Journal of Biological Physics最新文献

The exploration of microgravity has garnered substantial scholarly attention due to its potential to offer unique insights into the behavior of biological systems. This study presents a preliminary investigation into the effects of simulated microgravity on esophageal cancer cells, examining various aspects such as morphology, growth behavior, adhesion, inhibition rate, and DNA damage. To achieve this, a novel microgravity simulator named “Gravity Challenge” was utilized for its effectiveness in minimizing external influences that could compromise microgravity conditions. The international cell line SK-GT-4 was utilized as the focal point of this investigation. Results revealed noticeable alterations in the growth behavior of cancer cells following exposure to simulated microgravity for 24 h, characterized by a loss of adhesion properties compared to control cells. Concurrently, cell viability exhibited a decline, as evidenced by cytotoxicity testing. Furthermore, the comet assay test demonstrated that cells subjected to microgravity simulation experienced a higher incidence of DNA damage compared to their control counterparts. In conclusion, this comprehensive examination of the impact of simulated microgravity on esophageal cancer cells extends beyond morphological changes, delving into genetic implications through observed DNA damage. The diminished vitality of cells under microgravity conditions underscores the multifaceted effects on cellular behavior in response to environmental variations. These findings represent a significant step towards understanding the dynamics of cancer cells, laying the groundwork for future research aimed at identifying potential therapeutic strategies for this disease.

The evolutionary origin of the inverted retina in the vertebrate eye is unknown. This paper explores a hypothetical evolutionary scenario that explains the unique orientation of the photoreceptors in the vertebrate retina. The proposed scenario follows the scientific accepted scenario for eye evolution and gradually builds up towards an eye prototype by considering light direction detection and increase in achievable spatial resolution as the driving forces. It suggests that eye retinas developed along two different morphological processes, an evagination process that results in the inverted retina in vertebrate eyes and an invagination process that results in a verted retina in cephalopod eyes. The development of the inverted vertebrate retina and eye prototype morphology is strongly substantiated by physics of vision. The proposed evolutionary sequence for vertebrate eye development is simple and has the full potential to explain the origin of the inverted retina and leads to an eye prototype enabling visual detection and orientation. It allows the emergence of eye structures like, extraocular muscles, tapetum lucidum, biconvex lens, cornea, and pupil. This study supports the suggestion that a primitive inverted retina in the predecessor of vertebrates is of ectodermal origin and available before neurulation occurred.

During the asymmetric loop extrusion of DNA by a condensin complex, one domain of the complex stably anchors to the DNA molecule, and another domain reels in the DNA strand into a loop. The DNA strand in the loop is fully relaxed, or there is no tension in the loop. Just outside of the loop, there is a tension that resists the extrusion of DNA. To maintain the extrusion of the DNA loop, the condensin complex must have a domain capable of generating a force to overcome the tension outside of the loop. This study proposes that the groove-shaped HEAT repeat domain Ycg1 plays the role of a molecular motor. A DNA molecule may bind to the groove electrostatically, and the weak binding force facilitates the random thermal motion of DNA molecules. A mechanical model that random collisions between DNA and the nonparallel inner surfaces of the groove may generate a directional force which is required for the loop extrusion to sustain. The hinge domain binds to the DNA molecule and acts as an anchor during asymmetric DNA loop extrusion. When the effects of ATP hydrolysis and the viscous drag of the fluid environment are considered, the motor–anchor model for the condensin complex and the mechanical model might explain the asymmetric loop extrusion, the formation of steps, the step size distribution in the loop extrusion, the tension-dependent extrusion speed, the interaction between coexisting loops on the DNA strand, and untying the knots during extrusion. This model can also explain the observed formation of the Z-loop.

Collective cell invasion underlies several biological processes such as wound healing, embryonic development, and cancerous invasion. Here, we investigate the impact of cell motility on invasion in epithelial monolayers and its coupling to cellular mechanical properties, such as cell-cell adhesion and cortex contractility. We develop a two-dimensional computational model for cells with active motility based on the cellular Potts model, which predicts that the cellular invasion speed is mainly determined by active cell motility and is independent of the biological and mechanical properties of the cells. We also find that, in general, motile cells out-compete and invade non-motile cells, however, this can be reversed by differential cell proliferation. Stable coexistence of motile and static cell types is also possible for certain parameter regimes.

External electric and mechanical stimuli can induce shape deformation in excitable media because of its intrinsic flexible property. When the signals propagation in the media is described by a neural network, creation of heterogeneity or defect is considered as the effect of shape deformation due to accumulation or release of energy in the media. In this paper, a temperature-light sensitive neuron model is developed from a nonlinear circuit composed of a phototube and a thermistor, and the physical energy is kept in capacitive and inductive terms. Furthermore, the Hamilton energy for this function neuron is obtained in theoretical way. A regular neural network is built on a square array by activating electric synapse between adjacent neurons, and a few of neurons in local area is excited by noisy disturbance, which induces local energy diversity, and continuous coupling enables energy propagation and diffusion. Initially, the Hamilton energy function for a temperature-light sensitive neuron can be obtained. Then, the finite neurons are applied noise to obtain energy diversity to explore the energy spread between neurons in the network. For keeping local energy balance, one intrinsic parameter is regulated adaptively until energy diversity in this local area is decreased greatly. Regular pattern formation indicates that local energy balance creates heterogeneity or defects and a few of neurons show continuous parameter shift for keeping energy balance in a local area, which supports gradient energy distribution for propagating waves in the network.

Bone is a complex tissue that fulfills the role of a resistance structure. This quality is most commonly assessed by bone densitometry, but bone strength may not only be related to bone mineral density but also to the preservation of bone cytoarchitectonics. The study included two groups of rats, ovariectomized and non-ovariectomized. Each group was divided into three batches: control, simvastatin-treated, and fenofibrate-treated. In the ovariectomized group, hypolipidemic treatment was instituted at 12 weeks post ovariectomy. One rat from each of the 6 batches was sacrificed 8 weeks after the start of treatment in the group. The experimental study was performed using a Bruker Minispec mq 20 spectrometer operating at a frequency of 20 MHz, subsequently also performed by ¹H T₂-T₂ molecular exchange maps. The results were represented by T₂-T₂ molecular exchange maps that showed, comparatively, both pore size and their interconnectivity at the level of the femoral epiphysis, being able to evaluate both the effect of estrogen on bone tissue biology and the effect of the lipid-lowering medication, simvastatin, and fenofibrate, in both the presence and absence of estrogen. T₂-T₂ molecular exchange maps showed that the absence of estrogen results in an increase in bone tissue pore size and interconnectivity. In the presence of estrogen, lipid-lowering medication, both simvastatin and fenofibrate alter bone tissue cytoarchitectonics by reducing pore interconnectivity. In the absence of estrogen, fenofibrate improves bone tissue cytoarchitectonics, the T₂-T₂ molecular exchange map being similar to that of non-osteoporotic bone tissue.

Studying the calcium dynamics within a fibroblast cell individually has provided only a restricted understanding of its functions. However, research efforts focusing on systems biology approaches for such investigations have been largely neglected by researchers until now. Fibroblast cells rely on signaling from calcium ((Ca^{2+})) and nitric oxide (NO) to maintain their physiological functions and structural stability. Various studies have demonstrated the correlation between NO and the control of (Ca^{2+}) dynamics in cells. However, there is currently no existing model to assess the disruptions caused by various factors in regulatory dynamics, potentially resulting in diverse fibrotic disorders. A mathematical model has been developed to investigate the effects of changes in parameters such as buffer, receptor, sarcoplasmic endoplasmic reticulum (Ca^{2+})-ATPase (SERCA) pump, and source influx on the regulation and dysregulation of spatiotemporal calcium and NO dynamics in fibroblast cells. This model is based on a system of reaction-diffusion equations, and numerical simulations are conducted using the finite element method. Disturbances in key processes related to calcium and nitric oxide, including source influx, buffer mechanism, SERCA pump, and inositol trisphosphate ((IP_3)) receptor, may contribute to deregulation in the calcium and NO dynamics within fibroblasts. The findings also provide new insights into the extent and severity of disorders resulting from alterations in various parameters, potentially leading to deregulation and the development of fibrotic disease.

The detection of magnetic fields by animals is known as magnetoreception. The ferromagnetic hypothesis explains magnetoreception assuming that magnetic nanoparticles are used as magnetic field transducers. Magnetite nanoparticles in the abdomen of Apis mellifera honeybees have been proposed in the literature as the magnetic field transducer. However, studies with ants and stingless bees have shown that the whole body of the insect contain magnetic material, and that the largest magnetization is in the antennae. The aim of the present study is to investigate the magnetization of all the body parts of honeybees as has been done with ants and stingless bees. To do that, the head without antennae, antennae, thorax, and abdomen obtained from Apis mellifera honeybees were analyzed using magnetometry and Ferromagnetic Resonance (FMR) techniques. The magnetometry and FMR measurements show the presence of magnetic material in all honeybee body parts. Our results present evidence of the presence of biomineralized magnetite nanoparticles in the honeybee abdomen and, for the first time, magnetite in the antennae. FMR measurements permit to identify the magnetite in the abdomen as biomineralized. As behavioral experiments reported in the literature have shown that the abdomen is involved in magnetoreception, new experimental approaches must be done to confirm or discard the involvement of the antennae in magnetoreception.

Time of day affects how well the immune system responds to viral or bacterial infections. While it is well known that the immune system is regulated by the circadian clock, the dynamic origin of time-of-day-dependent immunity remains unclear. In this paper, we studied the circadian control of immune response upon infection of influenza A virus through mathematical modeling. Dynamic simulation analyses revealed that the time-of-day-dependent immunity was rooted in the relative phase between the circadian clock and the pulse of viral infection. The relative phase, which depends on the time the infection occurs, plays a crucial role in the immune response. It can drive the immune system to one of two distinct bistable states, a high inflammatory state with a higher mortality rate or a safe state characterized by low inflammation. The mechanism we found here also explained why the same species infected by different viruses has different time-of-day-dependent immunities. Further, the time-of-day-dependent immunity was found to be abolished when the immune system was regulated by an impaired circadian clock with decreased oscillation amplitude or without oscillations.

Epilepsy is a type of brain disorder triggered by an abrupt electrical imbalance of neuronal networks. An electroencephalogram (EEG) is a diagnostic tool to capture the underlying brain mechanisms and detect seizure onset in epileptic patients. To detect seizures, neurologists need to manually monitor EEG recordings for long periods, which is challenging and susceptible to errors depending on expertise and experience. Therefore, automatic identification of seizure and seizure-free EEG signals becomes essential. This study introduces a method based on the features extracted from the phase space reconstruction for classifying seizure and seizure-free EEG signals. The computed features are derived from the elliptical area and interquartile range of the Euclidean distance by varying percentage values of data points ranging from 50 to 100%. We consider two public datasets and evaluate these features in each EEG epoch that includes the healthy, interictal, preictal, and ictal stages of epileptic subjects, utilizing the K-nearest neighbor classifier for classification. Results show that the features have higher values during the seizure than the seizure-free EEG signals and healthy subjects. Furthermore, the proposed features can effectively discriminate seizure EEG signals from the seizure-free and normal subjects with 100% accuracy, sensitivity, and specificity in both datasets. Likewise, the classification between the preictal stage and seizure EEG signals attains 98% accuracy. Overall, the reconstructed phase space features significantly enhance the accuracy of detecting epileptic EEG signals compared with existing methods. This advancement holds great potential in assisting neurologists in swiftly and accurately diagnosing epileptic seizures from EEG signals.