Viscoelastic Properties of Human Autopsy Brain Tissues as Biomarkers for Alzheimer's Diseases

Diabetes and Cognitive Decline: An Innovative Approach to Analyzing the Biophysical and Vibrational Properties of the Hippocampus

Diabetes Mellitus (DM) is a disease characterized by high blood glucose levels, known as hyperglycemia. Diabetes represents a risk factor for the development of neurodegenerative diseases, such as Alzheimer's Disease (AD), one of the most prevalent neurodegenerative diseases worldwide, which leads to progressive mental, behavioral, and functional decline, affecting many brain structures, especially the hippocampus. Here, we aim to characterize the ultrastructural, nanomechanical, and vibrational changes in hyperglycemic hippocampal tissue using atomic force microscopy (AFM) and Raman spectroscopy. DM was induced in rats by streptozotocin injection (type 1) or dietary intervention (type 2). Cryosections of the hippocampus were prepared and analyzed on an MM8 AFM (Bruker) in Peak Force Quantitative Nanomechanics mode, performing 25 μm2 scans in 9 regions of 3 samples from each group. Ultrastructural and nanomechanical data such as surface roughness, area, volume, Young's modulus, and adhesion were evaluated. The hippocampal samples were also analyzed on a T64000 Spectrometer (Horiba), using a laser λ = 632.8 nm, and for each sample, four spectra were obtained in different regions. AFM analyses show changes on the ultrastructural scale since diabetic animals had hippocampal tissue with greater roughness and volume. Meanwhile, diabetic tissues had decreased adhesion and Young's modulus compared to control tissues. These were corroboratedby Raman data that shows changes in the molecular composition of diabetic tissues. The individual spectra show that the most significant changes are in the amide, cholesterol, and lipid bands. Overall, the data presented here show that hyperglycemia induces biophysical alterations in the hippocampal tissue of diabetic rats, providing novel biophysical and vibrational cues on the relationship between hyperglycemia and dementia.

Meta-analysis of the make-up and properties of in vitro models of the healthy and diseased blood-brain barrier

In vitro models of the human blood-brain barrier (BBB) are increasingly used to develop therapeutics that can cross the BBB for treating diseases of the central nervous system. Here we report a meta-analysis of the make-up and properties of transwell and microfluidic models of the healthy BBB and of BBBs in glioblastoma, Alzheimer's disease, Parkinson's disease and inflammatory diseases. We found that the type of model, the culture method (static or dynamic), the cell types and cell ratios, and the biomaterials employed as extracellular matrix are all crucial to recapitulate the low permeability and high expression of tight-junction proteins of the BBB, and to obtain high trans-endothelial electrical resistance. Specifically, for models of the healthy BBB, the inclusion of endothelial cells and pericytes as well as physiological shear stresses (~10-20 dyne cm-2) are necessary, and when astrocytes are added, astrocytes or pericytes should outnumber endothelial cells. We expect this meta-analysis to facilitate the design of increasingly physiological models of the BBB.

Vesicle fusion and release in neurons under dynamic mechanical equilibrium

Vesicular fusion plays a pivotal role in cellular processes, involving stages like vesicle trafficking, fusion pore formation, content release, and membrane integration or separation. This dynamic process is regulated by a complex interplay of protein assemblies, osmotic forces, and membrane tension, which together maintain a mechanical equilibrium within the cell. Changes in cellular mechanics or external pressures prompt adjustments in this equilibrium, highlighting the system's adaptability. This review delves into the synergy between intracellular proteins, structural components, and external forces in facilitating vesicular fusion and release. It also explores how cells respond to mechanical stress, maintaining equilibrium and offering insights into vesicle fusion mechanisms and the development of neurological disorders.

Photoacoustic viscoelasticity assessment of prefrontal cortex and cerebellum in normal and prenatal valproic acid-exposed rats

Mechanical properties of brain tissues are from principal features from different points of view; diagnosis, the performance of the brain and neurological disorders. Particularly viscoelastic properties of the brain tissues are determinative. In this study based on a proposed accurate and non-invasive method, we have measured the viscoelastic properties of prefrontal cortex and cerebellum, two important brain regions involved in motor learning and pathophysiology of autism spectrum disorder (ASD). In this regard, using photoacoustic systems, viscoelastic properties of tissues from the cerebellum and prefrontal cortex of normal and prenatal VPA (Valproic acid)-exposed (i.e. autistic-like) offspring rats are measured. Results of our study show that the cerebellums of normal tissues are stiffer than the tissue obtained from autistic-like rats, while the viscoelasticity of the prefrontal cortex of normal tissues is higher than that of autistic ones. The proposed method for the measurement of viscoelastic properties of the brain tissue has the potential not only for the fundamental studies but as a diagnosis technique.

Atomic Force Microscopy Applied to the Study of Tauopathies

Atomic force microscopy (AFM) is a scanning probe microscopy technique which has a physical principle, the measurement of interatomic forces between a very thin tip and the surface of a sample, allowing the obtaining of quantitative data at the nanoscale, contributing to the surface study and mechanical characterization. Due to its great versatility, AFM has been used to investigate the structural and nanomechanical properties of several inorganic and biological materials, including neurons affected by tauopathies. Tauopathies are neurodegenerative diseases featured by aggregation of phosphorylated tau protein inside neurons, leading to functional loss and progressive neurotoxicity. In the broad universe of neurodegenerative diseases, tauopathies comprise the most prevalent, with Alzheimer's disease as its main representative. This review highlights the use of AFM as a suitable research technique for the study of cellular damages in tauopathies, even in early stages, allowing elucidation of pathogenic mechanisms of these diseases.

Engineering the Physical Microenvironment into Neural Organoids for Neurogenesis and Neurodevelopment

Understanding the signals from the physical microenvironment is critical for deciphering the processes of neurogenesis and neurodevelopment. The discovery of how surrounding physical signals shape human developing neurons is hindered by the bottleneck of conventional cell culture and animal models. Notwithstanding neural organoids provide a promising platform for recapitulating human neurogenesis and neurodevelopment, building neuronal physical microenvironment that accurately mimics the native neurophysical features is largely ignored in current organoid technologies. Here, it is discussed how the physical microenvironment modulates critical events during the periods of neurogenesis and neurodevelopment, such as neural stem cell fates, neural tube closure, neuronal migration, axonal guidance, optic cup formation, and cortical folding. Although animal models are widely used to investigate the impacts of physical factors on neurodevelopment and neuropathy, the important roles of human stem cell-derived neural organoids in this field are particularly highlighted. Considering the great promise of human organoids, building neural organoid microenvironments with mechanical forces, electrophysiological microsystems, and light manipulation will help to fully understand the physical cues in neurodevelopmental processes. Neural organoids combined with cutting-edge techniques, such as advanced atomic force microscopes, microrobots, and structural color biomaterials might promote the development of neural organoid-based research and neuroscience.

Dynamic Hydrogels with Viscoelasticity and Tunable Stiffness for the Regulation of Cell Behavior and Fate

The extracellular matrix (ECM) of natural cells typically exhibits dynamic mechanical properties (viscoelasticity and dynamic stiffness). The viscoelasticity and dynamic stiffness of the ECM play a crucial role in biological processes, such as tissue growth, development, physiology, and disease. Hydrogels with viscoelasticity and dynamic stiffness have recently been used to investigate the regulation of cell behavior and fate. This article first emphasizes the importance of tissue viscoelasticity and dynamic stiffness and provides an overview of characterization techniques at both macro- and microscale. Then, the viscoelastic hydrogels (crosslinked via ion bonding, hydrogen bonding, hydrophobic interactions, and supramolecular interactions) and dynamic stiffness hydrogels (softening, stiffening, and reversible stiffness) with different crosslinking strategies are summarized, along with the significant impact of viscoelasticity and dynamic stiffness on cell spreading, proliferation, migration, and differentiation in two-dimensional (2D) and three-dimensional (3D) cell cultures. Finally, the emerging trends in the development of dynamic mechanical hydrogels are discussed.

Advanced 3D Models of Human Brain Tissue Using Neural Cell Lines: State-of-the-Art and Future Prospects

Human-relevant three-dimensional (3D) models of cerebral tissue can be invaluable tools to boost our understanding of the cellular mechanisms underlying brain pathophysiology. Nowadays, the accessibility, isolation and harvesting of human neural cells represents a bottleneck for obtaining reproducible and accurate models and gaining insights in the fields of oncology, neurodegenerative diseases and toxicology. In this scenario, given their low cost, ease of culture and reproducibility, neural cell lines constitute a key tool for developing usable and reliable models of the human brain. Here, we review the most recent advances in 3D constructs laden with neural cell lines, highlighting their advantages and limitations and their possible future applications.

Phase-Resolved Optical Coherence Elastography: An Insight into Tissue Displacement Estimation

Robust methods to compute tissue displacements in optical coherence elastography (OCE) data are paramount, as they play a significant role in the accuracy of tissue elastic properties estimation. In this study, the accuracy of different phase estimators was evaluated on simulated OCE data, where the displacements can be accurately set, and on real data. Displacement (∆d) estimates were computed from (i) the original interferogram data (Δφori) and two phase-invariant mathematical manipulations of the interferogram: (ii) its first-order derivative (Δφd) and (iii) its integral (Δφint). We observed a dependence of the phase difference estimation accuracy on the initial depth location of the scatterer and the magnitude of the tissue displacement. However, by combining the three phase-difference estimates (Δdav), the error in phase difference estimation could be minimized. By using Δdav, the median root-mean-square error associated with displacement prediction in simulated OCE data was reduced by 85% and 70% in data with and without noise, respectively, in relation to the traditional estimate. Furthermore, a modest improvement in the minimum detectable displacement in real OCE data was also observed, particularly in data with low signal-to-noise ratios. The feasibility of using Δdav to estimate agarose phantoms' Young's modulus is illustrated.

Unravelling the mechanotransduction pathways in Alzheimer's disease

Alzheimer's disease (AD) represents one of the most common and debilitating neurodegenerative disorders. By the end of 2040, AD patients might reach 11.2 million in the USA, around 70% higher than 2022, with severe consequences on the society. As now, we still need research to find effective methods to treat AD. Most studies focused on the tau and amyloid hypothesis, but many other factors are likely involved in the pathophysiology of AD. In this review, we summarize scientific evidence dealing with the mechanotransduction players in AD to highlight the most relevant mechano-responsive elements that play a role in AD pathophysiology. We focused on the AD-related role of extracellular matrix (ECM), nuclear lamina, nuclear transport and synaptic activity. The literature supports that ECM alteration causes the lamin A increment in the AD patients, leading to the formation of nuclear blebs and invaginations. Nuclear blebs have consequences on the nuclear pore complexes, impairing nucleo-cytoplasmic transport. This may result in tau hyperphosphorylation and its consequent self-aggregation in tangles, which impairs the neurotransmitters transport. It all exacerbates in synaptic transmission impairment, leading to the characteristic AD patient's memory loss. Here we related for the first time all the evidence associating the mechanotransduction pathway with neurons. In addition, we highlighted the entire pathway influencing neurodegenerative diseases, paving the way for new research perspectives in the context of AD and related pathologies.

Orientation-dependent indentation reveals the crosslink-mediated deformation mechanisms of collagen fibrils

The spatial arrangement and interactions of the extracellular matrix (ECM) components control the mechanical behavior of tissue at multiple length scales. Changes in microscale deformation mechanisms affect tissue function and are often hallmarks of remodeling and disease. Despite their importance, the deformation mechanisms that modulate the mechanical behavior of collagenous tissue, particularly in indentation and compression modes of deformation, remain poorly understood. Here, we develop an integrated computational and experimental approach to investigate the deformation mechanisms of collagenous tissue at the microscale. While the complex deformation arising from indentation with a spherical probe is often considered a pitfall rather than an opportunity, we leverage this orientation-dependent deformation to examine the shear-regulated interactions of collagen fibrils and the role of crosslinks in modulating these interactions. We specifically examine tendon and cervix, two tissues rich in collagen with quite different microstructures and mechanical functions. We find that interacting, crosslinked collagen fibrils resist microscale longitudinal compressive forces, while widely used constitutive models fail to capture this behavior. The reorientation of collagen fibrils tunes the compressive stiffness of complex tissues like cervix. This study offers new insights into the mechanical behavior of collagen fibrils during indentation, and more generally, under longitudinal compressive forces, and illustrates the mechanisms that contribute to the experimentally observed orientation-dependent mechanical behavior. STATEMENT OF SIGNIFICANCE: Remodeling and disease can affect the deformation and interaction of tissue constituents, and thus mechanical function of tissue. Yet, the microscale deformation mechanisms are not well characterized in many tissues. Here, we develop a combined experimental-computational approach to infer the microscale deformation mechanisms of collagenous tissues with very different functions: tendon and cervix. Results show that collagen fibrils resist microscale forces along their length, though widely-used constitutive models do not account for this mechanism. This deformation process partially modulates the compressive stiffness of complex tissues such as cervix. Computational modeling shows that crosslink-mediated shear deformations are central to this unexpected behavior. This study offers new insights into the deformation mechanisms of collagenous tissue and the function of collagen crosslinkers.

A methodology to evaluate different histological preparations of soft tissues: Intervertebral disc tissues study

A tissue preparation method will inevitably alter the tissue content. This study aims to evaluate how different common sample preparation methods will affect the tissue morphology, biomechanical properties, and chemical composition of samples. The study focuses on intervertebral disc (IVD) tissue; however, it can be applied to other soft tissues. Raman spectroscopy synchronized with nanoindentation instrumentation was employed to investigate the compositional changes of IVD, specifically, nucleus pulposus (NP) and annulus fibrosus (AF), together with their biomechanical properties of IVD. These properties were examined through the following histological specimen types: fresh cryosection (control), fixed cryosection, and paraffin-embedded. The IVD tissue could be located using an optical microscope under three different preparation methods. Paraffin-embedded samples showed the most explicit details where the lamellae structure of AF could be identified. In terms of biomechanical properties, there was no significant difference between the fresh and fixed cryosection (p > 0.05). In contrast, the fresh cryosection and paraffin-embedded samples showed a significant difference (p < 0.05). It was also found that the tissue preparations affected the chemical content of the tissues and structure of the tissue, which are expected to contribute to biomechanical properties changes. Fresh cryosection and fixed cryosection samples are more promising to work with for biomechanical assessment in histological tissues. The findings fill essential gaps in the literature by providing valuable insight into the characteristics of IVD at the microscale. This study can also become a reference for a better approach to assessing the mechanical properties and chemical content of soft tissues at the microscale.

Correlation of the degenerative stage of a disc with magnetic resonance imaging, chemical content, and biomechanical properties of the nucleus pulposus

Intervertebral disc degeneration (IDD) is closely related to changes in the intervertebral disc (IVD) composition and the resulting viscoelastic properties. IDD is a severe condition because it decreases the disc's ability to resist mechanical loads. Our research aims to understand IDD at the cellular level, specifically the changes in the viscoelastic properties of the nucleus pulposus (NP), which are poorly understood. This study employed a system integrating nanoindentation with Raman spectrometry to correlate biomechanics with subtle changes in the biochemical makeup of the NP. The characterization was, in turn, correlated with the degenerative severity of IVD as assessed using magnetic resonance imaging (MRI) of different patients with spinal stenosis, degenerative spondylolisthesis, and degenerative scoliosis. It is shown that there is an increase in the crosslinking ratio in collagen, a reduction in proteoglycan, and a build-up of minerals upon the rise in the severity level of the disc damage in the NP. Assessment of mechanical characteristics reveals that the increasing disc degeneration makes the NP lose its elasticity, becoming more viscous. This shows that the tissue undergoes abnormalities in weight-bearing ability, which contributes to spinal instability. The correlation of the individual discs shows that grades III and IV have similarities in the changes of Amide I and III toward the storage modulus. In contrast, grades IV and V correlate with mineralization toward the storage modulus. Reduction of proteoglycan has the highest impact on the changes of the storage modulus in all grades of IDD. Connecting compositional alterations to IVD micromechanics at various degrees of degeneration expands our understanding of tissue behavior and provides critical insight into clinical diagnostics, treatment, and tissue engineering.

Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine

Quantitative phase imaging (QPI) is a label-free, wide-field microscopy approach with significant opportunities for biomedical applications. QPI uses the natural phase shift of light as it passes through a transparent object, such as a mammalian cell, to quantify biomass distribution and spatial and temporal changes in biomass. Reported in cell studies more than 60 years ago, ongoing advances in QPI hardware and software are leading to numerous applications in biology, with a dramatic expansion in utility over the past two decades. Today, investigations of cell size, morphology, behavior, cellular viscoelasticity, drug efficacy, biomass accumulation and turnover, and transport mechanics are supporting studies of development, physiology, neural activity, cancer, and additional physiological processes and diseases. Here, we review the field of QPI in biology starting with underlying principles, followed by a discussion of technical approaches currently available or being developed, and end with an examination of the breadth of applications in use or under development. We comment on strengths and shortcomings for the deployment of QPI in key biomedical contexts and conclude with emerging challenges and opportunities based on combining QPI with other methodologies that expand the scope and utility of QPI even further.

A System-based Approach for the Evaluation of Electromechanical Properties of Brain Tumors

We have developed a semi-automated system integrated with MEMS-based electromechanical sensors to characterize human brain tumors. The electrical impedance and elastic moduli of three types of brain tumors and six normal brain regions were evaluated using the system. The impedance and elastic modulus of glioma was found to be significantly lower than the normal region. It was also observed that the white matter tissues had higher impedance and elastic moduli compared with the grey matter of the same neuroanatomic location. There were observable differences in the electromechanical behavior of gliomas, which originate from glial cells to that of schwannoma and meningioma of different cellular origins. Clinical Relevance- The observations suggest that simultaneous electromechanical characterization of brain tumors can serve as an effective tool for tumor delineation. The developed tool can be used alongside gold standard histopathological analysis to better understand human brain tumors.

Constitutive Equations for Analyzing Stress Relaxation and Creep of Viscoelastic Materials Based on Standard Linear Solid Model Derived with Finite Loading Rate

The viscoelastic properties of materials such as polymers can be quantitatively evaluated by measuring and analyzing the viscoelastic behaviors such as stress relaxation and creep. The standard linear solid model is a classical and commonly used mathematical model for analyzing stress relaxation and creep behaviors. Traditionally, the constitutive equations for analyzing stress relaxation and creep behaviors based on the standard linear solid model are derived using the assumption that the loading is a step function, implying that the loading rate used in the loading process of stress relaxation and creep tests is infinite. Using such constitutive equations may cause significant errors in analyses since the loading rate must be finite (no matter how fast it is) in a real stress relaxation or creep experiment. The purpose of this paper is to introduce the constitutive equations for analyzing stress relaxation and creep behaviors based on the standard linear solid model derived with a finite loading rate. The finite element computational simulation results demonstrate that the constitutive equations derived with a finite loading rate can produce accurate results in the evaluation of all viscoelastic parameters regardless of the loading rate in most cases. It is recommended that the constitutive equations derived with a finite loading rate should replace the traditional ones derived with an infinite loading rate to analyze stress relaxation and creep behaviors for quantitatively evaluating the viscoelastic properties of materials.

Viscoelasticity Acts as a Marker for Tumor Extracellular Matrix Characteristics

Biological materials such as extracellular matrix scaffolds, cancer cells, and tissues are often assumed to respond elastically for simplicity; the viscoelastic response is quite commonly ignored. Extracellular matrix mechanics including the viscoelasticity has turned out to be a key feature of cellular behavior and the entire shape and function of healthy and diseased tissues, such as cancer. The interference of cells with their local microenvironment and the interaction among different cell types relies both on the mechanical phenotype of each involved element. However, there is still not yet clearly understood how viscoelasticity alters the functional phenotype of the tumor extracellular matrix environment. Especially the biophysical technologies are still under ongoing improvement and further development. In addition, the effect of matrix mechanics in the progression of cancer is the subject of discussion. Hence, the topic of this review is especially attractive to collect the existing endeavors to characterize the viscoelastic features of tumor extracellular matrices and to briefly highlight the present frontiers in cancer progression and escape of cancers from therapy. Finally, this review article illustrates the importance of the tumor extracellular matrix mechano-phenotype, including the phenomenon viscoelasticity in identifying, characterizing, and treating specific cancer types.

Microscale characterisation of the time-dependent mechanical behaviour of brain white matter

Brain mechanics is a topic of deep interest because of the significant role of mechanical cues in both brain function and form. Specifically, capturing the heterogeneous and anisotropic behaviour of cerebral white matter (WM) is extremely challenging and yet the data on WM at a spatial resolution relevant to tissue components are sparse. To investigate the time-dependent mechanical behaviour of WM, and its dependence on local microstructural features when subjected to small deformations, we conducted atomic force microscopy (AFM) stress relaxation experiments on corpus callosum (CC), corona radiata (CR) and fornix (FO) of fresh ovine brain. Our experimental results show a dependency of the tissue mechanical response on axons orientation, with e.g. the stiffness of perpendicular and parallel samples is different in all three regions of WM whereas the relaxation behaviour is different for the CC and FO regions. An inverse modelling approach was adopted to extract Prony series parameters of the tissue components, i.e. axons and extra cellular matrix with its accessory cells, from experimental data. Using a bottom-up approach, we developed analytical and FEA estimates that are in good agreement with our experimental results. Our systematic characterisation of sheep brain WM using a combination of AFM experiments and micromechanical models provide a significant contribution for predicting localised time-dependent mechanics of brain tissue. This information can lead to more accurate computational simulations, therefore aiding the development of surgical robotic solutions for drug delivery and accurate tissue mimics, as well as the determination of criteria for tissue injury and predict brain development and disease progression.

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.

Mechanical alterations of the hippocampus in the APP/PS1 Alzheimer's disease mouse model

There is increasing evidence of altered tissue mechanics in neurodegeneration. However, due to difficulties in mechanical testing procedures and the complexity of the brain, there is still little consensus on the role of mechanics in the onset and progression of neurodegenerative diseases. In the case of Alzheimer's disease (AD), magnetic resonance elastography (MRE) studies have indicated viscoelastic differences in the brain tissue of AD patients and healthy controls. However, there is a lack of viscoelastic data from contact mechanical testing at higher spatial resolution. Therefore, we report viscoelastic maps of the hippocampus obtained by a dynamic indentation on brain slices from the APP/PS1 mouse model where individual brain regions are resolved. A comparison of viscoelastic parameters shows that regions in the hippocampus of the APP/PS1 mice are significantly stiffer than wild-type (WT) mice and have increased viscous dissipation. Furthermore, indentation mapping at the cellular scale directly on the plaques and their surroundings did not show local alterations in stiffness although overall mechanical heterogeneity of the tissue was high (SD∼40%).

Micromechanical poroelastic and viscoelastic properties of ex-vivo soft tissues

Soft biological tissues demonstrate strong time-dependent mechanical behavior, arising from their intrinsic viscoelasticity and fluid flow-induced poroelasticity. It is increasingly recognized that time-dependent mechanical properties of soft tissues influence their physiological functions and are linked to several pathological processes. Nevertheless, soft tissue time-dependent characteristics, especially their micromechanical variation with tissue composition and location, remain poorly understood. Nanoindentation is a well-established technique to measure local elastic properties but has not been fully explored to determine micro-scale time-dependent properties of soft tissues. Here, a nanoindentation-based experimental strategy is implemented to characterize the micro-scale poroelastic and viscoelastic behavior of mouse heart, kidney, and liver tissues. It is demonstrated that heart tissue exhibits substantial mechanical heterogeneity where the elastic modulus varies spatially from 1 to 30 kPa. In contrast, both kidney and liver tissues show relatively homogeneous response with elastic modulus 0.5-3 kPa. All three tissues demonstrate marked load relaxation under constant indentation, where the relaxation behavior is observed to be largely dominated by tissue viscoelasticity. Intrinsic permeability varies among different tissues, where heart tissue is found to be less permeable compared to kidney and liver tissues. Overall, the results presented herein provide key insights into the time-dependent micromechanical behavior of different tissues and can therefore contribute to studies of tissue pathology and tissue engineering applications.

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.