Model of cellular mechanotransduction via actin stress fibers

Mechanical stresses due to blood flow regulate vascular endothelial cell structure and function and play a key role in arterial physiology and pathology. In particular, the development of atherosclerosis has been shown to correlate with regions of disturbed blood flow where endothelial cells are round and have a randomly organized cytoskeleton. Thus, deciphering the relation between the mechanical environment, cell structure, and cell function is a key step toward understanding the early development of atherosclerosis. Recent experiments have demonstrated very rapid (\(\sim \)100 ms) and long-distance (\(\sim \)10 \(\upmu \)m) cellular mechanotransduction in which prestressed actin stress fibers play a critical role. Here, we develop a model of mechanical signal transmission within a cell by describing strains in a network of prestressed viscoelastic stress fibers following the application of a force to the cell surface. We find force transmission dynamics that are consistent with experimental results. We also show that the extent of stress fiber alignment and the direction of the applied force relative to this alignment are key determinants of the efficiency of mechanical signal transmission. These results are consistent with the link observed experimentally between cytoskeletal organization, mechanical stress, and cellular responsiveness to stress. Based on these results, we suggest that mechanical strain of actin stress fibers under force constitutes a key link in the mechanotransduction chain.     

A method for three-dimensional quantification of vascular smooth muscle orientation: application in viable murine carotid arteries

When studying in vivo arterial mechanical behaviour using constitutive models, smooth muscle cells (SMCs) should be considered, while they play an important role in regulating arterial vessel tone. Current constitutive models assume a strictly circumferential SMC orientation, without any dispersion. We hypothesised that SMC orientation would show considerable dispersion in three dimensions and that helical dispersion would be greater than transversal dispersion. To test these hypotheses, we developed a method to quantify the 3D orientation of arterial SMCs. Fluorescently labelled SMC nuclei of left and right carotid arteries of ten mice were imaged using two-photon laser scanning microscopy. Arteries were imaged at a range of luminal pressures. 3D image processing was used to identify individual nuclei and their orientations. SMCs showed to be arranged in two distinct layers. Orientations were quantified by fitting a Bingham distribution to the observed orientations. As hypothesised, orientation dispersion was much larger helically than transversally. With increasing luminal pressure, transversal dispersion decreased significantly, whereas helical dispersion remained unaltered. Additionally, SMC orientations showed a statistically significant (\(p < 0.05\)) mean right-handed helix angle in both left and right arteries and in both layers, which is a relevant finding from a developmental biology perspective. In conclusion, vascular SMC orientation (1) can be quantified in 3D; (2) shows considerable dispersion, predominantly in the helical direction; and (3) has a distinct right-handed helical component in both left and right carotid arteries. The obtained quantitative distribution data are instrumental for constitutive modelling of the artery wall and illustrate the merit of our method.     

Modeling of cell adhesion and deformation mediated by receptor–ligand interactions

The current work is devoted to studying adhesion and deformation of biological cells mediated by receptors and ligands in order to enhance the existing models. Due to the sufficient in-plane continuity and fluidity of the phospholipid molecules, an isotropic continuum fluid membrane is proposed for modeling the cell membrane. The developed constitutive model accounts for the influence of the presence of receptors on the deformation and adhesion of the cell membrane through the introduction of spontaneous area dilation. Motivated by physics, a nonlinear receptor–ligand binding force is introduced based on charge-induced dipole interaction. Diffusion of the receptors on the membrane is governed by the receptor–ligand interaction via Fick’s Law and receptor-ligand interaction. The developed model is then applied to study the deformation and adhesion of a biological cell. The proposed model is used to study the role of the material, binding, spontaneous area dilation and environmental properties on the deformation and adhesion of the cell.     

Failure properties of vena cava tissue due to deep penetration during filter insertion

In this work, we use an in-vitro mechanical test to explore the resistance of biaxially stretched vena cava tissue against deep perforation and a methodology which integrates experimental and numerical modeling to identify constitutive fracture properties of the vena cava. Six sheep vena cava were harvested just after killing, and cyclic uniaxial tension tests in longitudinal and circumferential directions and biaxial deep penetration tests were performed. After that, we use a nonlinear finite element model to simulate in vitro penetration of the cava tissue in order to fit the fracture properties under penetration of the vena cava by defining a cohesive fracture zone. An iterative process was developed in order to fit the fracture properties of the vena cava using the previously obtained experimental results. The proposed solutions were obtained with fracture energy of 0.22 or 0.33 N/mm. In comparison with the experimental data, the simulation using \(\delta _{0}=0.01\,\hbox {mm}\), \(\delta _{r}=0.35\,\hbox {mm}\), and \(K=220\, \hbox {N}/\hbox {mm}^{3}\) parameters (\(F_{\hbox {max}}=0.92\)) is in good agreement with results from penetration experiments of cava tissue. It is noticeable that the parameter estimation process of the fracture behavior is more accurate than the estimation process of the elastic behavior for the toe region of the curve.     

Prediction of apparent trabecular bone stiffness through fourth-order fabric tensors

The apparent stiffness tensor is an important mechanical parameter for characterizing trabecular bone. Previous studies have modeled this parameter as a function of mechanical properties of the tissue, bone density, and a second-order fabric tensor, which encodes both anisotropy and orientation of trabecular bone. Although these models yield strong correlations between observed and predicted stiffness tensors, there is still space for reducing accuracy errors. In this paper, we propose a model that uses fourth-order instead of second-order fabric tensors. First, the totally symmetric part of the stiffness tensor is assumed proportional to the fourth-order fabric tensor in the logarithmic scale. Second, the asymmetric part of the stiffness tensor is derived from relationships among components of the harmonic tensor decomposition of the stiffness tensor. The mean intercept length (MIL), generalized MIL (GMIL), and fourth-order global structure tensor were computed from images acquired through microcomputed tomography of 264 specimens of the femur. The predicted tensors were compared to the stiffness tensors computed by using the micro-finite element method (\(\upmu \)FE), which was considered as the gold standard, yielding strong correlations (\(R^2\) above 0.962). The GMIL tensor yielded the best results among the tested fabric tensors. The Frobenius error, geodesic error, and the error of the norm were reduced by applying the proposed model by 3.75, 0.07, and 3.16 %, respectively, compared to the model by Zysset and Curnier (Mech Mater 21(4):243–250, 1995) with the second-order MIL tensor. From the results, fourth-order fabric tensors are a good alternative to the more expensive \(\upmu \)FE stiffness predictions.     

A homogenized constrained mixture (and mechanical analog) model for growth and remodeling of soft tissue

Most mathematical models of the growth and remodeling of load-bearing soft tissues are based on one of two major approaches: a kinematic theory that specifies an evolution equation for the stress-free configuration of the tissue as a whole or a constrained mixture theory that specifies rates of mass production and removal of individual constituents within stressed configurations. The former is popular because of its conceptual simplicity, but relies largely on heuristic definitions of growth; the latter is based on biologically motivated micromechanical models, but suffers from higher computational costs due to the need to track all past configurations. In this paper, we present a temporally homogenized constrained mixture model that combines advantages of both classical approaches, namely a biologically motivated micromechanical foundation, a simple computational implementation, and low computational cost. As illustrative examples, we show that this approach describes well both cell-mediated remodeling of tissue equivalents in vitro and the growth and remodeling of aneurysms in vivo. We also show that this homogenized constrained mixture model suggests an intimate relationship between models of growth and remodeling and viscoelasticity. That is, important aspects of tissue adaptation can be understood in terms of a simple mechanical analog model, a Maxwell fluid (i.e., spring and dashpot in series) in parallel with a “motor element” that represents cell-mediated mechanoregulation of extracellular matrix. This analogy allows a simple implementation of homogenized constrained mixture models within commercially available simulation codes by exploiting available models of viscoelasticity.     

A microstructurally based continuum model of cartilage viscoelasticity and permeability incorporating measured statistical fiber orientations

The remarkable mechanical properties of cartilage derive from an interplay of isotropically distributed, densely packed and negatively charged proteoglycans; a highly anisotropic and inhomogeneously oriented fiber network of collagens; and an interstitial electrolytic fluid. We propose a new 3D finite strain constitutive model capable of simultaneously addressing both solid (reinforcement) and fluid (permeability) dependence of the tissue’s mechanical response on the patient-specific collagen fiber network. To represent fiber reinforcement, we integrate the strain energies of single collagen fibers—weighted by an orientation distribution function (ODF) defined over a unit sphere—over the distributed fiber orientations in 3D. We define the anisotropic intrinsic permeability of the tissue with a structure tensor based again on the integration of the local ODF over all spatial fiber orientations. By design, our modeling formulation accepts structural data on patient-specific collagen fiber networks as determined via diffusion tensor MRI. We implement our new model in 3D large strain finite elements and study the distributions of interstitial fluid pressure, fluid pressure load support and shear stress within a cartilage sample under indentation. Results show that the fiber network dramatically increases interstitial fluid pressure and focuses it near the surface. Inhomogeneity in the tissue’s composition also increases fluid pressure and reduces shear stress in the solid. Finally, a biphasic neo-Hookean material model, as is available in commercial finite element codes, does not capture important features of the intra-tissue response, e.g., distributions of interstitial fluid pressure and principal shear stress.     

Yeasts from peat in a tropical peat swamp forest in Thailand and their ability to produce ethanol,indole-3-acetic acid and extracellular enzymes

This study aimed to isolate and identify yeasts from peat in To Daeng peat swamp forest in southern of Thailand, and to investigate their ability to produce ethanol from glucose and xylose and to produce indole-3-acetic acid (IAA) and extracellular enzymes. A total of 65 yeast strains were obtained from 15 peat samples using an enrichment technique, and 61 strains were identified to be five species belonging to the phylum Ascomycota, namely Cyberlindnera subsufficiens, Debaryomyces fabryi, Meyerozyma guilliermondii, Saturnispora diversa and Schwanniomyces polymorphus var. africanus, and five species of the phylum Basidiomycota, namely Cryptococcus taiwanensis pro tem, Cutaneotrichosporon mucoides, Papiliotrema flavescens, Papiliotrema laurentii and Rhodotorula mucilaginosa. Four strains were unidentified and require further analysis. They differed from the type strain of P. flavescens by two nucleotide substitutions in the D1/D2 region of the LSU rRNA gene and nine nucleotide substitutions in the ITS region. R. mucilaginosa was the most prevalent yeast species, followed by S. polymorphus var. africanus, Cy. subsufficiens and D. fabryi. None of the yeast strains obtained in this study were able to ferment xylose to ethanol, but all ascomycetous yeast strains produced ethanol from glucose in a range of 9.0–58.0 g/L, with Cy. subsufficiens DMKU-YNB42-1 producing the highest ethanol concentration. A total of 62 strains produced IAA in a range of 9.0 to 66.9 mg/L, with the highest IAA produced by R. mucilaginosa DMKU-Y33-A. Investigation of the production of cellulases, xylanase, pectinase, amylase, protease and lipase revealed that all 65 yeast strains produced at least one extracellular enzyme, a lipase.     

Hydrogen production by the hyperthermophilic bacterium <Emphasis Type="Italic">Thermotoga maritima</Emphasis> part I: effects of sulfured nutriments,with thiosulfate as model,on hydrogen production and growth

Background

Thermotoga maritima and T. neapolitana are hyperthermophile bacteria chosen by many research teams to produce bio-hydrogen because of their potential to ferment a wide variety of sugars with the highest theoretical H₂/glucose yields. However, to develop economically sustainable bio-processes, the culture medium formulation remained to be optimized. The main aim of this study was to quantify accurately and specifically the effect of thiosulfate, used as sulfured nutriment model, on T. maritima growth, yields and productivities of hydrogen. The results were obtained from batch cultures, performed into a bioreactor, carefully controlled, and specifically designed to prevent the back-inhibition by hydrogen.

Results

Among sulfured nutriments tested, thiosulfate, cysteine, and sulfide were found to be the most efficient to stimulate T. maritima growth and hydrogen production. In particular, under our experimental conditions (glucose 60 mmol L^?1 and yeast extract 1 g L^?1), the cellular growth was limited by thiosulfate concentrations lower than 0.06 mmol L^?1. Under these conditions, the cellular yield on thiosulfate (Y X/Thio) could be determined at 3617 mg mmol^?1. In addition, it has been shown that the limitations of T. maritima growth by thiosulfate lead to metabolic stress marked by a significant metabolic shift of glucose towards the production of extracellular polysaccharides (EPS). Finally, it has been estimated that the presence of thiosulfate in the T. maritima culture medium significantly increased the cellular and hydrogen productivities by a factor 6 without detectable sulfide production.

Conclusions

The stimulant effects of thiosulfate at very low concentrations on T. maritima growth have forced us to reconsider its role in this species and more probably also in all thiosulfato-reducer hyperthermophiles. Henceforth, thiosulfate should be considered in T. maritima as (1) an essential sulfur source for cellular materials when it is present at low concentrations (about 0.3 mmol g^?1 of cells), and (2) as both sulfur source and detoxifying agent for H₂ when thiosulfate is present at higher concentrations and, when, simultaneously, the pH₂ is high. Finally, to improve the hydrogen production in bio-processes using Thermotoga species, it should be recommended to incorporate thiosulfate in the culture medium.