European Biophysics Journal最新文献

Atherosclerosis is one of the important diseases of the circulatory system because atherosclerotic plaques cause significant disruption of blood flow. Therefore, it is very important to properly understand these processes and skillfully simulate blood flow. In our work, we consider blood flow through an abdominal aorta with iliac arteries, assuming that the right iliac artery is narrowed by an atherosclerotic lesion. Blood flow is simulated using the laminar, standard $k-\omega$ and standard $k-ϵ$ models. The obtained results show that despite the use of identical initial conditions, the distribution of velocity flow and wall shear stress depends on the choice of flow simulation model. For the $k-ϵ$ model, we obtain higher values of speed and wall shear stress on atherosclerotic plaque than in the other two models. The laminar and $k-\omega$ models predict larger areas where reverse blood flow occurs in the area behind the atherosclerotic lesion. This effect is associated with negative wall shear stress. These two models give very similar results. The results obtained by us, and those reported in the literature, indicate that $k-\omega$ model is the most suitable for blood flow analysis.

This communication summarizes findings from the earliest encounters with extreme enthalpy‒entropy compensation, a phenomenon first detected in the 1950s by a reappraisal of isopiestic and calorimetric measurements on aqueous urea solutions in terms of solute self-association. Because concurrent studies of carboxylic acid association were confined to measurement of the equilibrium constant by conductance, IR spectrophotometry or potentiometric titration measurements, temperature-independence of the dimerization constant was mistakenly taken to signify a value of zero for Δ $H^o$ instead of (Δ $H^o$  ‒ TΔ $S^o$ ). In those studies of small-solute self-association the extreme enthalpy‒entropy compensation was reflecting the action of water as a reactant whose hydroxyl groups were competing for the solute carbonyl involved in self-association. Such action gives rise to a positive temperature dependence of Δ $H^o$ that could well be operating in concert with that responsible for the commonly observed negative dependence for protein‒ligand interactions exhibiting extreme enthalpy‒entropy compensation, where the solvent contribution to the energetics reflects changes in the extent of ordered water structure in hydrophobic environments.

This study aimed to calculate the effect of nanopatterns' peak sharpness, width, and spacing parameters on P. aeruginosa and S. aureus cell walls by artificial neural network and finite element analysis. Elastic and creep deformation models of bacteria were developed in silico. Maximum deformation, maximum stress, and maximum strain values of the cell walls were calculated. According to the results, while the spacing of the nanopatterns is constant, it was determined that when their peaks were sharpened and their width decreased, maximum deformation, maximum stress, and maximum strain affecting the cell walls of both bacteria increased. When sharpness and width of the nano-patterns are kept constant and the spacing is increased, maximum deformation, maximum stress, and maximum strain in P. aeruginosa cell walls increase, but a decrease in S. aureus was observed. This study proves that changes in the geometric structures of nanopatterned surfaces can show different effects on different bacteria.

Antifreeze proteins (AFPs) have unique features to sustain life in sub-zero environments due to ice recrystallization inhibition (IRI) and thermal hysteresis (TH). AFPs are in demand as agents in cryopreservation, but some antifreeze proteins have low levels of activity. This research aims to improve the cryopreservation activity of an AFPIV. In this in silico study, the helical peptide afp1m from an Antarctic yeast AFP was modeled into a sculpin AFPIV, to replace each of its four α-helices in turn, using various computational tools. Additionally, a new linker between the first two helices of AFPIV was designed, based on a flounder AFPI, to boost the ice interaction activity of the mutants. Bioinformatics tools such as ExPASy Prot-Param, Pep-Wheel, SOPMA, GOR IV, Swiss-Model, Phyre2, MODFOLD, MolPropity, and ProQ were used to validate and analyze the structural and functional properties of the model proteins. Furthermore, to evaluate the AFP/ice interaction, molecular dynamics (MD) simulations were executed for 20, 100, and 500 ns at various temperatures using GROMACS software. The primary, secondary, and 3D modeling analysis showed the best model for a redesigned antifreeze protein (AFP1mb, with afp1m in place of the fourth AFPIV helix) with a QMEAN (Swiss-Model) Z score value of 0.36, a confidence of 99.5%, a coverage score of 22%, and a p value of 0.01. The results of the MD simulations illustrated that AFP1mb had more rigidity and better ice interactions as a potential cryoprotectant than the other models; it also displayed enhanced activity in limiting ice growth at different temperatures.

Lignin, one of the most abundant biopolymers on Earth, is of great research interest due to its industrial applications including biofuel production and materials science. The structural composition of lignin plays an important role in shaping its properties and functionalities. Notably, lignin exhibits substantial compositional diversity, which varies not only between different plant species but even within the same plant. Currently, it is unclear to what extent this compositional diversity plays on the overall structure and dynamics of lignin. To address this question, this paper reports on the development of two models of lignin containing all guaiacyl (G) subunits with varied linkage sequences and makes use of all-atom molecular dynamics simulations to examine the impact of linkage sequence alone on the lignin’s structure and dynamics. This work demonstrates that the structure of the lignin polymer depends on its linkage sequence at temperatures above and below the glass transition temperature ((T_textrm{g})), but the polymers exhibit similar structural properties as it is approaching the viscous flow state (480 K). At low temperatures, both of lignin models have a local dynamics confined in a cage, but the size of cages varies depending on structural differences. Interestingly, at temperatures higher than (T_textrm{g}), the different linkage sequence leads to the subtle dynamical difference which diminishes at 480 K.

The maintenance of homeostasis and the retention of ordered epithelial cell self-organization are essential for morphogenesis, wound healing, and the spread of cancer across the epithelium. However, cell–cell interactions in an overcrowded environment introduce a diversity of complications. Such interactions arise from an interplay between the cell compressive and shear stress components that accompany increased cell packing density. They can lead to various kinds of cell rearrangement such as: the epithelial-to-mesenchymal cell state transition; live cell extrusion; and cell jamming. All of these scenarios of cell rearrangement under mechanical stress relate to changes in the strengths of the cell–cell and cell–matrix adhesion contacts. The objective of this review study is twofold: first, to provide a comprehensive summary of the biological and physical factors influencing the effects of cell mechanical stress on cell–cell interactions, and the consequences of these interactions for the status of cell–cell and cell–matrix adhesion contacts; and secondly, to offer a bio-physical/mathematical analysis of the aforementioned biological aspects. By presenting these two approaches in conjunction, we seek to highlight the intricate nature of biological systems, which manifests in the form of complex bio-physical/mathematical equations. Furthermore, the juxtaposition of these apparently disparate approaches underscores the importance of conducting experiments to determine the multitude of parameters that contribute to the development of these intricate bio-physical/mathematical models.