling framework, we simulate the effects of molecular crowding on effective diffusion and have validated the results of our model using Langevin dynamics simulations and note that they are in good agreement with previous experimental data. Furthermore, we investigate an extension of this framework where single discrete cells can contain multiple particles of varying size in an effort to highlight errors that can arise from discretization that lead to the unnatural behavior of particles undergoing diffusion. Subsequently, we explore various algorithms that differ in how they handle the movement of multiple particles per cell and suggest an algorithm that properly accommodates multiple particles of various sizes per cell that can replicate the natural behavior of these particles diffusing. Finally, we use the present modeling framework to investigate the effect of structural geometry on the directionality of diffusion in the cell cytoskeleton with the observation that parallel orientation in the structural geometry of actin filaments of filopodia and the branched structure of lamellipodia can give directionality to diffusion at the filopodia-lamellipodia interface. [ABSTRACT FROM AUTHOR]

The nuclear pore complex (NPC) regulates molecular traffic across the nuclear envelope (NE). Selective transport happens on the order of milliseconds and the length scale of tens of nanometers; however, the transport mechanism remains elusive. Central to the transport process is the hydrophobic interactions between karyopherins (kaps) and Phe-Gly (FG) repeat domains. Taking into account the polymeric nature of FG-repeats grafted on the elastic structure of the NPC, and the kap-FG hydrophobic affinity, we have established a coarse-grained model of the NPC structure that mimics nucleocytoplasmic transport. To establish a foundation for future works, the methodology and biophysical rationale behind the model is explained in details. The model predicts that the first-passage time of a 15 nm cargo-complex is about 2.6±0.13 ms with an inverse Gaussian distribution for statistically adequate number of independent Brownian dynamics simulations. Moreover, the cargo-complex is primarily attached to the channel wall where it interacts with the FG-layer as it passes through the central channel. The kap-FG hydrophobic interaction is highly dynamic and fast, which ensures an efficient translocation through the NPC. Further, almost all eight hydrophobic binding spots on kap-β are occupied simultaneously during transport. Finally, as opposed to intact NPCs, cytoplasmic filaments-deficient NPCs show a high degree of permeability to inert cargos, implying the defining role of cytoplasmic filaments in the selectivity barrier. [ABSTRACT FROM AUTHOR]

Understanding the biomechanical properties and the effect of biomechanical force on epithelial cells is key to understanding how epithelial cells form uniquely shaped structures in two or three-dimensional space. Nevertheless, with the limitations and challenges posed by biological experiments at this scale, it becomes advantageous to use mathematical and 'in silico' (computational) models as an alternate solution. This paper introduces a single-cell-based model representing the cross section of a typical tissue. Each cell in this model is an individual unit containing several sub-cellular elements, such as the elastic plasma membrane, enclosed viscoelastic elements that play the role of cytoskeleton, and the viscoelastic elements of the cell nucleus. The cell membrane is divided into segments where each segment (or point) incorporates the cell's interaction and communication with other cells and its environment. The model is capable of simulating how cells cooperate and contribute to the overall structure and function of a particular tissue; it mimics many aspects of cellular behavior such as cell growth, division, apoptosis and polarization. The model allows for investigation of the biomechanical properties of cells, cell-cell interactions, effect of environment on cellular clusters, and how individual cells work together and contribute to the structure and function of a particular tissue. To evaluate the current approach in modeling different topologies of growing tissues in distinct biochemical conditions of the surrounding media, we model several key cellular phenomena, namely monolayer cell culture, effects of adhesion intensity, growth of epithelial cell through interaction with extra-cellular matrix (ECM), effects of a gap in the ECM, tensegrity and tissue morphogenesis and formation of hollow epithelial acini. The proposed computational model enables one to isolate the effects of biomechanical properties of individual cells and the communication between cells and their microenvironment while simultaneously allowing for the formation of clusters or sheets of cells that act together as one complex tissue. [ABSTRACT FROM AUTHOR]

Abstract The magnetic properties of tetragonal structure of stoichiometric NiMn alloy is investigated using density functional theory within the local spin density approximation. The system studied here, is a free standing film. The effect of thickness and epitaxial strain on the magnetic and structural properties is examined. It is found that while the magnetic moments of Mn surface atoms vary depending on the number of layers being odd (3.60 μ B) or even (3.55 μ B) the magnitude of the magnetic moment for surface Ni atoms is constant (0.11 μ B). By applying epitaxial strain on the slabs, it was observed, for the first time, that the magnetic phase of NiMn films changes from "A-type-like" ferrimagnetic for compressive strains to "G-type-like" ferrimagnetic for tensile strains. Highlights • Effect of thickness and epitaxial strain on the magnetic structure of NiMn films are investigated. • Surface buckling phenomenon for different thicknesses is studied. • A magnetic phase transition from A-type-like ferrimagnetic to G-type-like ferrimagnetic was observed by applying epitaxial strain. [ABSTRACT FROM AUTHOR]

The martensitic phase transformation in stoichiometric NiMn alloy and its shape memory effect is investigated using first principles method based on Density Functional Theory (DFT). The elastic properties of the B2 austenite and the L1 0 martensite phases were compared and the results indicated that the B2 phase has a low elastic shear modulus along the [110] direction giving rise to the formation of L1 0. Electronic density of states (DOS) calculations showed that the existence of the pseudo-gap appearing at the Fermi level which stabilizes the martensite phase against the austenite depends on both magnetism and the tetragonality ratio. Using geometrically nonlinear theory of martensite it was found that large volume change and twinning shear, and the low value of middle eigenvalue of the transformation stretch tensor (λ 2 = 0.8766) are some of the properties of the martensitic transformation in NiMn which inhibit the shape memory effect in this system despite being structurally similar to other shape memory alloys such as NiAl. The effect of the addition of 8 alloying elements on the martensitic transformation and shape memory effect is investigated. The results showed, in agreement with the experimental findings, that addition of Ti and Al can improve the shape memory effect. Also, it was found that among the 8 elements considered here, Al, Ti, and Ge are the most effective alloying elements in enhancing the shape memory properties of NiMn by lowering the transformation temperature, decreasing the volume change, and increasing the value of λ 2.. • The dependence of the pseudogap on both magnetic structure and tetragonality was examined. • Large variation of the lattice parameters with temperature hinders the complete shape memory effect. • The effect of ternary alloying elements on the martensitic transformation is studied. [ABSTRACT FROM AUTHOR]

Since brain structural connectivity is the foundation of its functionality, in order to understand brain abilities, studying the relation between structural and functional connectivity is essential. Several approaches have been applied to measure the role of the structural connectivity in the emergent correlation/synchronization patterns. In this study, we investigates the cross-correlation and synchronization sensitivity to coupling strength between neural regions for different topological networks. We model the neural populations by a neural mass model that express an oscillatory dynamic. The results highlight that coupling between neural ensembles leads to various cross-correlation patterns and local synchrony even on an ordered network. Moreover, as the network departs from an ordered organization to a small-world architecture, correlation patterns, and synchronization dynamics change. Interestingly, at a certain range of the synaptic strength, by fixing the structural conditions, different organized patterns are seen at the different input signals. This variety switches to a bifurcation region by increasing the synaptic strength. We show that topological variations is a major factor of synchronization behavior and lead to alterations in correlated local clusters. We found the coupling strength (between cortical areas) to be especially important at conversions of correlation and synchronization states. Since correlation patterns generate functional connections and transitions of functional connectivity have been related to cognitive operations, these diverse correlation patterns may be considered as different dynamical states corresponding to various cognitive tasks.

Viscoelasticity and other related phenomena are of great importance in the study of mechanical properties of materials, especially biological materials. Certain materials demonstrate some complicated behavior under mechanical tests that cannot be described by a standard linear equation (SLE), mostly due to the shape memory effect during the deformation phase. Recently, researchers have been making use of fractional calculus (FC) in order to probe viscoelasticity of such materials accurately. FC is a powerful tool for modeling complicated phenomena. In this tutorial paper, it is sought to provide clear descriptions of this powerful tool and its techniques and implementation. It is endeavored to keep the details to a minimum while still conveying a good idea of what and how can be done with this powerful tool. The reader will be provided with the basic techniques that are used to solve the fractional equations analytically and/or numerically. More specifically, simulating the shape memory phenomena with this powerful tool will be studied from different perspectives, and some physical interpretations are made in this regard. This paper is also a review of fractional order models of viscoelastic phenomena that are widespread in bioengineering. Thus, in order to show the relationship between fractional models and SLEs, a new fractal system comprising spring and damper elements is considered and the constitutive equation is approximated with a fractional element. Finally, after a brief literature review, two fractional models are utilized to investigate the viscoelasticity of the cell and a comparison is made between the findings and the experimental data from the previous models. Verification results indicate that the fractional model not only matches well with the experimental data but also can be a good substitute for previously used models.

Ca V channels are transmembrane proteins that mediate and regulate ion fluxes across cell membranes, and they are activated in response to action potentials to allow Ca 2+ influx. Since ion channels are composed of charge or polar groups, an external alternating electric field may affect the ion-selective membrane transport and the performance of the channel. In this article, we have investigated the effect of an external GHz electric field on the dynamics of calcium ions in the selectivity filter of the Ca V Ab channel. Molecular dynamics (MD) simulations and the potential of mean force (PMF) calculations were carried out, via the umbrella sampling method, to determine the free energy profile of Ca 2+ ions in the Ca V Ab channels in presence and absence of an external field. Exposing Ca V Ab channel to 1, 2, 3, 4, and 5 GHz electric fields increases the depth of the potential energy well and this may result in an increase in the affinity and strength of Ca 2+ ions to binding sites in the selectivity filter the channel. This increase of strength of Ca 2+ ions binding in the selectivity filter may interrupt the mechanism of Ca 2+ ion conduction, and leads to a reduction of Ca 2+ ion permeation through the Ca V Ab channel., (© 2018 Wiley Periodicals, Inc.)

Activation of voltage-gated calcium channels by action potentials leads to the influx of Ca 2+ ions. In this study, the ion permeation characteristics in bacterial voltage-gated calcium (Ca V Ab) channels were investigated using molecular dynamics simulations. Furthermore, the potential of mean force (PMF) calculations was evaluated to determine the free energy profile for the permeation of cations (Ca 2+ and Na + ) and anions (Cl - ) in the Ca V Ab channel. The results showed that both Ca 2+ and Na + cations experienced a deep energy well, while the Cl - anion experienced a relatively high energy barrier at the center of the selectivity filter (site 2). Consistent with the experimental data, the results obtained from this study demonstrate that sites 2 and 3 displayed the highest and lowest affinities to Ca 2+ , respectively. These findings also indicate that Na + can easily and quickly pass through the Ca V Ab channel in the absence of Ca 2+ , while Cl - ions lack this ability.

"J-STAGE Advance published date: 15 January 2015" on p. 317 should be changed to "J-STAGE Advance published date: 15 January 2016".