Tissue-level Model Research Articles

MODELLING PARACRINE CHONDROCYTE COMMUNICATION EFFECTS AT THE TISSUE LEVEL

Osteoarthritis (OA) leads to articular cartilage degradation, following complex dysregulation of chondrocyte's metabolism towards a catabolic state. Mechanical and biochemical signals are involved and need to be considered to understand the condition. Regulatory network-based models (RNM) successfully simulated the biological activity of the chondrocyte and the transduction of mechanical signals at the molecular and cell levels. However, the knowledge gap between single-cell regulation and intercellular communication in tissue volumes hinders the interpretability of such models at larger scales. Accordingly, a novel tissue-level biochemical model is proposed. We hypothesise that it is possible to simulate interacting network effects through the transport of diluted species in a finite-element model, to grasp relevant dynamics of cell and tissue regulation in OA. Chondrocyte RNM equations were translated into a reaction term of 18 multi-species diffusion model (e.g., 3 anti-inflammatory and 8 pro-inflammatory interleukins, 3 pro-anabolic and 1 pro-catabolic growth factors, 2 nociceptive factors and 2 pro-inflammatory cytokines). Elements with RNM reaction terms represented the chondrocytes and were distributed randomly through the model, according to known cellular density in the knee cartilage, and could both react to and produce diffusive entities through the pericellular matrix, associated with reduced diffusion coefficients. The model was constructed over a 2D square of 0.47 mm sides considered to be in the middle of the cartilage, so boundary conditions were settled as periodic. Different simulations were initialised with initial concentrations of either healthy or pro-OA mediators. Preliminary results showed that, independently of the initial conditions, the chondrocytes successfully evolved into anabolic states, in absence of sustained pro-catabolic external stimulations, in contrast to single-cell RNM [2]. Our intercellular model suggests that paracrine communication may increase robustness towards cartilage maintenance, and future tests shall reveal new OA dynamics.Acknowledgements: Funding was provided by the European Commission (ERC-2021-CoG-O-Health-101044828).

Estimating the probability of early afterdepolarizations and predicting arrhythmic risk associated with long QT syndrome type 1 mutations

Early afterdepolarizations (EADs) are action potential (AP) repolarization abnormalities that can trigger lethal arrhythmias. Simulations using biophysically detailed cardiac myocyte models can reveal how model parameters influence the probability of these cellular arrhythmias; however, such analyses can pose a huge computational burden. We have previously developed a highly simplified approach in which logistic regression models (LRMs) map parameters of complex cell models to the probability of ectopic beats. Here, we extend this approach to predict the probability of EADs (P(EAD)) as a mechanistic metric of arrhythmic risk. We use the LRM to investigate how changes in parameters of the slow-activating delayed rectifier current (IKs) affect P(EAD) for 17 different long QT syndrome type 1 (LQTS1) mutations. In this LQTS1 clinical arrhythmic risk prediction task, we compared P(EAD) for these 17 mutations with two other recently published model-based arrhythmia risk metrics (AP morphology metric across populations of myocyte models and transmural repolarization prolongation based on a one-dimensional [1D] tissue-level model). These model-based risk metrics yield similar prediction performance; however, each fails to stratify clinical risk for a significant number of the 17 studied LQTS1 mutations. Nevertheless, an interpretable ensemble model using multivariate linear regression built by combining all of these model-based risk metrics successfully predicts the clinical risk of 17 mutations. These results illustrate the potential of computational approaches in arrhythmia risk prediction.

Tissue-level alveolar epithelium model for recapitulating SARS-CoV-2 infection and cellular plasticity

Pulmonary sequelae following COVID-19 pneumonia have been emerging as a challenge; however, suitable cell sources for studying COVID-19 mechanisms and therapeutics are currently lacking. In this paper, we present a standardized primary alveolar cell culture method for establishing a human alveolar epithelium model that can recapitulate viral infection and cellular plasticity. The alveolar model is infected with a SARS-CoV-2 pseudovirus, and the clinically relevant features of the viral entry into the alveolar type-I/II cells, cytokine production activation, and pulmonary surfactant destruction are reproduced. For this damaged alveolar model, we find that the inhibition of Wnt signaling via XAV939 substantially improves alveolar repair function and prevents subsequent pulmonary fibrosis. Thus, the proposed alveolar cell culture strategy exhibits potential for the identification of pathogenesis and therapeutics in basic and translational research.

Classifying Breast Histopathology Images with a Ductal Instance-Oriented Pipeline.

In this study, we propose the Ductal Instance-Oriented Pipeline (DIOP) that contains a duct-level instance segmentation model, a tissue-level semantic segmentation model, and three-levels of features for diagnostic classification. Based on recent advancements in instance segmentation and the Mask RCNN model, our duct-level segmenter tries to identify each ductal individual inside a microscopic image; then, it extracts tissue-level information from the identified ductal instances. Leveraging three levels of information obtained from these ductal instances and also the histopathology image, the proposed DIOP outperforms previous approaches (both feature-based and CNN-based) in all diagnostic tasks; for the four-way classification task, the DIOP achieves comparable performance to general pathologists in this unique dataset. The proposed DIOP only takes a few seconds to run in the inference time, which could be used interactively on most modern computers. More clinical explorations are needed to study the robustness and generalizability of this system in the future.

Stress and Strain Distribution Patterns in Bone around Tissue- and Bone-Level Implant-Supported Mandibular Overdentures Using Three-Dimensional Finite-Element Analysis.

Our aim is to investigate the effect of implant placement in two positions (bone level and tissue level) on stress and strain distribution around mandibular implant overdentures. We use two models of mandibular overdentures. Taper implants are inserted and collimated between the lateral and canine teeth. All structures are scanned, digitized, and three-dimensioned (3D) model designed. We apply a vertical load of 100 N simultaneously on the central fossa of the mandibular first molar of the two models (bone- and tissue-level implant). Stress and strain values are obtained using 3D finite-element analysis (FEA). In comparison to the tissue-level model, bone-level implants can reduce overdenture movement and tension by 0.8 μm. The results of this study show that using bone-level implants can reduce tension on the prosthesis part of the overdenture and the bone around the implants as well as on the movement of the distal end of the mandibular overdenture. We found that bone strain occurred around implants within physiological limits in model 1 (bone level) compared to model 2 (tissue level). This shows that the distribution of physical forces in bone-level implants generally produces better results than those of issue-level implants. However, more research on the subject is needed.

Advanced computational workflow for the multi-scale modeling of the bone metabolic processes.

Multi-scale modeling of the musculoskeletal system plays an essential role in the deep understanding of complex mechanisms underlying the biological phenomena and processes such as bone metabolic processes. Current multi-scale models suffer from the isolation of sub-models at each anatomical scale. The objective of this present work was to develop a new fully integrated computational workflow for simulating bone metabolic processes at multi-scale levels. Organ-level model employs multi-body dynamics to estimate body boundary and loading conditions from body kinematics. Tissue-level model uses finite element method to estimate the tissue deformation and mechanical loading under body loading conditions. Finally, cell-level model includes bone remodeling mechanism through an agent-based simulation under tissue loading. A case study on the bone remodeling process located on the human jaw was performed and presented. The developed multi-scale model of the human jaw was validated using the literature-based data at each anatomical level. Simulation outcomes fall within the literature-based ranges of values for estimated muscle force, tissue loading and cell dynamics during bone remodeling process. This study opens perspectives for accurately simulating bone metabolic processes using a fully integrated computational workflow leading to a better understanding of the musculoskeletal system function from multiple length scales as well as to provide new informative data for clinical decision support and industrial applications.

Fruit shape diversity in the Brassicaceae is generated by varying patterns of anisotropy.

Fruits exhibit a vast array of different 3D shapes, from simple spheres and cylinders to more complex curved forms; however, the mechanism by which growth is oriented and coordinated to generate this diversity of forms is unclear. Here, we compare the growth patterns and orientations for two very different fruit shapes in the Brassicaceae: the heart-shaped Capsella rubella silicle and the near-cylindrical Arabidopsis thaliana silique. We show, through a combination of clonal and morphological analyses, that the different shapes involve different patterns of anisotropic growth during three phases. These experimental data can be accounted for by a tissue-level model in which specified growth rates vary in space and time and are oriented by a proximodistal polarity field. The resulting tissue conflicts lead to deformation of the tissue as it grows. The model allows us to identify tissue-specific and temporally specific activities required to obtain the individual shapes. One such activity may be provided by the valve-identity gene FRUITFULL, which we show through comparative mutant analysis to modulate fruit shape during post-fertilisation growth of both species. Simple modulations of the model presented here can also broadly account for the variety of shapes in other Brassicaceae species, thus providing a simplified framework for fruit development and shape diversity.

A meso-scale layer-specific structural constitutive model of the mitral heart valve leaflets

Fundamental to developing a deeper understanding of pathophysiological remodeling in mitral valve (MV) disease is the development of an accurate tissue-level constitutive model. In the present work, we developed a novel meso-scale (i.e. at the level of the fiber, 10–100μm in length scale) structural constitutive model (MSSCM) for MV leaflet tissues. Due to its four-layer structure, we focused on the contributions from the distinct collagen and elastin fiber networks within each tissue layer. Requisite collagen and elastin fibrous structural information for each layer were quantified using second harmonic generation microscopy and conventional histology. A comprehensive mechanical dataset was also used to guide model formulation and parameter estimation. Furthermore, novel to tissue-level structural constitutive modeling approaches, we allowed the collagen fiber recruitment function to vary with orientation. Results indicated that the MSSCM predicted a surprisingly consistent mean effective collagen fiber modulus of 162.72MPa, and demonstrated excellent predictive capability for extra-physiological loading regimes. There were also anterior-posterior leaflet-specific differences, such as tighter collagen and elastin fiber orientation distributions (ODF) in the anterior leaflet, and a thicker and stiffer atrialis in the posterior leaflet. While a degree of angular variance was observed, the tight valvular tissue ODF also left little room for any physically meaningful angular variance in fiber mechanical responses. Finally, a novel fibril-level (0.1–1μm) validation approach was used to compare the predicted collagen fiber/fibril mechanical behavior with extant MV small angle X-ray scattering data. Results demonstrated excellent agreement, indicating that the MSSCM fully captures the tissue-level function. Future utilization of the MSSCM in computational models of the MV will aid in producing highly accurate simulations in non-physiological loading states that can occur in repair situations, as well as guide the form of simplified models for real-time simulation tools.

The influence and biomechanical role of cartilage split line pattern on tibiofemoral cartilage stress distribution during the stance phase of gait.

This study presents an evaluation of the role that cartilage fibre 'split line' orientation plays in informing femoral cartilage stress patterns. A two-stage model is presented consisting of a whole knee joint coupled to a tissue-level cartilage model for computational efficiency. The whole joint model may be easily customised to any MRI or CT geometry using free-form deformation. Three 'split line' patterns (medial-lateral, anterior-posterior and random) were implemented in a finite element model with constitutive properties referring to this 'split line' orientation as a finite element fibre field. The medial-lateral orientation was similar to anatomy and was derived from imaging studies. Model predictions showed that 'split lines' are formed along the line of maximum principal strains and may have a biomechanical role of protecting the cartilage by limiting the cartilage deformation to the area of higher cartilage thickness.

High Rotation Rate Behavior of Cervical Spine Segments in Flexion and Extension

Numerical finite element (FE) models of the neck have been developed to simulate occupant response and predict injury during motor vehicle collisions. However, there is a paucity of data on the response of young cervical spine segments under dynamic loading in flexion and extension, which is essential for the development or validation of tissue-level FE models. This limitation was identified during the development and validation of the FE model used in this study. The purpose of this study was to measure the high rotation rate loading response of human cervical spine segments in flexion and extension, and to investigate a new tissue-level FE model of the cervical spine with the experimental data to address a limitation in available data. Four test samples at each segment level from C2-C3 to C7-T1 were dissected from eight donors and were tested to 10 deg of rotation at 1 and 500 deg/s in flexion and extension using a custom built test apparatus. There was strong evidence (p < 0.05) of increased stiffness at the higher rotation rate above 4 deg of rotation in flexion and at 8 deg and 10 deg of rotation in extension. Cross-correlation software, Cora, was used to evaluate the fit between the experimental data and model predictions. The average rating was 0.771, which is considered to demonstrate a good correlation to the experimental data.

Mechanical modelling quantifies the functional importance of outer tissue layers during root elongation and bending.

Root elongation and bending require the coordinated expansion of multiple cells of different types. These processes are regulated by the action of hormones that can target distinct cell layers. We use a mathematical model to characterise the influence of the biomechanical properties of individual cell walls on the properties of the whole tissue.Taking a simple constitutive model at the cell scale which characterises cell walls via yield and extensibility parameters, we derive the analogous tissue-level model to describe elongation and bending. To accurately parameterise the model, we take detailed measurements of cell turgor, cell geometries and wall thicknesses.The model demonstrates how cell properties and shapes contribute to tissue-level extensibility and yield. Exploiting the highly organised structure of the elongation zone (EZ) of the Arabidopsis root, we quantify the contributions of different cell layers, using the measured parameters. We show how distributions of material and geometric properties across the root cross-section contribute to the generation of curvature, and relate the angle of a gravitropic bend to the magnitude and duration of asymmetric wall softening.We quantify the geometric factors which lead to the predominant contribution of the outer cell files in driving root elongation and bending.

Bridging Population and Tissue Scale Tumor Dynamics: A New Paradigm for Understanding Differences in Tumor Growth and Metastatic Disease

To provide a better understanding of the relationship between primary tumor growth rates and metastatic burden, we present a method that bridges tumor growth dynamics at the population level, extracted from the SEER database, to those at the tissue level. Specifically, with this method, we are able to relate estimates of tumor growth rates and metastatic burden derived from a population-level model to estimates of the primary tumor vascular response and the circulating tumor cell (CTC) fraction derived from a tissue-level model. Variation in the population-level model parameters produces differences in cancer-specific survival and cure fraction. Variation in the tissue-level model parameters produces different primary tumor dynamics that subsequently lead to different growth dynamics of the CTCs. Our method to bridge the population and tissue scales was applied to lung and breast cancer separately, and the results were compared. The population model suggests that lung tumors grow faster and shed a significant number of lethal metastatic cells at small sizes, whereas breast tumors grow slower and do not significantly shed lethal metastatic cells until becoming larger. Although the tissue-level model does not explicitly model the metastatic population, we are able to disengage the direct dependency of the metastatic burden on primary tumor growth by introducing the CTC population as an intermediary and assuming dependency. We calibrate the tissue-level model to produce results consistent with the population model while also revealing a more dynamic relationship between the primary tumor and the CTCs. This leads to exponential tumor growth in lung and power law tumor growth in breast. We conclude that the vascular response of the primary tumor is a major player in the dynamics of both the primary tumor and the CTCs, and is significantly different in breast and lung cancer.

Electro-Chemo-Mechanical Modeling of the Artery Myogenic Response

ABSTRACTActive contraction of smooth muscle results in the myogenic response and vasomotion of arteries, which adjusts the blood flow and nutrient supply of the organism. It involves coupled electrobiochemical and chemomechanical processes. This paper presents a new constitutive model to describe the myogenic response of the artery wall under different transmural pressures. The model includes two major components: a cell-level model for the electrobiochemical process, and a tissue-level model for the chemomechanical coupling. The electrochemical model is a lumped Hodgkin-Huxley-type cell membrane model for the nanoscopic ionic currents: calcium, sodium, and potassium. The calculated calcium concentration serves as input for the chemomechanical portion of the model; its molecular binding and the reactions with other enzymes cause the relative sliding of thin and thick filaments of the contractile unit. In the chemomechanical model, a new nonlinear viscoelastic model is introduced to describe the time varying behavior of the smooth muscle. Specifically, this model captures the filament overlap effect, active stress evolution, initial velocity, and elastic recoil in the media layer. Using the proposed constitutive model and a thin-walled equilibrium equation, the myogenic response is calculated for different transmural pressures. The integrated model is able to capture the pressure-diameter relationship incorporating fewer parameters than previous work and with clear physical meanings.

Effects of Regional Mitochondrial Depolarization on Electrical Propagation

Sudden cardiac death often involves arrhythmias triggered by metabolic stress. Loss of mitochondrial function is thought to contribute to the arrhythmogenic substrate, but how mitochondria contribute to uncoordinated electrical activity is poorly understood. It has been proposed that the formation of metabolic current sinks, caused by the nonuniform collapse of mitochondrial inner membrane potential (ΔΨm), contributes to re-entrant arrhythmias because ΔΨm depolarization is tightly coupled to the activation of sarcolemmal ATP-sensitive K(+) channels, hastening action potential repolarization and shortening the refractory period. Here, we use computational and experimental methods to investigate how ΔΨm instability can induce re-entrant arrhythmias. We develop the first tissue-level model of cardiac electrical propagation incorporating cellular electrophysiology, excitation-contraction coupling, mitochondrial energetics, and reactive oxygen species balance. Simulations show that re-entry and fibrillation can be initiated by regional ΔΨm loss because of the disparity of refractory periods inside and outside the metabolic sink. Computational results are compared with the effects of a metabolic sink generated experimentally by local perfusion of a mitochondrial uncoupler in a monolayer of cardiac myocytes. The results demonstrate that regional mitochondrial depolarization triggered by oxidative stress activates sarcolemmal ATP-sensitive K(+) currents to form a metabolic sink. Consequent shortening of the action potential inside, but not outside, the sink increases the propensity for re-entry. ΔΨm recovery during pacing can lead to novel mechanisms of ectopic activation. The findings highlight the importance of mitochondria as potential therapeutic targets for sudden death associated with cardiovascular disease.

Evaluation of a post-processing approach for multiscale analysis of biphasic mechanics of chondrocytes

Understanding the mechanical behaviour of chondrocytes as a result of cartilage tissue mechanics has significant implications for both evaluation of mechanobiological function and to elaborate on damage mechanisms. A common procedure for prediction of chondrocyte mechanics (and of cell mechanics in general) relies on a computational post-processing approach where tissue-level deformations drive cell-level models. Potential loss of information in this numerical coupling approach may cause erroneous cellular-scale results, particularly during multiphysics analysis of cartilage. The goal of this study was to evaluate the capacity of first- and second-order data passing to predict chondrocyte mechanics by analysing cartilage deformations obtained for varying complexity of loading scenarios. A tissue-scale model with a sub-region incorporating representation of chondron size and distribution served as control. The post-processing approach first required solution of a homogeneous tissue-level model, results of which were used to drive a separate cell-level model (same characteristics as the sub-region of control model). The first-order data passing appeared to be adequate for simplified loading of the cartilage and for a subset of cell deformation metrics, for example, change in aspect ratio. The second-order data passing scheme was more accurate, particularly when asymmetric permeability of the tissue boundaries was considered. Yet, the method exhibited limitations for predictions of instantaneous metrics related to the fluid phase, for example, mass exchange rate. Nonetheless, employing higher order data exchange schemes may be necessary to understand the biphasic mechanics of cells under lifelike tissue loading states for the whole time history of the simulation.

Shear strength behavior of human trabecular bone

The shear strength of human trabecular bone may influence overall bone strength under fall loading conditions and failure at bone-implant interfaces. Here, we sought to compare shear and compressive yield strengths of human trabecular bone and elucidate the underlying failure mechanisms. We analyzed 54 specimens (5-mm cubes), all aligned with the main trabecular orientation and spanning four anatomic sites, 44 different cadavers, and a wide range of bone volume fraction (0.06–0.38). Micro-CT-based non-linear finite element analysis was used to assess the compressive and shear strengths and the spatial distribution of yielded tissue; the tissue-level constitutive model allowed for kinematic non-linearity and yielding with strength asymmetry. We found that the computed values of both the shear and compressive strengths depended on bone volume fraction via power law relations having an exponent of 1.7 (R2=0.95 shear; R2=0.97 compression). The ratio of shear to compressive strengths (mean±SD, 0.44±0.16) did not depend on bone volume fraction (p=0.24) but did depend on microarchitecture, most notably the intra-trabecular standard deviation in trabecular spacing (R2=0.23, p<0.005). For shear, the main tissue-level failure mode was tensile yield of the obliquely oriented trabeculae. By contrast, for compression, specimens having low bone volume fraction failed primarily by large-deformation-related tensile yield of horizontal trabeculae and those having high bone volume failed primarily by compressive yield of vertical trabeculae. We conclude that human trabecular bone is generally much weaker in shear than compression at the apparent level, reflecting different failure mechanisms at the tissue level.

Culturing Bovine Nucleus Pulposus Explants by Balancing Medium Osmolarity

Regenerative therapies are promising treatments for early intervertebral disc degeneration. To test their efficacy, an in vitro tissue-level model would be valuable. Nucleus pulposus (NP) explant culture may constitute such a model, as the earliest signs of degeneration are in the NP. However, in NP explant cultures, balancing tissue osmolarity is crucial to preventing swelling, proteoglycan (PG) loss and, therefore, maintaining a native cell environment. In this study, we investigated the effect of medium osmolarity on NP explants. We hypothesized that balancing the inherent tissue osmolarity would prevent swelling and thus maintain NP tissue in a native state. Bovine NP explants were cultured for 21 days in hypo-, iso-, and hyper-tonic conditions using either sucrose or polyethylene glycol (PEG) to raise medium osmolarity. Explants were analyzed for water and biochemical content, cell viability, gene expression, and tissue histology, and compared to day 0 samples. In hypo-tonic and both sucrose cultures, swelling was not prevented, resulting in PG loss and changes in cell behavior. Only PEG cultures maintained water and biochemical content and a histological aspect similar to those of native tissue, with better results for hyper- than for iso-tonic conditions. Using PEG to raise culture medium osmolarity, we were able to maintain the NP tissue specific matrix composition, important for disc cell behavior. This approach, thus, constitutes a promising model to test regenerative therapies for early intervertebral disc degeneration.

A Tissue-Level Electromechanical Model of the Left Ventricle: Application to the Analysis of Intraventricular Pressure

The ventricular pressure profile is characteristic of the cardiac contraction progress and is useful to evaluate the cardiac performance. In this contribution, a tissue-level electromechanical model of the left ventricle is proposed, to assist the interpretation of left ventricular pressure waveforms. The left ventricle has been modeled as an ellipsoid composed of twelve mechano-hydraulic sub-systems. The asynchronous contraction of these twelve myocardial segments has been represented in order to reproduce a realistic pressure profiles. To take into account the different energy domains involved, the tissue-level scale and to facilitate the building of a modular model, multiple formalisms have been used: Bond Graph formalism for the mechano-hydraulic aspects and cellular automata for the electrical activation. An experimental protocol has been defined to acquire ventricular pressure signals from three pigs, with different afterload conditions. Evolutionary Algorithms have been used to identify the model parameters in order to minimize the error between experimental and simulated ventricular pressure signals. Simulation results show that the model is able to reproduce experimental ventricular pressure. In addition, electro-mechanical activation times have been determined in the identification process. For example, the maximum electrical activation time is reached, respectively, 96.5, 139.3 and 131.5 ms for the first, second, and third pigs. These preliminary results are encouraging for the application of the model on non-invasive data like ECG, arterial pressure or myocardial strain.

In-Situ Deformation of the Aortic Valve Interstitial Cell Nucleus Under Diastolic Loading

Within the aortic valve (AV) leaflet resides a population of interstitial cells (AVICs), which serve to maintain tissue structural integrity via protein synthesis and enzymatic degradation. AVICs are typically characterized as myofibroblasts, exhibit phenotypic plasticity, and may play an important role in valve pathophysiology. While it is known that AVICs can respond to mechanical stimuli in vitro, the level of in vivo AVIC deformation and its relation to local collagen fiber reorientation during the cardiac cycle remain unknown. In the present study, the deformation of AVICs was investigated using porcine AV glutaraldehyde fixed under 0-90 mm Hg transvalvular pressures. The resulting change in nuclear aspect ratio (NAR) was used as an index of overall cellular strain, and dependencies on spatial location and pressure loading levels quantified. Local collagen fiber alignment in the same valves was also quantified using small angle light scattering. A tissue-level finite element (FE) model of an AVIC embedded in the AV extracellular matrix was also used explore the relation between AV tissue- and cellular-level deformations. Results indicated large, consistent increases in AVIC NAR with transvalvular pressure (e.g., from mean of 1.8 at 0 mm Hg to a mean of 4.8 at 90 mm Hg), as well as pronounced layer specific dependencies. Associated changes in collagen fiber alignment indicated that little AVIC deformation occurs with the large amount of fiber straightening for pressures below approximately 1 mm Hg, followed by substantial increases in AVIC NAR from 4 mm Hg to 90 mm Hg. While the tissue-level FE model was able to capture the qualitative response, it also underpredicted the extent of AVIC deformation. This result suggested that additional micromechanical and fiber-compaction effects occur at high pressure levels. The results of this study form the basis of understanding transvalvular pressure-mediated mechanotransduction within the native AV and first time quantitative data correlating AVIC nuclei deformation with AV tissue microstructure and deformation.