A zipper network model of the failure mechanics of extracellular matrices

CT Radiomics Features Predict Change in Lung Density and Rate of Emphysema Progression

Rationale Emphysema progression is heterogeneous. Predicting temporal changes in lung density and detecting rapid progressors may facilitate selection of individuals for targeted therapies. Objective To test whether computed tomography (CT) radiomics can be used to predict changes in lung density and detect rapid progressors. Methods We extracted radiomics features from inspiratory chest CT in 4,575 subjects with and without airflow obstruction at enrollment, who completed a follow-up visit at approximately 5 years. We quantified emphysema using adjusted lung density (ALD) and estimated emphysema progression as the annualized change in ALD (∆ALD/year) between visits. We categorized participants into rapid progressors (>1% ∆ALD/year) and stable disease (≤1% ∆ALD/year). A gradient boosting model was used (1) to predict ALD at 5-years and (2) to identify rapid progressors. Four models using demographics (base clinical model); CT density; radiomics; and combined features (clinical, radiomics, and CT density) were evaluated and tested. Results There were 1,773 (38.8%) rapid progressors. For predicting ALD at 5-years in the 20% held-out data, the base model explained 31% of the variance (adjusted R2 = 0.31) whereas R2 was 0.74 for the CT density model, 0.66 for the radiomics-only model, and 0.77 for the combined features model. For detecting rapid progressors, the base model (AUC = 0.57, 95%CI 0.53-0.61) was outperformed by the radiomics-only model (AUC = 0.73, 95%CI 0.69-0.76, ∆ =0.0003, p < 0.001) and the combined model (AUC = 0.74, 95%CI 0.71-0.77, ∆ = 0.0003, p < 0.001). Conclusions Parenchymal and airway radiomics features derived from inspiratory scans can be used to predict temporal changes in lung density and help identify rapid progressors.

Regional distribution of mechanical strain and macrophage-associated lung inflammation after ventilator-induced lung injury: an experimental study

BACKGROUND

Alveolar macrophages activation to the pro-inflammatory phenotype M1 is pivotal in the pathophysiology of Ventilator-Induced Lung Injury (VILI). Increased lung strain is a known determinant of VILI, but a direct correspondence between regional lung strain and macrophagic activation remains unestablished. [68Ga]Ga-DOTA-TATE is a Positron Emission Tomography (PET) radiopharmaceutical with a high affinity for somatostatin receptor subtype 2 (SSTR2), which is overexpressed by pro-inflammatory-activated macrophages. Aim of the study was to determine, in a porcine model of VILI, whether mechanical strain correlates topographically with distribution of activated macrophages detected by [68Ga]Ga-DOTA-TATE uptake.

METHODS

Seven anesthetized pigs underwent VILI, while three served as control. Lung CT scans were acquired at incremental tidal volumes, simultaneously recording lung mechanics. [68Ga]Ga-DOTA-TATE was administered, followed by dynamic PET scans. Custom MatLab scripts generated voxel-by-voxel gas volume and strain maps from CT slices at para-diaphragmatic (Para-D) and mid-thoracic (Mid-T) levels. Analysis of regional Voxel-associated Normal Strain (VoStrain) and [68Ga]Ga-DOTA-TATE uptake was performed and a measure of the statistical correlation between these two variables was quantified using the linear mutual information (LMI) method.

RESULTS

Compared to controls, the VILI group exhibited statistically significant higher VoStrain and Standardized Uptake Value Ratios (SUVR) both at Para-D and Mid-T levels. Both VoStrain and SUVR increased along the gravitational axis with an increment described by statistically different regression lines between VILI and healthy controls and reaching the peak in the dependent regions of the lung (for strain in VILI vs. control was at Para-D: 760 ± 210 vs. 449 ± 106; at Mid-T level 497 ± 373 vs. 193 ± 160; for SUVR, in VILI vs. control was at Para-D: 2.2 ± 1.3 vs. 1.3 ± 0.1; at Mid-T level 1.3 ± 1.0 vs. 0.6 ± 0.03). LMI in both Para-D and Mid-T was statistically significantly higher in VILI than in controls.

CONCLUSIONS

In this porcine model of VILI, we found a topographical correlation between lung strain and [68Ga]Ga-DOTA-TATE uptake at voxel level, suggesting that mechanical alteration and specific activation of inflammatory cells are strongly linked in VILI. This study represents the first voxel-by-voxel examination of this relationship in a multi-modal imaging analysis.

Nonlinear Mechanical Properties of Prestressed Branched Fibrous Networks

Random fiber networks constitute the solid skeleton of many biological materials such as the cytoskeleton of cells and extracellular matrix of soft tissues. These random networks show unique mechanical properties such as nonlinear shear strain-stiffening and strain softening when subjected to preextension and precompression, respectively. In this study, we perform numerical simulations to characterize the influence of axial prestress on the nonlinear mechanical response of random network structures as a function of their micromechanical and geometrical properties. We build our numerical network models using the microstructure of disordered hexagonal lattices and quantify their nonlinear shear response as a function of uniaxial prestress strain. We consider three different material models for individual fibers and fully characterize their influence on the mechanical response of prestressed networks. Moreover, we investigate both the influence of geometric disorder keeping the network connectivity constant and the influence of the randomness in the stiffness of individual fibers keeping their mean stiffness constant. The effects of network connectivity and bending rigidity of fibers are also determined. Several important conclusions are made, including that the tensile and compressive prestress strains, respectively, increase and decrease the initial network shear stiffness but have no effect on the maximal shear modulus. We discuss the findings in terms of microstructural properties such as the local strain energy distribution.

A viscoelastic two-dimensional network model of the lung extracellular matrix

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 pathologies result in changes in the structure and composition of the ECM; however, the impact of these alterations on the mechanical properties of the tissue is not well understood. In this study, a novel network model was developed to incorporate the combinatorial effect of lung tissue ECM constituents such as collagen, elastin and proteoglycans (PGs) and used to mimic the experimentally derived length-tension response of the tissue to uniaxial loading. By modelling the effect of collagen elasticity as an exponential function with strain, and in concert with the linear elastic response of elastin, the network model's mechanical response matched experimental stress-strain curves from the literature. In addition, by incorporating spring-dashpot viscoelastic elements, to represent the PGs, the hysteresis response was also simulated. Finally, by selectively reducing volume fractions of the different ECM constituents, we were able to gain insight into their relative mechanical contribution to the larger scale tissue mechanical response.

An Analytical Model for Estimating Alveolar Wall Elastic Moduli From Lung Tissue Uniaxial Stress-Strain Curves

The non-linear stress-strain behavior of uniaxially-stretched lung parenchyma is thought to be an emergent phenomenon arising from the ensemble behavior of its microscopic constituents. Such behavior includes the alignment and elongation of randomly oriented alveolar walls with initially flaccid fibers in the direction of strain. To account for the link between microscopic wall behavior and the macroscopic stress-strain curve, we developed an analytical model that represents both alignment and elongation of alveolar walls during uniaxial stretching. The model includes the kinetics and mechanical behavior of randomly oriented elastic alveolar walls that have a bending stiffness at their intersections. The alignment and stretch of the walls following incremental stretch of the tissue were determined based on energy minimization, and the total stress was obtained by differentiating the total energy density with respect to strain. The stress-strain curves predicted by the model were comparable to curves generated by a previously published numerical alveolar network model. The model was also fit to experimentally measured stress-strain curves in parenchymal strips obtained from mice with decreased lung collagen content, and from young and aged mice. This yielded estimates for the elastic modulus of an alveolar wall, which increased with age from 4.4 to 5.9 kPa (p = 0.043), and for the elastic modulus of fibers within the wall, which increased with age from 311 to 620 kPa (p = 0.001). This demonstrates the possibility of estimating alveolar wall mechanical properties in biological soft tissue from its macroscopic behavior given appropriate assumptions about tissue structure.

Integrated lung tissue mechanics one piece at a time: Computational modeling across the scales of biology

The lung is a delicately balanced and highly integrated mechanical system. Lung tissue is continuously exposed to the environment via the air we breathe, making it susceptible to damage. As a consequence, respiratory diseases present a huge burden on society and their prevalence continues to rise. Emergent function is produced not only by the sum of the function of its individual components but also by the complex feedback and interactions occurring across the biological scales - from genes to proteins, cells, tissue and whole organ - and back again. Computational modeling provides the necessary framework for pulling apart and putting back together the pieces of the body and organ systems so that we can fully understand how they function in both health and disease. In this review, we discuss models of lung tissue mechanics spanning from the protein level (the extracellular matrix) through to the level of cells, tissue and whole organ, many of which have been developed in isolation. This is a vital step in the process but to understand the emergent behavior of the lung, we must work towards integrating these component parts and accounting for feedback across the scales, such as mechanotransduction. These interactions will be key to unlocking the mechanisms occurring in disease and in seeking new pharmacological targets and improving personalized healthcare.

Imaging Advances in Chronic Obstructive Pulmonary Disease. Insights from the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) Study

The Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, which began in 2007, is an ongoing multicenter observational cohort study of more than 10,000 current and former smokers. The study is aimed at understanding the etiology, progression, and heterogeneity of chronic obstructive pulmonary disease (COPD). In addition to genetic analysis, the participants have been extensively characterized by clinical questionnaires, spirometry, volumetric inspiratory and expiratory computed tomography, and longitudinal follow-up, including follow-up computed tomography at 5 years after enrollment. The purpose of this state-of-the-art review is to summarize the major advances in our understanding of COPD resulting from the imaging findings in the COPDGene study. Imaging features that are associated with adverse clinical outcomes include early interstitial lung abnormalities, visual presence and pattern of emphysema, the ratio of pulmonary artery to ascending aortic diameter, quantitative evaluation of emphysema, airway wall thickness, and expiratory gas trapping. COPD is characterized by the early involvement of the small conducting airways, and the addition of expiratory scans has enabled measurement of small airway disease. Computational advances have enabled indirect measurement of nonemphysematous gas trapping. These metrics have provided insights into the pathogenesis and prognosis of COPD and have aided early identification of disease. Important quantifiable extrapulmonary findings include coronary artery calcification, cardiac morphology, intrathoracic and extrathoracic fat, and osteoporosis. Current active research includes identification of novel quantitative measures for emphysema and airway disease, evaluation of dose reduction techniques, and use of deep learning for phenotyping COPD.

Elastic Backbone Defines a New Transition in the Percolation Model

The elastic backbone is the set of all shortest paths. We found a new phase transition at p_{eb} above the classical percolation threshold at which the elastic backbone becomes dense. At this transition in 2D, its fractal dimension is 1.750±0.003, and one obtains a novel set of critical exponents β_{eb}=0.50±0.02, γ_{eb}=1.97±0.05, and ν_{eb}=2.00±0.02, fulfilling consistent critical scaling laws. Interestingly, however, the hyperscaling relation is violated. Using Binder's cumulant, we determine, with high precision, the critical probabilities p_{eb} for the triangular and tilted square lattice for site and bond percolation. This transition describes a sudden rigidification as a function of density when stretching a damaged tissue.

Computed Tomography Measure of Lung at Risk and Lung Function Decline in Chronic Obstructive Pulmonary Disease

RATIONALE

The rate of decline of lung function is greater than age-related change in a substantial proportion of patients with chronic obstructive pulmonary disease, even after smoking cessation. Regions of the lung adjacent to emphysematous areas are subject to abnormal stretch during respiration, and this biomechanical stress likely influences emphysema initiation and progression.

OBJECTIVES

To assess whether quantifying this penumbra of lung at risk would predict FEV₁ decline.

METHODS

We analyzed paired inspiratory-expiratory computed tomography images at baseline of 680 subjects participating in a large multicenter study (COPDGene) over approximately 5 years. By matching inspiratory and expiratory images voxel by voxel using image registration, we calculated the Jacobian determinant, a measure of local lung expansion and contraction with respiration. We measured the distance between each normal voxel to the nearest emphysematous voxel, and quantified the percentage of normal voxels within each millimeter distance from emphysematous voxels as mechanically affected lung (MAL). Multivariable regression analyses were performed to assess the relationship between the Jacobian determinant, MAL, and FEV₁ decline.

MEASUREMENTS AND MAIN RESULTS

The mean (SD) rate of decline in FEV₁ was 39.0 (58.6) ml/yr. There was a progressive decrease in the mean Jacobian determinant of both emphysematous and normal voxels with increasing disease stage (P < 0.001). On multivariable analyses, the mean Jacobian determinant of normal voxels within 2 mm of emphysematous voxels (MAL₂) was significantly associated with FEV₁ decline. In mild-moderate disease, for participants at or above the median MAL₂ (threshold, 36.9%), the mean decline in FEV₁ was 56.4 (68.0) ml/yr versus 43.2 (59.9) ml/yr for those below the median (P = 0.044).

CONCLUSIONS

Areas of normal-appearing lung are mechanically influenced by emphysematous areas and this lung at risk is associated with lung function decline. Clinical trial registered with www.clinicaltrials.gov (NCT00608764).

Crack Propagation Versus Fiber Alignment in Collagen Gels: Experiments and Multiscale Simulation

It is well known that the organization of the fibers constituting a collagenous tissue can affect its failure behavior. Less clear is how that effect can be described computationally so as to predict the failure of a native or engineered tissue under the complex loading conditions that can occur in vivo. Toward the goal of a general predictive strategy, we applied our multiscale model of collagen gel mechanics to the failure of a double-notched gel under tension, comparing the results for aligned and isotropic samples. In both computational and laboratory experiments, we found that the aligned gels were more likely to fail by connecting the two notches than the isotropic gels. For example, when the initial notches were 30% of the sample width (normalized tip-to-edge distance = 0.7), the normalized tip-to-tip distance at which the transition occurred from between-notch failure to across-sample failure shifted from 0.6 to 1.0. When the model predictions for the type of failure event (between the two notches versus across the sample width) were compared to the experimental results, the two were found to be strongly covariant by Fisher's exact test (p < 0.05) for both the aligned and isotropic gels with no fitting parameters. Although the double-notch system is idealized, and the collagen gel system is simpler than a true tissue, it presents a simple model system for studying failure of anisotropic tissues in a controlled setting. The success of the computational model suggests that the multiscale approach, in which the structural complexity is incorporated via changes in the model networks rather than via changes to a constitutive equation, has the potential to predict tissue failure under a wide range of conditions.

Epithelial and endothelial damage induced by mechanical ventilation modes

PURPOSE OF REVIEW

The adult respiratory distress syndrome (ARDS) is a common cause of respiratory failure with substantial impact on public health. Patients with ARDS generally require mechanical ventilation, which risks further lung damage. Recent improvements in ARDS outcomes have been attributed to reductions in deforming stress associated with lung protective mechanical ventilation modes and settings. The following review details the mechanics of the lung parenchyma at different spatial scales and the response of its resident cells to deforming stress in order to provide the biologic underpinnings of lung protective care.

RECENT FINDINGS

Although lung injury is typically viewed through the lens of altered barrier properties and mechanical ventilation-associated immune responses, in this review, we call attention to the importance of heterogeneity and the physical failure of the load bearing cell and tissue elements in the pathogenesis of ARDS. Specifically, we introduce a simple elastic network model to better understand the deformations of lung regions, intra-acinar alveoli and cells within a single alveolus, and consider the role of regional distension and interfacial stress-related injury for various ventilation modes.

SUMMARY

Heterogeneity of stiffness and intercellular and intracellular stress failure are fundamental components of ARDS and their development also depends on the ventilation mode.

Proteoglycans maintain lung stability in an elastase-treated mouse model of emphysema

Extracellular matrix remodeling and tissue rupture contribute to the progression of emphysema. Lung tissue elasticity is governed by the tensile stiffness of fibers and the compressive stiffness of proteoglycans. It is not known how proteoglycan remodeling affects tissue stability and destruction in emphysema. The objective of this study was to characterize the role of remodeled proteoglycans in alveolar stability and tissue destruction in emphysema. At 30 days after treatment with porcine pancreatic elastase, mouse lung tissue stiffness and alveolar deformation were evaluated under varying tonicity conditions that affect the stiffness of proteoglycans. Proteoglycans were stained and measured in the alveolar walls. Computational models of alveolar stability and rupture incorporating the mechanical properties of fibers and proteoglycans were developed. Although absolute tissue stiffness was only 24% of normal, changes in relative stiffness and alveolar shape distortion due to changes in tonicity were increased in emphysema (P < 0.01 and P < 0.001). Glycosaminoglycan amount per unit alveolar wall length, which is responsible for proteoglycan stiffness, was higher in emphysema (P < 0.001). Versican expression increased in the tissue, but decorin decreased. Our network model predicted that the rate of tissue deterioration locally governed by mechanical forces was reduced when proteoglycan stiffness was increased. Consequently, this general network model explains why increasing proteoglycan deposition protects the alveolar walls from rupture in emphysema. Our results suggest that the loss of proteoglycans observed in human emphysema contributes to disease progression, whereas treatments that promote proteoglycan deposition in the extracellular matrix should slow the progression of emphysema.

Complexity and emergent phenomena

Complex biological systems operate under non-equilibrium conditions and exhibit emergent properties associated with correlated spatial and temporal structures. These properties may be individually unpredictable, but tend to be governed by power-law probability distributions and/or correlation. This article reviews the concepts that are invoked in the treatment of complex systems through a wide range of respiratory-related examples. Following a brief historical overview, some of the tools to characterize structural variabilities and temporal fluctuations associated with complex systems are introduced. By invoking the concept of percolation, the notion of multiscale behavior and related modeling issues are discussed. Spatial complexity is then examined in the airway and parenchymal structures with implications for gas exchange followed by a short glimpse of complexity at the cellular and subcellular network levels. Variability and complexity in the time domain are then reviewed in relation to temporal fluctuations in airway function. Next, an attempt is given to link spatial and temporal complexities through examples of airway opening and lung tissue viscoelasticity. Specific examples of possible and more direct clinical implications are also offered through examples of optimal future treatment of fibrosis, exacerbation risk prediction in asthma, and a novel method in mechanical ventilation. Finally, the potential role of the science of complexity in the future of physiology, biology, and medicine is discussed.

Microscale fiber network alignment affects macroscale failure behavior in simulated collagen tissue analogs

A tissue's microstructure determines its failure properties at larger length scales, however, the specific relationship between microstructure and macroscopic failure in native and engineered soft tissues (such as capsular ligaments, aortic aneurysms, or vascular grafts) has proven elusive. In this study, variations in the microscale fiber alignment in collagen gel tissue analogs were modeled in order to understand their effects on macroscale damage and failure outcomes. The study employed a multiscale finite-element (FE) model for damage and failure in collagen-based materials. The model relied on microstructural representative volume elements (RVEs) that consisted of stochastically-generated networks of discrete type-I collagen fibers. Fiber alignment was varied within RVEs and between layers of RVEs in a macroscopic FE model of a notched dogbone geometry. The macroscale stretch and the microscale response of fibers for each of the differently aligned cases were compared as the dogbone was uniaxially extended to failure. Networks with greater fiber alignment parallel to the direction of extension failed at smaller strains (with a 6-22% reduction in the Green strain at failure), however, at greater grip forces (a 28-60% increase) than networks with fibers aligned perpendicular to the extension. Alternating layers of crisscrossed network alignments (aligned ±45 deg to the direction of extension) failed at smaller strains but at greater grip forces than those created using one fiber alignment type. In summary, variations in microscale structure via fiber alignment produced different macroscale failure trends. To conclude, these findings may be significant in the realm of tissue engineering and in soft tissue biomechanics.

Multiscale model predicts tissue-level failure from collagen fiber-level damage

Excessive tissue-level forces communicated to the microstructure and extracellular matrix of soft tissues can lead to damage and failure through poorly understood physical processes that are multiscale in nature. In this work, we propose a multiscale mechanical model for the failure of collagenous soft tissues that incorporates spatial heterogeneity in the microstructure and links the failure of discrete collagen fibers to the material response of the tissue. The model, which is based on experimental failure data derived from different collagen gel geometries, was able to predict the mechanical response and failure of type I collagen gels, and it demonstrated that a fiber-based rule (at the micrometer scale) for discrete failure can strongly shape the macroscale failure response of the gel (at the millimeter scale). The model may be a useful tool in predicting the macroscale failure conditions for soft tissues and engineered tissue analogs. In addition, the multiscale model provides a framework for the study of failure in complex fiber-based mechanical systems in general.

Micromechanical model of a surrogate for collagenous soft tissues: development, validation and analysis of mesoscale size effects

Aligned, collagenous tissues such as tendons and ligaments are composed primarily of water and type I collagen, organized hierarchically into nanoscale fibrils, microscale fibers and mesoscale fascicles. Force transfer across scales is complex and poorly understood. Since innervation, the vasculature, damage mechanisms and mechanotransduction occur at the microscale and mesoscale, understanding multiscale interactions is of high importance. This study used a physical model in combination with a computational model to isolate and examine the mechanisms of force transfer between scales. A collagen-based surrogate served as the physical model. The surrogate consisted of extruded collagen fibers embedded within a collagen gel matrix. A micromechanical finite element model of the surrogate was validated using tensile test data that were recorded using a custom tensile testing device mounted on a confocal microscope. Results demonstrated that the experimentally measured macroscale strain was not representative of the microscale strain, which was highly inhomogeneous. The micromechanical model, in combination with a macroscopic continuum model, revealed that the microscale inhomogeneity resulted from size effects in the presence of a constrained boundary. A sensitivity study indicated that significant scale effects would be present over a range of physiologically relevant inter-fiber spacing values and matrix material properties. The results indicate that the traditional continuum assumption is not valid for describing the macroscale behavior of the surrogate and that boundary-induced size effects are present.

Mechanics of a fiber network within a non-fibrillar matrix: model and comparison with collagen-agarose co-gels

While collagen is recognized as the predominant mechanical component of soft connective tissues, the role of the non-fibrillar matrix (NFM) is less well understood. Even model systems, such as the collagen-agarose co-gel, can exhibit complex behavior, making it difficult to identify relative contributions of specific tissue constituents. In the present study, we developed a two-component microscale model of collagen-agarose tissue analogs and used it to elucidate the interaction between collagen and NFM in uniaxial tension. Collagen fibers were represented with Voronoi networks, and the NFM was modeled as a neo-Hookean solid. Model predictions of total normal stress and Poisson's ratio matched experimental observations well (including high Poisson's values of ~3), and the addition of NFM led to composition-dependent decreases in volume change and increases in fiber stretch. Because the NFM was more resistant to volume change than the fiber network, extension of the composite led to pressurization of the NFM. Within a specific range of parameter values (low shear modulus and moderate Poisson's ratio), the magnitude of the reaction force decreased relative to this pressurization component resulting in a negative (compressive) NFM stress in the loading direction, even though the composite tissue was in tension.

Micropatterned cell sheets with defined cell and extracellular matrix orientation exhibit anisotropic mechanical properties

For an arterial replacement graft to be effective, it must possess the appropriate strength in order to withstand long-term hemodynamic stress without failure, yet be compliant enough that the mismatch between the stiffness of the graft and the native vessel wall is minimized. The native vessel wall is a structurally complex tissue characterized by circumferentially oriented collagen fibers/cells and lamellar elastin. Besides the biochemical composition, the functional properties of the wall, including stiffness, depend critically on the structural organization. Therefore, it will be crucial to develop methods of producing tissues with defined structures in order to more closely mimic the properties of a native vessel. To this end, we sought to generate cell sheets that have specific ECM/cell organization using micropatterned polydimethylsiloxane (PDMS) substrates to guide cell organization and tissue growth. The patterns consisted of large arrays of alternating grooves and ridges. Adult bovine aortic smooth muscle cells cultured on these substrates in the presence of ascorbic acid produced ECM-rich sheets several cell layers thick in which both the cells and ECM exhibited strong alignment in the direction of the micropattern. Moreover, mechanical testing revealed that the sheets exhibited mechanical anisotropy similar to that of native vessels with both the stiffness and strength being significantly larger in the direction of alignment, demonstrating that the microscale control of ECM organization results in functional changes in macroscale material behavior.

Real-time observation of flow-induced cytoskeletal stress in living cells

The mechanical stress due to shear flow has profound effects on cell proliferation, transport, gene expression, and apoptosis. The mechanisms for flow sensing and transduction are unclear, but it is postulated that fluid flow pulls upon the apical surface, and the resulting stress is eventually transmitted through the cytoskeleton to adhesion plaques on the basal surface. Here we report a direct observation of this flow-induced stress in the cytoskeleton in living cells using a parallel plate microfluidic chip with a fluorescence resonance energy transfer (FRET)-based mechanical stress sensor in actinin. The sensing cassette was genetically inserted into the cytoskeletal host protein and transfected into Madin-Darby canine kidney cells. A shear stress of 10 dyn/cm(2) resulted in a rapid increase in the FRET ratio indicating a decrease in stress across actinin with flow. The effect was reversible, and cells were able to respond to repeated stimulation and showed adaptive changes in the cytoskeleton. Flow-induced Ca(2+) elevation did not affect the response, suggesting that flow-induced changes in actinin stress are insensitive to intracellular Ca(2+) level. The reduction in FRET ratio suggests actin filaments are under normal compression in the presence of flow shear stress due to changes in cell shape, and/or actinin is not in series with actin. Treatment with cytochalasin-D that disrupts F-actin reduced prestress and the response to flow. The FRET/flow method is capable of resolving changes of stress in multiple proteins with optical spatial resolution and time resolution >1 Hz. This promises to provide insight into the force distribution and transduction in all cells.

Mechanical failure, stress redistribution, elastase activity and binding site availability on elastin during the progression of emphysema

Emphysema is a disease of the lung parenchyma with progressive alveolar tissue destruction that leads to peripheral airspace enlargement. In this review, we discuss how mechanical forces can contribute to disease progression at various length scales. Airspace enlargement requires mechanical failure of alveolar walls. Because the lung tissue is under a pre-existing tensile stress, called prestress, the failure of a single wall results in a redistribution of the local prestress. During this process, the prestress increases on neighboring alveolar walls which in turn increases the probability that these walls also undergo mechanical failure. There are several mechanisms that can contribute to this increased probability: exceeding the failure threshold of the ECM, triggering local mechanotransduction to release enzymes, altering enzymatic reactions on ECM molecules. Next, we specifically discuss recent findings that stretching of elastin induces an increase in the binding off rate of elastase to elastin as well as unfolds hidden binding sites along the fiber. We argue that these events can initiate a positive feedback loop which generates slow avalanches of breakdown that eventually give rise to the relentless progression of emphysema. We propose that combining modeling at various length scales with corresponding biological assays, imaging and mechanics data will provide new insight into the progressive nature of emphysema. Such approaches will have the potential to contribute to resolving many of the outstanding issues which in turn may lead to the amelioration or perhaps the treatment of emphysema in the future.

Influence of acellular natural lung matrix on murine embryonic stem cell differentiation and tissue formation

We report here the first attempt to produce and use whole acellular (AC) lung as a matrix to support development of engineered lung tissue from murine embryonic stem cells (mESCs). We compared the influence of AC lung, Gelfoam, Matrigel, and a collagen I hydrogel matrix on the mESC attachment, differentiation, and subsequent formation of complex tissue. We found that AC lung allowed for better retention of cells with more differentiation of mESCs into epithelial and endothelial lineages. In constructs produced on whole AC lung, we saw indications of organization of differentiating ESC into three-dimensional structures reminiscent of complex tissues. We also saw expression of thyroid transcription factor-1, an immature lung epithelial cell marker; pro-surfactant protein C, a type II pneumocyte marker; PECAM-1/CD31, an endothelial cell marker; cytokeratin 18; alpha-actin, a smooth muscle marker; CD140a or platelet-derived growth factor receptor-alpha; and Clara cell protein 10. There was also evidence of site-specific differentiation in the trachea with the formation of sheets of cytokeratin-positive cells and Clara cell protein 10-expressing Clara cells. Our findings support the utility of AC lung as a matrix for engineering lung tissue and highlight the critical role played by matrix or scaffold-associated cues in guiding ESC differentiation toward lung-specific lineages.

Emergent structure-function relations in emphysema and asthma

Structure-function relationships in the respiratory system are often a result of the emergence of self-organized patterns or behaviors that are characteristic of certain respiratory diseases. Proper description of such self-organized behavior requires network models that include nonlinear interactions among different parts of the system. This review focuses on 2 models that exhibit self-organized behavior: a network model of the lung parenchyma during the progression of emphysema that is driven by mechanical force-induced breakdown, and an integrative model of bronchoconstriction in asthma that describes interactions among airways within the bronchial tree. Both models suggest that the transition from normal to pathologic states is a nonlinear process that includes a tipping point beyond which interactions among the system components are reinforced by positive feedback, further promoting the progression of pathologic changes. In emphysema, the progressive destruction of tissue is irreversible, while in asthma, it is possible to recover from a severe bronchoconstriction. These concepts may have implications for pulmonary medicine. Specifically, we suggest that structure-function relationships emerging from network behavior across multiple scales should be taken into account when the efficacy of novel treatments or drug therapy is evaluated. Multiscale, computational, network models will play a major role in this endeavor.

Recent advances and new opportunities in lung mechanobiology

Lung function is inextricably linked to mechanics. On short timescales every breath generates dynamic cycles of cell and matrix stretch, along with convection of fluids in the airways and vasculature. Perturbations such airway smooth muscle shortening or surfactant dysfunction rapidly alter respiratory mechanics, with profound influence on lung function. On longer timescales, lung development, maturation, and remodeling all strongly depend on cues from the mechanical environment. Thus mechanics has long played a central role in our developing understanding of lung biology and respiratory physiology. This concise review focuses on progress over the past 5 years in elucidating the molecular origins of lung mechanical behavior, and the cellular signaling events triggered by mechanical perturbations that contribute to lung development, homeostasis, and injury. Special emphasis is placed on the tools and approaches opening new avenues for investigation of lung behavior at integrative cellular and molecular scales. We conclude with a brief summary of selected opportunities and challenges that lie ahead for the lung mechanobiology research community.