Determination of viscohyperelastic properties of tubule epithelial cells by an approach combined with AFM nanoindentation and finite element analysis

Multidepth quantitative analysis of liver cell viscoelastic properties: Fusion of nanoindentation and finite element modeling techniques

Liver cells are the basic functional unit of the liver. However, repeated or sustained injury leads to structural disorders of liver lobules, proliferation of fibrous tissue and changes in structure, thus increasing scar tissue. Cellular fibrosis affects tissue stiffness, shear force, and other cellular mechanical forces. Mechanical force characteristics can serve as important indicators of cell damage and cirrhosis. Atomic force microscopy (AFM) has been widely used to study cell surface mechanics. However, characterization of the deep mechanical properties inside liver cells remains an underdeveloped field. In this work, cell nanoindentation was combined with finite element analysis to simulate and analyze the mechanical responses of liver cells at different depths in vitro and their internal responses and stress diffusion distributions after being subjected to normal stress. The sensitivities of the visco-hyperelastic parameters of the finite element model to the effects of the peak force and equilibrium force were compared. The force curves of alcohol-damaged liver cells at different depths were measured and compared with those of undamaged liver cells. The inverse analysis method was used to simulate the finite element model in vitro. Changes in the parameters of the cell model after injury were explored and analyzed, and their potential for characterizing hepatocellular injury and related treatments was evaluated. RESEARCH HIGHLIGHTS: This study aims to establish an in vitro hyperelastic model of liver cells and analyze the mechanical changes of cells in vitro. An analysis method combining finite element analysis model and nanoindentation was used to obtain the key parameters of the model. The multi-depth mechanical differences and internal structural changes of injured liver cells were analyzed.

Multi-scale characterization and analysis of cellular viscoelastic mechanical phenotypes by atomic force microscopy

The viscoelasticity of cells serves as a biomarker that reveals changes induced by malignant transformation, which aids the cytological examinations. However, differences in the measurement methods and parameters have prevented the consistent and effective characterization of the viscoelastic phenotype of cells. To address this issue, nanomechanical indentation experiments were conducted using an atomic force microscope (AFM). Multiple indentation methods were applied, and the indentation parameters were gradually varied to measure the viscoelasticity of normal liver cells and cancerous liver cells to create a database. This database was employed to train machine-learning algorithms in order to analyze the differences in the viscoelasticity of different types of cells and as well as to identify the optimal measurement methods and parameters. These findings indicated that the measurement speed significantly influenced viscoelasticity and that the classification difference between the two cell types was most evident at 5 μm/s. In addition, the precision and the area under the receiver operating characteristic curve were comparatively analyzed for various widely employed machine-learning algorithms. Unlike previous studies, this research validated the effectiveness of measurement parameters and methods with the assistance of machine-learning algorithms. Furthermore, the results confirmed that the viscoelasticity obtained from the multiparameter indentation measurement could be effectively used for cell classification. RESEARCH HIGHLIGHTS: This study aimed to analyze the viscoelasticity of liver cancer cells and liver cells. Different nano-indentation methods and parameters were used to measure the viscoelasticity of the two kinds of cells. The neural network algorithm was used to reverse analyze the dataset, and the methods and parameters for accurate classification and identification of cells are successfully found.

Reduction of alcohol-induced mitochondrial damage with ginsenoside Rg1 studied by atomic force microscopy

The quantification of mitochondrial morphology and mechanical properties is useful for the diagnosis and treatment of mitochondrial and alcoholic liver disease. In this study, the effects of ginsenoside Rg1 (G-Rg1) on the morphology and mechanical properties of mitochondria that had suffered alcohol-induced damage were investigated under near-physiological conditions. Additionally, the morphological and mechanical properties of mitochondria were quantified through atomic force microscopy. Atomic force microscopy revealed that alcohol-induced significant morphological changes in mitochondria. Compared with that of the mitochondria of normal hepatocytes, the average surface area of the damaged mitochondria was found to have increased significantly under the influence of alcohol. Furthermore, the mitochondrial area tended to be normal under the action of G-Rg1, whilst other parameters (length, width and perimeter) were significantly different from those of the mitochondria with the alcohol-induced damage. Simultaneously, alcohol significantly reduced the adhesion and elastic modulus of mitochondria, whilst the adhesion and elastic modulus of mitochondria in the G-Rg1 treatment group were closer to the values of normal mitochondria. This study overall showed that G-Rg1 could effectively alleviate the swelling and anomalous mechanical properties of mitochondria induced by alcohol.

Machine learning method for extracting elastic modulus of cells

The Hertz contact mechanics model is commonly used to extract the elastic modulus of the cell, but the basic assumptions of the model are often not met in cell indentation experiments, which can lead to errors in the obtained elastic modulus of cell. The establishment of theoretical formulas or modification of the Hertz formulas has been proposed to reduce the errors introduced by indentation depth and cell thickness, but errors from cell radius and probe radius are largely neglected. Herein, we build a neural network model in machine learning to extract the elastic modulus of cell, which takes into account of four variables: indentation depth, cell thickness, cell radius, and probe radius. The validity of the model is demonstrated by the indentation experiment. The introduction of machine learning methods provides an alternative solution for extracting the elastic modulus of the cell and has potential for application.

Auxeticity in biosystems: an exemplification of its effects on the mechanobiology of heterogeneous living cells

Auxeticity (negative Poisson's ratio) is the unique mechanical property found in an extensive variety of materials, such as metals, graphene, composites, polymers, foams, fibers, ceramics, zeolites, silicates and biological tissues. The enhanced mechanical features of the auxetic materials have motivated scientists to design, engineer and manufacture man-made auxetic materials to fully leverage their capabilities in different fields of research applications, including aeronautics, medical, protective equipments, smart sensors, filter cleaning, and so on. Atomic force microscopy (AFM) indentation is one of the most widely used methods for characterizing the mechanical properties and response of the living cells. In this contribution, we highlight main consequences of auxeticity for biosystems and provide a representative example to quantify the effect of nucleus auxeticity on the force response of the embryonic stem cells. A parametric study has been conducted on a heterogeneous stem cell to evaluate the effect of nucleus diameter, nucleus elasticity, indenter's shape and location on the force-indentation curve. The developed model has also been validated with the recently reported experimental studies available in the literature. Our results suggest that the nucleus auxeticity plays a profound role in cell mechanics especially for large size nucleus. We also report the mechanical stresses induced within the hyperelastic cell model under different loading conditions that would be quite useful in decoding the interrelations between mechanical stimuli and cellular behavior of auxetic biosystems. Finally, current and potential areas of applications of our findings for regenerative therapies, tissue engineering, 3 D/4D bioprinting, and the development of meta-biomaterials are discussed.

Recent advances in AFM-based biological characterization and applications at multiple levels

Atomic force microscopy (AFM) has found a wide range of bio-applications in the past few decades due to its ability to measure biological samples in natural environments at a high spatial resolution. AFM has become a key platform in biomedical, bioengineering and drug research fields, enabling mechanical and morphological characterization of live biological systems. Hence, we provide a comprehensive review on recent advances in the use of AFM for characterizing the biomechanical properties of multi-scale biological samples, ranging from molecule, cell to tissue levels. First, we present the fundamental principles of AFM and two AFM-based models for the characterization of biomechanical properties of biological samples, covering key AFM devices and AFM bioimaging as well as theoretical models for characterizing the elasticity and viscosity of biomaterials. Then, we elaborate on a series of new experimental findings through analysis of biomechanics. Finally, we discuss the future directions and challenges. It is envisioned that the AFM technique will enable many remarkable discoveries, and will have far-reaching impacts on bio-related studies and applications in the future.

Recent Advances on the Model, Measurement Technique, and Application of Single Cell Mechanics

Since the cell was discovered by humans, it has been an important research subject for researchers. The mechanical response of cells to external stimuli and the biomechanical response inside cells are of great significance for maintaining the life activities of cells. These biomechanical behaviors have wide applications in the fields of disease research and micromanipulation. In order to study the mechanical behavior of single cells, various cell mechanics models have been proposed. In addition, the measurement technologies of single cells have been greatly developed. These models, combined with experimental techniques, can effectively explain the biomechanical behavior and reaction mechanism of cells. In this review, we first introduce the basic concept and biomechanical background of cells, then summarize the research progress of internal force models and experimental techniques in the field of cell mechanics and discuss the latest mechanical models and experimental methods. We summarize the application directions of cell mechanics and put forward the future perspectives of a cell mechanics model.

Effect of AFM Nanoindentation Loading Rate on the Characterization of Mechanical Properties of Vascular Endothelial Cell

Vascular endothelial cells form a barrier that blocks the delivery of drugs entering into brain tissue for central nervous system disease treatment. The mechanical responses of vascular endothelial cells play a key role in the progress of drugs passing through the blood-brain barrier. Although nanoindentation experiment by using AFM (Atomic Force Microscopy) has been widely used to investigate the mechanical properties of cells, the particular mechanism that determines the mechanical response of vascular endothelial cells is still poorly understood. In order to overcome this limitation, nanoindentation experiments were performed at different loading rates during the ramp stage to investigate the loading rate effect on the characterization of the mechanical properties of bEnd.3 cells (mouse brain endothelial cell line). Inverse finite element analysis was implemented to determine the mechanical properties of bEnd.3 cells. The loading rate effect appears to be more significant in short-term peak force than that in long-term force. A higher loading rate results in a larger value of elastic modulus of bEnd.3 cells, while some mechanical parameters show ambiguous regulation to the variation of indentation rate. This study provides new insights into the mechanical responses of vascular endothelial cells, which is important for a deeper understanding of the cell mechanobiological mechanism in the blood-brain barrier.