Comparison of 2D fiber network orientation measurement methods

Stiffening of a fibrous matrix after recovery of contracted inclusions

Disordered fibrous matrices in living tissues are subjected to forces exerted by cells that contract to pull on matrix fibers. To maintain homeostasis or facilitate disease progression, contracted cells often push on matrix fibers as they recover their original sizes. Recent advances have shown that matrix geometry encodes loading history into mechanical memory independently of plasticity mechanisms such as inter-fiber cohesion or fiber yielding. Conceptualizing cells as inclusions undergoing sequential contraction and recovery, prior work documented matrix remodeling surrounding a solitary recovered inclusion. However, because the remodeling induced by the contraction of multiple inclusions differs from that caused by a single contracted inclusion, we investigate how matrix remodeling occurs when multiple contracted inclusions recover simultaneously, a scenario that more accurately reflects real tissues containing many closely spaced cells. Using mechanics-based computational models of fibrous matrices embedded with clusters of inclusions, we studied the mechanical remodeling of the matrix during the simultaneous recovery of inclusions after contraction. The results revealed permanent mechanical remodeling of the matrix within the cluster, with stiffening observed in areas of the matrix enclosed by closely spaced inclusions. This stiffening was driven by microstructural changes in matrix geometry and was corroborated in experiments, where collagen matrices permanently remodeled by the contraction and recovery of closely spaced embedded cells also exhibited stiffening. By enriching the understanding of memory formation in fibrous matrices, this study opens new possibilities for estimating cell forces on matrix substrates and refining metamaterial design strategies.

An algorithmic and software framework to incorporate orientation distribution functions in finite element simulations for biomechanics and biophysics

Biological tissues and biomaterials routinely feature a fibrous microstructure that contributes to physical and mechanical properties while influencing cellular guidance, organization and extracellular matrix (ECM) production. Specialized three-dimensional (3D) imaging techniques can visualize fibrillar structure and orientation, and previously we developed a nonparametric approach to extract orientation distribution functions (ODFs) directly from 3D image data [1]. In this work, we expanded our previous approach to provide a complete algorithmic and software framework to characterize inhomogeneous ODFs in image data and use ODFs to model the physics of materials with the finite element method. We characterized inhomogeneity using image subdomains and specialized interpolation methods, and we developed methods to incorporate ODFs directly into constitutive models. To facilitate its adoption by the biomechanics and biophysics communities, we developed a unified software framework in FEBio Studio (www.febio.org). This included new interpolation methods to spatially map the ODFs onto finite element meshes and an approach to downsample ODFs for efficient numerical calculations. The software provides the option to fit ODFs to parametric distributions, and scalar metrics provide means to assess goodness of fit. We evaluated the utility and accuracy of the algorithms and implementation using representative 3D image datasets. Our results demonstrated that utilizing the true measured ODFs provide a more accurate and spatially resolved representation of fiber ODFs and the resulting predicted mechanical response when compared with parametric approaches to approximating the true ODFs. This research provides a powerful, interactive software framework to extract and represent the inhomogeneous anisotropic characteristics of fibrous tissues directly from image data, and to incorporate them into biomechanics and biophysics simulations using the finite element method. STATEMENT OF SIGNIFICANCE: Biological tissues and biomaterials routinely feature a fibrous microstructure that contributes to physical and mechanical properties while influencing cellular guidance, organization and extracellular matrix (ECM) production. In this study, we developed a complete algorithmic and software framework to characterize inhomogeneous orientation distribution functions (ODFs) directly from biomedical image data and apply the ODFs to model the physics of biological materials. We characterized inhomogeneity using image subdomains and specialized interpolation methods, and we developed methods to incorporate ODFs directly into constitutive models. We developed a unified software framework in FEBio Studio (www.febio.org) to accommodate its adoption by the biomechanics and biophysics communities. The result is a powerful, interactive software framework to extract and represent inhomogeneous, anisotropic characteristics directly from image data, and incorporate them into biomechanics and biophysics simulations.

A finite element model for biomechanical characterization of ex vivo peripheral nerve dysfunction during stretch

Peripheral nerve damage can cause debilitating symptoms ranging from numbness and pain to sensory loss and atrophy. To uncover the underlying mechanisms of peripheral nerve injury, our research aims to develop a relationship between biomechanical peripheral nerve damage and function through finite element modeling. A noncontact, ex vivo electrophysiology chamber, capable of axially stretching explanted nerves while recording electrical signals, was used to investigate peripheral nerve injury. Successive stretch trials were run on eight sciatic nerves (four females and four males) excised from Sprague-Dawley rats. Nerves were stretched until 50% compound action potential (CAP) amplitude reduction was obtained. A constitutive model developed by Raghavan and Vorp was suitable for rat sciatic nerves, with an average α and β of 0.183 MPa and 1.88 MPa, respectively. We then generated 95% confidence intervals for the stretch at which specific CAP amplitude reductions would occur, which compares well to previous studies. We also developed a finite element model that can predict stretch-induced signaling deficits, applicable for complex nerve geometries and injuries. This relationship between nerve biomechanics and function can be expanded upon to create a clinical model for peripheral nerve dysfunction due to stretch.

Extraction of collagen morphological features from second-harmonic generation microscopy images via GLCM and CT analyses: A cross-laboratory study

Second-harmonic generation (SHG) microscopy provides a high-resolution label-free approach for noninvasively detecting collagen organization and its pathological alterations. Up to date, several imaging analysis algorithms for extracting collagen morphological features from SHG images-such as fiber size and length, order and anisotropy-have been developed. However, the dependence of extracted features on experimental setting represents a significant obstacle for translating the methodology in the clinical practice. We tackled this problem by acquiring SHG images of the same kind of collagenous sample in various laboratories using different experimental setups and imaging conditions. The acquired images were analyzed by commonly used algorithms, such as gray-level co-occurrence matrix or curvelet transform; the extracted morphological features were compared, finding that they strongly depend on some experimental parameters, whereas they are almost independent from others. We conclude with useful suggestions for comparing results obtained in different labs using different experimental setups and conditions.

Dynamic Biophysical Cues Near the Tip Cell Microenvironment Provide Distinct Guidance Signals to Angiogenic Neovessels

The formation of new vascular networks via angiogenesis is a crucial biological mechanism to balance tissue metabolic needs, yet the coordination of factors that influence the guidance of growing neovessels remain unclear. This study investigated the influence of extracellular cues within the immediate environment of sprouting tips over multiple hours and obtained quantitative relationships describing their effects on the growth trajectories of angiogenic neovessels. Three distinct microenvironmental cues-fibril tracks, ECM density, and the presence of nearby cell bodies-were extracted from 3D time series image data. The prominence of each cue was quantified along potential sprout trajectories to predict the response to multiple microenvironmental factors simultaneously. Sprout trajectories significantly correlated with the identified microenvironmental cues. Specifically, ECM density and nearby cellular bodies were the strongest predictors of the trajectories taken by neovessels (p < 0.001 and p = 0.016). Notwithstanding, direction changing trajectories, deviating from the initial neovessel orientation, were significantly correlated with fibril tracks (p = 0.003). Direction changes also occurred more frequently with strong microenvironmental cues. This provides evidence for the first time that local matrix fibril alignment influences changes in sprout trajectories but does not materially contribute to persistent sprouting. Together, our results suggest the microenvironmental cues significantly contribute to guidance of sprouting trajectories. Further, the presented methods quantitatively distinguish the influence of individual microenvironmental stimuli during guidance.

Extracellular matrix deformations of the porcine recurrent laryngeal nerve in response to hydrostatic pressure

Damage to the recurrent laryngeal nerve (RLN) caused by supraphysiological compression or tension imposed by adjacent tissue structures, such as the aorta, may contribute to onset of idiopathic unilateral vocal fold paralysis (iUVP) resulting in difficulty speaking, breathing, and swallowing. We previously demonstrated in adolescent pigs that the right RLN epineurium exhibits uniform composition of adipose tissue, with larger quantities along its length within the neck region in contrast to the left RLN that shows greater collagen composition in the thoracic region and greater quantities of adipose tissue in the neck region. In contrast, the epineurium in piglets was primarily composed of collagen tissue that remained uniform along the length of the left and right RLNs. Tensile testing of the left and right RLN in piglets and pigs showed associated differences in strain by RLN side and segment by age. The goal of this study was to investigate how external hydrostatic compression of the RLN affects the nerve's connective tissue and microstructure. RLN segments were harvested from the distal (cervical/neck) regions and proximal (subclavian for the right RLN, thoracic for the left RLN) regions from eight adolescent pigs and nine piglets. RLN segments were isolated and assessed under fluid compression to test hypotheses regarding epineurium composition and response to applied forces. Second harmonic generation (SHG) imaging of epineurial collagen was conducted at 0, 40, and 80 mmHg of compression. The cartesian strain tensor, principal strain (Eps1), and principal direction of the RLN collagen fibers were determined at each pressure step. Significantly larger values of the 1st principal strain occurred in the proximal segments of the pig left RLN when compared to the same segment in piglets (p = 0.001, pig = 0.0287 [IQR = 0.0161 - 0.0428], piglet = 0.0061 [IQR = 0.0033 - 0.0156]). Additionally, the median transverse strain Eyy) for the second pressure increment was larger in the right proximal segment of pigs compared to piglets (p < 0.001, pig = 0.0122 [IQR = 0.0033 - 0.0171], piglet = 0.0013 [IQR = 0.00001 - 0.0028]). Eyy values were significantly larger in the right proximal RLN versus the left proximal RLNs in pigs but not in piglets (p < 0.001). In contrast to piglets, histological analysis of pig RLN demonstrated increased axial alignment of epineurial and endoneurial collagen in response to compressive pressure. These findings support the hypothesis that the biomechanical response of the RLN to compressive pressure changed from being similar to being different between the right and left RLNs during development in the porcine model. Further investigation of these findings associated with age-related onset of idiopathic UVP may illuminate underlying etiologic mechanisms. STATEMENT OF SIGNIFICANCE: Damage to the recurrent laryngeal nerve (RLN) caused by compression imposed by the aorta may contribute to the onset of left-sided idiopathic unilateral vocal fold paralysis resulting in difficulty speaking, breathing, and swallowing. The goal of this study was to investigate how compression affects the connective tissue and microstructure of the RLN. We quantified the pressure induced deformation of the RLN using multiphoton imaging as a function of both location (proximal versus distal) and age (piglets, adolescent pigs). Our results demonstrate that the biomechanical response of the RLN to compression changes in the right versus left RLN throughout development, providing further evidence that the the left RLN is exposed to increasing dynamic loads with age.

Highly accurate, automated quantification of 2D/3D orientation for cerebrovasculature using window optimizing method

SIGNIFICANCE

Deep-imaging of cerebral vessels and accurate organizational characterization are vital to understanding the relationship between tissue structure and function.

AIM

We aim at large-depth imaging of the mouse brain vessels based on aggregation-induced emission luminogens (AIEgens), and we create a new algorithm to characterize the spatial orientation adaptively with superior accuracy.

APPROACH

Assisted by AIEgens with near-infrared-II excitation, three-photon fluorescence (3PF) images of large-depth cerebral blood vessels are captured. A window optimizing (WO) method is developed for highly accurate, automated 2D/3D orientation determination. The application of this system is demonstrated by establishing the orientational architecture of mouse cerebrovasculature down to the millimeter-level depth.

RESULTS

The WO method is proved to have significantly higher accuracy in both 2D and 3D cases than the method with a fixed window size. Depth- and diameter-dependent orientation information is acquired based on in vivo 3PF imaging and the WO analysis of cerebral vessel images with a penetration depth of 800 μm in mice.

CONCLUSIONS

We built an imaging and analysis system for cerebrovasculature that is conducive to applications in neuroscience and clinical fields.

Intra-articular MMP-1 in the spinal facet joint induces sustained pain and neuronal dysregulation in the DRG and spinal cord, and alters ligament kinematics under tensile loading

Chronic joint pain is a major healthcare challenge with a staggering socioeconomic burden. Pain from synovial joints is mediated by the innervated collagenous capsular ligament that surrounds the joint and encodes nociceptive signals. The interstitial collagenase MMP-1 is elevated in painful joint pathologies and has many roles in collagen regulation and signal transduction. Yet, the role of MMP-1 in mediating nociception in painful joints remains poorly understood. The goal of this study was to determine whether exogenous intra-articular MMP-1 induces pain in the spinal facet joint and to investigate effects of MMP-1 on mediating the capsular ligament’s collagen network, biomechanical response, and neuronal regulation. Intra-articular MMP-1 was administered into the cervical C6/C7 facet joints of rats. Mechanical hyperalgesia quantified behavioral sensitivity before, and for 28 days after, injection. On day 28, joint tissue structure was assessed using histology. Multiscale ligament kinematics were defined under tensile loading along with microstructural changes in the collagen network. The amount of degraded collagen in ligaments was quantified and substance P expression assayed in neural tissue since it is a regulatory of nociceptive signaling. Intra-articular MMP-1 induces behavioral sensitivity that is sustained for 28 days (p < 0.01), absent any significant effects on the structure of joint tissues. Yet, there are changes in the ligament’s biomechanical and microstructural behavior under load. Ligaments from joints injected with MMP-1 exhibit greater displacement at yield (p = 0.04) and a step-like increase in the number of anomalous reorganization events of the collagen fibers during loading (p ≤ 0.02). Collagen hybridizing peptide, a metric of damaged collagen, is positively correlated with the spread of collagen fibers in the unloaded state after MMP-1 (p = 0.01) and that correlation is maintained throughout the sub-failure regime (p ≤ 0.03). MMP-1 injection increases substance P expression in dorsal root ganglia (p < 0.01) and spinal cord (p < 0.01) neurons. These findings suggest that MMP-1 is a likely mediator of neuronal signaling in joint pain and that MMP-1 presence in the joint space may predispose the capsular ligament to altered responses to loading. MMP-1-mediated pathways may be relevant targets for treating degenerative joint pain in cases with subtle or no evidence of structural degeneration.

Risky interpretations across the length scales: continuum vs. discrete models for soft tissue mechanobiology

Modelling and simulation in mechanobiology play an increasingly important role to unravel the complex mechanisms that allow resident cells to sense and respond to mechanical cues. Many of the in vivo mechanical loads occur on the tissue length scale, thus raising the essential question how the resulting macroscopic strains and stresses are transferred across the scales down to the cellular and subcellular levels. Since cells anchor to the collagen fibres within the extracellular matrix, the reliable representation of fibre deformation is a prerequisite for models that aim at linking tissue biomechanics and cell mechanobiology. In this paper, we consider the two-scale mechanical response of an affine structural model as an example of a continuum mechanical approach and compare it with the results of a discrete fibre network model. In particular, we shed light on the crucially different mechanical properties of the 'fibres' in these two approaches. While assessing the capability of the affine structural approach to capture the fibre kinematics in real tissues is beyond the scope of our study, our results clearly show that neither the macroscopic tissue response nor the microscopic fibre orientation statistics can clarify the question of affinity.

A Nonparametric Approach for Estimating Three-Dimensional Fiber Orientation Distribution Functions (ODFs) in Fibrous Materials

Many biological tissues contain an underlying fibrous microstructure that is optimized to suit a physiological function. The fiber architecture dictates physical characteristics such as stiffness, diffusivity, and electrical conduction. Abnormal deviations of fiber architecture are often associated with disease. Thus, it is useful to characterize fiber network organization from image data in order to better understand pathological mechanisms. We devised a method to quantify distributions of fiber orientations based on the Fourier transform and the Qball algorithm from diffusion MRI. The Fourier transform was used to decompose images into directional components, while the Qball algorithm efficiently converted the directional data from the frequency domain to the orientation domain. The representation in the orientation domain does not require any particular functional representation, and thus the method is nonparametric. The algorithm was verified to demonstrate its reliability and used on datasets from microscopy to show its applicability. This method increases the ability to extract information of microstructural fiber organization from experimental data that will enhance our understanding of structure-function relationships and enable accurate representation of material anisotropy in biological tissues.

Effect of the Fibre Orientation Distribution on the Mechanical and Preforming Behaviour of Nonwoven Preform Made of Recycled Carbon Fibres

Recycling carbon-fibre-reinforced plastic (CFRP) and recovering high-cost carbon fibre (CF) is a preoccupation of scientific and industrial committees due to the environmental and economic concerns. A commercialised nonwoven mat, made of recycled carbon fibre and manufactured using carding and needle-punching technology, can promote second-life opportunities for carbon fibre. This paper aims to evaluate the mechanical and preforming behaviour of this nonwoven material. We focus on the influence that the fibre orientation distribution in the nonwoven material has on its mechanical and preforming behaviour at the preform scale, as well as the tensile properties at composite scale. The anisotropy index induced by fibre orientation is evaluated by analysing SEM micrographs using the fast Fourier transform (FFT) method. Then, the anisotropy in the tensile, bending, and preforming behaviour of the preform is inspected, as well as in the tensile behaviour of the composite. Additionally, we evaluate the impact of the stacking order of multi-layers of the nonwoven material, associated with its preferred fibre orientation (nonwoven anisotropy), on its compaction behaviour. The nonwoven anisotropy, in terms of fibre orientation, induces a strong effect on the preform mechanical and preforming behaviour, as well as the tensile behaviour of the composite. The tensile behaviour of the nonwoven material is governed by the inter-fibre cohesion, which depends on the fibre orientation. The low inter-fibre cohesion, which characterises this nonwoven material, leads to poor resistance to tearing. This type of defect rapidly occurs during preforming, even at too-low membrane tension. Otherwise, the increase in nonwoven layer numbers leads to a decrease in the impact of the nonwoven anisotropy behaviour under compaction load.

A workflow for rapid unbiased quantification of fibrillar feature alignment in biological images

Measuring the organisation of the cellular cytoskeleton and the surrounding extracellular matrix (ECM) is currently of wide interest as changes in both local and global alignment can highlight alterations in cellular functions and material properties of the extracellular environment. Different approaches have been developed to quantify these structures, typically based on fibre segmentation or on matrix representation and transformation of the image, each with its own advantages and disadvantages. Here we present AFT-Alignment by Fourier Transform, a workflow to quantify the alignment of fibrillar features in microscopy images exploiting 2D Fast Fourier Transforms (FFT). Using pre-existing datasets of cell and ECM images, we demonstrate our approach and compare and contrast this workflow with two other well-known ImageJ algorithms to quantify image feature alignment. These comparisons reveal that AFT has a number of advantages due to its grid-based FFT approach. 1) Flexibility in defining the window and neighbourhood sizes allows for performing a parameter search to determine an optimal length scale to carry out alignment metrics. This approach can thus easily accommodate different image resolutions and biological systems. 2) The length scale of decay in alignment can be extracted by comparing neighbourhood sizes, revealing the overall distance that features remain anisotropic. 3) The approach is ambivalent to the signal source, thus making it applicable for a wide range of imaging modalities and is dependent on fewer input parameters than segmentation methods. 4) Finally, compared to segmentation methods, this algorithm is computationally inexpensive, as high-resolution images can be evaluated in less than a second on a standard desktop computer. This makes it feasible to screen numerous experimental perturbations or examine large images over long length scales. Implementation is made available in both MATLAB and Python for wider accessibility, with example datasets for single images and batch processing. Additionally, we include an approach to automatically search parameters for optimum window and neighbourhood sizes, as well as to measure the decay in alignment over progressively increasing length scales.

Design and Production of Customizable and Highly Aligned Fibrillar Collagen Scaffolds

The ability to fabricate anisotropic collagenous materials rapidly and reproducibly has remained elusive despite decades of research. Balancing the natural propensity of monomeric collagen (COL) to spontaneously polymerize in vitro with the mild processing conditions needed to maintain its native substructure upon polymerization introduces challenges that are not easily amenable with off-the-shelf instrumentation. To overcome these challenges, we have designed a platform that simultaneously aligns type I COL fibrils under mild shear flow and builds up the material through layer-by-layer assembly. We explored the mechanisms propagating fibril alignment, targeting experimental variables such as shear rate, viscosity, and time. Coarse-grained molecular dynamics simulations were also employed to help understand how initial reaction conditions including chain length, indicative of initial polymerization, and chain density, indicative of concentration, in the reaction environment impact fibril growth and alignment. When taken together, the mechanistic insights gleaned from these studies inspired the design, iteration, fabrication, and then customization of the fibrous collagenous materials, illustrating a platform material that can be readily adapted to future tissue engineering applications.

Centrifugation and index matching yield a strong and transparent bioinspired nacreous composite

[Figure: see text].

Microfluidic model of monocyte extravasation reveals the role of hemodynamics and subendothelial matrix mechanics in regulating endothelial integrity

Extravasation of circulating cells is an essential process that governs tissue inflammation and the body's response to pathogenic infection. To initiate anti-inflammatory and phagocytic functions within tissues, immune cells must cross the vascular endothelial barrier from the vessel lumen to the subluminal extracellular matrix. In this work, we present a microfluidic approach that enables the recreation of a three-dimensional, perfused endothelial vessel formed by human endothelial cells embedded within a collagen-rich matrix. Monocytes are introduced into the vessel perfusate, and we investigate the role of luminal flow and collagen concentration on extravasation. In vessels conditioned with the flow, increased monocyte adhesion to the vascular wall was observed, though fewer monocytes extravasated to the collagen hydrogel. Our results suggest that the lower rates of extravasation are due to the increased vessel integrity and reduced permeability of the endothelial monolayer. We further demonstrate that vascular permeability is a function of collagen hydrogel mass concentration, with increased collagen concentrations leading to elevated vascular permeability and increased extravasation. Collectively, our results demonstrate that extravasation of monocytes is highly regulated by the structural integrity of the endothelial monolayer. The microfluidic approach developed here allows for the dissection of the relative contributions of these cues to further understand the key governing processes that regulate circulating cell extravasation and inflammation.

Engineering fiber anisotropy within natural collagen hydrogels

It is well known that biophysical properties of the extracellular matrix (ECM), including stiffness, porosity, composition, and fiber alignment (anisotropy), play a crucial role in controlling cell behavior in vivo. Type I collagen (collagen I) is a ubiquitous structural component in the ECM and has become a popular hydrogel material that can be tuned to replicate the mechanical properties found in vivo. In this review article, we describe popular methods to create 2-D and 3-D collagen I hydrogels with anisotropic fiber architectures. We focus on methods that can be readily translated from engineering and materials science laboratories to the life-science community with the overall goal of helping to increase the physiological relevance of cell culture assays.

Adaptive Remodeling in the Elastase-induced Rabbit Aneurysms

BACKGROUND

Rupture of brain aneurysms is associated with high fatality and morbidity rates. Through remodeling of the collagen matrix, many aneurysms can remain unruptured for decades, despite an enlarging and evolving geometry.

OBJECTIVE

Our objective was to explore this adaptive remodeling for the first time in an elastase induced aneurysm model in rabbits.

METHODS

Saccular aneurysms were created in 22 New Zealand white rabbits and remodeling was assessed in tissue harvested 2, 4, 8 and 12 weeks after creation.

RESULTS

The intramural principal stress ratio doubled after aneurysm creation due to increased longitudinal loads, triggering a remodeling response. A distinct wall layer with multi-directional collagen fibers developed between the media and adventitia as early as 2 weeks, and in all cases by 4 weeks with an average thickness of 50.6 ± 14.3 μm. Collagen fibers in this layer were multi-directional (AI = 0.56 ± 0.15) with low tortuosity (1.08 ± 0.02) compared with adjacent circumferentially aligned medial fibers (AI = 0.78 ± 0.12) and highly tortuous adventitial fibers (1.22 ± 0.03). A second phase of remodeling replaced circumferentially aligned fibers in the inner media with longitudinal fibers. A structurally motivated constitutive model with both remodeling modes was introduced along with methodology for determining material parameters from mechanical testing and multiphoton imaging.

CONCLUSIONS

A new mechanism was identified by which aneurysm walls can rapidly adapt to changes in load, ensuring the structural integrity of the aneurysm until a slower process of medial reorganization occurs. The rabbit model can be used to evaluate therapies to increase aneurysm wall stability.

Intra-articular collagenase in the spinal facet joint induces pain, DRG neuron dysregulation and increased MMP-1 absent evidence of joint destruction

Degeneration is a hallmark of painful joint disease and is mediated by many proteases that degrade joint tissues, including collagenases. We hypothesized that purified bacterial collagenase would initiate nociceptive cascades in the joint by degrading the capsular ligament's matrix and activating innervating pain fibers. Intra-articular collagenase in the rat facet joint was investigated for its effects on behavioral sensitivity, joint degeneration, and nociceptive pathways in the peripheral and central nervous systems. In parallel, a co-culture collagen gel model of the ligament was used to evaluate effects of collagenase on microscale changes to the collagen fibers and embedded neurons. Collagenase induced sensitivity within one day, lasting for 3 weeks (p < 0.001) but did not alter ligament structure, cartilage health, or chondrocyte homeostasis. Yet, nociceptive mediators were increased in the periphery (substance P, pERK, and MMP-1; p ≤ 0.039) and spinal cord (substance P and MMP-1; p ≤ 0.041). The collagen loss (p = 0.008) induced by exposing co-cultures to collagenase was accompanied by altered neuronal activity (p = 0.002) and elevated neuronal MMP-1 (p < 0.001), suggesting microscale collagen degradation mediates sensitivity in vivo. The induction of sustained sensitivity and nociception without joint damage may explain the clinical disconnect in which symptomatic joint pain patients present without radiographic evidence of joint destruction.

Fibrillar Collagen Quantification With Curvelet Transform Based Computational Methods

Quantification of fibrillar collagen organization has given new insight into the possible role of collagen topology in many diseases and has also identified candidate image-based bio-markers in breast cancer and pancreatic cancer. We have been developing collagen quantification tools based on the curvelet transform (CT) algorithm and have demonstrated this to be a powerful multiscale image representation method due to its unique features in collagen image denoising and fiber edge enhancement. In this paper, we present our CT-based collagen quantification software platform with a focus on new features and also giving a detailed description of curvelet-based fiber representation. These new features include C++-based code optimization for fast individual fiber tracking, Java-based synthetic fiber generator module for method validation, automatic tumor boundary generation for fiber relative quantification, parallel computing for large-scale batch mode processing, region-of-interest analysis for user-specified quantification, and pre- and post-processing modules for individual fiber visualization. We present a validation of the tracking of individual fibers and fiber orientations by using synthesized fibers generated by the synthetic fiber generator. In addition, we provide a comparison of the fiber orientation calculation on pancreatic tissue images between our tool and three other quantitative approaches. Lastly, we demonstrate the use of our software tool for the automatic tumor boundary creation and the relative alignment quantification of collagen fibers in human breast cancer pathology images, as well as the alignment quantification of in vivo mouse xenograft breast cancer images.

The use of mixed collagen-Matrigel matrices of increasing complexity recapitulates the biphasic role of cell adhesion in cancer cell migration: ECM sensing, remodeling and forces at the leading edge of cancer invasion

The migration of cancer cells is highly regulated by the biomechanical properties of their local microenvironment. Using 3D scaffolds of simple composition, several aspects of cancer cell mechanosensing (signal transduction, EMC remodeling, traction forces) have been separately analyzed in the context of cell migration. However, a combined study of these factors in 3D scaffolds that more closely resemble the complex microenvironment of the cancer ECM is still missing. Here, we present a comprehensive, quantitative analysis of the role of cell-ECM interactions in cancer cell migration within a highly physiological environment consisting of mixed Matrigel-collagen hydrogel scaffolds of increasing complexity that mimic the tumor microenvironment at the leading edge of cancer invasion. We quantitatively show that the presence of Matrigel increases hydrogel stiffness, which promotes β1 integrin expression and metalloproteinase activity in H1299 lung cancer cells. Then, we show that ECM remodeling activity causes matrix alignment and compaction that favors higher tractions exerted by the cells. However, these traction forces do not linearly translate into increased motility due to a biphasic role of cell adhesions in cell migration: at low concentration Matrigel promotes migration-effective tractions exerted through a high number of small sized focal adhesions. However, at high Matrigel concentration, traction forces are exerted through fewer, but larger focal adhesions that favor attachment yielding lower cell motility.

Noise reduction and quantification of fiber orientations in greyscale images

Quantification of the angular orientation distribution of fibrous tissue structures in scientific images benefits from the Fourier image analysis to obtain quantitative information. Measurement uncertainties represent a major challenge and need to be considered by propagating them in order to determine an adaptive anisotropic Fourier filter. Our adaptive filter method (AF) is based on the maximum relative uncertainty δcut of the power spectrum as well as a weighted radial sum with weighting factor α. We use a Monte-Carlo simulation to obtain realistic greyscale images that include defined variations in fiber thickness, length, and angular dispersion as well as variations in noise. From this simulation the best agreement between predefined and derived angular orientation distribution is found for evaluation parameters δcut = 2.1% and α = 1.5. The resulting cumulative orientation distribution was modeled by a sigmoid function to obtain the mean angle and the fiber dispersion. A comparison to a state-of-the-art band-pass method revealed that the AF method is more suitable for the application on greyscale fiber images, since the error of the fiber dispersion significantly decreased from (33.9 ± 26.5)% to (13.2 ± 12.7)%. Both methods were found to accurately quantify the mean fiber orientation with an error of (1.9 ± 1.5)° and (2.3 ± 2.1)° in case of the AF and the band-pass method, respectively. We demonstrate that the AF method is able to accurately quantify the fiber orientation distribution in in vivo second-harmonic generation images of dermal collagen with a mean fiber orientation error of (6.0 ± 4.0)° and a dispersion error of (9.3 ± 12.1)%.

An Agent-Based Discrete Collagen Fiber Network Model of Dynamic Traction Force-Induced Remodeling

Microstructural properties of extracellular matrix (ECM) promote cell and tissue homeostasis as well as contribute to the formation and progression of disease. In order to understand how microstructural properties influence the mechanical properties and traction force-induced remodeling of ECM, we developed an agent-based model that incorporates repetitively applied traction force within a discrete fiber network. An important difference between our model and similar finite element models is that by implementing more biologically realistic dynamic traction, we can explore a greater range of matrix remodeling. Here, we validated our model by reproducing qualitative trends observed in three sets of experimental data reported by others: tensile and shear testing of cell-free collagen gels, collagen remodeling around a single isolated cell, and collagen remodeling between pairs of cells. In response to tensile and shear strain, simulated acellular networks with straight fibrils exhibited biphasic stress-strain curves indicative of strain-stiffening. When fibril curvature was introduced, stress-strain curves shifted to the right, delaying the onset of strain-stiffening. Our data support the notion that strain-stiffening might occur as individual fibrils successively align along the axis of strain and become engaged in tension. In simulations with a single, contractile cell, peak collagen displacement occurred closest to the cell and decreased with increasing distance. In simulations with two cells, compaction of collagen between cells appeared inversely related to the initial distance between cells. These results for cell-populated collagen networks match in vitro findings. A demonstrable benefit of modeling is that it allows for further analysis not feasible with experimentation. Within two-cell simulations, strain energy within the collagen network measured from the final state was relatively uniform around the outer surface of cells separated by 250 μm, but became increasingly nonuniform as the distance between cells decreased. For cells separated by 75 and 100 μm, strain energy peaked in the direction toward the other cell in the region in which fibrils become highly aligned and reached a minimum adjacent to this region, not on the opposite side of the cell as might be expected. This pattern of strain energy was partly attributable to the pattern of collagen compaction, but was still present when mapping strain energy divided by collagen density. Findings like these are of interest because fibril alignment, density, and strain energy may each contribute to contact guidance during tissue morphogenesis.

A computational multi-scale approach to investigate mechanically-induced changes in tricuspid valve anterior leaflet microstructure

The tricuspid valve is an atrioventricular valve that prevents blood backflow from the right ventricle into the right atrium during ventricular contractions. It is important to study mechanically induced microstructural alterations in the tricuspid valve leaflets, as this aids both in understanding valvular diseases and in the development of new engineered tissue replacements. The structure and composition of the extracellular matrix (ECM) fiber networks are closely tied to an overall biomechanical function of the tricuspid valve. In this study, we conducted experiments and implemented a multiscale modeling approach to predict ECM microstructural changes to tissue-level mechanical responses in a controlled loading environment. In particular, we characterized a sample of a porcine anterior leaflet at a macroscale using a biaxial mechanical testing method. We then generated a three-dimensional finite element model, to which computational representations of corresponding fiber networks were incorporated based on properties of the microstructural architecture obtained from small angle light scattering. Using five different biaxial boundary conditions, we performed iterative simulations to obtain model parameters with an overall R² value of 0.93. We observed that mechanical loading could markedly alter the underlying ECM architecture. For example, a relatively isotropic fiber network (with an anisotropy index value α of 28%) became noticeably more anisotropic (with an α of 40%) when it underwent mechanical loading. We also observed that the mechanical strain was distributed in a different manner at the ECM/fiber level as compared to the tissue level. The approach presented in this study has the potential to be implemented in pathophysiologically altered biomechanical and structural conditions and to bring insights into the mechanobiology of the tricuspid valve. STATEMENT OF SIGNIFICANCE: Quantifying abnormal cellar/ECM-level deformation of tricuspid valve leaflets subjected to a modified loading environment is of great importance, as it is believed to be linked to valvular remodeling responses. For example, developing surgical procedures or engineered tissue replacements that maintain/mimic ECM-level mechanical homeostasis could lead to more durable outcomes. To quantify leaflet deformation, we built a multiscale framework encompassing the contributions of disorganized ECM components and organized fibers, which can predict the behavior of the tricuspid valve leaflets under physiological loading conditions both at the tissue level and at the ECM level. In addition to future in-depth studies of tricuspid valve pathologies, our model can be used to characterize tissues in other valves of the heart.

Extracellular Matrix From Hypertrophic Myocardium Provokes Impaired Twitch Dynamics in Healthy Cardiomyocytes

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The goal of this study was to examine the effects of diseased extracellular matrix on the behavior of healthy heart cells.

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Myocardium was harvested from a genetically engineered miniature pig carrying the hypertrophic cardiomyopathy mutation MYH7 R403Q and from a wild-type littermate.

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Engineered heart tissues were created by seeding healthy human induced pluripotent stem cell–derived cardiomyocytes onto thin strips of decellularized porcine myocardium.

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Engineered heart tissues made from the extracellular matrix of hypertrophic cardiomyopathy hearts exhibit increased stiffness, impaired relaxation, and increased force development.

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This suggests that diseased extracellular matrix can provoke abnormal contractile behavior in otherwise healthy cardiomyocytes.

Hypertrophic cardiomyopathy (HCM) is often caused by single sarcomeric gene mutations that affect muscle contraction. Pharmacological correction of mutation effects prevents but does not reverse disease in mouse models. Suspecting that diseased extracellular matrix is to blame, we obtained myocardium from a miniature swine model of HCM, decellularized thin slices of the tissue, and re-seeded them with healthy human induced pluripotent stem cell–derived cardiomyocytes. Compared with cardiomyocytes grown on healthy extracellular matrix, those grown on the diseased matrix exhibited prolonged contractions and poor relaxation. This outcome suggests that extracellular matrix abnormalities must be addressed in therapies targeting established HCM.

Quantification of collagen fiber structure using second harmonic generation imaging and two-dimensional discrete Fourier transform analysis: Application to the human optic nerve head

Second harmonic generation (SHG) microscopy is widely used to image collagen fiber microarchitecture due to its high spatial resolution, optical sectioning capabilities and relatively nondestructive sample preparation. Quantification of SHG images requires sensitive methods to capture fiber alignment. This article presents a two-dimensional discrete Fourier transform (DFT)-based method for collagen fiber structure analysis from SHG images. The method includes integrated periodicity plus smooth image decomposition for correction of DFT edge discontinuity artefact, avoiding the loss of peripheral image data encountered with more commonly used windowing methods. Outputted parameters are as follows: the collagen fiber orientation distribution, aligned collagen content and the degree of collagen fiber dispersion along the principal orientation. We demonstrate its application to determine collagen microstructure in the human optic nerve head, showing its capability to accurately capture characteristic structural features including radial fiber alignment in the innermost layers of the bounding sclera and a circumferential collagen ring in the mid-stromal tissue. Higher spatial resolution rendering of individual lamina cribrosa beams within the nerve head is also demonstrated. Validation of the method is provided in the form of correlative results from wide-angle X-ray scattering and application of the presented method to other fibrous tissues.

Quantitative Label-Free Imaging of 3D Vascular Networks Self-Assembled in Synthetic Hydrogels

Vascularization is an important strategy to overcome diffusion limits and enable the formation of complex, physiologically relevant engineered tissues and organoids. Self-assembly is a technique to generate in vitro vascular networks, but engineering the necessary network morphology and function remains challenging. Here, autofluorescence multiphoton microscopy (aMPM), a label-free imaging technique, is used to quantitatively evaluate in vitro vascular network morphology. Vascular networks are generated using human embryonic stem cell-derived endothelial cells and primary human pericytes encapsulated in synthetic poly(ethylene glycol)-based hydrogels. Two custom-built bioreactors are used to generate distinct fluid flow patterns during vascular network formation: recirculating flow or continuous flow. aMPM is used to image these 3D vascular networks without the need for fixation, labels, or dyes. Image processing and analysis algorithms are developed to extract quantitative morphological parameters from these label-free images. It is observed with aMPM that both bioreactors promote formation of vascular networks with lower network anisotropy compared to static conditions, and the continuous flow bioreactor induces more branch points compared to static conditions. Importantly, these results agree with trends observed with immunocytochemistry. These studies demonstrate that aMPM allows label-free monitoring of vascular network morphology to streamline optimization of growth conditions and provide quality control of engineered tissues.

Abnormalities of vascular histology and collagen fiber configuration in patients with advanced chronic kidney disease

INTRODUCTION:

Several histologic features have been identified in the upper-extremity arteries and veins of patients with advanced chronic kidney disease, which may affect arteriovenous fistula maturation. However, it is unclear whether these chronic kidney disease vascular features are abnormal.

METHODS:

We obtained upper-extremity arterial and venous specimens from 125 advanced chronic kidney disease patients undergoing arteriovenous fistula creation and from 15 control subjects. We quantified medial fibrosis, micro-calcification, and intimal hyperplasia with appropriate histology stains. We characterized medial collagen fiber configuration in second-harmonic-generation microscopy images for the fiber anisotropy index and the dominant fiber direction.

RESULTS:

The advanced chronic kidney disease patients were significantly younger than control subjects (53 ± 14 years vs 76 ± 11 years, p < 0.001). After controlling for age, the chronic kidney disease patients had greater arterial medial fibrosis (69% ± 14% vs 51% ± 10%, p < 0.001) and greater arterial micro-calcification (3.03% ± 5.17% vs 0.01% ± 0.03%, p = 0.02), but less arterial intimal thickness (30 ± 25 µm vs 63 ± 25 µm, p < 0.001), as compared to control subjects. The anisotropy index of medial collagen fibers was lower in both arteries (0.24 ± 0.10 vs 0.44 ± 0.04, p < 0.001) and veins (0.28 ± 0.09 vs 0.53 ± 0.10, p < 0.001) in chronic kidney disease patients, indicating that orientation of the fibers was more disordered. The dominant direction of medial collagen fibers in chronic kidney disease patients was greater in the arteries (49.3° ± 23.6° vs 4.0° ± 2.0°, p < 0.001) and the veins (30.0° ± 19.6° vs 3.9° ± 2.1°, p < 0.001), indicating that the fibers in general were aligned more perpendicular to the lumen.

CONCLUSION:

Advanced chronic kidney disease is associated with several abnormalities in vascular histology and collagen fiber configuration. Future research is needed to investigate whether these abnormalities affect the maturation outcomes of arteriovenous fistulas.

Incorporating 4D into Bioprinting: Real-Time Magnetically Directed Collagen Fiber Alignment for Generating Complex Multilayered Tissues

In vitro multilayered tissues with mimetic architectures resembling native tissues are valuable tools for application in medical research. In this study, an advanced bioprinting strategy is presented for aligning collagen fibers contained in functional bioinks. Streptavidin-coated iron nanoparticles are embedded in printable bioinks with varying concentrations of low gelling temperature agarose and type I collagen. By applying a straightforward magnetic-based mechanism in hydrogels during bioprinting, it is possible to align collagen fibers in less concentrated hydrogel blends with a maximum agarose concentration of 0.5 w/v%. Conversely, more elevated concentrations of agarose in printable blends show random collagen fiber distribution. Interestingly, hydrogel blends with unidirectionally aligned collagen fibers show significantly higher compression moduli compared to hydrogel blends including random fibers. Considering its application in the field of cartilage tissue engineering, bioprinted constructs with alternating layers of aligned and random fibers are fabricated. After 21 days of culture, cell-loaded constructs with alternating layers of aligned and random fibers express markedly more collagen II in comparison to solely randomly oriented fiber constructs. These encouraging results translate the importance of the structure and architecture of bioinks used in bioprinting in light of their use for tissue engineering and personalized medical applications.

Static-Aligned Piezoelectric Poly (Vinylidene Fluoride) Electrospun Nanofibers/MWCNT Composite Membrane: Facile Method

Polyvinylidene Fluoride (PVDF) piezoelectric electrospun nanofibers have been intensively used for sensing and actuation applications in the last decade. However, in most cases, random PVDF piezoelectric nanofiber mats have moderate piezoelectric response compared to aligned PVDF nanofibers. In this work, we demonstrate the effect of alignment conducted by a collector setup composed of two-metal bars with gab inside where the aligned fiber can be formed. That is what we called static aligned nanofibers, which is distinct from the dynamic traditional technique using a high speed rotating drum. The two-bar system shows a superior alignment degree for the PVDF nanofibers. Also, the effect of added carbon nanotubes (CNTs) of different concentrations to PVDF nanofibers is studied to observe the enhancement of piezoelectric response of PVDF nanofibers. Improvement of β-phase content of aligned (PVDF) nanofibers, as compared to randomly orientated fibers, is achieved. Significant change in the piezoelectricity of PVDF fiber is produced with added CNTs with saturation response in the case of 0.3 wt % doping of CNTs, and piezoelectric sensitivity of 73.8 mV/g with applied masses down to 100 g.

Methods for Quantifying Fibrillar Collagen Alignment

Recent evidence has implicated collagen, particularly fibrillar collagen, in a number of diseases ranging from osteogenesis imperfecta and asthma to breast and ovarian cancer. A key property of collagen that has been correlated with disease has been the alignment of collagen fibers. Collagen can be visualized using a variety of imaging techniques including second-harmonic generation (SHG) microscopy, polarized light microscopy, and staining with dyes or antibodies. However, there exists a great need to easily and robustly quantify images from these modalities for individual fibers in specified regions of interest and with respect to relevant boundaries. Most currently available computational tools rely on calculation of pixel-wise orientation or global window-wise orientation that do not directly calculate or give visible fiber-wise information and do not provide relative orientation against boundaries. We describe and detail how to use a freely available, open-source MATLAB software framework that includes two separate but linked packages "CurveAlign" and "CT-FIRE" that can address this need by either directly extracting individual fibers using an improved fiber tracking algorithm or directly finding optimal representation of fiber edges using the curvelet transform. This curvelet-based framework allows the user to measure fiber alignment on a global, region of interest, and fiber basis. Additionally, users can measure fiber angle relative to manually or automatically segmented boundaries. This tool does not require prior experience of programming or image processing and can handle multiple files, enabling efficient quantification of collagen organization from biological datasets.

Heterogeneity and Robustness in Plant Morphogenesis: From Cells to Organs

Development is remarkably reproducible, producing organs with the same size, shape, and function repeatedly from individual to individual. For example, every flower on the Antirrhinum stalk has the same snapping dragon mouth. This reproducibility has allowed taxonomists to classify plants and animals according to their morphology. Yet these reproducible organs are composed of highly variable cells. For example, neighboring cells grow at different rates in Arabidopsis leaves, sepals, and shoot apical meristems. This cellular variability occurs in normal, wild-type organisms, indicating that cellular heterogeneity (or diversity in a characteristic such as growth rate) is either actively maintained or, at a minimum, not entirely suppressed. In fact, cellular heterogeneity can contribute to producing invariant organs. Here, we focus on how plant organs are reproducibly created during development from these highly variable cells.

Pressure-induced microstructural changes in porcine tricuspid valve leaflets

Quantifying mechanically-induced changes in the tricuspid valve extracellular matrix (ECM) structural components, e.g. collagen fiber spread and distribution, is important as it determines the overall macro-scale tissue responses and subsequently its function/malfunction in physiological/pathophysiological states. For example, functional tricuspid regurgitation, a common tricuspid valve disorder, could be caused by elevated right ventricular pressure due to pulmonary hypertension. In such patients, the geometry and the normal function of valve leaflets alter due to chronic pressure overload, which could cause remodeling responses in the ECM and change its structural components. To understand such a relation, we developed an experimental setup and measured alteration of leaflet microstructure in response to pressure increase in porcine tricuspid valves using the small angle light scattering technique. The anisotropy index, a measure of the fiber spread and distribution, was obtained and averaged for each region of the anterior, posterior, and septal leaflet using four averaging methods. The average anisotropy indices (mean ± standard error) in the belly region of the anterior, posterior, and septal leaflets of non-pressurized valves were found to be 12 ± 2%, 21 ± 3% and 12 ± 1%, respectively. For the pressurized valve, the average values of the anisotropy index in the belly region of the anterior, posterior, and septal leaflets were 56 ± 5%, 39 ± 7% and 32 ± 5%, respectively. Overall, the average anisotropy index was found to be higher for all leaflets in the pressurized valves as compared to the non-pressurized valves, indicating that the ECM fibers became more aligned in response to an increased ventricular pressure.

STATEMENT OF SIGNIFICANCE

Mechanics plays a critical role in development, regeneration, and remodeling of tissues. In the current study, we have conducted experiments to examine how increasing the ventricular pressure leads to realignment of protein fibers comprising the extracellular matrix (ECM) of the tricuspid valve leaflets. Like many other tissues, in cardiac valves, cell-matrix interactions and gene expressions are heavily influenced by changes in the mechanical microenvironment at the ECM/cellular level. We believe that our study will help us better understand how abnormal increases in the right ventricular pressure (due to pulmonary hypertension) could change the structural architecture of tricuspid valve leaflets and subsequently the mechanical microenvironment at the ECM/cellular level.

Degradation of extracellular matrix regulates osteoblast migration: A microfluidic-based study

Bone regeneration is strongly dependent on the capacity of cells to move in a 3D microenvironment, where a large cascade of signals is activated. To improve the understanding of this complex process and to advance in the knowledge of the role of each specific signal, it is fundamental to analyze the impact of each factor independently. Microfluidic-based cell culture is an appropriate technology to achieve this objective, because it allows recreating realistic 3D local microenvironments by taking into account the extracellular matrix, cells and chemical gradients in an independent or combined scenario. The main aim of this work is to analyze the impact of extracellular matrix properties and growth factor gradients on 3D osteoblast movement, as well as the role of cell matrix degradation. For that, we used collagen-based hydrogels, with and without crosslinkers, under different chemical gradients, and eventually inhibiting metalloproteinases to tweak matrix degradation. We found that osteoblast's 3D migratory patterns were affected by the hydrogel properties and the PDGF-BB gradient, although the strongest regulatory factor was determined by the ability of cells to remodel the matrix.

Collagen organization regulates stretch-initiated pain-related neuronal signals in vitro: Implications for structure-function relationships in innervated ligaments

Injury to the spinal facet capsule, an innervated ligament with heterogeneous collagen organization, produces pain. Although mechanical facet joint trauma activates embedded afferents, it is unclear if, and how, the varied extracellular microstructure of its ligament affects sensory transduction for pain from mechanical inputs. To investigate the effects of macroscopic deformations on afferents in collagen matrices with different organizations, an in vitro neuron-collagen construct (NCC) model was used. NCCs with either randomly organized or parallel aligned collagen fibers were used to mimic the varied microstructure in the facet capsular ligament. Embryonic rat dorsal root ganglia (DRG) were encapsulated in the NCCs; axonal outgrowth was uniform and in all directions in random NCCs, but parallel in aligned NCCs. NCCs underwent uniaxial stretch (0.25 ± 0.06 strain) corresponding to sub-failure facet capsule strains that induce pain. Macroscopic NCC mechanics were measured and axonal expression of phosphorylated extracellular signal-regulated kinase (pERK) and the neurotransmitter substance P (SP) was assayed at 1 day to assess neuronal activation and nociception. Stretch significantly upregulated pERK expression in both random and aligned gels (p < 0.001), with the increase in pERK being significantly higher (p = 0.013) in aligned than in random NCCs. That increase likely relates to the higher peak force (p = 0.025) and stronger axon alignment (p < 0.001) with stretch direction in the aligned NCCs. In contrast, SP expression was greater in stretched NCCs (p < 0.001) regardless of collagen organization. These findings suggest that collagen organization differentially modulates pain-related neuronal signaling and support structural heterogeneity of ligament tissue as mediating sensory function. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:770-777, 2018.

Fiber Network Models Predict Enhanced Cell Mechanosensing on Fibrous Gels

The propagation of mechanical signals through nonlinear fibrous tissues is much more extensive than through continuous synthetic hydrogels. Results from recent studies indicate that increased mechanical propagation arises from the fibrous nature of the material rather than the strain-stiffening property. The relative importance of different parameters of the fibrous network structure to this propagation, however, remains unclear. In this work, we directly compared the mechanical response of substrates of varying thickness subjected to a constant cell traction force using either a nonfibrous strain-stiffening continuum-based model or a volume-averaged fiber network model consisting of two different types of fiber network structures: one with low fiber connectivity (growth networks) and one with high fiber connectivity (Delaunay networks). The growth network fiber models predicted a greater propagation of substrate displacements through the model and a greater sensitivity to gel thickness compared to the more connected Delaunay networks and the nonlinear continuum model. Detailed analysis of the results indicates that rotational freedom of the fibers in a network with low fiber connectivity is critically important for enhanced, long-range mechanosensing. Our findings demonstrate the utility of multiscale models in predicting cells mechanosensing on fibrous gels, and they provide a more complete understanding of how cell traction forces propagate through fibrous tissues, which has implications for the design of engineered tissues and the stem cell niche.

Human in vitro Model Reveals the Effects of Collagen Cross-linking on Keratoconus Pathogenesis

Keratoconus (KC) is a corneal thinning disorder that leads to severe vision impairment As opposed to corneal transplantation; corneal collagen crosslinking (CXL) is a relatively non-invasive procedure that leads to an increase in corneal stiffness. In order to evaluate the effect of CXL on human corneal stromal cells in vitro, we developed a 3-D in vitro CXL model, using primary Human corneal fibroblasts (HCFs) from healthy patients and Human Keratoconus fibroblasts (HKCs) from KC patients. Cells were plated on transwell polycarbonate membranes and stimulated by a stable vitamin C. CXL was performed using a mixed riboflavin 0.1% PBS solution followed by UVA irradiation. Our data revealed no significant apoptosis in either HCFs or HKCs following CXL. However, corneal fibrosis markers, Collagen III and α-smooth muscle actin, were significantly downregulated in CXL HKCs. Furthermore, a significant downregulation was seen in SMAD3, SMAD7, and phosphorylated SMADs -2 and -3 expression in CXL HKCs, contrary to a significant upregulation in both SMAD2 and Lysyl oxidase expression, compared to HCFs. Our novel 3-D in vitro model can be utilized to determine the cellular and molecular effects on the human corneal stroma post CXL, and promises to establish optimized treatment modalities in patients with KC.

Image-based multiscale mechanical modeling shows the importance of structural heterogeneity in the human lumbar facet capsular ligament

The lumbar facet capsular ligament (FCL) primarily consists of aligned type I collagen fibers that are mainly oriented across the joint. The aim of this study was to characterize and incorporate in-plane local fiber structure into a multiscale finite element model to predict the mechanical response of the FCL during in vitro mechanical tests, accounting for the heterogeneity in different scales. Characterization was accomplished by using entire-domain polarization-sensitive optical coherence tomography to measure the fiber structure of cadaveric lumbar FCLs ([Formula: see text]). Our imaging results showed that fibers in the lumbar FCL have a highly heterogeneous distribution and are neither isotropic nor completely aligned. The averaged fiber orientation was [Formula: see text] ([Formula: see text] in the inferior region and [Formula: see text] in the middle and superior regions), with respect to lateral-medial direction (superior-medial to inferior-lateral). These imaging data were used to construct heterogeneous structural models, which were then used to predict experimental gross force-strain behavior and the strain distribution during equibiaxial and strip biaxial tests. For equibiaxial loading, the structural model fit the experimental data well but underestimated the lateral-medial forces by [Formula: see text]16% on average. We also observed pronounced heterogeneity in the strain field, with stretch ratios for different elements along the lateral-medial axis of sample typically ranging from about 0.95 to 1.25 during a 12% strip biaxial stretch in the lateral-medial direction. This work highlights the multiscale structural and mechanical heterogeneity of the lumbar FCL, which is significant both in terms of injury prediction and microstructural constituents' (e.g., neurons) behavior.

Extracting Subcellular Fibrillar Alignment with Error Estimation: Application to Microtubules

The order and orientation of cortical microtubule (CMT) arrays and their dynamics play an essential role in plant morphogenesis. To extract detailed CMT alignment structures in an objective, local, and accurate way, we propose an error-based extraction method that applies to general fluorescence intensity data on three-dimensional cell surfaces. Building on previous techniques to quantify alignments, our method can determine the statistical error for specific local regions, or the minimal scales of local regions for a desired accuracy goal. After validating our method with synthetic images with known alignments, we demonstrate the ability of our method to quantify subcellular CMT alignments on images with microtubules marked with green fluorescent protein in various cell types. Our method could also be applied to detect alignment structures in other fibrillar elements, such as actin filaments, cellulose, and collagen.

The Use of Tomosynthesis in the Global Study of Knee Subchondral Insufficiency Fractures

RATIONALE AND OBJECTIVES

Subchondral insufficiency fractures (SIF), previously termed spontaneous osteonecrosis of the knee, are marked by a sudden onset of severe pain. Other than the size of the lesion, prediction for progression to joint replacement is difficult. The objective was to determine if quantitative analysis of bone texture using digital tomosynthesis imaging would be useful in predicting more rapid progression to joint replacement.

MATERIALS AND METHODS

Tomosynthesis studies of 30 knees with documented SIF were quantified by fractal, mean intercept length (MIL), and line fraction deviation analyses. Fractal dimension, lacunarity, MIL, and line fraction deviation variables measured from these analyses were then correlated to short interval progression to joint replacement surgery.

RESULTS

Higher odds for joint replacement were related to higher values of the standard deviation of slope lacunarity and to morphometric measures (eg, MIL).

CONCLUSIONS

Using digital tomosynthesis images for bone texture assessment may help distinguish condylar bone response in SIF, potentially acting as a clinically relevant predictive tool. In the future, contrasting SIF to the more gradual long-term process of osteoarthritis, there may be a better understanding of the different mechanisms for the two conditions.

Quantitative differentiation of normal and scarred tissues using second-harmonic generation microscopy

The aim of this study was to differentiate normal and scarred hamster cheek pouch samples by applying a quantitative image analysis technique for determining collagen fiber direction and density in second-harmonic generation microscopy images. This paper presents a collagen tissue analysis of scarred cheek pouches of four adult male Golden Syrian hamsters as an animal model for vocal fold scarring. One cheek pouch was scarred using an electrocautery unit and the other cheek was used as a control for each hamster. A home-built upright microscope and a compact ultrafast fiber laser were used to acquire depth resolved epi-collected second-harmonic generation images of collagen fibers. To quantify the average fiber direction and fiber density in each image, we applied two-dimensional Fourier analysis and intensity thresholding at five different locations for each control and scarred tissue sample, respectively. The resultant depth-resolved average fiber direction variance for scarred hamster cheek pouches (0.61 ± 0.03) was significantly lower (p < 0.05) than control tissue (0.73 ± 0.04), indicating increased fiber alignment within the scar. Depth-resolved average voxel density measurements indicated scarred tissues contained greater (p < 0.005) fiber density (0.72 ± 0.09) compared to controls (0.18 ± 0.03). In the present study, image analysis of both fiber alignment and density from depth-resolved second-harmonic generation images in epi-detection mode enabled the quantification of the increased collagen fiber deposition and alignment typically observed in fibrosis. The epi-detection geometry is the only viable method for in vivo imaging as well as imaging thick turbid tissues. These quantitative endpoints, clearly differentiating between control and scarred hamster cheek pouches, provide an objective means to characterize the extent of vocal fold scarring in vivo in preclinical and clinical research. In particular, this non-invasive method offers advantages for monitoring scar treatments in live animals and following the effects of scarring-related treatments such as application of steroids or drugs targeting pathways involved in fibrosis. SCANNING 38:684-693, 2016. © 2016 Wiley Periodicals, Inc.

Human Corneal Fibroblast Pattern Evolution and Matrix Synthesis on Mechanically Biased Substrates

In a fibroblast colony model of corneal stromal development, we asked how physiological tension influences the patterning dynamics of fibroblasts and the orientation of deposited extracellular matrix (ECM). Using long-term live-cell microscopy, enabled by an optically accessible mechanobioreactor, a primary human corneal fibroblast colony was cultured on three types of substrates: a mechanically biased, loaded, dense, disorganized collagen substrate (LDDCS), a glass coverslip, and an unloaded, dense, disorganized collagen substrate (UDDCS). On LDDCS, fibroblast orientation and migration along a preferred angle developed early, cell orientation was correlated over long distances, and the colony pattern was stable. On glass, fibroblast orientation was poorly correlated, developed more slowly, and colony patterns were metastable. On UDDCS, cell orientation was correlated over shorter distances compared with LDDCS specimens. On all substrates, the ECM pattern reflected the cell pattern. In summary, mechanically biasing the collagen substrate altered the early migration behavior of individual cells, leading to stable emergent cell patterning, which set the template for newly synthesized ECM.

Large strain stimulation promotes extracellular matrix production and stiffness in an elastomeric scaffold model

Mechanical conditioning of engineered tissue constructs is widely recognized as one of the most relevant methods to enhance tissue accretion and microstructure, leading to improved mechanical behaviors. The understanding of the underlying mechanisms remains rather limited, restricting the development of in silico models of these phenomena, and the translation of engineered tissues into clinical application. In the present study, we examined the role of large strip-biaxial strains (up to 50%) on ECM synthesis by vascular smooth muscle cells (VSMCs) micro-integrated into electrospun polyester urethane urea (PEUU) constructs over the course of 3 weeks. Experimental results indicated that VSMC biosynthetic behavior was quite sensitive to tissue strain maximum level, and that collagen was the primary ECM component synthesized. Moreover, we found that while a 30% peak strain level achieved maximum ECM synthesis rate, further increases in strain level lead to a reduction in ECM biosynthesis. Subsequent mechanical analysis of the formed collagen fiber network was performed by removing the scaffold mechanical responses using a strain-energy based approach, showing that the denovo collagen also demonstrated mechanical behaviors substantially better than previously obtained with small strain training and comparable to mature collagenous tissues. We conclude that the application of large deformations can play a critical role not only in the quantity of ECM synthesis (i.e. the rate of mass production), but also on the modulation of the stiffness of the newly formed ECM constituents. The improved understanding of the process of growth and development of ECM in these mechano-sensitive cell-scaffold systems will lead to more rational design and manufacturing of engineered tissues operating under highly demanding mechanical environments.

The Action of Discoidin Domain Receptor 2 in Basal Tumor Cells and Stromal Cancer-Associated Fibroblasts Is Critical for Breast Cancer Metastasis

High levels of collagen deposition in human and mouse breast tumors are associated with poor outcome due to increased local invasion and distant metastases. Using a genetic approach, we show that, in mice, the action of the fibrillar collagen receptor discoidin domain receptor 2 (DDR2) in both tumor and tumor-stromal cells is critical for breast cancer metastasis yet does not affect primary tumor growth. In tumor cells, DDR2 in basal epithelial cells regulates the collective invasion of tumor organoids. In stromal cancer-associated fibroblasts (CAFs), DDR2 is critical for extracellular matrix production and the organization of collagen fibers. The action of DDR2 in CAFs also enhances tumor cell collective invasion through a pathway distinct from the tumor-cell-intrinsic function of DDR2. This work identifies DDR2 as a potential therapeutic target that controls breast cancer metastases through its action in both tumor cells and tumor-stromal cells at the primary tumor site.

Mechanical signals regulate and activate SNAIL1 protein to control the fibrogenic response of cancer-associated fibroblasts

Increased deposition of collagen in extracellular matrix (ECM) leads to increased tissue stiffness and occurs in breast tumors. When present, this increases tumor invasion and metastasis. Precisely how this deposition is regulated and maintained in tumors is unclear. Much has been learnt about mechanical signal transduction in cells, but transcriptional responses and the pathophysiological consequences are just becoming appreciated. Here, we show that the SNAIL1 (also known as SNAI1) protein level increases and accumulates in nuclei of breast tumor cells and cancer-associated fibroblasts (CAFs) following exposure to stiff ECM in culture and in vivo SNAIL1 is required for the fibrogenic response of CAFs when exposed to a stiff matrix. ECM stiffness induces ROCK activity, which stabilizes SNAIL1 protein indirectly by increasing intracellular tension, integrin clustering and integrin signaling to ERK2 (also known as MAPK1). Increased ERK2 activity leads to nuclear accumulation of SNAIL1, and, thus, avoidance of cytosolic proteasome degradation. SNAIL1 also influences the level and activity of YAP1 in CAFs exposed to a stiff matrix. This work describes a mechanism whereby increased tumor fibrosis can perpetuate activation of CAFs to sustain tumor fibrosis and promote tumor metastasis through regulation of SNAIL1 protein level and activity.