Enhanced piezoelectric fibered extracellular matrix to promote cardiomyocyte maturation and tissue formation: a 3d computational model

Mechanical and electrical stimuli play a key role in tissue formation, guiding cell processes such as cell migration, differentiation, maturation, and apoptosis. Monitoring and controlling these stimuli on in vitro experiments is not straightforward due to the coupling of these different stimuli. In addition, active and reciprocal cell–cell and cell–extracellular matrix interactions are essential to be considered during formation of complex tissue such as myocardial tissue. In this sense, computational models can offer new perspectives and key information on the cell microenvironment. Thus, we present a new computational 3D model, based on the Finite Element Method, where a complex extracellular matrix with piezoelectric properties interacts with cardiac muscle cells during the first steps of tissue formation. This model includes collective behavior and cell processes such as cell migration, maturation, differentiation, proliferation, and apoptosis. The model has employed to study the initial stages of in vitro cardiac aggregate formation, considering cell–cell junctions, under different extracellular matrix configurations. Three different cases have been purposed to evaluate cell behavior in fibered, mechanically stimulated fibered, and mechanically stimulated piezoelectric fibered extra-cellular matrix. In this last case, the cells are guided by the coupling of mechanical and electrical stimuli. Accordingly, the obtained results show the formation of more elongated groups and enhancement in cell proliferation

A computational model for cardiomyocytes mechano-electric stimulation to enhance cardiac tissue regeneration

Electrical and mechanical stimulations play a key role in cell biological processes, being essential in processes such as cardiac cell maturation, proliferation, migration, alignment, attachment, and organization of the contractile machinery. However, the mechanisms that trigger these processes are still elusive. The coupling of mechanical and electrical stimuli makes it difficult to abstract conclusions. In this sense, computational models can establish parametric assays with a low economic and time cost to determine the optimal conditions of in-vitro experiments. Here, a computational model has been developed, using the finite element method, to study cardiac cell maturation, proliferation, migration, alignment, and organization in 3D matrices, under mechano-electric stimulation. Different types of electric fields (continuous, pulsating, and alternating) in an intensity range of 50–350 Vm−1, and extracellular matrix with stiffnesses in the range of 10–40 kPa, are studied. In these experiments, the group’s morphology and cell orientation are compared to define the best conditions for cell culture. The obtained results are qualitatively consistent with the bibliography. The electric field orientates the cells and stimulates the formation of elongated groups. Group lengthening is observed when applying higher electric fields in lower stiffness extracellular matrix. Groups with higher aspect ratios can be obtained by electrical stimulation, with better results for alternating electric fields

Mechanical stimulation of cell microenvironment for cardiac muscle tissue regeneration: a 3D in-silico model

The processes in which cardiac cells are reorganized for tissue regeneration is still unclear. It is a complicated process that is orchestrated by many factors such as mechanical, chemical, thermal, and/or electrical cues. Studying and optimizing these conditions in-vitro is complicated and time costly. In such cases, in-silico numerical simulations can offer a reliable solution to predict and optimize the considered conditions for the cell culture process. For this aim, a 3D novel and enhanced numerical model has been developed to study the effect of the mechanical properties of the extracellular matrix (ECM) as well as the applied external forces in the process of the cell differentiation and proliferation for cardiac muscle tissue regeneration. The model has into account the essential cellular processes such as migration, cell–cell interaction, cell–ECM interaction, differentiation, proliferation and/or apoptosis. It has employed to study the initial stages of cardiac muscle tissue formation within a wide range of ECM stiffness (8–50 kPa). The results show that, after cell culture within a free surface ECM, cells tend to form elongated aggregations in the ECM center. The formation rate, as well as the aggregation morphology, have been found to be a function of the ECM stiffness and the applied external force. Besides, it has been found that the optimum ECM stiffness for cardiovascular tissue regeneration is in the range of 29–39 kPa, combined with the application of a mechanical stimulus equivalent to deformations of 20–25%

In-vivo cell remote control: a mecano-electro computational study

Abstract ICBB17-12: Nowadays, due to its importance for human survival, tissue andorgans regeneration have received a high attention of the scientificcommunity. For the development of this field, understanding the cellbehavior is essential forin-vivotissue and organs regeneration. Cellbehavior can be controlledin-vitro, among other stimuli, by changingthe extracellular matrix mechanical properties, applying externalforces and/or electrical field. Controlling these stimuliin-vivois nottrivial. Therefore, in this work, to remotely control the local cellenvironment, we consider a microsphere of cell size that is fabricatedfrom a piezoelectric material and charged with nanomagnetic parti-cles. This microsphere is integrated within an extracellular matrix, insuch a way, through an external magnetic field, internal forces canbe generated within the microsphere. As a result, a stiffness gradientas well as an electric field are generated around the microsphere.These cues can be controlled externally by changing the magneticfield intensity..

Role of Mechanical Cues in Cell Differentiation and Proliferation: A 3D Numerical Model

Cell differentiation, proliferation and migration are essential processes in tissue regenera- tion. Experimental evidence confirms that cell differentiation or proliferation can be regulat- ed according to the extracellular matrix stiffness. For instance, mesenchymal stem cells (MSCs) can differentiate to neuroblast, chondrocyte or osteoblast within matrices mimicking the stiffness of their native substrate. However, the precise mechanisms by which the sub- strate stiffness governs cell differentiation or proliferation are not well known. Therefore, a mechano-sensing computational model is here developed to elucidate how substrate stiff- ness regulates cell differentiation and/or proliferation during cell migration. In agreement with experimental observations, it is assumed that internal deformation of the cell (a me- chanical signal) together with the cell maturation state directly coordinates cell differentia- tion and/or proliferation. Our findings indicate that MSC differentiation to neurogenic, chondrogenic or osteogenic lineage specifications occurs within soft (0.1-1 kPa), intermedi- ate (20-25 kPa) or hard (30-45 kPa) substrates, respectively. These results are consistent with well-known experimental observations. Remarkably, when a MSC differentiate to a compatible phenotype, the average net traction force depends on the substrate stiffness in such a way that it might increase in intermediate and hard substrates but it would reduce in a soft matrix. However, in all cases the average net traction force considerably increases at the instant of cell proliferation because of cell-cell interaction. Moreover cell differentiation and proliferation accelerate with increasing substrate stiffness due to the decrease in the cell maturation time. Thus, the model provides insights to explain the hypothesis that sub- strate stiffness plays a key role in regulating cell fate during mechanotaxis

Numerical modeling of cell differentiation and proliferation in force-induced substrates via encapsulated magnetic nanoparticles

Background and objective Cell migration, differentiation, proliferation and apoptosis are the main processes in tissue regeneration. Mesenchymal Stem Cells have the potential to differentiate into many cell phenotypes such as tissue- or organ-specific cells to perform special functions. Experimental observations illustrate that differentiation and proliferation of these cells can be regulated according to internal forces induced within their Extracellular Matrix. The process of how exactly they interpret and transduce these signals is not well understood. Methods A previously developed three-dimensional (3D) computational model is here extended and employed to study how force-free substrates and force-induced substrate control cell differentiation and/or proliferation during the mechanosensing process. Consistent with experimental observations, it is assumed that cell internal deformation (a mechanical signal) in correlation with the cell maturation state directly triggers cell differentiation and/or proliferation. The Extracellular Matrix is modeled as Neo-Hookean hyperelastic material assuming that cells are cultured within 3D nonlinear hydrogels. Results In agreement with well-known experimental observations, the findings here indicate that within neurogenic (0.1–1 kPa), chondrogenic (20–25 kPa) and osteogenic (30–45 kPa) substrates, Mesenchymal Stem Cells differentiation and proliferation can be precipitated by inducing the substrate with an internal force. Therefore, cells require a longer time to grow and maturate within force-free substrates than within force-induced substrates. In the instance of Mesenchymal Stem Cells differentiation into a compatible phenotype, the magnitude of the net traction force increases within chondrogenic and osteogenic substrates while it reduces within neurogenic substrates. This is consistent with experimental studies and numerical works recently published by the same authors. However, in all cases the magnitude of the net traction force considerably increases at the instant of cell proliferation because of cell–cell interaction. Conclusions The present model provides new perspectives to delineate the role of force-induced substrates in remotely controlling the cell fate during cell–matrix interaction, which open the door for new tissue regeneration methodologies

3D numerical modeling of cell migration and cell-cell interaction

Cell migration has an important role in physiological, biological and pathological processes such as tissue morphogenesis, cell differentiation, cell proliferation, cancer development, wound healing, as well as in tissue engineering applications [1,2]. Although cell behavior during migration is not completely clear for scientists yet, it has conclusively been known that mechanical and biochemical factors strongly affect cell locomotion. Mechanical changes in a substrate, such as topographical features, boundary conditions and stiffness distribution of substrate are all thought to guide and control cell migration. There are many 2D models describing cell behavior on a substrate [3], but there are only few 3D models for this purpose [4]. Majority of them just describe a single cell migration [4], while others study the behavior of high cell populations [5]. One major problem with some of these models is that they fail to properly balance the active locomotive forces acting on the cell or generated by the cell, in some cases the models do not even include them. Some models have an active force that moves the cell, but there is no discussion on where that force is applied. The model described by Borau et al. considers the maximum principal stess for the reorientation of cell and cytoskeleton which is not accurate enough [4]. In this work we will present an improved 3D computational model to investigate the effects of the mechanical properties of the substrate on cell migration. The main objective of this project is to understand the effect of substrate stiffness on cell migration, traction force, velocity and etc. Besides, we will study how deeply the cell feels during surface migration and how the cells interact each other when they are embedded in the same substrate. To validate our model, apart from comparing the obtained results with previous experimental [6] and numerical models [4,5], we will implement experimental part which includes preparation of 3D gel with desired boundary conditions and monitoring of cell behavior during migration. To monitor the cell behavior we are going to use fluorescence microscopy to record the cell movement. This experimental part will be performed by collaboration with laboratory of Aragon Institute of Engineering Research (i3A). Refrences [1] H. Behesti and S. Marino. Cerebellar granule cells: Insights into proliferation, differentiation, and role in medulloblastoma pathogenesis. Journal Applied Physiology, 41:435445, 2009. [2] P. Martin. Wound healing: aiming for perfect skin regeneration. Science, 276:75 81, 1997. [3] P. Moreo, J.M. Garcia-Aznar, and M. Doblaré. Modeling mechanosensing and its e˙ect on the migration and proliferation of adherent cells. Acta Biomaterialia, 4:613621, 2008. [4] C. Borau, R.D. Kamm, and J.M. García-Aznar. Mechano-sensing and cell migration: a 3d model approach. Journal Physical Biology, 8:107888, 2011. [5] E. Palsson. A three-dimensional model of cell movement in multicellular systems. Future Generation Computer System, 17:835852, 2001. [6] E. Hadjipanayi, V. Mudera, and R.A. Brown. Guiding cell migration in 3d: A collagen matrix with graded directional sti˙ness. Cell Motility and the Cytoskeleton, 66:435445, 2009

Altered Mechano-Electrochemical Behavior of Articular Cartilage in Populations with Obesity

Obesity, one of the major problems in modern society, adversely affects people’s health and increases the risk of suffering degeneration in supportive tissues such as cartilage, which loses its ability to support and distribute loads. However, no specific research regarding obesity-associated alterations in the mechano-electrochemical cartilage environment has been developed. Such studies could help us to understand the first signs of cartilage degeneration when body weight increases and to establish preventive treatments to avoid cartilage deterioration. In this work, a previous mechano-electrochemical computational model has been further developed and employed to analyze and quantify the effects of obesity on the articular cartilage of the femoral hip. A comparison between the obtained results of the healthy and osteoarthritic cartilage has been made. It shows that behavioral patterns of cartilage, such as ion fluxes and cation distribution, have considerable similarities with those obtained for the early stages of osteoarthritis. Thus, an increment in the outgoing ion fluxes is produced, resulting in lower cation concentrations in all the cartilage layers. These results suggest that people with obesity, i.e. a body mass index greater than 30 kg/m2, should undergo preventive treatments for osteoarthritis to avoid homeostatic alterations and, subsequent, tissue deterioration

A new reliability-based data-driven approach to simulation-based models

Data Science has burst into simulation-based en-gineering sciences with an impressive impulse. However, data are never uncertainty-free and a suitable approach is needed to face data measurement errors and their intrinsic randomness in problems with well-established physical constraints. We face this problem by hybridizing a standard mathematical modeling approach with a new data-driven solver accounting for the phenomenological part of the problem and able to handle the uncertainty of input data in an intelligent way. The reliability-based data-driven procedure performance is evaluated in a simple but illustrative unidimensional problem showing, in contrast with other data-driven solvers, better convergence, higher accuracy, clearer interpretation and major flexibility

Cell behavior under hypoxic conditions. Computational 3D model

During the early stages of bone regeneration, oxygen plays a key role, recruiting mesenchymal stem cells and regulating the processes of differentiation, proliferation, and apoptosis. To study in these effects, a 3D computational model has been developed, where the effects of oxygen in the mentioned processes are considered