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a The parameters of the elastic components (elastin and collagen) of the alveolar wall model were determined by fitting the model to measurements of stress and strain from Sugihara et al. (1971). The inset, bottom left, shows a magnification of the lower strain values to illustrate the difference between elastin, collagen and the model fit separately in this region. b This figure shows a comparison of an experimentally determined hysteresis loop of the alveolar wall in human lung tissue (Sugihara et al. 1972) compared to the alveolar model outputs (solid line). The loop area of the hysteresis curve was used to find the parameters of the Maxwell model (Sugihara et al. 1971, 1972)
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The extracellular matrix (ECM) comprises a large proportion of the lung parenchymal tissue and is an important contributor to the mechanical properties of the lung. The lung tissue is a biologically active scaffold with a complex ECM matrix structure and composition that provides physical support to the surrounding cells. Nearly all respiratory pat...
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Citations
... Numbers correspond to the following references: [1][2][3][4][5][6][7][8] Venegas et al., 2005;Tgavalekos et al., 2007;Winkler and Venegas, 2007;Bhatawadekar et al., 2015;Donovan, 2016;Leary et al., 2006;Donovan 2017;Foy et al., 2019. [9, 10] Choi et al., Yoon et al., 2020 [11-13] Berger et al., 2016;Tawhai et al., 2004;Werner et al., 2009 [14-17] Fredberg et al., 1997;Wang et al., 2000;Bates et al., 2009;LaPrad et al., 2010 [18, 19] Lavoie et al., 2012;Pybus et al., 2021b[20-23] Fung, 1974Eskandari et al., 2019;Birzle et al., 2019;Hill et al., 2018 [24-28] Mead et al., 1970, Cavalcante et al., 2005Iravani et al., 2020;Wellman et al., 2018;Oliveira et al., 2014[29, 30] Huh et al., 2010Kilic et al., 2019 [31-33] Chernyavsky et al., 2014;Chernyavsky et al., 2018;Pybus et al., 2021a [34] Lin et al., 2018 [35, 36] Sun et al., 2005;Smith et al., 2005 [37] Vargas et al., 2020 [38-43] Hai and Murphy, 1998;Mijailovich et al., 2000;Wang et al., 2008;Wang et al., 2010;Croisier et al., 2013;Croisier et al., 2015 [44] Irons et al., 2018 [45] Hao et al., 2015 [46, 47] Pascoe et al., 2020;Donovan et al., 2020[27, 48] Wellman et al., 2018Concha and Hurtado, 2020 [49, 50] Politi et al., 2010;Lauzon et al., 2012 [51-53] Hiorns et al., 2014;Hiorns et al., 2016;Brook 2014. Frontiers in Systems Biology frontiersin.org ...
... Alternatively, discrete methods such as spring network models have also been used to similarly reproduce experimental stress-strain curves (Mead et al., 1970;Cavalcante et al., 2005). Collagen, elastin, PGs, and viscoelastic matrix were considered within a 2D spring network model for parenchymal tissue and, under uniaxial loading, the model was able to generate stress-strain behaviour and hysteresis loops characteristic of experimental curves (Iravani et al., 2020). ...
Healthy lung function depends on a complex system of interactions which regulate the mechanical and biochemical environment of individual cells to the whole organ. Perturbations from these regulated processes give rise to significant lung dysfunction such as chronic inflammation, airway hyperresponsiveness and airway remodelling characteristic of asthma. Importantly, there is ongoing mechanobiological feedback where mechanical factors including airway stiffness and oscillatory loading have considerable influence over cell behavior. The recently proposed area of mechanopharmacology recognises these interactions and aims to highlight the need to consider mechanobiology when identifying and assessing pharmacological targets. However, these multiscale interactions can be difficult to study experimentally due to the need for measurements across a wide range of spatial and temporal scales. On the other hand, integrative multiscale mathematical models have begun to show success in simulating the interactions between different mechanobiological mechanisms or cell/tissue-types across multiple scales. When appropriately informed by experimental data, these models have the potential to serve as extremely useful predictive tools, where physical mechanisms and emergent behaviours can be probed or hypothesised and, more importantly, exploited to propose new mechanopharmacological therapies for asthma and other respiratory diseases. In this review, we first demonstrate via an exemplar, how a multiscale mathematical model of acute bronchoconstriction in an airway could be exploited to propose new mechanopharmacological therapies. We then review current mathematical modelling approaches in respiratory disease and highlight hypotheses generated by such models that could have significant implications for therapies in asthma, but that have not yet been the subject of experimental attention or investigation. Finally we highlight modelling approaches that have shown promise in other biological systems that could be brought to bear in developing mathematical models for optimisation of mechanopharmacological therapies in asthma, with discussion of how they could complement and accelerate current experimental approaches.
... In bio-integrated applications of stretchable electronic devices, especially those that require long-time (e.g., several hours or days) integration with human organs, an important design consideration is to offer bio-mimetic stress-strain responses, such that these devices are 'mechanically invisible' when mounted on the target biological tissues and organs [31,32]. For this purpose, developed from the conventional periodical network materials [33][34][35][36][37][38][39][40][41][42], a family of highly tailorable SNMs, consisting of periodical lattice constructions of curved filamentary microstructures inspired by those found in many collagenous tissues, have been developed [43][44][45][46][47][48]. By tailoring microstructure geometries (e.g., horseshoe, sinusoidal, crescent, and helical microstructures) and selecting appropriate lattice topologies (e.g., triangular, Kagome, honeycomb, square, cubic and octahedral lattices), these network materials are capable of reproducing accurately J-shaped stress-strain relationships of various biological tissues, such as muscles, lungs, skins, and blood vessels, etc. [49][50][51][52][53][54]. ...
Soft network materials (SNMs), consisting of rationally designed filamentary microstructures distributed periodically in lattice patterns, offer high air permeability, excellent defect insensitivity and highly tunable mechanical properties that could match precisely those of biological tissues. Owing to these excellent physical properties, SNMs have been widely used in stretchable electronics, biomedical engineering, soft robotics, and other areas. Although a few theoretical models were developed previously to predict nonlinear J-shaped stress–strain curves of SNMs with horseshoe microstructures, these models are not applicable to SNMs with arbitrarily curved microstructures. Herein, we establish a phenomenological framework capable of predicting nonlinear mechanical responses of SNMs with arbitrarily curved microstructures and various lattice topologies. The phenomenological framework incorporates a two-segment model that exploits simple, explicit expressions to capture the J-shaped stress–strain relationship, and a machine learning (ML) approach that enables the determination of the single phenomenological parameter in the model. Both finite element analysis (FEA) and experimental measurements on a diversity of SNMs have been conducted to validate the phenomenological model. The developed model enables a rapid inverse design of biomimetic SNMs for reproducing the target J-shaped stress–strain curves of soft biological tissues, and can be also extended to model anisotropic mechanical responses of SNMs with horseshoe microstructures. The versatile applicability of the phenomenological framework suggests that it can serve as a reliable design tool of SNMs for uses in tissue engineering and bioelectronics.
... Our model also provides new insight into the roles that fibres and their recruitment play in determining bulk alveolar mechanics, and in particular how they ensure inflation stability to protect the alveolus from overdistension. In contrast with the traditional view that attributes alveolar inflation stability to the nonlinear stiffness behaviour of collagen fibres [15][16][17], we have demonstrated that stability can be achieved through linearly elastic but wavy collagen fibres that become progressively recruited into the load-bearing role as the alveolus inflates according to a waviness distribution that we observed experimentally (figure 2). The finite thickness of the alveolar wall is an important feature of our model because we show that inflation stability can be compromised by a decrease in the wall thickness-toradius ratio as well as by a decrease in collagen fibre stiffness. ...
Inflation of hollow elastic structures can become unstable and exhibit a runaway phenomenon if the tension in their walls does not rise rapidly enough with increasing volume. Biological systems avoid such inflation instability for reasons that remain poorly understood. This is best exemplified by the lung, which inflates over its functional volume range without instability. The goal of this study was to determine how the constituents of lung parenchyma determine tissue stresses that protect alveoli from instability-related overdistension during inflation. We present an analytical model of a thick-walled alveolus composed of wavy elastic fibres, and investigate its pressure-volume behaviour under large deformations. Using second-harmonic generation imaging, we found that collagen waviness follows a beta distribution. Using this distribution to fit human pressure-volume curves, we estimated collagen and elastin effective stiffnesses to be 1247 kPa and 18.3 kPa, respectively. Furthermore, we demonstrate that linearly elastic but wavy collagen fibres are sufficient to achieve inflation stability within the physiological pressure range if the alveolar thickness-to-radius ratio is greater than 0.05. Our model thus identifies the constraints on alveolar geometry and collagen waviness required for inflation stability and provides a multiscale link between alveolar pressure and stresses on fibres in healthy and diseased lungs.
... A. Iravani et al., [16] A clever organization model was created to fuse the combinatorial impact of lung tissue ECM constituents like collagen, elastin and proteoglycan. ...
The mechanical resources of a cilium endure inadequately described. Cilia will bring about more profound comprehension of the natural capacity of cell stream detecting by this organelle. In the present paper proposed with an analytical investigation of the elasticity progression of a non-Newtonian mucus fluid influence of magnetic field and heat absorption in a ciliated channel during the MCC on respiratory system. We demonstrated the mathematical model for human lung contained mucus fluid in the presence of magnetic field and heat absorption parameter throughout Mucociliary clearance consecutive findings of testimony and mucociliary clearance computations address midpoints of basically unique dimensional numbers utilizing perturbation procedure and graphical figures are depicted aid of mathematical software.
... Studies combining experiments and theory suggest that the shear modulus of collagen fibers shows a strong correlation with the collagen volume fraction, and that these networks display connectivity near the percolation threshold [134][135][136][137][138]. Further experimental work however, has revealed that collagen networks with connectivity slightly below the isostatic threshold, can also become rigid in the presence of large deformation instead, thus in such cases passive rigidity percolation may not be sufficient to explain ECM rigidity [44,85]. In particular, increasing shear deformation in sub-isostatic networks leads to nonlinear increase of the elastic modulus of such networks along different connectivity values, an observation highlighting the possibility of incorporating the active nature of such systems when applying rigidity percolation theory [139]. ...
Spatiotemporal changes in viscoelasticity are a key component of the morphogenesis of living systems. Experimental and theoretical findings suggest that cellular- and tissue-scale viscoelasticity can be understood as a collective property emerging from macromolecular and cellular interactions, respectively. Linking the changes in the structural or material properties of cells and tissues, such as material phase transitions, to the microscopic interactions of their constituents, is still a challenge both at the experimental and theoretical level. In this review, we summarize work on the viscoelastic nature of cytoskeletal, extracellular and cellular networks. We then conceptualize viscoelasticity as a network theory problem and discuss its applications in several biological contexts. We propose that the statistical mechanics of networks can be used in the future as a powerful framework to uncover quantitatively the biomechanical basis of viscoelasticity across scales.
... Glycoproteins, fibulins, elastin microfibril interfacelocated proteins, and elastin-crosslinking lysyl oxidases are other proteins that are associated with elastic fibers (Ge et al., 2015;Liu et al., 2016;Burgstaller et al., 2017;Philp et al., 2018;Ito et al., 2019). PGs contribute to the viscoelasticity of the lung due to their hydrophilic nature (Burgstaller et al., 2017;Iravani et al., 2020). Post-translational modifications of ECM proteins, such as enzymatic or chemical crosslinking, glycation and glycosylation, and oxidation, allow for further structural and/ or function diversity (Burgstaller et al., 2017;Merl-Pham et al., 2019;Rani et al., 2021). ...
The extracellular matrix (ECM) is not simply a quiescent scaffold. This three-dimensional network of extracellular macromolecules provides structural, mechanical, and biochemical support for the cells of the lung. Throughout life, the ECM forms a critical component of the pulmonary stem cell niche. Basal cells (BCs), the primary stem cells of the airways capable of differentiating to all luminal cell types, reside in close proximity to the basolateral ECM. Studying BC-ECM interactions is important for the development of therapies for chronic lung diseases in which ECM alterations are accompanied by an apparent loss of the lung’s regenerative capacity. The complexity and importance of the native ECM in the regulation of BCs is highlighted as we have yet to create an in vitro culture model that is capable of supporting the long-term expansion of multipotent BCs. The interactions between the pulmonary ECM and BCs are, therefore, a vital component for understanding the mechanisms regulating BC stemness during health and disease. If we are able to replicate these interactions in airway models, we could significantly improve our ability to maintain basal cell stemness ex vivo for use in in vitro models and with prospects for cellular therapies. Furthermore, successful, and sustained airway regeneration in an aged or diseased lung by small molecules, novel compounds or via cellular therapy will rely upon both manipulation of the airway stem cells and their immediate niche within the lung. This review will focus on the current understanding of how the pulmonary ECM regulates the basal stem cell function, how this relationship changes in chronic disease, and how replicating native conditions poses challenges for ex vivo cell culture.
The extracellular matrix (ECM) is a highly dynamic system that constantly offers physical, biological, and chemical signals to embraced cells. Increasing evidence suggests that mechanical signals derived from the dynamic cellular microenvironment are essential controllers of cell behaviors. Conventional cell culture biomaterials, with static mechanical properties such as chemistry, topography, and stiffness, have offered a fundamental understanding of various vital biochemical and biophysical processes, such as cell adhesion, spreading, migration, growth, and differentiation. At present, novel biomaterials that can spatiotemporally impart biophysical cues to manipulate cell fate are emerging. The dynamic properties and adaptive traits of new materials endow them with the ability to adapt to cell requirements and enhance cell functions. In this review, an introductory overview of the key players essential to mechanobiology is provided. A biophysical perspective on the state‐of‐the‐art manipulation techniques and novel materials in designing static and dynamic ECM‐mimicking biomaterials is taken. In particular, different static and dynamic mechanical cues in regulating cellular mechanosensing and functions are compared. This review to benefit the development of engineering biomechanical systems regulating cell functions is expected. The heart of cell–materials interactions is to capture and understand the force crosstalk between cells and materials. However, these force dynamics have not been systemically discussed. Here a biophysical perspective on the state‐of‐the‐art manipulation techniques and novel materials in designing static and dynamic extracellular matrix (ECM)‐mimicking biomaterials is taken. The active force‐biosignaling feedback loops in the dynamic cell–matrix interactions are emphasized.
Fibrotic diseases are characterized by progressive and often irreversible scarring of connective tissue in various organs, leading to substantial changes in tissue mechanics largely as a result of alterations in collagen structure. This is particularly important in the lung because its bulk modulus is so critical to the volume changes that take place during breathing. Nevertheless, it remains unclear how fibrotic abnormalities in the mechanical properties of pulmonary connective tissue can be linked to the stiffening of its individual collagen fibers. To address this question, we developed a network model of randomly oriented collagen and elastin fibers to represent pulmonary alveolar wall tissue. We show that the stress–strain behavior of this model arises via the interactions of collagen and elastin fiber networks and is critically dependent on the relative fiber stiffnesses of the individual collagen and elastin fibers themselves. We also show that the progression from linear to nonlinear stress–strain behavior of the model is associated with the percolation of stress across the collagen fiber network, but that the location of the percolation threshold is influenced by the waviness of collagen fibers.
Anatomically based integrative models of the lung and their interaction with other key components of the respiratory system provide unique capabilities for investigating both normal and abnormal lung function. There is substantial regional variability in both structure and function within the normal lung, yet it remains capable of relatively efficient gas exchange by providing close matching of air delivery (ventilation) and blood delivery (perfusion) to regions of gas exchange tissue from the scale of the whole organ to the smallest continuous gas exchange units. This is despite remarkably different mechanisms of air and blood delivery, different fluid properties, and unique scale-dependent anatomical structures through which the blood and air are transported. This inherent heterogeneity can be exacerbated in the presence of disease or when the body is under stress. Current computational power and data availability allow for the construction of sophisticated data-driven integrative models that can mimic respiratory system structure, function, and response to intervention. Computational models do not have the same technical and ethical issues that can limit experimental studies and biomedical imaging, and if they are solidly grounded in physiology and physics they facilitate investigation of the underlying interaction between mechanisms that determine respiratory function and dysfunction, and to estimate otherwise difficult-to-access measures. © 2021 American Physiological Society. Compr Physiol 11:1501-1530, 2021.
