Journal of Biological Physics最新文献

Excessive neural synchronization of neural populations in the beta (β) frequency range (12–35 Hz) is intimately related to the symptoms of hypokinesia in Parkinson’s disease (PD). Studies have shown that delayed feedback stimulation strategies can interrupt excessive neural synchronization and effectively alleviate symptoms associated with PD dyskinesia. Work on optimizing delayed feedback algorithms continues to progress, yet it remains challenging to further improve the inhibitory effect with reduced energy expenditure. Therefore, we first established a neural mass model of the cortex-basal ganglia-thalamus-pedunculopontine nucleus (CBGTh-PPN) closed-loop system, which can reflect the internal properties of cortical and basal ganglia neurons and their intrinsic connections with thalamic and pedunculopontine nucleus neurons. Second, the inhibitory effects of three delayed feedback schemes based on the external globus pallidum (GPe) on β oscillations were investigated separately and compared with those based on the subthalamic nucleus (STN) only. Our results show that all four delayed feedback schemes achieve effective suppression of pathological β oscillations when using the linear delayed feedback algorithm. The comparison revealed that the three GPe-based delayed feedback stimulation strategies were able to have a greater range of oscillation suppression with reduced energy consumption, thus improving control performance effectively, suggesting that they may be more effective for the relief of Parkinson’s motor symptoms in practical applications.

An analytical model is presented for light scattering associated with heat transport near a cell membrane that divides a complex system into two topologically distinct half-spaces. Our analysis is motivated by experiments on vibrational photothermal microscopy which have not only demonstrated remarkably high contrast and resolution, but also are capable of providing label-free local information of heat transport in complex morphologies. In the first Born approximation, the derived Green’s function leads to the reconstruction of a full 3D image with photothermal contrast obtained using both amplitude and phase detection of periodic excitations. We show that important fundamental parameters including the Kapitza length and Kapitza resistance can be derived from experiments. Our goal is to spur additional experimental studies with high-frequency modulation and heterodyne detection in order to make contact with recent theoretical molecular dynamics calculations of thermal transport properties in membrane systems.

Cell fate decisions and transitions are common in almost all developmental processes. Therefore, it is important to identify the decision-making mechanisms and important individual molecules behind the fate decision processes. In this paper, we propose an interpretable strategy based on systematic perturbation, unsupervised hierarchical cluster analysis (HCA), machine learning (ML), and Shapley additive explanation (SHAP) analysis for inferring the contribution and importance of individual molecules in cell fate decision and transition processes. In order to verify feasibility of the approach, we apply it to the core epithelial to mesenchymal transition (EMT)-metastasis network. The key factors identified in EMT-metastasis are consistent with relevant experimental observations. The approach presented here can be applied to other biological networks to identify important factors related to cell fate decisions and transitions.

Calcium (Ca({}^{2+})) signals have a crucial role in regulating various processes of almost every cell to maintain its structure and function. Calcium dynamics has been studied in various cells including hepatocytes by many researchers, but the mechanisms of calcium signals involved in regulation and dysregulation of various processes like ATP degradation rate, IP(_{3}) and NADH production rate respectively in normal and obese cells are still poorly understood. In this paper, a reaction diffusion equation of calcium is employed to propose a model of calcium dynamics by coupling ATP degradation rate, IP(_{3}) and NADH production rate in hepatocyte cells under normal and obese conditions. The processes like source influx, buffer, endoplasmic reticulum (ER), mitochondrial calcium uniporters (MCU) and Na(^{+})/Ca(^{2+}) exchanger (NCX) have been incorporated in the model. Linear finite element method is used along spatial dimension, and Crank-Nicolson method is used along temporal dimension for numerical simulation. The results have been obtained for the normal hepatocyte cells and for cells due to obesity. The comparative study of these results reveal significant difference caused due to obesity in Ca(^{2+}) dynamics as well as in ATP degradation rate, IP(_{3}) and NADH production rate.

In this study, scanning electron microscopy (SEM) was used to study the cell structure of SARS-CoV-2 infected cells. Our measurements revealed infection remodeling caused by infection, including the emergence of new specialized areas where viral morphogenesis occurs at the cell membrane. Intercellular extensions for viral cell surfing have also been observed. Our results expand knowledge of SARS-CoV-2 interactions with cells, its spread from cell to cell, and their size distribution. Our findings suggest that SEM is a useful microscopic method for intracellular ultrastructure analysis of cells exhibiting specific surface modifications that could also be applied to studying other important biological processes.

We have analysed the synchronisation scenario and the rich spatiotemporal patterns in the network of Hindmarsh-Rose neurons under the influence of self, mixed and cross coupling of state variables which are realised by varying coupling phase. We have introduced a coupling matrix in the model to vary coupling phase. The excitatory and inhibitory couplings in the membrane potential induce in-phase and anti-phase bursting dynamics, respectively, in the two coupled system. When the off-diagonal elements of the matrix are zero, the system shows self coupling of the three variables, which helps to attain synchrony. The off-diagonal elements give cross interactions between the variables, which reduces synchrony. The stability of the synchrony attained is analysed using Lyapunov function approach. In our study, we found that self coupling in three variables is sufficient to induce chimera states in non-local coupling. The strength of incoherence and discontinuity measure validates the existence of chimera and multichimera states. The inhibitor self coupling in local interaction induces interesting patterns like Mixed Oscillatory State and clusters. The results may help in understanding the spatiotemporal communications of the brain, within the limitations of the size of the network analysed in this study.

We present an analysis of an epidemic spreading process on an Apollonian network that can describe an epidemic spreading in a non-sedentary population. We studied the modified diffusive epidemic process using the Monte Carlo method by computational analysis. Our model may be helpful for modeling systems closer to reality consisting of two classes of individuals: susceptible (A) and infected (B). The individuals can diffuse in a network according to constant diffusion rates (D_{A}) and (D_{B}), for the classes A and B, respectively, and obeying three diffusive regimes, i.e., (D_{A}<D_{B}), (D_{A}=D_{B}), and (D_{A}>D_{B}). Into the same site i, the reaction occurs according to the dynamical rule based on Gillespie’s algorithm. Finite-size scaling analysis has shown that our model exhibits continuous phase transition to an absorbing state with a set of critical exponents given by (beta /nu =0.66(1)), (1/nu =0.46(2)), and (gamma '/nu =-0.24(2)) familiar to every investigated regime. In summary, the continuous phase transition, characterized by this set of critical exponents, does not have the same exponents of the mean-field universality class in both regular lattices and complex networks.

Copper (Cu), one of the heavy metals, plays a vital role in many complex biochemical reactions as a trace element. However, it often becomes toxic when its concentration in the cell exceeds a certain level. Homeostasis of metals in the cell is primarily related to regulating metal transport into and out of the cell. Therefore, it is thought that porin proteins, which have a role in membrane permeability, may also play a role in developing Cu resistance. This study identified the differences between the molecular profiles of wild-type Escherichia coli W3110 and its seven different porin mutants exposed to Cu ions using attenuated total reflectance (ATR)–Fourier transform infrared (FTIR) spectroscopy. The results showed that the absence of porin genes elicits global changes in the structure and composition of membrane lipids and proteins, in both the absence and presence of Cu. The lack of porin genes significantly elevated the amounts of fatty acids and phospholipids. When the alterations in protein secondary structures were compared, the quantity of amide I proteins was diminished by the presence of Cu. However, the amount of amide II proteins increased in porin mutant groups independent of Cu presence or absence. The DNAs are transformed from B- and Z-form to A-form due to porin mutations and the presence of Cu ions. The lack of porin genes increased polysaccharide content independent of Cu presence. This study can help characterize Cu detoxification efficiency and guide for obtaining active living cells to be used in bioremediation.

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