Mean deformation metrics for quantifying 3D cell-matrix interactions without requiring information about matrix material properties.

Mechanobiology relates cellular processes to mechanical signals, such as determining the effect of variations in matrix stiffness with cell tractions. Cell traction recorded via traction force microscopy (TFM) commonly takes place on materials such as polyacrylamide- and polyethylene glycol-based gels. Such experiments remain limited in physiological relevance because cells natively migrate within complex tissue microenvironments that are spatially heterogeneous and hierarchical. Yet, TFM requires determination of the matrix constitutive law (stress-strain relationship), which is not always readily available. In addition, the currently achievable displacement resolution limits the accuracy of TFM for relatively small cells. To overcome these limitations, and increase the physiological relevance of in vitro experimental design, we present a new approach and a set of associated biomechanical signatures that are based purely on measurements of the matrix's displacements without requiring any knowledge of its constitutive laws. We show that our mean deformation metrics (MDM) approach can provide significant biophysical information without the need to explicitly determine cell tractions. In the process of demonstrating the use of our MDM approach, we succeeded in expanding the capability of our displacement measurement technique such that it can now measure the 3D deformations around relatively small cells (∼10 micrometers), such as neutrophils. Furthermore, we also report previously unseen deformation patterns generated by motile neutrophils in 3D collagen gels.

3D Viscoelastic traction force microscopy.

Native cell-material interactions occur on materials differing in their structural composition, chemistry, and physical compliance. While the last two decades have shown the importance of traction forces during cell-material interactions, they have been almost exclusively presented on purely elastic in vitro materials. Yet, most bodily tissue materials exhibit some level of viscoelasticity, which could play an important role in how cells sense and transduce tractions. To expand the realm of cell traction measurements and to encompass all materials from elastic to viscoelastic, this paper presents a general, and comprehensive approach for quantifying 3D cell tractions in viscoelastic materials. This methodology includes the experimental characterization of the time-dependent material properties for any viscoelastic material with the subsequent mathematical implementation of the determined material model into a 3D traction force microscopy (3D TFM) framework. Utilizing this new 3D viscoelastic TFM (3D VTFM) approach, we quantify the influence of viscosity on the overall material traction calculations and quantify the error associated with omitting time-dependent material effects, as is the case for all other TFM formulations. We anticipate that the 3D VTFM technique will open up new avenues of cell-material investigations on even more physiologically relevant time-dependent materials including collagen and fibrin gels.

The dynamic response of human lungs due to underwater shock wave exposure.

Since the 19th century, underwater explosions have posed a significant threat to service members. While there have been attempts to establish injury criteria for the most vulnerable organs, namely the lungs, existing criteria are highly variable due to insufficient human data and the corresponding inability to understand the underlying injury mechanisms. This study presents an experimental characterization of isolated human lung dynamics during simulated exposure to underwater shock waves. We found that the large acoustic impedance at the surface of the lung severely attenuated transmission of the shock wave into the lungs. However, the shock wave initiated large bulk pressure-volume cycles that are distinct from the response of the solid organs under similar loading. These pressure-volume cycles are due to compression of the contained gas, which we modeled with the Rayleigh-Plesset equation. The extent of these lung dynamics was dependent on physical confinement, which in real underwater blast conditions is influenced by factors such as rib cage properties and donned equipment. Findings demonstrate a potential causal mechanism for implosion injuries, which has significant implications for the understanding of primary blast lung injury due to underwater blast exposures.

Sampling rate requirement for accurate calculation of heart rate and its variability based on the electrocardiogram.

Objective. To develop analytical formulas which can serve as quantitative guidelines for the selection of the sampling rate for the electrocardiogram (ECG) required to calculate heart rate (HR) and heart rate variability (HRV) with a desired level of accuracy.Approach. We developed analytical formulas which relate the ECG sampling rate to conservative bounds on HR and HRV errors: (i) one relating HR and sampling rate to a HR error bound and (ii) the others relating sampling rate to HRV error bounds (in terms of root-mean-square of successive differences (RMSSD) and standard deviation of normal sinus beats (SDNN)). We validated the formulas using experimental data collected from 58 young healthy volunteers which encompass a wide HR and HRV ranges through strenuous exercise.Main results. The results strongly supported the validity of the analytical formulas as well as their tightness. The formulas can be used to (i) predict an upper bound of inaccuracy in HR and HRV for a given sampling rate in conjunction with HR and HRV as well as to (ii) determine a sampling rate to achieve a desired accuracy requirement at a given HR or HRV (or its range).Significance. HR and its variability (HRV) derived from the ECG have been widely utilized in a wide range of research in physiology and psychophysiology. However, there is no established guideline for the selection of the sampling rate for the ECG required to calculate HR and HRV with a desired level of accuracy. Hence, the analytical formulas may guide in selecting sampling rates for the ECG tailored to various applications of HR and HRV.

Uniform-intensity, visible light source for in situ imaging.

A flexible, low-cost, high-brightness light source for biological and biomedical imaging is presented. The illuminating device consists of a custom-size square plastic pouch 10 to 20 mm on a side and 1 to 3 mm thick that can be inserted fully or partially into both in situ or in vitro specimens to be imaged. The pouch contains a silicone-based gel medium embedded with silica particles that scatters light and provides a reasonably uniform, planar light source. Light is delivered to the pouch using a multimode optical fiber and a high-intensity tungsten lamp. Pouch size and geometry can be readily altered as needed for a particular application. Benefits of the device include reasonably uniform light intensity, low temperature rise (<2 degrees C), a nearly white light spectrum, and a thin (<2 mm thick) flexible form factor. The design, fabrication, and preliminary results from the device are presented using hamster cheek pouch tissue, with comparisons to standard intravital microscopy, along with suggestions for further improvement and potential uses.

Modular approach for resolving and mapping complex neural and other cellular structures and their associated deformation fields in three dimensions.

Understanding the biological implications of cellular mechanotransduction, especially in the context of pathogenesis, requires the accurate resolution of material deformation and strain fields surrounding the cells. This is particularly challenging for cells displaying branched, 3D architectures. Here, we provide a modular approach for 3D image segmentation and strain mapping of topologically complex structures. We describe how to use our approach, using neural cells and networks as an example. In addition to describing how to implement the computational analysis, we provide details of a cell culture protocol that can be used to generate neural networks for analysis and experimentation. This protocol allows for transformation of matrix-induced strains, and their full resolution across single cells or networks in three dimensions. The protocol also provides analyses to compute both the locally varying cytoskeletal strains and the average strain experienced by cells. An additional module allows spatial correlation of these strain maps with cytoskeletal features, including neurite disruptions such as neuronal blebs. Image processing and strain mapping take ≥3 h, with the exact time required being dependent on use case, software familiarity, and file size.

Strain and rate-dependent neuronal injury in a 3D in vitro compression model of traumatic brain injury.

In the United States over 1.7 million cases of traumatic brain injury are reported yearly, but predictive correlation of cellular injury to impact tissue strain is still lacking, particularly for neuronal injury resulting from compression. Given the prevalence of compressive deformations in most blunt head trauma, this information is critically important for the development of future mitigation and diagnosis strategies. Using a 3D in vitro neuronal compression model, we investigated the role of impact strain and strain rate on neuronal lifetime, viability, and pathomorphology. We find that strain magnitude and rate have profound, yet distinctively different effects on the injury pathology. While strain magnitude affects the time of neuronal death, strain rate influences the pathomorphology and extent of population injury. Cellular injury is not initiated through localized deformation of the cytoskeleton but rather driven by excess strain on the entire cell. Furthermore we find that, mechanoporation, one of the key pathological trigger mechanisms in stretch and shear neuronal injuries, was not observed under compression.

Three-dimensional traction forces of Schwann cells on compliant substrates.

The mechanical interaction between Schwann cells (SCs) and their microenvironment is crucial for the development, maintenance and repair of the peripheral nervous system. In this paper, we present a detailed investigation on the mechanosensitivity of SCs across a physiologically relevant substrate stiffness range. Contrary to many other cell types, we find that the SC spreading area and cytoskeletal actin architecture were relatively insensitive to substrate stiffness with pronounced stress fibre formation across all moduli tested (0.24-4.80 kPa). Consistent with the presence of stress fibres, we found that SCs generated large surface tractions on stiff substrates and large, finite material deformations on soft substrates. When quantifying the three-dimensional characteristics of the SC traction profiles, we observed a significant contribution from the out-of-plane traction component, locally giving rise to rotational moments similar to those observed in mesenchymal embryonic fibroblasts. Taken together, these measurements provide the first set of quantitative biophysical metrics of how SCs interact with their physical microenvironment, which are anticipated to aid in the development of tissue engineering scaffolds designed to promote functional integration of SCs into post-injury in vivo environments.

High resolution, large deformation 3D traction force microscopy.

Traction Force Microscopy (TFM) is a powerful approach for quantifying cell-material interactions that over the last two decades has contributed significantly to our understanding of cellular mechanosensing and mechanotransduction. In addition, recent advances in three-dimensional (3D) imaging and traction force analysis (3D TFM) have highlighted the significance of the third dimension in influencing various cellular processes. Yet irrespective of dimensionality, almost all TFM approaches have relied on a linear elastic theory framework to calculate cell surface tractions. Here we present a new high resolution 3D TFM algorithm which utilizes a large deformation formulation to quantify cellular displacement fields with unprecedented resolution. The results feature some of the first experimental evidence that cells are indeed capable of exerting large material deformations, which require the formulation of a new theoretical TFM framework to accurately calculate the traction forces. Based on our previous 3D TFM technique, we reformulate our approach to accurately account for large material deformation and quantitatively contrast and compare both linear and large deformation frameworks as a function of the applied cell deformation. Particular attention is paid in estimating the accuracy penalty associated with utilizing a traditional linear elastic approach in the presence of large deformation gradients.