The mechanical importance of myelination in the central nervous system

The Networking Brain: How Extracellular Matrix, Cellular Networks, and Vasculature Shape the In Vivo Mechanical Properties of the Brain

Mechanically, the brain is characterized by both solid and fluid properties. The resulting unique material behavior fosters proliferation, differentiation, and repair of cellular and vascular networks, and optimally protects them from damaging shear forces. Magnetic resonance elastography (MRE) is a noninvasive imaging technique that maps the mechanical properties of the brain in vivo. MRE studies have shown that abnormal processes such as neuronal degeneration, demyelination, inflammation, and vascular leakage lead to tissue softening. In contrast, neuronal proliferation, cellular network formation, and higher vascular pressure result in brain stiffening. In addition, brain viscosity has been reported to change with normal blood perfusion variability and brain maturation as well as disease conditions such as tumor invasion. In this article, the contributions of the neuronal, glial, extracellular, and vascular networks are discussed to the coarse-grained parameters determined by MRE. This reductionist multi-network model of brain mechanics helps to explain many MRE observations in terms of microanatomical changes and suggests that cerebral viscoelasticity is a suitable imaging marker for brain disease.

A comprehensive review on modeling aspects of infusion-based drug delivery in the brain

Brain disorders represent an ever-increasing health challenge worldwide. While conventional drug therapies are less effective due to the presence of the blood-brain barrier, infusion-based methods of drug delivery to the brain represent a promising option. Since these methods are mechanically controlled and involve multiple physical phases ranging from the neural and molecular scales to the brain scale, highly efficient and precise delivery procedures can significantly benefit from a comprehensive understanding of drug-brain and device-brain interactions. Behind these interactions are principles of biophysics and biomechanics that can be described and captured using mathematical models. Although biomechanics and biophysics have received considerable attention, a comprehensive mechanistic model for modeling infusion-based drug delivery in the brain has yet to be developed. Therefore, this article reviews the state-of-the-art mechanistic studies that can support the development of next-generation models for infusion-based brain drug delivery from the perspective of fluid mechanics, solid mechanics, and mathematical modeling. The supporting techniques and database are also summarized to provide further insights. Finally, the challenges are highlighted and perspectives on future research directions are provided. STATEMENT OF SIGNIFICANCE: Despite the immense potential of infusion-based drug delivery methods for bypassing the blood-brain barrier and efficiently delivering drugs to the brain, achieving optimal drug distribution remains a significant challenge. This is primarily due to our limited understanding of the complex interactions between drugs and the brain that are governed by principles of biophysics and biomechanics, and can be described using mathematical models. This article provides a comprehensive review of state-of-the-art mechanistic studies that can help to unravel the mechanism of drug transport in the brain across the scales, which underpins the development of next-generation models for infusion-based brain drug delivery. More broadly, this review will serve as a starting point for developing more effective treatments for brain diseases and mechanistic models that can be used to study other soft tissue and biomaterials.

Mechanobiological insight into brain diseases based on mechanosensitive channels: Common mechanisms and clinical potential

BACKGROUND

As physical signals, mechanical cues regulate the neural cells in the brain. The mechanosensitive channels (MSCs) perceive the mechanical cues and transduce them by permeating specific ions or molecules across the plasma membrane, and finally trigger a series of intracellular bioelectrical and biochemical signals. Emerging evidence supports that wide-distributed, high-expressed MSCs like Piezo1 play important roles in several neurophysiological processes and neurological disorders.

AIMS

To systematically conclude the functions of MSCs in the brain and provide a novel mechanobiological perspective for brain diseases.

METHOD

We summarized the mechanical cues and MSCs detected in the brain and the research progress on the functional roles of MSCs in physiological conditions. We then concluded the pathological activation and downstream pathways triggered by MSCs in two categories of brain diseases, neurodegenerative diseases and place-occupying damages. Finally, we outlined the methods for manipulating MSCs and discussed their medical potential with some crucial outstanding issues.

RESULTS

The MSCs present underlying common mechanisms in different brain diseases by acting as the "transportation hubs" to transduce the distinct signal patterns: the upstream mechanical cues and the downstream intracellular pathways. Manipulating the MSCs is feasible to alter the complicated downstream processes, providing them promising targets for clinical treatment.

CONCLUSIONS

Recent research on MSCs provides a novel insight into brain diseases. The common mechanisms mediated by MSCs inspire a wide range of therapeutic potentials targeted on MSCs in different brain diseases.

Mechanical Properties of White Matter Tracts in Aging Assessed via Anisotropic MR Elastography

Magnetic resonance elastography (MRE) is a promising neuroimaging technique to probe tissue microstructure, which has revealed widespread softening with loss of structural integrity in the aging brain. Traditional MRE approaches assume mechanical isotropy. However, white matter is known to be anisotropic from aligned, myelinated axonal bundles, which can lead to uncertainty in mechanical property estimates in these areas when using isotropic MRE. Recent advances in anisotropic MRE now allow for estimation of shear and tensile anisotropy, along with substrate shear modulus, in white matter tracts. The objective of this study was to investigate age-related differences in anisotropic mechanical properties in human brain white matter tracts for the first time. Anisotropic mechanical properties in all tracts were found to be significantly lower in older adults compared to young adults, with average property differences ranging between 0.028-0.107 for shear anisotropy and between 0.139-0.347 for tensile anisotropy. Stiffness perpendicular to the axonal fiber direction was also significantly lower in older age, but only in certain tracts. When compared with fractional anisotropy measures from diffusion tensor imaging, we found that anisotropic MRE measures provided additional, complementary information in describing differences between the white matter integrity of young and older populations. Anisotropic MRE provides a new tool for studying white matter structural integrity in aging and neurodegeneration.

Heterogeneity of brain extracellular matrix and astrocyte activation

From the blood brain barrier to the synaptic space, astrocytes provide structural, metabolic, ionic, and extracellular matrix (ECM) support across the brain. Astrocytes include a vast array of subtypes, their phenotypes and functions varying both regionally and temporally. Astrocytes' metabolic and regulatory functions poise them to be quick and sensitive responders to injury and disease in the brain as revealed by single cell sequencing. Far less is known about the influence of the local healthy and aging microenvironments on these astrocyte activation states. In this forward-looking review, we describe the known relationship between astrocytes and their local microenvironment, the remodeling of the microenvironment during disease and injury, and postulate how they may drive astrocyte activation. We suggest technology development to better understand the dynamic diversity of astrocyte activation states, and how basal and activation states depend on the ECM microenvironment. A deeper understanding of astrocyte response to stimuli in ECM-specific contexts (brain region, age, and sex of individual), paves the way to revolutionize how the field considers astrocyte-ECM interactions in brain injury and disease and opens routes to return astrocytes to a healthy quiescent state.

Evaluating the Effects of Pulsed Electrical Stimulation on the Mechanical Behavior and Microstructure of Medulla Oblongata Tissues

The development of remote surgery hinges on comprehending the mechanical properties of the tissue at the surgical site. Understanding the mechanical behavior of the medulla oblongata tissue is instrumental for precisely determining the remote surgery implementation site. Additionally, exploring this tissue's response under electric fields can inform the creation of electrical stimulation therapy regimens. This could potentially reduce the extent of medulla oblongata tissue damage from mechanical compression. Various types of pulsed electric fields were integrated into a custom-built indentation device for this study. Experimental findings suggested that applying pulsed electric fields amplified the shear modulus of the medulla oblongata tissue. In the electric field, the elasticity and viscosity of the tissue increased. The most significant influence was noted from the low-frequency pulsed electric field, while the burst pulsed electric field had a minimal impact. At the microstructural scale, the application of an electric field led to the concentration of myelin in areas distant from the surface layer in the medulla oblongata, and the orderly structure of proteoglycans became disordered. The alterations observed in the myelin and proteoglycans under an electric field were considered to be the fundamental causes of the changes in the mechanical behavior of the medulla oblongata tissue. Moreover, cell polarization and extracellular matrix cavitation were observed, with transmission electron microscopy results pointing to laminar separation within the myelin at the ultrastructure scale. This study thoroughly explored the impact of electric field application on the mechanical behavior and microstructure of the medulla oblongata tissue, delving into the underlying mechanisms. This investigation delved into the changes and mechanisms in the mechanical behavior and microstructure of medulla oblongata tissue under the influence of electric fields. Furthermore, this study could serve as a reference for the development of electrical stimulation regimens in the central nervous system. The acquired mechanical behavior data could provide valuable baseline information to aid in the evolution of remote surgery techniques involving the medulla oblongata tissue.

Viscoelastic response of gray matter and white matter brain tissues under creep and relaxation

Accurate measurement of the mechanical properties of brain tissue is of paramount importance for understanding its mechanics-biology relationship. Most published studies on brain viscoelasticity have been conducted using a single relaxation test, without validating the validity of linear viscoelasticity, which is insufficient to establish an accurate constitutive equation for brain tissue. We obtained the creep and relaxation profiles of fresh adult porcine white matter (N = 120) and gray matter (N = 56) under finite step-and-hold uniaxial compression, using a mechanical testing machine, with 16.67 mm/s loading rate and 80 s hold time. These curves were employed to determine viscoelastic properties and demonstrated an excellent fit with a concise power-law function. The average initial modulus for gray matter (GM) was 6.619 kPa, higher than that for white matter under transverse loading (WM-2D) at 5.579 kPa (p < 0.01), yet lower than that for white matter under axial loading (WM-1D) at 6.759 kPa (p = 0.0121). Notably, WM-2D exhibited the highest degree of fluidity (β = 0.216). Our findings reveal that gray matter behaves as a linear viscoelastic material with power-law creep compliance and relaxation modulus. Conversely, the creep and relaxation behavior of white matter deviates from the verification relationship derived from linear viscoelastic theory, indicating its nonlinearity. This fact underscores the inaccuracy of assuming a linear constitutive relationship to characterize the viscoelastic properties of white matter. By combining the power-law function with the experimentally obtained creep compliance and relaxation modulus, we offer a unique approach to determining the viscoelastic characteristics of brain tissue.

Histology-informed multiscale modeling of human brain white matter

In this study, we propose a novel micromechanical model for the brain white matter, which is described as a heterogeneous material with a complex network of axon fibers embedded in a soft ground matrix. We developed this model in the framework of RVE-based multiscale theories in combination with the finite element method and the embedded element technique for embedding the fibers. Microstructural features such as axon diameter, orientation and tortuosity are incorporated into the model through distributions derived from histological data. The constitutive law of both the fibers and the matrix is described by isotropic one-term Ogden functions. The hyperelastic response of the tissue is derived by homogenizing the microscopic stress fields with multiscale boundary conditions to ensure kinematic compatibility. The macroscale homogenized stress is employed in an inverse parameter identification procedure to determine the hyperelastic constants of axons and ground matrix, based on experiments on human corpus callosum. Our results demonstrate the fundamental effect of axon tortuosity on the mechanical behavior of the brain's white matter. By combining histological information with the multiscale theory, the proposed framework can substantially contribute to the understanding of mechanotransduction phenomena, shed light on the biomechanics of a healthy brain, and potentially provide insights into neurodegenerative processes.

An in vitro study of micromechanics, cellular proliferation and viability on both decellularized porcine dura grafts and native porcine dura grafts

Damage to the dura mater may occur during intracranial or spinal surgeries, which can result in cerebrospinal fluid leakage and other potentially fatal physiological changes. As a result, biological and synthetic derived scaffolds are typically used to repair dura mater post intracranial or spinal surgeries. The extracellular matrix of xenogeneic dura scaffolds has been shown to exhibit increased cell infiltration and regeneration than synthetic dura materials. In this study, we investigated the biocompatibility of native and decellularized porcine dura by seeding rat fibroblast cells onto the constructs. Cell proliferation, cell viability, and the mechanical properties of these dural grafts were evaluated post-re-seeding on days 3,7 and 14. Live-dead staining and resazurin salts were used to quantify cell viability and cell proliferation, respectively. Micro indentation was conducted to quantify the mechanical integrity of the native and acellular dura graft. The findings indicate that the acellular porcine dura graft creates a beneficial setting for infiltrating rat fibroblast cells. Cell viability, proliferation, and micro indentation results on the acellular grafts are comparable with the native control porcine dura tissue. In conclusion, the porcine scaffold material showed increased cell viability at each time point evaluated. The sustained mechanical response and favorable viability of the cells on the decellularized grafts provide promising insight into the potential use of porcine dura in clinical cranial dura mater graft applications.

Brain Stiffness Follows Cuprizone-Induced Variations in Local Myelin Content

Brain maturation and neurological diseases are intricately linked to microstructural changes that inherently affect the brain's mechanical behavior. Animal models are frequently used to explore relative brain stiffness changes as a function of underlying microstructure. Here, we are using the cuprizone mouse model to study indentation-derived stiffness changes resulting from acute and chronic demyelination during a 15-week observation period. We focus on the corpus callosum, cingulum, and cortex which undergo different degrees of de- and remyelination and, therefore, result in region-specific stiffness changes. Mean stiffness of the corpus callosum starts at 1.1 ± 0.3 kPa in untreated mice, then cuprizone treatment causes stiffness to drop to 0.6 ± 0.1 kPa by week 3, temporarily increase to 0.9 ± 0.3 kPa by week 6, and ultimately stabilize around 0.7 ± 0.1 kPa by week 9 for the rest of the observation period. The cingulum starts at 3.2 ± 0.9 kPa, then drops to 1.6 ± 0.4 kPa by week 3, and then gradually stabilizes around 1.4 ± 0.3 kPa by week 9. Cortical stiffness exhibits less stiffness variations overall; it starts at 4.2 ± 1.3 kPa, drops to 2.4 ± 0.6 kPa by week 3, and stabilizes around 2.7 ± 0.9 kPa by week 6. We also assess the impact of tissue fixation on indentation-based mechanical tissue characterization. On the one hand, fixation drastically increases untreated mean tissue stiffness by a factor of 3.3 for the corpus callosum, 2.9 for the cingulum, and 3.6 for the cortex; on the other hand, fixation influences interregional stiffness ratios during demyelination, thus suggesting that fixation affects individual brain tissues differently. Lastly, we determine the spatial correlation between stiffness measurements and myelin density and observe a region-specific proportionality between myelin content and tissue stiffness. STATEMENT OF SIGNIFICANCE: Despite extensive work, the relationship between microstructure and mechanical behavior in the brain remains mostly unknown. Additionally, the existing variation of measurement results reported in literature requires in depth investigation of the impact of individual cell and protein populations on tissue stiffness and interregional stiffness ratios. Here, we used microindentation measurements to show that brain stiffness changes with myelin density in the cuprizone-based demyelination mouse model. Moreover, we explored the impact of tissue fixation prior to mechanical characterization because of conflicting results reported in literature. We observe that fixation has a distinctly different impact on our three regions of interest, thus causing region-specific tissue stiffening and, more importantly, changing interregional stiffness ratios.

Brain tissue mechanics is governed by microscale relations of the tissue constituents

Local mechanical tissue properties are a critical regulator of cell function in the central nervous system (CNS) during development and disorder. However, we still don't fully understand how the mechanical properties of individual tissue constituents, such as cell nuclei or myelin, determine tissue mechanics. Here we developed a model predicting local tissue mechanics, which induces non-affine deformations of the tissue components. Using the mouse hippocampus and cerebellum as model systems, we show that considering individual tissue components alone, as identified by immunohistochemistry, is not sufficient to reproduce the local mechanical properties of CNS tissue. Our results suggest that brain tissue shows a universal response to applied forces that depends not only on the amount and stiffness of the individual tissue constituents but also on the way how they assemble. Our model may unify current incongruences between the mechanics of soft biological tissues and the underlying constituents and facilitate the design of better biomedical materials and engineered tissues. To this end, we provide a freely-available platform to predict local tissue elasticity upon providing immunohistochemistry images and stiffness values for the constituents of the tissue.

AI-dente: an open machine learning based tool to interpret nano-indentation data of soft tissues and materials

Nano-indentation is a promising method to identify the constitutive parameters of soft materials, including soft tissues. Especially when materials are very small and heterogeneous, nano-indentation allows mechanical interrogation where traditional methods may fail. However, because nano-indentation does not yield a homogeneous deformation field, interpreting the resulting load-displacement curves is non-trivial and most investigators resort to simplified approaches based on the Hertzian solution. Unfortunately, for small samples and large indentation depths, these solutions are inaccurate. We set out to use machine learning to provide an alternative strategy. We first used the finite element method to create a large synthetic data set. We then used these data to train neural networks to inversely identify material parameters from load-displacement curves. To this end, we took two different approaches. First, we learned the indentation forward problem, which we then applied within an iterative framework to identify material parameters. Second, we learned the inverse problem of directly identifying material parameters. We show that both approaches are effective at identifying the parameters of the neo-Hookean and Gent models. Specifically, when applied to synthetic data, our approaches are accurate even for small sample sizes and at deep indentation. Additionally, our approaches are fast, especially compared to the inverse finite element approach. Finally, our approaches worked on unseen experimental data from thin mouse brain samples. Here, our approaches proved robust to experimental noise across over 1000 samples. By providing open access to our data and code, we hope to support others that conduct nano-indentation on soft materials.

Neuronal actin cytoskeleton gain of function in the human brain

BACKGROUND

While advancements in imaging techniques have led to major strides in deciphering the human brain, successful interventions are elusive and represent some of the most persistent translational gaps in medicine. Human restricted CHRFAM7A has been associated with neuropsychiatric disorders.

METHODS

The physiological role of CHRFAM7A in human brain is explored using multiomics approach on 600 post mortem human brain tissue samples. The emerging pathways and mechanistic hypotheses are tested and validated in an isogenic hiPSC model of CHRFAM7A knock-in medial ganglionic eminence progenitors and neurons.

FINDINGS

CHRFAM7A is identified as a modulator of intracellular calcium dynamics and an upstream regulator of Rac1. Rac1 activation re-designs the actin cytoskeleton leading to dynamic actin driven remodeling of membrane protrusion and a switch from filopodia to lamellipodia. The reinforced cytoskeleton leads to an advantage to tolerate stiffer mechanical properties of the extracellular environment.

INTERPRETATION

CHRFAM7A modifies the actin cytoskeleton to a more dynamic and stiffness resistant state in an α7nAChR dependent manner. CHRFAM7A may facilitate neuronal adaptation to changes in the brain environment in physiological and pathological conditions contributing to risk or recovery. Understanding how CHRFAM7A affects human brain requires human studies in the areas of memory formation and erasure, cognitive reserve, and neuronal plasticity.

FUNDING

This work is supported in part by the Community Foundation for Greater Buffalo (Kinga Szigeti). Also, in part by the International Society for Neurochemistry (ISN) and The Company of Biologists (Nicolas Rosas). ROSMAP is supported by NIA grants P30AG10161, P30AG72975, R01AG15819, R01AG17917. U01AG46152, and U01AG61356.

Rate- and Region-Dependent Mechanical Properties of Göttingen Minipig Brain Tissue in Simple Shear and Unconfined Compression

Traumatic brain injury (TBI), particularly from explosive blasts, is a major cause of casualties in modern military conflicts. Computational models are an important tool in understanding the underlying biomechanics of TBI but are highly dependent on the mechanical properties of soft tissue to produce accurate results. Reported material properties of brain tissue can vary by several orders of magnitude between studies, and no published set of material parameters exists for porcine brain tissue at strain rates relevant to blast. In this work, brain tissue from the brainstem, cerebellum, and cerebrum of freshly euthanized adolescent male Göttingen minipigs was tested in simple shear and unconfined compression at strain rates ranging from quasi-static (QS) to 300 s-1. Brain tissue showed significant strain rate stiffening in both shear and compression. Minimal differences were seen between different regions of the brain. Both hyperelastic and hyper-viscoelastic constitutive models were fit to experimental stress, considering data from either a single loading mode (unidirectional) or two loading modes together (bidirectional). The unidirectional hyper-viscoelastic models with an Ogden hyperelastic representation and a one-term Prony series best captured the response of brain tissue in all regions and rates. The bidirectional models were generally able to capture the response of the tissue in high-rate shear and all compression modes, but not the QS shear. Our constitutive models describe the first set of material parameters for porcine brain tissue relevant to loading modes and rates seen in blast injury.

Bridging the Gap in Ashby's Map for Soft Material Properties for Tissue Engineering

Ashby's map's role in rationally selecting materials for optimal performance is well-established in traditional engineering applications. However, there is a major gap in Ashby's maps in selecting materials for tissue engineering, which are very soft with an elastic modulus of less than 100 kPa. To fill the gap, we create an elastic modulus database to effectively connect soft engineering materials with biological tissues such as the cardiac, kidney, liver, intestine, cartilage, and brain. This soft engineering material mechanical property database is created for widely applied agarose hydrogels based on big-data screening and experiments conducted using ultra-low-concentration (0.01-0.5 wt %) hydrogels. Based on that, an experimental and analysis protocol is established for evaluating the elastic modulus of ultra-soft engineering materials. Overall, we built a mechanical bridge connecting soft matter and tissue engineering by fine-tuning the agarose hydrogel concentration. Meanwhile, a soft matter scale (degree of softness) is established to enable the manufacturing of implantable bio-scaffolds for tissue engineering.

Multi-contrast digital histopathology of mouse organs using quantitative phase imaging and virtual staining

Quantitative phase imaging (QPI) has emerged as a new digital histopathologic tool as it provides structural information of conventional slide without staining process. It is also capable of imaging biological tissue sections with sub-nanometer sensitivity and classifying them using light scattering properties. Here we extend its capability further by using optical scattering properties as imaging contrast in a wide-field QPI. In our first step towards validation, QPI images of 10 major organs of a wild-type mouse have been obtained followed by H&E-stained images of the corresponding tissue sections. Furthermore, we utilized deep learning model based on generative adversarial network (GAN) architecture for virtual staining of phase delay images to a H&E-equivalent brightfield (BF) image analogues. Using the structural similarity index, we demonstrate similarities between virtually stained and H&E histology images. Whereas the scattering-based maps look rather similar to QPI phase maps in the kidney, the brain images show significant improvement over QPI with clear demarcation of features across all regions. Since our technology provides not only structural information but also unique optical property maps, it could potentially become a fast and contrast-enriched histopathology technique.

Exploring the multiphysics of the brain during development, aging, and in neurological diseases

The human brain remains an endless source of wonder and represents an intruiging scientific frontier. Multiphysics approaches naturally lend themselves to combine our extensive knowledge about the neurobiology of aging and diseases with mechanics to better capture the multiscale behavior of the brain. Our group uses experimental methods, medical image analysis, and constitutive modeling to develop better disease models with the long-term goal to improve diagnosis, treatment, and ultimately enable prevention of many prevalent age- and disease-related brain changes. In the present perspective, we outline on-going work related to neurodevelopment, aging, and neurodegenerative disease.

Toward assessing the role of dietary fatty acids in lamb's neurological and cognitive development

Understanding and measuring sheep cognition and behavior can provide us with measures to safeguard the welfare of these animals in production systems. Optimal neurological and cognitive development of lambs is important to equip individuals with the ability to better cope with environmental stressors. However, this development can be affected by nutrition with a special role from long-chain fatty acid supply from the dam to the fetus or in lamb's early life. Neurological development in lambs takes place primarily during the first two trimesters of gestation. Through late fetal and early postnatal life, the lamb brain has a high level of cholesterol synthesis. This rate declines rapidly at weaning and remains low throughout adulthood. The main polyunsaturated fatty acids (PUFA) in the brain are ω-6 arachidonic acid and ω-3 docosahexaenoic acid (DHA), which are elements of plasma membranes' phospholipids in neuronal cells. DHA is essential for keeping membrane integrity and is vital for normal development of the central nervous system (CNS), and its insufficiency can damage cerebral functions and the development of cognitive capacities. In sheep, there is evidence that supplying PUFA during gestation or after birth may be beneficial to lamb productive performance and expression of species-specific behaviors. The objective of this perspective is to discuss concepts of ruminant behavior and nutrition and reflect on future research directions that could help to improve our knowledge on how dietary fatty acids (FA) relate to optimal neurological and cognitive development in sheep.

The epigenetic landscape of oligodendrocyte lineage cells

The epigenetic landscape of oligodendrocyte lineage cells refers to the cell-specific modifications of DNA, chromatin, and RNA that define a unique gene expression pattern of functionally specialized cells. Here, we focus on the epigenetic changes occurring as progenitors differentiate into myelin-forming cells and respond to the local environment. First, modifications of DNA, RNA, nucleosomal histones, key principles of chromatin organization, topologically associating domains, and local remodeling will be reviewed. Then, the relationship between epigenetic modulators and RNA processing will be explored. Finally, the reciprocal relationship between the epigenome as a determinant of the mechanical properties of cell nuclei and the target of mechanotransduction will be discussed. The overall goal is to provide an interpretative key on how epigenetic changes may account for the heterogeneity of the transcriptional profiles identified in this lineage.

Bidirectional hyperelastic characterization of brain white matter tissue

Biomechanical study of brain injuries originated from mechanical damages to white matter tissue requires detailed information on mechanical characteristics of its main components, the axonal fibers and extracellular matrix, which is very limited due to practical difficulties of direct measurement. In this paper, a new theoretical framework was established based on microstructural modeling of brain white matter tissue as a soft composite for bidirectional hyperelastic characterization of its main components. First the tissue was modeled as an Ogden hyperelastic material, and its principal Cauchy stresses were formulated in the axonal and transverse directions under uniaxial and equibiaxial tension using the theory of homogenization. Upon fitting these formulae to the corresponding experimental test data, direction-dependent hyperelastic constants of the tissue were obtained. These directional properties then were used to estimate the strain energy stored in the homogenized model under each loading scenario. A new microstructural composite model of the tissue was also established using principles of composites micromechanics, in which the axonal fibers and surrounding matrix are modeled as different Ogden hyperelastic materials with unknown constants. Upon balancing the strain energies stored in the homogenized and composite models under different loading scenarios, fully coupled nonlinear equations as functions of unknown hyperelastic constants were derived, and their optimum solutions were found in a multi-parametric multi-objective optimization procedure using the response surface methodology. Finally, these solutions were implemented, in a bottom-up approach, into a micromechanical finite element model to reproduce the tissue responses under the same loadings and predict the tissue responses under unseen non-equibiaxial loadings. Results demonstrated a very good agreement between the model predictions and experimental results in both directions under different loadings. Moreover, the axonal fibers with hyperelastic characteristics stiffer than the extracellular matrix were shown to play the dominant role in directional reinforcement of the tissue.

Effects of Different Types of Electric Fields on Mechanical Properties and Microstructure of Ex Vivo Porcine Brain Tissues

Electrotherapy plays a crucial role in regulating neuronal activity. Nevertheless, the relevant therapeutic mechanisms are still unclear; thus, the effects of electric fields on brain tissue's mechanical properties and microstructure need to be explored. In this study, focusing on the changes in mechanical properties and microstructure of ex vivo porcine brain tissues under different types of electric fields, directional and alternating electric fields (frequencies of 5, 20, 50, and 80 Hz, respectively) integrate with a custom-designed indentation device. The experimental results showed that for the ex vivo brain tissue, the directional electric field (DEF) can reduce the elastic properties of brain tissue. Simultaneously, the DEF can increase the cell spacing and reduce the proteoglycan content. The transmission electron microscope (TEM) analysis observed that the DEF can reduce the integrity of the plasma membrane, the endoplasmic reticulum's stress response, and the myelin lamella's separation. The alternating electric field (AEF) can accelerate the stress relaxation process of brain tissue and change the time-dependent mechanical properties of brain tissue. Meanwhile, with the increase in frequency, the cell spacing decreased, and the proteoglycan content gradually approached the control group without electric fields. TEM analysis observed that with the increase in frequency, the integrity of the plasma membrane increases, and the separation of the myelin lamella gradually disappears. Understanding the changes in the mechanical properties and microstructure of brain tissue under AEF and DEF enables a preliminary exploration of the therapeutic mechanism of electrotherapy. Simultaneously, the essential data was provided to support the development of embedded electrodes. In addition, the ex vivo experiments build a solid foundation for future in vivo experiments.

Tissue-Scale Biomechanical Testing of Brain Tissue for the Calibration of Nonlinear Material Models

Brain tissue is one of the most complex and softest tissues in the human body. Due to its ultrasoft and biphasic nature, it is difficult to control the deformation state during biomechanical testing and to quantify the highly nonlinear, time-dependent tissue response. In numerous experimental studies that have investigated the mechanical properties of brain tissue over the last decades, stiffness values have varied significantly. One reason for the observed discrepancies is the lack of standardized testing protocols and corresponding data analyses. The tissue properties have been tested on different length and time scales depending on the testing technique, and the corresponding data have been analyzed based on simplifying assumptions. In this review, we highlight the advantage of using nonlinear continuum mechanics based modeling and finite element simulations to carefully design experimental setups and protocols as well as to comprehensively analyze the corresponding experimental data. We review testing techniques and protocols that have been used to calibrate material model parameters and discuss artifacts that might falsify the measured properties. The aim of this work is to provide standardized procedures to reliably quantify the mechanical properties of brain tissue and to more accurately calibrate appropriate constitutive models for computational simulations of brain development, injury and disease. Computational models can not only be used to predictively understand brain tissue behavior, but can also serve as valuable tools to assist diagnosis and treatment of diseases or to plan neurosurgical procedures. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.

Alcohol-Induced Alterations in the Vascular Basement Membrane in the Substantia Nigra of the Adult Human Brain

The blood–brain barrier (BBB) represents a highly specialized interface that acts as the first line of defense against toxins. Herein, we investigated the structural and ultrastructural changes in the basement membrane (BM), which is responsible for maintaining the integrity of the BBB, in the context of chronic alcoholism. Human post-mortem tissues from the Substantia Nigra (SN) region were obtained from 44 individuals, then grouped into controls, age-matched alcoholics, and non-age-matched alcoholics and assessed using light and electron microscopy. We found significantly less CD31+ vessels in alcoholic groups compared to controls in both gray and white matter samples. Alcoholics showed increased expression levels of collagen-IV, laminin-111, and fibronectin, which were coupled with a loss of BM integrity in comparison with controls. The BM of the gray matter was found to be more disintegrated than the white matter in alcoholics, as demonstrated by the expression of both collagen-IV and laminin-111, thereby indicating a breakdown in the BM’s structural composition. Furthermore, we observed that the expression of fibronectin was upregulated in the BM of the white matter vasculature in both alcoholic groups compared to controls. Taken together, our findings highlight some sort of aggregation or clumping of BM proteins that occurs in response to chronic alcohol consumption.

Trifluoperazine reduces cuprizone-induced demyelination via targeting Nrf2 and IKB in mice

Multiple sclerosis (MS) is one of the most common neurodegenerative diseases. In this disease, the immune system attacks oligodendrocyte cells and the myelin sheath of myelinated neurons in the central nervous system, causing their destruction. These conditions lead to impaired conduction of nerve impulses and are manifested by symptoms such as weakness, fatigue, visual and motor disorders. This study aimed to evaluate the ability of trifluoperazine (TF) to improve cuprizone-induced behavioral and histopathological changes in the prefrontal cortex of C57BL/6 male mice. Demyelination was induced by adding 0.2% cuprizone (CPZ) to the standard animal diet for 6 weeks. Three doses of TF (0.5, 1 and 2 mg/kg/day; i.p.) were given once daily for the last 2 weeks of treatment. Treatment with CPZ induced a weight loss during 6 weeks of treatment compared to the control group, which was reversed by the administration of TF. Behavioral tests (pole test and rotarod performance test) showed a decrease in motor coordination and balance in the group treated with CPZ (P < 0.01). Treatment with TF during the last two weeks was able to improve these motor deficiencies. Histopathological examination also evidenced an increase in demyelination in the CPZ group, which was improved by TF administration. In addition, CPZ intake significantly decreased the cerebral cortex levels of p-Nrf2 (P < 0.001) and increased the levels of p-IKB (P < 0.001) and, these changes were normalized in the TF groups. TF administration also reversed the increased levels of nitrite and the reduced activity of the antioxidant enzyme superoxide dismutase associated with CPZ exposure. TF can to reduce the harmful effects of CPZ by reducing the demyelination and modulating the Nrf2 and NF-kB signaling pathways.

Unraveling the Local Relation Between Tissue Composition and Human Brain Mechanics Through Machine Learning

The regional mechanical properties of brain tissue are not only key in the context of brain injury and its vulnerability towards mechanical loads, but also affect the behavior and functionality of brain cells. Due to the extremely soft nature of brain tissue, its mechanical characterization is challenging. The response to loading depends on length and time scales and is characterized by nonlinearity, compression-tension asymmetry, conditioning, and stress relaxation. In addition, the regional heterogeneity-both in mechanics and microstructure-complicates the comprehensive understanding of local tissue properties and its relation to the underlying microstructure. Here, we combine large-strain biomechanical tests with enzyme-linked immunosorbent assays (ELISA) and develop an extended type of constitutive artificial neural networks (CANNs) that can account for viscoelastic effects. We show that our viscoelastic constitutive artificial neural network is able to describe the tissue response in different brain regions and quantify the relevance of different cellular and extracellular components for time-independent (nonlinearity, compression-tension-asymmetry) and time-dependent (hysteresis, conditioning, stress relaxation) tissue mechanics, respectively. Our results suggest that the content of the extracellular matrix protein fibronectin is highly relevant for both the quasi-elastic behavior and viscoelastic effects of brain tissue. While the quasi-elastic response seems to be largely controlled by extracellular matrix proteins from the basement membrane, cellular components have a higher relevance for the viscoelastic response. Our findings advance our understanding of microstructure - mechanics relations in human brain tissue and are valuable to further advance predictive material models for finite element simulations or to design biomaterials for tissue engineering and 3D printing applications.

Mechanotransduction assays for neural regeneration strategies: A focus on glial cells

Glial cells are mechanosensitive, and thus, engineered systems have taken a step forward to design mechanotransduction platforms in order to impart diverse mechanical stresses to cells. Mechanical strain encountered in the central nervous system can arise from diverse mechanisms, such as tissue reorganization, fluid flow, and axon growth, as well as pathological events including axon swelling or mechanical trauma. Biomechanical relevance of the in vitro mechanical testing requires to be placed in line with the physiological and mechanical changes in central nervous tissues that occur during the progression of neurodegenerative diseases. Mechanotransduction signaling utilized by glial cells and the recent approaches intended to model altered microenvironment adapted to pathological context are discussed in this review. New insights in systems merging substrate's stiffness and topography should be considered for further glial mechanotransduction studies, while testing platforms for drug discoveries promise great advancements in pharmacotherapy. Potential leads and strategies for clinical outcomes are expected to be developed following the exploration of these glial mechanosensitive signaling pathways.

Aging brain mechanics: Progress and promise of magnetic resonance elastography

Neuroimaging techniques that can sensitivity characterize healthy brain aging and detect subtle neuropathologies have enormous potential to assist in the early detection of neurodegenerative conditions such as Alzheimer's disease. Magnetic resonance elastography (MRE) has recently emerged as a reliable, high-resolution, and especially sensitive technique that can noninvasively characterize tissue biomechanical properties (i.e., viscoelasticity) in vivo in the living human brain. Brain tissue viscoelasticity provides a unique biophysical signature of neuroanatomy that are representative of the composition and organization of the complex tissue microstructure. In this article, we detail how progress in brain MRE technology has provided unique insights into healthy brain aging, neurodegeneration, and structure-function relationships. We further discuss additional promising technical innovations that will enhance the specificity and sensitivity for brain MRE to reveal considerably more about brain aging as well as its potentially valuable role as an imaging biomarker of neurodegeneration. MRE sensitivity may be particularly useful for assessing the efficacy of rehabilitation strategies, assisting in differentiating between dementia subtypes, and in understanding the causal mechanisms of disease which may lead to eventual pharmacotherapeutic development.

Mechanisms of Local Stress Amplification in Axons near the Gray-White Matter Interface

Diffuse axonal injury is a primary neuropathological feature of concussion and is thought to greatly contribute to the classical symptoms of decreased processing speed and memory dysfunction. Although previous studies have investigated the injury biomechanics at the micro- and mesoscale of concussion, few have addressed the multiscale transmission of mechanical loading at thresholds that can induce diffuse axonal injury. Because it has been recognized that axonal pathology is commonly found at anatomic interfaces across all severities of traumatic brain injury, we combined computational, analytical, and experimental approaches to investigate the potential mechanical vulnerability of axons that span the gray-white tissue interface. Our computational models predict that material heterogeneities at the gray-white interface lead to a highly nonuniform distribution of stress in axons, which was most amplified in axonal regions near the interface. This mechanism was confirmed using an analytical model of an individual fiber in a strained bimaterial interface. Comparisons of these collective data with histopathological evaluation of a swine model of concussion demonstrated a notably similar pattern of axonal damage adjacent to the gray-white interface. The results suggest that the tissue property mismatch at the gray-white matter interface places axons crossing this region at greater risk of mechanical damage during brain tissue deformation from traumatic brain injury.

So-Called Lamina Cribrosa Defects May Mitigate IOP-Induced Neural Tissue Insult

Purpose

The prevailing theory about the function of lamina cribrosa (LC) connective tissues is that they provide structural support to adjacent neural tissues. Missing connective tissues would compromise this support and therefore are regarded as “LC defects”, despite scarce actual evidence of their role. We examined how so-called LC defects alter IOP-related mechanical insult to the LC neural tissues.

Methods

We built numerical models incorporating LC microstructure from polarized light microscopy images. To simulate LC defects of varying sizes, individual beams were progressively removed. We then compared intraocular pressure (IOP)-induced neural tissue deformations between models with and without defects. To better understand the consequences of defect development, we also compared neural tissue deformations between models with partial and complete loss of a beam.

Results

The maximum stretch of neural tissues decreased non-monotonically with defect size. Maximum stretch in the model with the largest defect decreased by 40% in comparison to the model with no defects. Partial loss of a beam increased the maximum stretch of neural tissues in its adjacent pores by 162%, compared with 63% in the model with complete loss of a beam.

Conclusions

Missing LC connective tissues can mitigate IOP-induced neural tissue insult, suggesting that the role of the LC connective tissues is more complex than simply fortifying against IOP. The numerical models further predict that partial loss of a beam is biomechanically considerably worse than complete loss of a beam, perhaps explaining why defects have been reported clinically but partial beams have not.

Physical aspects of cortical folding

The characteristically folded surface of the human brain is critical for brain function and allows for higher cognitive abilities. Recent mostly computational research advances have shown that mechanical instabilities play a crucial role during early brain development and cortical folding. However, it is difficult to investigate such mechanisms in vivo. To experimentally gain deeper insights into the physical mechanisms that underlie the development of brain shape, we use a setup of swelling polymers. We investigate the influence of cortical thickness and the stiffness ratio between cortex and subcortex on the resulting surface pattern by taking the initially smooth fetal brain geometry at week 22 into consideration. The gel specimens possess a two-layered structure accounting for gray and white matter tissue and yield complex surface morphologies that well resemble patterns in the human brain. The results are in good agreement with analytical predictions. Through the variation of cortical thickness and stiffness, it is possible to reproduce cortical malformations such as polymicrogyria and lissencephaly. The results suggest that wrinkling with subsequent transition into folding is the driving instability mechanism during brain development. In addition, the experiments provide valuable insights towards the distinction between wrinkling and creasing instabilities. Taken together, the presented swelling experiments impressively demonstrate the purely physical aspects of brain shape and constitute a valuable tool to advance our understanding of human brain development.

Superviscous properties of the in vivo brain at large scales

There is growing awareness that brain mechanical properties are important for neural development and health. However, published values of brain stiffness differ by orders of magnitude between static measurements and in vivo magnetic resonance elastography (MRE), which covers a dynamic range over several frequency decades. We here show that there is no fundamental disparity between static mechanical tests and in vivo MRE when considering large-scale properties, which encompass the entire brain including fluid filled compartments. Using gradient echo real-time MRE, we investigated the viscoelastic dispersion of the human brain in, so far, unexplored dynamic ranges from intrinsic brain pulsations at 1 Hz to ultralow-frequency vibrations at 5, 6.25, 7.8 and 10 Hz to the normal frequency range of MRE of 40 Hz. Surprisingly, we observed variations in brain stiffness over more than two orders of magnitude, suggesting that the in vivo human brain is superviscous on large scales with very low shear modulus of 42±13 Pa and relatively high viscosity of 6.6±0.3 Pa∙s according to the two-parameter solid model. Our data shed light on the crucial role of fluid compartments including blood vessels and cerebrospinal fluid (CSF) for whole brain properties and provide, for the first time, an explanation for the variability of the mechanical brain responses to manual palpation, local indentation, and high-dynamic tissue stimulation as used in elastography.

Folding drives cortical thickness variations

The cortical thickness is a characteristic biomarker for a wide variety of neurological disorders. While the structural organization of the cerebral cortex is tightly regulated and evolutionarily preserved, its thickness varies widely between 1.5 and 4.5 mm across the healthy adult human brain. It remains unclear whether these thickness variations are a cause or consequence of cortical development. Recent studies suggest that cortical thickness variations are primarily a result of genetic effects. Previous studies showed that a simple homogeneous bilayered system with a growing layer on an elastic substrate undergoes a unique symmetry breaking into a spatially heterogeneous system with discrete gyri and sulci. Here, we expand on that work to explore the evolution of cortical thickness variations over time to support our finding that cortical pattern formation and thickness variations can be explained - at least in part - by the physical forces that emerge during cortical folding. Strikingly, as growth progresses, the developing gyri universally thicken and the sulci thin, even in the complete absence of regional information. Using magnetic resonance images, we demonstrate that these naturally emerging thickness variations agree with the cortical folding pattern in n = 9 healthy adult human brains, in n = 564 healthy human brains ages 7-64, and in n = 73 infant brains scanned at birth, and at ages one and two. Additionally, we show that cortical organoids develop similar patterns throughout their growth. Our results suggest that genetic, geometric, and physical events during brain development are closely interrelated. Understanding regional and temporal variations in cortical thickness can provide insight into the evolution and causative factors of neurological disorders, inform the diagnosis of neurological conditions, and assess the efficacy of treatment options.

Viscoelastic mapping of mouse brain tissue: Relation to structure and age

There is growing evidence that mechanical factors affect brain functioning. However, brain components responsible for regulating the physiological mechanical environment are not completely understood. To determine the relationship between structure and stiffness of brain tissue, we performed high-resolution viscoelastic mapping by dynamic indentation of the hippocampus and the cerebellum of juvenile mice brains, and quantified relative area covered by neurons (NeuN-staining), axons (neurofilament NN18-staining), astrocytes (GFAP-staining), myelin (MBP-staining) and nuclei (Hoechst-staining) of juvenile and adult mouse brain slices. Results show that brain subregions have distinct viscoelastic parameters. In gray matter (GM) regions, the storage modulus correlates negatively with the relative area of nuclei and neurons, and positively with astrocytes. The storage modulus also correlates negatively with the relative area of myelin and axons (high cell density regions are excluded). Furthermore, adult brain regions are ∼ 20%-150% stiffer than the comparable juvenile regions which coincide with increase in astrocyte GFAP-staining. Several linear regression models are examined to predict the mechanical properties of the brain tissue based on (immuno)histochemical stainings.

Standard-space atlas of the viscoelastic properties of the human brain

Standard anatomical atlases are common in neuroimaging because they facilitate data analyses and comparisons across subjects and studies. The purpose of this study was to develop a standardized human brain atlas based on the physical mechanical properties (i.e., tissue viscoelasticity) of brain tissue using magnetic resonance elastography (MRE). MRE is a phase contrast‐based MRI method that quantifies tissue viscoelasticity noninvasively and in vivo thus providing a macroscopic representation of the microstructural constituents of soft biological tissue. The development of standardized brain MRE atlases are therefore beneficial for comparing neural tissue integrity across populations. Data from a large number of healthy, young adults from multiple studies collected using common MRE acquisition and analysis protocols were assembled (N = 134; 78F/ 56 M; 18–35 years). Nonlinear image registration methods were applied to normalize viscoelastic property maps (shear stiffness, μ, and damping ratio, ξ) to the MNI152 standard structural template within the spatial coordinates of the ICBM‐152. We find that average MRE brain templates contain emerging and symmetrized anatomical detail. Leveraging the substantial amount of data assembled, we illustrate that subcortical gray matter structures, white matter tracts, and regions of the cerebral cortex exhibit differing mechanical characteristics. Moreover, we report sex differences in viscoelasticity for specific neuroanatomical structures, which has implications for understanding patterns of individual differences in health and disease. These atlases provide reference values for clinical investigations as well as novel biophysical signatures of neuroanatomy. The templates are made openly available (github.com/mechneurolab/mre134) to foster collaboration across research institutions and to support robust cross‐center comparisons.

Dynamic indentation reveals differential viscoelastic properties of white matter versus gray matter-derived astrocytes upon treatment with lipopolysaccharide

Astrocytes in white matter (WM) and gray matter (GM) brain regions have been reported to have different morphology and function. Previous single cell biomechanical studies have not differentiated between WM- and GM-derived samples. In this study, we explored the local viscoelastic properties of isolated astrocytes and show that astrocytes from rat brain WM-enriched areas are ~1.8 times softer than astrocytes from GM-enriched areas. Upon treatment with pro-inflammatory lipopolysaccharide, GM-derived astrocytes become significantly softer in the nuclear and the cytoplasmic regions, where the F-actin network appears rearranged, whereas WM-derived astrocytes preserve their initial mechanical features and show no alteration in the F-actin cytoskeletal network. We hypothesize that the flexibility in biomechanical properties of GM-derived astrocytes may contribute to promote regeneration of the brain under neuroinflammatory conditions.

A knowledge map analysis of brain biomechanics: Current evidence and future directions

Although brain, one of the most complex organs in the mammalian body, has been subjected to many studies from physiological and pathological points of view, there remain significant gaps in the available knowledge regarding its biomechanics. This article reviews the research trends in brain biomechanics with a focus on injury. We used published scientific articles indexed by Web of Science database over the past 40 years and tried to address the gaps that still exist in this field. We analyzed the data using VOSviewer, which is a software tool designed for scientometric studies. The results of this study showed that the response of brain tissue to external forces has been one of the significant research topics among biomechanicians. These studies have addressed the effects of mechanical forces on the brain and mechanisms of traumatic brain injury, as well as characterized changes in tissue behavior under trauma and other neurological diseases to provide new diagnostic and monitoring methods. In this study, some challenges in the field of brain injury biomechanics have been identified and new directions toward understanding the gaps in this field are suggested.

Towards microstructure-informed material models for human brain tissue

Emerging evidence suggests that the mechanical behavior of the brain plays a critical role in development, disease, and aging. Recent studies have begun to characterize the mechanical behavior of gray and white matter tissue and to identify sets of material models that best reproduce the stress-strain behavior of different brain regions. Yet, these models are mainly phenomenological in nature, their parameters often lack clear physical interpretation, and they fail to correlate the mechanical behavior to the underlying microstructural composition. Here we make a first attempt towards identifying general relations between microstructure and mechanics with the ultimate goal to develop microstructurally motivated constitutive equations for human brain tissue. Using histological staining, we analyze the microstructure of brain specimens from different anatomical regions, the cortex, basal ganglia, corona radiata, and corpus callosum, and identify the regional stiffness and viscosity under multiple loading conditions, simple shear, compression, and tension. Strikingly, our study reveals a negative correlation between cell count and stiffness, a positive correlation between myelin content and stiffness, and a negative correlation between proteoglycan content and stiffness. Additionally, our analysis shows a positive correlation between lipid and proteoglycan content and viscosity. We demonstrate how understanding the microstructural origin of the macroscopic behavior of the brain can help us design microstructure-informed material models for human brain tissue that inherently capture regional heterogeneities. This study represents an important step towards using brain tissue stiffness and viscosity as early diagnostic markers for clinical conditions including chronic traumatic encephalopathy, Alzheimer's and Parkinson's disease, or multiple sclerosis. STATEMENT OF SIGNIFICANCE: The complex and heterogeneous mechanical properties of brain tissue play a critical role for brain function. To understand and predict how brain tissue properties vary in space and time, it will be key to link the mechanical behavior to the underlying microstructural composition. Here we use histological staining to quantify area fractions of microstructural components of mechanically tested specimens and evaluate their individual contributions to the nonlinear macroscopic mechanical response. We further propose a microstructure-informed material model for human brain tissue that inherently captures regional heterogeneities. The current work provides unprecedented insights into the biomechanics of human brain tissue, which are highly relevant to develop refined computational models for brain tissue behavior or to advance neural tissue engineering.

Mechanical property alterations across the cerebral cortex due to Alzheimer's disease

Alzheimer's disease is a personally devastating neurodegenerative disorder and a major public health concern. There is an urgent need for medical imaging techniques that better characterize the early stages and monitor the progression of the disease. Magnetic resonance elastography (MRE) is a relatively new and highly sensitive MRI technique that can non-invasively assess tissue microstructural integrity via measurement of brain viscoelastic mechanical properties. For the first time, we use high-resolution MRE methods to conduct a voxel-wise MRE investigation and state-of-the-art post hoc region of interest analysis of the viscoelastic properties of the cerebral cortex in patients with Alzheimer's disease (N = 11) compared with cognitively healthy older adults (N = 12). We replicated previous findings that have reported significant volume and stiffness reductions at the whole-brain level. Significant reductions in volume were also observed in Alzheimer's disease when white matter, cortical grey matter and subcortical grey matter compartments were considered separately; lower stiffness was also observed in white matter and cortical grey matter, but not in subcortical grey matter. Voxel-based morphometry of both cortical and subcortical grey matter revealed localized reductions in volume due to Alzheimer's disease in the hippocampus, fusiform, middle, superior temporal gyri and precuneus. Similarly, voxel-based MRE identified lower stiffness in the middle and superior temporal gyri and precuneus, although the spatial distribution of these effects was not identical to the pattern of volume reduction. Notably, MRE additionally identified stiffness deficits in the operculum and precentral gyrus located within the frontal lobe; regions that did not undergo volume loss identified through voxel-based morphometry. Voxel-based-morphometry and voxel-based MRE results were confirmed by a complementary post hoc region-of-interest approach in native space where the viscoelastic changes remained significant even after statistically controlling for regional volumes. The pattern of reduction in cortical stiffness observed in Alzheimer's disease patients raises the possibility that MRE may provide unique insights regarding the neural mechanisms which underlie the development and progression of the disease. The measured mechanical property changes that we have observed warrant further exploration to investigate the diagnostic usefulness of MRE in cases of Alzheimer's disease and other dementias.

Brain maturation is associated with increasing tissue stiffness and decreasing tissue fluidity

Biomechanical cues guide proliferation, growth and maturation of neurons. Yet the molecules that shape the brain's biomechanical properties are unidentified and the relationship between neural development and viscoelasticity of brain tissue remains elusive. Here we combined novel in-vivo tomoelastography and ex-vivo proteomics to investigate whether viscoelasticity of the mouse brain correlates with protein alterations within the critical phase of brain maturation. For the first time, high-resolution atlases of viscoelasticity of the mouse brain were generated, revealing that (i) brain stiffness increased alongside progressive accumulation of microtubular structures, myelination, cytoskeleton linkage and cell-matrix attachment, and that (ii) viscosity-related tissue fluidity decreased alongside downregulated actin crosslinking and axonal organization. Taken together, our results show that brain maturation is associated with a shift of brain mechanical properties towards a more solid-rigid behavior consistent with reduced tissue fluidity. This shift appears to be driven by several molecular processes associated with myelination, cytoskeletal crosslinking and axonal organization. STATEMENT OF SIGNIFICANCE: The viscoelastic properties of brain tissue shape the environment in which neurons proliferate, grow, and mature. In the present study, novel tomoelastography was used to spatially map tissue mechanical properties of the in-vivo mouse brain during maturation. In vivo tomoelastography was also combined with ex vivo mass spectrometry proteomic analysis to identify the molecules which shape the biomechanical properties of brain tissue. With the combined technique, we observed that brain maturation is associated with a shift of brain mechanical properties towards a more solid-rigid behavior consistent with reduced tissue fluidity which is driven by multiple molecular processes. We believe that this shift of brain mechanical properties discovered in our study reflects a fundamental biophysical signature of brain maturation.

Mechanical changes of peripheral nerve tissue microenvironment and their structural basis during development

Peripheral nerves are constantly exposed to mechanical stresses associated with body growth and limb movements. Although some aspects of these nerves' biomechanical properties are known, the link between nerve biomechanics and tissue microstructures during development is poorly understood. Here, we used atomic force microscopy to comprehensively investigate the elastic modulus of living peripheral nerve tissue cross sections ex vivo at distinct stages of development and correlated these elastic moduli with various cellular and extracellular aspects of the underlying histological microstructure. We found that local nerve tissue stiffness is spatially heterogeneous and evolves biphasically during maturation. Furthermore, we found the intracellular microtubule network and the extracellular matrix collagens type I and type IV as major contributors to the nerves' biomechanical properties, but surprisingly not cellular density and myelin content as previously shown for the central nervous system. Overall, these findings characterize the mechanical microenvironment that surrounds Schwann cells and neurons and will further our understanding of their mechanosensing mechanisms during nerve development. These data also provide the design of artificial nerve scaffolds to promote biomedical nerve regeneration therapies by considering mechanical properties that better reflect the nerve microenvironment.

Engineering biomaterial microenvironments to promote myelination in the central nervous system

Promoting remyelination and/or minimizing demyelination are key therapeutic strategies under investigation for diseases and injuries like multiple sclerosis (MS), spinal cord injury, stroke, and virus-induced encephalopathy. Myelination is essential for efficacious neuronal signaling. This myelination process is originated by oligodendrocyte progenitor cells (OPCs) in the central nervous system (CNS). Resident OPCs are capable of both proliferation and differentiation, and also migration to demyelinated injury sites. OPCs can then engage with these unmyelinated or demyelinated axons and differentiate into myelin-forming oligodendrocytes (OLs). However this process is frequently incomplete and often does not occur at all. Biomaterial strategies can now be used to guide OPC and OL development with the goal of regenerating healthy myelin sheaths in formerly damaged CNS tissue. Growth and neurotrophic factors delivered from such materials can promote proliferation of OPCs or differentiation into OLs. While cell transplantation techniques have been used to replace damaged cells in wound sites, they have also resulted in poor transplant cell viability, uncontrollable differentiation, and poor integration into the host. Biomaterial scaffolds made from extracellular matrix (ECM) mimics that are naturally or synthetically derived can improve transplanted cell survival, support both transplanted and endogenous cell populations, and direct their fate. In particular, stiffness and degradability of these scaffolds are two parameters that can influence the fate of OPCs and OLs. The future outlook for biomaterials research includes 3D in vitro models of myelination / remyelination / demyelination to better mimic and study these processes. These models should provide simple relationships of myelination to microenvironmental biophysical and biochemical properties to inform improved therapeutic approaches.

Mechanical properties of the in vivo adolescent human brain

Viscoelastic mechanical properties of the in vivo human brain, measured noninvasively with magnetic resonance elastography (MRE), have recently been shown to be affected by aging and neurological disease, as well as relate to performance on cognitive tasks in adults. The demonstrated sensitivity of brain mechanical properties to neural tissue integrity make them an attractive target for examining the developing brain; however, to date, MRE studies on children are lacking. In this work, we characterized global and regional brain stiffness and damping ratio in a sample of 40 adolescents aged 12-14 years, including the lobes of the cerebrum and subcortical gray matter structures. We also compared the properties of the adolescent brain to the healthy adult brain. Temporal and parietal cerebral lobes were softer in adolescents compared to adults. We found that of subcortical gray matter structures, the caudate and the putamen were significantly stiffer in adolescents, and that the hippocampus and amygdala were significantly less stiff than all other subcortical structures. This study provides the first detailed characterization of adolescent brain viscoelasticity and provides baseline data to be used in studying development and pathophysiology.

PROBING MECHANICAL PROPERTIES OF BRAIN IN A TUBEROUS SCLEROSIS MODEL OF AUTISM

Causes of Autism Spectrum Disorders (ASD) are understood poorly, making diagnosis and treatment challenging. While many studies have investigated the biochemical and genetic aspects of ASD, whether and how mechanical characteristics of the autistic brain can modulate neuronal connectivity and cognition in ASD are unknown. Previously, it has been shown that ASD brains are characterized by abnormal white matter and disorganized neuronal connectivity; we hypothesized that these significant cellular-level structural changes may translate to changes in the mechanical properties of the autistic brain or regions therein. Here, we focused on tuberous sclerosis complex (TSC), a genetic disorder with a high penetrance of ASD. We investigated mechanical differences between murine brains obtained from control and TSC cohorts at various deformation length- and time-scales. At the microscale, we conducted creep-compliance and stress relaxation experiments using atomic force microscope-enabled indentation. At the mesoscale, we conducted impact indentation using a pendulum-based instrumented indenter to extract mechanical energy dissipation metrics. At the macroscale, we used oscillatory shear rheology to quantify the frequency-dependent shear moduli. Despite significant changes in the cellular organization of TSC brain tissue, we found no corresponding changes in the quantified mechanical properties at every length- and time-scale explored. This investigation of the mechanical characteristics of the brain has broadened our understanding of causes and markers of TSC/ASD, while raising questions about whether any mechanical differences can be detected in other animal models of ASD or other disease models that also feature abnormal brain structure.

Buckling without Bending: A New Paradigm in Morphogenesis

A curious feature of organ and organoid morphogenesis is that in certain cases, spatial oscillations in the thickness of the growing "film" are out of phase with the deformation of the slower-growing "substrate," while in other cases, the oscillations are in phase. The former cannot be explained by elastic bilayer instability, and contradict the notion that there is a universal mechanism by which brains, intestines, teeth, and other organs develop surface wrinkles and folds. Inspired by the microstructure of the embryonic cerebellum, we develop a new model of 2D morphogenesis in which system-spanning elastic fibers endow the organ with a preferred radius, while a separate fiber network resides in the otherwise fluidlike film at the outer edge of the organ and resists thickness gradients thereof. The tendency of the film to uniformly thicken or thin is described via a "growth potential." Several features of cerebellum, +blebbistatin organoid, and retinal fovea morphogenesis, including out-of-phase behavior and a film thickness amplitude that is comparable to the radius amplitude, are readily explained by our simple analytical model, as may be an observed scale invariance in the number of folds in the cerebellum. We also study a nonlinear variant of the model, propose further biological and bioinspired applications, and address how our model is and is not unique to the developing nervous system.