Dynamic Cell Behavior Research Articles

Profiling Dynamic Patterns of Single-Cell Motility.

Cell motility plays an essential role in many biological processes as cells move and interact within their local microenvironments. Current methods for quantifying cell motility typically involve tracking individual cells over time, but the results are often presented as averaged values across cell populations. While informative, these ensemble approaches have limitations in assessing cellular heterogeneity and identifying generalizable patterns of single-cell behaviors, at baseline and in response to perturbations. In this study, CaMI is introduced, a computational framework designed to leverage the single-cell nature of motility data. CaMI identifies and classifies distinct spatio-temporal behaviors of individual cells, enabling robust classification of single-cell motility patterns in a large dataset (n = 74253 cells). This framework allows quantification of spatial and temporal heterogeneities, determination of single-cell motility behaviors across various biological conditions and provides a visualization scheme for direct interpretation of dynamic cell behaviors. Importantly, CaMI reveals insights that conventional cell motility analyses may overlook, showcasing its utility in uncovering robust biological insights. Together, a multivariate framework is presented to classify emergent patterns of single-cell motility, emphasizing the critical role of cellular heterogeneity in shaping cell behaviors across populations.

Observation and modeling of dynamic fracture behaviors of battery cell under impact loading using enhanced representative volume element concept

The burgeoning electric automobile industry has increased interest in battery safety. Battery cells experience significant mechanical stress during operation, including the impact of accidents and vibrations from driving. The potential for thermal runaway reactions in battery cells raises safety concerns. Although numerous researchers have defined the dynamic behavior of battery cells and proposed numerical models to describe it, few studies have focused on the high-strain rate mechanical impact phase correlated with the onset of fracture. In this study, we describe the dynamic behavior of pouch battery cells and propose a modeling method to study their mechanical failure under impact situations. Impact tests are conducted at various velocities and heights. To overcome numerical issues commonly encountered under rapid deformation scenarios, a new finite element model is developed based on the representative volume element model. The proposed approach efficiently simulates continuous crack propagation and brittleness behavior during impact by permitting the individual behavior of the cell components. Therefore, engineers can reliably design safer electric vehicle battery cells by measuring the properties of the cell components.

Decoding dynamic bamboo cell shrinkage with time-lapse microscopy and machine-learning

The shrinkage of bamboo can be traced to the cellular scale; however, research on the shrinkage of bamboo cells’ scale is rare. This gap primarily arises from the intrinsic heterogeneity of biomass materials, leading to significant differences in the shrinkage behaviors of bamboo cells. Consequently, conventional measurement and analysis techniques struggle to obtain comprehensive and accurate results. To fill in this gap, this study investigated the dynamic shrinking behavior of individual bamboo cells, including fiber cells and parenchyma cells, using time-lapse microscopy and machine-learning techniques. Time-lapse observations revealed that the shrinkage rate of fiber cells across the cross-section surpassed that of parenchyma cells, accompanied by a greater shrinkage deformation. Specifically, fiber cells exhibited a shrinkage rate of 2.53 %/min, whereas parenchyma cells showed a rate of 0.58 %/min. This resulted in corresponding diameter reductions of approximately −30 % and −7 %, respectively. Additionally, machine-learning results demonstrated the efficacy of the trained long short-term memory (LSTM) model in accurately predicting morphological changes in individual parenchyma cells during the shrinkage process. This study advances understanding of bamboo-moisture interaction mechanisms and offers crucial theoretical data for improving bamboo drying and minimizing crack formation.

Modeling Excitable Cells with Memristors

This paper presents an in-depth analysis of an excitable membrane of a biological system by proposing a novel approach that the cells of the excitable membrane can be modeled as the networks of memristors. We provide compelling evidence from the Chay neuron model that the state-independent mixed ion channel is a nonlinear resistor, while the state-dependent voltage-sensitive potassium ion channel and calcium-sensitive potassium ion channel function as generic memristors from the perspective of electrical circuit theory. The mechanisms that give rise to periodic oscillation, aperiodic (chaotic) oscillation, spikes, and bursting in an excitable cell are also analyzed via a small-signal model, a pole-zero diagram of admittance functions, local activity, the edge of chaos, and the Hopf bifurcation theorem. It is also proved that the zeros of the admittance functions are equivalent to the eigen values of the Jacobian matrix, and the presence of the positive real parts of the eigen values between the two bifurcation points lead to the generation of complicated electrical signals in an excitable membrane. The innovative concepts outlined in this paper pave the way for a deeper understanding of the dynamic behavior of excitable cells, offering potent tools for simulating and exploring the fundamental characteristics of biological neurons.

Imaging Approaches in Cancer Biology.

A majority of cancer research is focused on defining the cellular and molecular basis of cancer cells and the signals that control oncogenic transformation; as a consequence, we know very little about the dynamic behavior of cancer cells in vivo. To begin to view and understand the mechanisms and interactions that control cancer initiation, growth, and metastatic progression and how these processes are influenced by the microenvironment and the signals derived from it, it is essential to develop strategies that allow imaging of the cancer cells in the context of the living microenvironment. Here, we discuss emerging work designed to visualize how cancer cells function within the microenvironment to discover how these interactions act coordinately to enable aberrant growth and to understand how they could be targeted to design new approaches to intercept the disease.

Effects of Tenofovir Disoproxil Fumarate on Bone Quality beyond Bone Density-A Scoping Review of the Literature.

Tenofovir disoproxil fumarate (TDF) is a widely used pharmacological agent for the treatment of human immunodeficiency virus infection. While prolonged exposure to TDF has been associated with a decrease in bone mineral density (BMD) and increased fracture risk, limited discussion exists on its effects on various aspects of bone quality. This scoping review aims to provide a comprehensive overview of the impact of TDF on bone quality beyond BMD. A literature search was conducted using the PubMed and Scopus databases to identify studies investigating the effects of TDF on bone quality. Original research articles written in English, irrespective of study type or publication year, were included in the review. Seven articles met the inclusion criteria. Findings indicate that prolonged exposure to TDF adversely affects bone microarchitecture and strength, impeding fracture healing and skeletal microdamage repair. The observed effects suggest a complex interplay involving bone cell signalling, cytokines and bone remodelling processes as potential mechanisms underlying TDF's impact on bone quality. As a conclusion, TDF impairs bone remodelling and microarchitecture by influencing dynamic bone cell behaviour and signalling pathways. Future studies should delve deeper into understanding the intricate negative effects of TDF on bone and explore strategies for reversing these effects.

An integrative temperature-controlled microfluidic system for budding yeast heat shock response analysis at the single-cell level.

Cells can respond and adapt to complex forms of environmental change. Budding yeast is widely used as a model system for these stress response studies. In these studies, the precise control of the environment with high temporal resolution is most important. However, there is a lack of single-cell research platforms that enable precise control of the temperature and form of cell growth. This has hindered our understanding of cellular coping strategies in the face of diverse forms of temperature change. Here, we developed a novel temperature-controlled microfluidic platform that integrates a microheater (using liquid metal) and a thermocouple (liquid metal vs. conductive PDMS) on a chip. Three forms of temperature changes (step, gradient, and periodical oscillations) were realized by automated equipment. The platform has the advantages of low cost and a simple fabrication process. Moreover, we investigated the nuclear entry and exit behaviors of the transcription factor Msn2 in yeast in response to heat stress (37 °C) with different heating modes. The feasibility of this temperature-controlled platform for studying the protein dynamic behavior of yeast cells was demonstrated.

Telocyte Recruitment During the Emergence of a Metaplastic Niche in the Stomach

Background & AimTelocytes, a recently identified type of sub-epithelial interstitial cell, have garnered attention for their potential roles in tissue homeostasis and repair. However, their contribution to gastric metaplasia remains unexplored. This study aimed to elucidate the role of telocytes in the development of metaplasia within the gastric environment. MethodsTo investigate the presence and behavior of telocytes during metaplastic transitions, we utilized both drug-induced acute injury models (using DMP-777 or L635) and a genetically engineered mouse model (Mist1-Kras). Lineage tracing via the Foxl1-CreERT2;R26R-tdTomato mouse model was used to track telocyte migratory dynamics. Immunofluorescence staining was used to identify telocyte markers and evaluate their correlation with metaplasia-related changes. ResultsWe confirmed the existence of FOXL1+/PDGFRα+ double-positive telocytes in the stomach's isthmus region. As metaplasia developed, we observed a marked increase in the telocyte population. The distribution of telocytes expanded beyond the isthmus to encompass the entire gland and closely reflected the expansion of the proliferative cell zone. Rather than a general response to mucosal damage, the shift in telocyte distribution was associated with the establishment of a metaplastic cell niche at the gland base. Furthermore, lineage-tracing experiments highlighted the active recruitment of telocytes to the emerging metaplastic cell niche, and we observed expression of Wnt5a, Bmp4, and Bmp7 in PDGFRα+ telocytes. ConclusionsThese results suggest that telocytes contribute to the evolution of a gastric metaplasia niche. The dynamic behavior of these stromal cells, their responsiveness to metaplastic changes, and potential association with Wnt5a, Bmp4, and Bmp7 signaling emphasize the significance of telocytes in tissue adaptation and repair.

Establishment of the microscope incubation system and its application in evaluating tumor treatment effects through real-time live cellular imaging.

Introduction: Long-term imaging of live cells is commonly used for the study of dynamic cell behaviors. It is crucial to keep the cell viability during the investigation of physiological and biological processes by live cell imaging. Conventional incubators that providing stable temperature, carbon dioxide (CO2) concentration, and humidity are often incompatible with most imaging tools. Available commercial or custom-made stage-top incubators are bulky or unable to provide constant environmental conditions during long time culture. Methods: In this study, we reported the development of the microscope incubation system (MIS) that can be easily adapted to any inverted microscope stage. Incremental PID control algorithm was introduced to keep stable temperature and gas concentration of the system. Moreover, efficient translucent materials were applied for the top and bottom of the incubator which make it possible for images taken during culture. Results: The MIS could support cell viability comparable to standard incubators. When used in real time imaging, the MIS was able to trace single cell migration in scratch assay, T cell mediated tumor cells killing in co-culture assay, inflation-collapse and fusion of organoids in 3D culture. And the viability and drug responses of cells cultured in the MIS were able to be calculated by a label-free methods based on long term imaging. Discussion: We offer new insights into monitoring cell behaviors during long term culture by using the stage adapted MIS. This study illustrates that the newly developed MIS is a viable solution for long-term imaging during in vitro cell culture and demonstrates its potential in cell biology, cancer biology and drug discovery research where long-term real-time recording is required.

Numerical Simulations for in-Plane Distribution of Platinum Degradation in Dynamic Operating Conditions of Polymer Electrolyte Membrane Fuel Cells

Predicting degradation of polymer electrolyte membrane fuel cells (PEMFCs) is an important issue from the viewpoint of durability and cost. In fact, in technical roadmaps regarding fuel cell of each country, high targets of durability and performance are set for transport applications especially for heavy duty vehicles. One of important degradation process takes place in catalyst layer. PEMFC catalysts are typically platinum or platinum alloys and consist of nanoparticles to increase the electrochemically active surface area (ECSA). However, these particles are not stable in dynamic operating conditions of the transport applications. A typical degradation mechanism of the catalyst is the electrochemical Ostwald ripening mechanism, and it is known that the platinum particle size distribution shifts to larger particle diameter, resulting in lower ECSA and lower performance. Therefore, predicting platinum catalyst degradation is important to enhance durability of the products.Various numerical models for catalyst degradation of PEMFC have been proposed and used to explore degradation mechanisms. Many of these are zero or one-dimensional models, but factors that affect catalyst degradation, such as temperature, potential, and humidity, have non-uniform distributions in the active area of large-size (several hundred cm2) cells. Furthermore, these factors change unsteadily due to the dynamic operating conditions. In order to predict the degradation of cells, it is necessary to analyze the dynamic behavior of large-area cells, but there are few spatially resolved catalyst degradation predictions [1].In this analysis, transient analysis of a large-area cell for a dynamic operating conditions is performed to predict in-plane distribution of catalyst degradation. Furthermore, we will analyze changes in the power generation performance of the cells when these degradations progress. A three-dimensional numerical simulation model based on our original methodology [2] was used as the performance prediction model for the PEMFC. Catalyst degradation considers the mechanisms of platinum dissolution, oxidation, and platinum oxide dissolution [3]. The in-plane distribution of platinum degradation is predicted from the time-series results of in-plane distributions of temperature, potential, humidity, etc., obtained by the performance prediction model. The performance of the PEMFC at the time of progressive degradation is analyzed by reflecting the effect of ECSA decrease due to platinum degradation in the performance prediction model. Although this method considers only a part of the catalyst degradation process, a path is presented to analyze the distribution of catalyst degradation under dynamic operating conditions in large-area cells.

Characterization of Hematopoietic Stem Cell Diversity Using Spatiotemporal Quantitative Phase Imaging

Cells undergo continual transformations, never retaining their original state. Hematopoietic stem cells (HSCs), at the apex of the hematopoietic hierarchy, are not exempt from this dynamic process. In recent years, the advent of single-cell analysis techniques such as scRNAseq has progressively unveiled the heterogeneity within cell populations previously presumed to be homogeneous. However, these techniques are limited to evaluating the cellular state at a single temporal point based on snapshot analysis, thus failing to account for temporal changes and dynamic behavior of cells. Therefore, the true diversity inherent to the ever-changing HSCs remains uncertain. In this study, we comprehensively elucidate HSC diversity, including temporal changes, by integrating our recently established ex vivo HSC expansion techniques (Wilkinson et al., Nature, Becker et al., Cell Stem Cell), single-cell quantitative phase imaging (QPI), and post-transplantation dynamics analysis. For live imaging, HSCs were harvested from hepatic leukemia factor ( Hlf)-tdTomato reporter mice, which specifically marks long-term HSCs. Index sorted single Hlf-tdTomato + HSC were expanded with a single-HSC culture system and monitored by QPI fluorescence time-lapse imaging. Surprisingly, even though the cells were derived from the same HSC fraction, significant variations in mitotic rate, motility, morphological changes, and Hlf expression levels were observed at the single-cell level. Stemness did not decrease stepwise over time, but always exhibited continuous changes. Thus, analysis including the temporal dimension illuminated the infinitely branched nature of HSC diversity. Interestingly, Hlf expression level correlated with the dynamic behavior of HSCs in the expansion culture system. Hlf-high HSCs exhibited a slow division rate, small, rounded morphology and low motility, while Hlf-low HSCs actively divided and differentiated, displayed larger morphological size with low sphericity, and exhibited high motility. Furthermore, spatiotemporal dynamics analysis of Hlf-high/low HSCs after transplantation, employing the highly sensitive in vivo imaging system Akaluc bioluminescence imaging (AkaBLI), revealed that Hlf-high HSCs initiate systemic hematopoiesis slowly, while Hlf-low HSCs expanded quickly, characterized by short-term explosive hematopoiesis in the spleen. As expected, only Hlf-high HSCs had long-term bone marrow reconstitution ability. Thus, based on the expression level of Hlf, it is possible to predict the dynamic behavior of the cells in the expansion medium and in the post-transplant body. Next, we investigated whether Hlf expression level could be predicted based on the kinetic features of cells during HSC ex vivo expansion. Interestingly, multidimensional analysis based on kinetic features extracted from time-lapse imaging showed multiple clusters, each linked to Hlf expression levels. In human HSCs, the dynamic diversity of HSCs was also observed in our recently established ex vivo expansion system (Sakurai et al., Nature). Notably, the kinetic features of human HSCs differed from those of mouse HSCs. Transplantation of human HSCs exhibiting specific morphological characteristics showed long-term reconstitution ability. Thus, classification of HSCs based on kinetic features facilitated enrichment of functional HSCs. This study demonstrates the importance of characterizing cells, including the temporal dimension, and illustrates the existence of infinite dynamic individuality in mouse and human HSCs.

3D bioprinted tumor-vessel-bone co-culture scaffold for breast cancer bone metastasis modeling and drug testing

Bone metastasis is one of the most common complications of advanced breast cancer (BrCa) with a poor clinical prognosis, due to the lack of effective drugs and therapeutics. Traditional screening systems for anti-cancer drugs are not capable of exactly reflecting the efficacy of drugs in vivo, mainly because they cannot replicate the dynamic metastasis process involving primary tumor, blood circulation and bone microenvironment. To precisely simulate the behavior of native BrCa cells, herein, a biomimetic 3D co-culture metastatic model composed of tumor, hollow vascular, and bone tissues is fabricated by one-step 3D bioprinting method for effective drug testing. Gelatin methacryloyl-based photocrosslinkable bioinks containing breast cancer cells (MDA-MB-231), human umbilical vein endothelial cells (HUVECs) and osteoblasts (h-OB) are applied to highly imitate the native metastatic niches with the formation of blood vessels, vascularized tumors, as well as vascularized bone tissues. The dynamic invasion behavior of BrCa cells from original sites to bone tissues through blood vessels is reproduced, and the interactive effect of cancer, vascular and bone cells are investigated. Moreover, the 3D co-culture metastatic model allows for higher drug resistance of BrCa cells than 2D culture and 3D mono-culture models. These results demonstrate that the 3D bioprinted co-culture metastatic model facilitates in-depth understanding of the basic mechanisms of BrCa migration and provides a physiologically relevant platform for the development of new therapeutic drugs.

Improving the efficiency and stability of perovskite solar cell: Application of innovative machine learning algorithm

Solar cells are modern inventions that use the photovoltaic effect to directly convert light energy into electricity, generating electrical charges that are free to move through semiconductors. The semiconductor is typically utilized as the raw material for solar cells. In order to convert energy, electron–hole pairs that are responsible for producing light (photon) energy must be absorbed in a semiconductor, followed by charge carrier separation. Enhancing solar cells’ stability is crucial in engineering because they are used in a variety of environments. Moreover, graphene nanoplatelets (GPLs) have a great deal of potential to enhance ceramic–GNP composites’ mechanical, tribological, electrical, thermal, and biological characteristics, all at once. Machine learning algorithms (MLA) are often used to forecast how various systems would behave. In an MLA network, hyperparameters like the number of hidden layers and learning rate are often selected manually as required. MLA is used in this work to examine spinning cylindrical constructions’ stability at the microscale. In this context, the particle swarm optimization (PSO) is used to optimize the weights and biases of the network. The number of perceptions in the two hidden layers is optimized in a second parallel process using a genetic algorithm. The modified torque–stress theory (MCST) equation’s numerical solution for the dynamic behavior of GPL-reinforced perovskite solar cells was used to train the MLA. It is proposed to guide the spatial discretization of governing equations using the variational differential quadrature (VDQ) method as a direct discretization of the energy functional in the space domain. Lastly, the findings demonstrate that the stability of the current cantilevered solar cell reinforced by GPLs is significantly influenced by curvature, length scale, the shape of the solar cell, and mode number factors.

Combining sound and light to study live cells using a 3D-printed acoustofluidic device

Using acoustofluidic devices and Raman spectroscopy to study the dynamic behavior of cells in real time.

Significance of dynamic thickness changes and compression effects of commercial lithium-ion spring-braced cells

Lithium-ion battery (LIB) cells undergo thickness changes during cycling that can be reversible and irreversible. According to the literature, cell compression can prevent various defects, such as volume-change-induced contact losses. Moreover, densely packed cells represent the battery electric vehicle (BEV) use case, where volumetric energy density can still be optimized. In this study, a uniaxial compression test bench is developed to evaluate the dynamic dilation behavior and stress susceptibility of commercial LIB pouch cells. Using a spring-compression approach, the active material can expand and contract under moderate normal stress variations while keeping the inner cell layers in permanent contact. After applying stress to the cell, the cycling behavior and thickness changes are monitored under the variation of several parameters. A rig-integrated force measurement mat is used to monitor stress distribution, providing additional insight. Our results show that varying the charging rate leads to significant differences in the thickness change of a mildly compressed cell. In this particular case, both reversible and irreversible dilation fractions are present and electro-mechanical effects were identified. As a result, gained insights can serve battery system manufacturers with information to optimize their battery pack regarding operating efficiency, sustainability and mechanical safety.

Models of vimentin organization under actin-driven transport.

Intermediate filaments form an essential structural network, spread throughout the cytoplasm, and play a key role in cell mechanics, intracellular organization, and molecular signaling. The maintenance of the network and its adaptation to the cell's dynamic behavior relies on several mechanisms implicating cytoskeletal crosstalk which are not fully understood. Mathematical modeling allows us to compare several biologically realistic scenarios to help us interpret experimental data. In this study we observe and model the dynamics of the vimentin intermediate filaments in single glial cells seeded on circular micropatterns following microtubule disruption by nocodazole treatment. In these conditions, the vimentin filaments move towards the cell center and accumulate before eventually reaching a steady state. In the absence of microtubule-driven transport, the motion of the vimentin network is primarily driven by actin-related mechanisms. To model these experimental findings, we hypothesize that vimentin may exist in two states, mobile and immobile, and switch between the states at unknown (either constant or nonconstant) rates. Mobile vimentin is assumed to advect with either constant or nonconstant velocity. We introduce several biologically realistic scenarios using this set of assumptions. For each scenario, we use differential evolution to find the best parameter sets resulting in a solution that most closely matches the experimental data and then the assumptions are evaluated using the Akaike information criterion. This modeling approach allows us to conclude that our experimental data are best explained by a spatially dependent trapping of intermediate filaments or a spatially dependent speed of actin-dependent transport.

Regulation of aortic morphogenesis and VE-cadherin dynamics by VEGF.

In amniote vertebrates, the definitive dorsal aorta is formed by the fusion of two primordial aortic endothelial tubes. Formation of the definitive dorsal aorta requires extensive cellular migrations and rearrangements of the primordial tubes in order to generate a single vessel located at the embryonic ventral midline. This study examines the role of VEGF signaling in the generation of the definitive dorsal aorta. Through gain- and loss-of-function studies in vivo in the chick embryo, we document a requirement for VEGF signaling in growth and remodeling of the paired primordia. We find that regions of the aorta are differentially sensitive to levels of VEGF signaling, and present evidence that areas of low blood flow are more sensitive to the loss of VEGF signaling. We also find that VEGF signaling regulates the intracellular distribution between membrane and cytoplasm of the cell-cell adhesion molecule VE-cadherin in aortic endothelial cells in vivo. Together, these finding identify mechanisms that likely contribute to the dynamic behavior of endothelial cells during aorta morphogenesis.

Single-cell transcriptomics of a dynamic cell behavior in murine airways.

Despite advances in high-dimensional cellular analysis, the molecular profiling of dynamic behaviors of cells in their native environment remains a major challenge. We present a method that allows us to couple the physiological behaviors of cells in an intact murine tissue to deep molecular profiling of individual cells. This method enabled us to establish a novel molecular signature for a striking migratory cellular behavior following injury in murine airways.

Two-point optical manipulation reveals mechanosensitive remodeling of cell–cell contacts in vivo

Biological tissues acquire reproducible shapes during development through dynamic cell behaviors. Most of these behaviors involve the remodeling of cell-cell contacts. During epithelial morphogenesis, contractile actomyosin networks remodel cell-cell contacts by shrinking and extending junctions between lateral cell surfaces. However, actomyosin networks not only generate mechanical stresses but also respond to them, confounding our understanding of how mechanical stresses remodel cell-cell contacts. Here, we develop a two-point optical manipulation method to impose different stress patterns on cell-cell contacts in the early epithelium of the Drosophila embryo. The technique allows us to produce junction extension and shrinkage through different push and pull manipulations at the edges of junctions. We use these observations to expand classical vertex-based models of tissue mechanics, incorporating negative and positive mechanosensitive feedback depending on the type of remodeling. In particular, we show that Myosin-II activity responds to junction strain rate and facilitates full junction shrinkage. Altogether our work provides insight into how stress produces efficient deformation of cell-cell contacts invivo and identifies unanticipated mechanosensitive features of their remodeling.

Quantitative Image Analysis of Dynamic Cell Behaviors During Border Cell Migration.

Drosophila border cells have emerged as a genetically tractable model to investigate dynamic collective cell migration within the context of a developing organ. Studies of live border cell cluster migration have revealed similarities with other migrating collectives, including formation and restriction of cellular protrusions to the front of the cluster, supracellular actomyosin contractility of the entire collective, and intra-collective cell motility. Here, we describe protocols to prepare ex vivo cultures of stage 9 egg chambers followed by live time-lapse imaging of fluorescently labeled border cells to image dynamic cell behaviors. We provide options to perform live imaging using either a widefield epifluorescent microscope or a confocal microscope. We further outline steps to quantify various cellular behaviors and protein dynamics of live migrating border cells using the Fiji image processing package of ImageJ. These methods can be adapted to other migrating cell collectives in cultured tissues and organs.