Journal of Biological Physics最新文献

Fluid flow at the microscale level exhibits a unique phenomenon that can be explored to fabricate microfluidic devices integrated with components that can perform various biological functions. In this manuscript, the importance of physics for microscale fluid dynamics using microfluidic devices has been reviewed. Microfluidic devices provide new opportunities with regard to spatial and temporal control over cell growth. Furthermore, the manuscript presents an overview of cellular stimuli observed by combining surfaces that mimic the complex biochemistries and different geometries of the extracellular matrix, with microfluidic channels regulating the transport of fluids, soluble factors, etc. We have also explained the concept of mechanotransduction, which defines the relation between mechanical force and biological response. Furthermore, the manipulation of cellular microenvironments by the use of microfluidic systems has been highlighted as a useful device for basic cell biology research activities. Finally, the article focuses on highly integrated microfluidic platforms that exhibit immense potential for biomedical and pharmaceutical research as robust and portable point-of-care diagnostic devices for the assessment of clinical samples.

The membrane potential of a cell (V_m) regulates several physiological processes. The voltage sensor domain (VSD) is a region that confers voltage sensitivity to different types of transmembrane proteins such as the following: voltage-gated ion channels, the voltage-sensing phosphatase (Ci-VSP), and the sperm-specific Na⁺/H⁺ exchanger (sNHE). VSDs contain four transmembrane segments (S1–S4) and several positively charged amino acids in S4, which are essential for the voltage sensitivity of the protein. Generally, in response to changes of the V_m, the positive residues of S4 displace along the plasma membrane without generating ionic currents through this domain. However, some native (e.g., Hv1 channel) and mutants of VSDs produce ionic currents. These gating pore currents are usually observed in VSDs that lack one or more of the conserved positively charged amino acids in S4. The gating pore currents can also be induced by the isolation of a VSD from the rest of the protein domains. In this review, we summarize gating pore currents from all families of proteins with VSDs with classification into three cases: (1) pathological, (2) physiological, and (3) artificial currents. We reinforce the model in which the position of S4 that lacks the positively charged amino acid determines the voltage dependency of the gating pore current of all VSDs independent of protein families.

Human-induced extinction and rapid ecological changes require the development of techniques that can help avoid extinction of endangered species. The most used strategy to avoid extinction is reintroduction of the endangered species, but only 31% of these attempts are successful and they require up to 15 years for their results to be evaluated. In this research, we propose a novel strategy that improves the chances of survival of endangered predators, like lynx, by controlling only the availability of prey. To simulate the prey-predator relationship we used a Lotka-Volterra model to analyze the effects of varying prey availability on the size of the predator population. We calculate the number of prey necessary to support the predator population using a high-order sliding mode control (HOSMC) that maintains the predator population at the desired level. In the wild, nature introduces significant and complex uncertainties that affect species’ survival. This complexity suggests that HOSMC is a good choice of controller because it is robust to variability and does not require prior knowledge of system parameters. These parameters can also be time varying. The output measurement required by the HOSMC is the number of predators. It can be obtained using continuous monitoring of environmental DNA that measures the number of lynxes and prey in a specific geographic area. The controller efficiency in the presence of these parametric uncertainties was demonstrated with a numerical simulation, where random perturbations were forced in all four model parameters at each simulation step, and the controller provides the specific prey input that will maintain the predator population. The simulation demonstrates how HOSMC can increase and maintain an endangered population (lynx) in just 21–26 months by regulating the food supply (hares), with an acceptable maximal steady-state error of 3%.

Sustained spiral waves, also known as rotors, are pivotal mechanisms in persistent atrial fibrillation (AF). Stochasticity is inevitable in nonlinear biological systems such as the heart; however, it is unclear how noise affects the instability of spiral waves in human AF. This study presents a stochastic two-dimensional mathematical model of human AF and explores how Gaussian white noise affects the instability of spiral waves. In homogeneous tissue models, Gaussian white noise may lead to spiral-wave meandering and wavefront break-up. As the noise intensity increases, the spatial dispersion of phase singularity (PS) points increases. This finding indicates the potential AF-protective effects of cardiac system stochasticity by destabilizing the rotors. By contrast, Gaussian white noise is unlikely to affect the spiral-wave instability in the presence of localized scar or fibrosis regions. The PS points are located at the boundary or inside the scar/fibrosis regions. Localized scar or fibrosis may play a pivotal role in stabilizing spiral waves regardless of the presence of noise. This study suggests that fibrosis and scars are essential for stabilizing the rotors in stochastic mathematical models of AF. Further patient-derived realistic modeling studies are required to confirm the role of scar/fibrosis in AF pathophysiology.

Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons driven by spike-timing-dependent plasticity (STDP) and temporal networks subject to homeostatic structural plasticity (HSP) rules remain unclear. Here, we bridge this gap by determining the configurations required to achieve high and stable degrees of complete synchronization (CS) and phase synchronization (PS) in time-varying small-world and random neural networks driven by STDP and HSP. In particular, we found that decreasing P (which enhances the strengthening effect of STDP on the average synaptic weight) and increasing F (which speeds up the swapping rate of synapses between neurons) always lead to higher and more stable degrees of CS and PS in small-world and random networks, provided that the network parameters such as the synaptic time delay (tau _c), the average degree (langle k rangle), and the rewiring probability (beta) have some appropriate values. When (tau _c), (langle k rangle), and (beta) are not fixed at these appropriate values, the degree and stability of CS and PS may increase or decrease when F increases, depending on the network topology. It is also found that the time delay (tau _c) can induce intermittent CS and PS whose occurrence is independent F. Our results could have applications in designing neuromorphic circuits for optimal information processing and transmission via synchronization phenomena.

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.