Search

Biomechanical and morphological analysis of the cells is a novel approach for monitoring the environmental features, drugs, and toxic compounds' effects on cells. Graphene oxide (GO) has a broad range of medical applications such as tissue engineering and drug delivery. However, the effects of GO nanosheets on biological systems have not been completely understood. In this study, we focused on the biophysical characteristics of cells and their changes resulting from the effect of GO nanosheets. The biophysical properties of the cell population were characterized as follows: cell stiffness was calculated by atomic force microscopy, cell motility and invasive properties were characterized in the microfluidic chip in which the cells are able to visualize cell migration at a single-cell level. Intracellular actin was stained to establish a quantitative picture of the intracellular cytoskeleton. In addition, to understand the molecular interaction of GO nanosheets and actin filaments, coarse-grained (CG) molecular dynamics (MD) simulations were carried out. Our results showed that GO nanosheets can reduce cell stiffness in MCF7 cells and MDA-MB-231 cell lines and highly inhibited cell migration (39.2%) in MCF-7 and (38.6%) in MDA-MB-231 cell lines through the GO nanosheets-mediated disruption of the intracellular cytoskeleton. In the presence of GO nanosheets, the cell migration of both cell lines, as well as the cell stiffness, significantly decreased. Moreover, after GO nanosheets treatment, the cell actin network dramatically changed. The experimental and theoretical approaches established a quantitative picture of changes in these networks. Our results showed the reduction of the order parameter in actin filaments was 23% in the MCF7 cell line and 20.4% in the MDA-MB-231 cell line. The theoretical studies also showed that the GO nanosheet-actin filaments have stable interaction during MD simulation. Moreover, the 2D free energy plot indicated the GO nanosheet can induce conformational changes in actin filaments. Our findings showed that the GO nanosheets can increase the distance of actin-actin subunits from 3.22 to 3.5 nm and in addition disrupt native contacts between two subunits which lead to separate actin subunits from each other in actin filaments. In this study, the biomechanical characteristics were used to explain the effect of GO nanosheets on cells which presents a novel view of how GO nanosheets can affect the biological properties of cells without cell death. These findings have the potential to be applied in different biomedical applications., (© 2021. The Author(s).)

Single-cell RNA sequencing is a high-throughput novel method that provides transcriptional profiling of individual cells within biological samples. This method typically uses microfluidics systems to uncover the complex intercellular communication networks and biological pathways buried within highly heterogeneous cell populations in tissues. One important application of this technology sits in the fields of organ and stem cell transplantation, where complications such as graft rejection and other post-transplantation life-threatening issues may occur. In this review, we first focus on research in which single-cell RNA sequencing is used to study the transcriptional profile of transplanted tissues. This technology enables the analysis of the donor and recipient cells and identifies cell types and states associated with transplant complications and pathologies. We also review the use of single-cell RNA sequencing in stem cell implantation. This method enables studying the heterogeneity of normal and pathological stem cells and the heterogeneity in cell populations. With their remarkably rapid pace, the single-cell RNA sequencing methodologies will potentially result in breakthroughs in clinical transplantation in the coming years. [ABSTRACT FROM AUTHOR]

Lung cancer is a leading cause of cancer death in both men and women worldwide. The high mortality rate in lung cancer is in part due to late-stage diagnostics as well as spread of cancer-cells to organs and tissues by metastasis. Automated lung cancer detection and its sub-types classification from cell's images play a crucial role toward an early-stage cancer prognosis and more individualized therapy. The rapid development of machine learning techniques, especially deep learning algorithms, has attracted much interest in its application to medical image problems. In this study, to develop a reliable Computer-Aided Diagnosis (CAD) system for accurately distinguishing between cancer and healthy cells, we grew popular Non-Small Lung Cancer lines in a microfluidic chip followed by staining with Phalloidin and images were obtained by using an IX-81 inverted Olympus fluorescence microscope. We designed and tested a deep learning image analysis workflow for classification of lung cancer cell-line images into six classes, including five different cancer cell-lines (P-C9, SK-LU-1, H-1975, A-427, and A-549) and normal cell-line (16-HBE). Our results demonstrate that ResNet18, a residual learning convolutional neural network, is an efficient and promising method for lung cancer cell-lines categorization with a classification accuracy of 98.37% and F1-score of 97.29%. Our proposed workflow is also able to successfully distinguish normal versus cancerous cell-lines with a remarkable average accuracy of 99.77% and F1-score of 99.87%. The proposed CAD system completely eliminates the need for extensive user intervention, enabling the processing of large amounts of image data with robust and highly accurate results. [ABSTRACT FROM AUTHOR]

Organ-on-a-chip technology has gained great interest in recent years given its ability to control the spatio-temporal microenvironments of cells and tissues precisely. While physical parameters of the respective niche such as microchannel network sizes, geometric features, flow rates, and shear forces, as well as oxygen tension and concentration gradients, have been optimized for stem cell cultures, little has been done to improve cell-matrix interactions in microphysiological systems. Specifically, detailed research on the effect of matrix elasticity and extracellular matrix (ECM) nanotopography on stem cell differentiation are still in its infancy, an aspect that is known to alter a stem cell's fate. Although a wide range of hydrogels such as gelatin, collagen, fibrin, and others are available for stem cell chip cultivations, only a limited number of elasticities are generally employed. Matrix elasticity and the corresponding nanotopography are key factors that guide stem cell differentiation. Given this, we investigated the addition of gold nanowires into hydrogels to create a tunable biointerface that could be readily integrated into any organ-on-a-chip and cell chip system. In the presented work, we investigated the matrix elasticity (Young's modulus, stiffness, adhesive force, and roughness) and nanotopography of gold nanowire loaded onto fibrin hydrogels using the bio-AFM (atomic force microscopy) method. Additionally, we investigated the capacity of human amniotic mesenchymal stem cells (hAMSCs) to differentiate into osteo- and chondrogenic lineages. Our results demonstrated that nanogold structured-hydrogels promoted differentiation of hAMSCs as shown by a significant increase in Collagen I and II production. Additionally, there was enhanced calcium mineralization activity and proteoglycans formation after a cultivation period of two weeks within microfluidic devices. [ABSTRACT FROM AUTHOR]

Microfluidic cell encapsulation has provided a platform for studying the behavior of individual cells and has become a turning point in single-cell analysis during the last decade. The engineered microenvironment, along with protecting the immune response, has led to increasingly presenting the results of practical and pre-clinical studies with the goals of disease treatment, tissue engineering, intelligent control of stem cell differentiation, and regenerative medicine. However, the significance of cell-substrate interaction versus cell-cell communications in the microgel is still unclear. In this study, monodisperse alginate microgels were generated using a flow-focusing microfluidic device to determine how the cell microenvironment can control human bone marrow-derived mesenchymal stem cells (hBMSCs) viability, proliferation, and biomechanical features in single-cell droplets versus multi-cell droplets. Collected results show insufficient cell proliferation (234 % and 329 %) in both single- and multi-cell alginate microgels. Alginate hydrogels supplemented with poly- l -lysine (PLL) showed a better proliferation rate (514 % and 780 %) in a comparison of free alginate hydrogels. Cell stiffness data illustrate that hBMSCs cultured in alginate hydrogels have higher membrane flexibility and migration potency (Young's modulus equal to 1.06 kPa), whereas PLL introduces more binding sites for cell attachment and causes lower flexibility and migration potency (Young's modulus equal to 1.83 kPa). Considering that cell adhesion is the most important parameter in tissue engineering, in which cells do not run away from a 3D substrate, PLL enhances cell stiffness and guarantees cell attachments. In conclusion, cell attachment to PLL-mediated alginate hydrogels is crucial for cell viability and proliferation. It suggests that cell-cell signaling is good enough for stem cell viability, but cell-PLL attachment alongside cell-cell signaling is crucial for stem cell proliferation and self-renewal. • Microfluidic single cell encapsulation is used as a platform for studying cell-substrate and cell-cell interaction. • The cell microenvironment promotes stem cell viability and proliferation. • Cell-substrate interaction affects stem cell mechanical behavior, which reduces cell migration tendency. • Cell-substrate interaction is essential for the initiation of cell-cell crosstalk and leads to proliferation signaling. [ABSTRACT FROM AUTHOR]