Soft robotics informs how an early echinoderm moved.

The transition from sessile suspension to active mobile detritus feeding in early echinoderms (c.a. 500 Mya) required sophisticated locomotion strategies. However, understanding locomotion adopted by extinct animals in the absence of trace fossils and modern analogues is extremely challenging. Here, we develop a biomimetic soft robot testbed with accompanying computational simulation to understand fundamental principles of locomotion in one of the most enigmatic mobile groups of early stalked echinoderms-pleurocystitids. We show that these Paleozoic echinoderms were likely able to move over the sea bottom by means of a muscular stem that pushed the animal forward (anteriorly). We also demonstrate that wide, sweeping gaits could have been the most effective for these echinoderms and that increasing stem length might have significantly increased velocity with minimal additional energy cost. The overall approach followed here, which we call "Paleobionics," is a nascent but rapidly developing research agenda in which robots are designed based on extinct organisms to generate insights in engineering and evolution.

Fly Me to the Micron: Microtechnologies for Drosophila Research.

Multicellular model organisms, such as Drosophila melanogaster (fruit fly), are frequently used in a myriad of biological research studies due to their biological significance and global standardization. However, traditional tools used in these studies generally require manual handling, subjective phenotyping, and bulk treatment of the organisms, resulting in laborious experimental protocols with limited accuracy. Advancements in microtechnology over the course of the last two decades have allowed researchers to develop automated, high-throughput, and multifunctional experimental tools that enable novel experimental paradigms that would not be possible otherwise. We discuss recent advances in microtechnological systems developed for small model organisms using D. melanogaster as an example. We critically analyze the state of the field by comparing the systems produced for different applications. Additionally, we suggest design guidelines, operational tips, and new research directions based on the technical and knowledge gaps in the literature. This review aims to foster interdisciplinary work by helping engineers to familiarize themselves with model organisms while presenting the most recent advances in microengineering strategies to biologists.

Decidual Vasculopathy Identification in Whole Slide Images Using Multiresolution Hierarchical Convolutional Neural Networks.

After a child is born, the examination of the placenta by a pathologist for abnormalities, such as infection or maternal vascular malperfusion, can provide important information about the immediate and long-term health of the infant. Detection of the pathologic placental blood vessel lesion decidual vasculopathy (DV) has been shown to predict adverse pregnancy outcomes, such as preeclampsia, which can lead to mother and neonatal morbidity in subsequent pregnancies. However, because of the high volume of deliveries at large hospitals and limited resources, currently a large proportion of delivered placentas are discarded without inspection. Furthermore, the correct diagnosis of DV often requires the expertise of an experienced perinatal pathologist. We introduce a hierarchical machine learning approach for the automated detection and classification of DV lesions in digitized placenta slides, along with a method of coupling learned image features with patient metadata to predict the presence of DV. Ultimately, the approach will allow many more placentas to be screened in a more standardized manner, providing feedback about which cases would benefit most from more in-depth pathologic inspection. Such computer-assisted examination of human placentas will enable real-time adjustment to infant and maternal care and possible chemoprevention (eg, aspirin therapy) to prevent preeclampsia, a disease that affects 2% to 8% of pregnancies worldwide, in women identified to be at risk with future pregnancies.

Polycarbonate Heat Molding for Soft Lithography.

Soft lithography enables rapid microfabrication of many types of microsystems by replica molding elastomers into master molds. However, master molds can be very costly, hard to fabricate, vulnerable to damage, and have limited casting life. Here, an approach for the multiplication of master molds into monolithic thermoplastic sheets for further soft lithographic fabrication is introduced. The technique is tested with master molds fabricated through photolithography, mechanical micromilling as well as 3D printing, and the results are demonstrated. Microstructures with submicron feature sizes and high aspect ratios are successfully copied. The copying fidelity of the technique is quantitatively characterized and the microfluidic devices fabricated through this technique are functionally tested. This approach is also used to combine different master molds with up to 19 unique geometries into a single monolithic copy mold in a single step displaying the effectiveness of the copying technique over a large footprint area to scale up the microfabrication. This microfabrication technique can be performed outside the cleanroom without using any sophisticated equipment, suggesting a simple way for high-throughput rigid monolithic mold fabrication that can be used in analytical chemistry studies, biomedical research, and microelectromechanical systems.

Robust mechanobiological behavior emerges in heterogeneous myosin systems.

Biological complexity presents challenges for understanding natural phenomenon and engineering new technologies, particularly in systems with molecular heterogeneity. Such complexity is present in myosin motor protein systems, and computational modeling is essential for determining how collective myosin interactions produce emergent system behavior. We develop a computational approach for altering myosin isoform parameters and their collective organization, and support predictions with in vitro experiments of motility assays with α-actinins as molecular force sensors. The computational approach models variations in single myosin molecular structure, system organization, and force stimuli to predict system behavior for filament velocity, energy consumption, and robustness. Robustness is the range of forces where a filament is expected to have continuous velocity and depends on used myosin system energy. Myosin systems are shown to have highly nonlinear behavior across force conditions that may be exploited at a systems level by combining slow and fast myosin isoforms heterogeneously. Results suggest some heterogeneous systems have lower energy use near stall conditions and greater energy consumption when unloaded, therefore promoting robustness. These heterogeneous system capabilities are unique in comparison with homogenous systems and potentially advantageous for high performance bionanotechnologies. Findings open doors at the intersections of mechanics and biology, particularly for understanding and treating myosin-related diseases and developing approaches for motor molecule-based technologies.

Mechanochemical actuators of embryonic epithelial contractility.

Spatiotemporal regulation of cell contractility coordinates cell shape change to construct tissue architecture and ultimately directs the morphology and function of the organism. Here we show that contractility responses to spatially and temporally controlled chemical stimuli depend much more strongly on intercellular mechanical connections than on biochemical cues in both stimulated tissues and adjacent cells. We investigate how the cell contractility is triggered within an embryonic epithelial sheet by local ligand stimulation and coordinates a long-range contraction response. Our custom microfluidic control system allows spatiotemporally controlled stimulation with extracellular ATP, which results in locally distinct contractility followed by mechanical strain pattern formation. The stimulation-response circuit exposed here provides a better understanding of how morphogenetic processes integrate responses to stimulation and how intercellular responses are transmitted across multiple cells. These findings may enable one to create a biological actuator that actively drives morphogenesis.

Emergent systems energy laws for predicting myosin ensemble processivity.

In complex systems with stochastic components, systems laws often emerge that describe higher level behavior regardless of lower level component configurations. In this paper, emergent laws for describing mechanochemical systems are investigated for processive myosin-actin motility systems. On the basis of prior experimental evidence that longer processive lifetimes are enabled by larger myosin ensembles, it is hypothesized that emergent scaling laws could coincide with myosin-actin contact probability or system energy consumption. Because processivity is difficult to predict analytically and measure experimentally, agent-based computational techniques are developed to simulate processive myosin ensembles and produce novel processive lifetime measurements. It is demonstrated that only systems energy relationships hold regardless of isoform configurations or ensemble size, and a unified expression for predicting processive lifetime is revealed. The finding of such laws provides insight for how patterns emerge in stochastic mechanochemical systems, while also informing understanding and engineering of complex biological systems.

An embedded microfluidic valve for dynamic control of cellular communication.

The communication between different cell populations is an important aspect of many natural phenomena that can be studied with microfluidics. Using microfluidic valves, these complex interactions can be studied with a higher level of control by placing a valve between physically separated populations. However, most current valve designs do not display the properties necessary for this type of system, such as providing variable flow rate when embedded inside a microfluidic device. While some valves have been shown to have such tunable behavior, they have not been used for dynamic, real-time outputs. We present an electric solenoid valve that can be fabricated completely outside of a cleanroom and placed into any microfluidic device to offer control of dynamic fluid flow rates and profiles. After characterizing the behavior of this valve under controlled test conditions, we developed a regression model to determine the required input electrical signal to provide the solenoid the ability to create a desired flow profile. With this model, we demonstrated that the valve could be controlled to replicate a desired, time-varying pattern for the interface position of a co-laminar fluid stream. Our approach can be performed by other investigators with their microfluidic devices to produce predictable, dynamic fluidic behavior. In addition to modulating fluid flows, this work will be impactful for controlling cellular communication between distinct populations or even chemical reactions occurring in microfluidic channels.

Soft magnetic thin film deformation with a bistable electropermanent magnet.

Physically soft magnetic materials (PSMMs) represent an emerging class of materials that can change shape or rheology in response to an external magnetic field. However, until now, no studies have investigated using an electropermanent magnet (EPM) and magnetic repulsion to magnetically deform PSMMs. Such capabilities would enable the ability to deform PSMMs without the need for continuous electrical input and produce PSMM film deformation without an air gap, as would be required with magnetic attraction. To address this, we introduce a PSMM-EPM architecture in which the shape of a soft deformable thin film is controlled by switching between bistable on/off states of the EPM circuit. We characterized the deflection of a PSMM thin film when placed at controlled distances normal to the surface of the EPM and compared its response for cases when the EPM is in the 'on' and 'off' states. This work is the first to demonstrate a magnetically repelled soft deformable thin film that achieves two electronically-controlled modes of deformation through the on and off states of an EPM. This work has the potential to advance the development of new magneto-responsive soft materials and systems.

Controlling C2C12 Cytotoxicity on Liquid Metal Embedded Elastomer (LMEE).

Liquid metal embedded elastomers (LMEEs) are highly stretchable composites comprising microscopic droplets of eutectic gallium-indium (EGaIn) liquid metal embedded in a soft rubber matrix. They have a unique combination of mechanical, electrical, and thermal properties that make them attractive for potential applications in flexible electronics, thermal management, wearable computing, and soft robotics. However, the use of LMEEs in direct contact with human tissue or organs requires an understanding of their biocompatibility and cell cytotoxicity. In this study, the cytotoxicity of C2C12 cells in contact with LMEE composites composed of EGaIn droplets embedded with a polydimethylsiloxane (PDMS) matrix is investigated. In particular, the influence of EGaIn volume ratio and shear mixing time during synthesis on cell proliferation and viability is examined. The special case of electrically-conductive LMEE composites in which a percolating network of EGaIn droplets is created through "mechanical sintering" is also examined. This study in C2C12 cytotoxicity represents a first step in determining whether LMEE is safe for use in implantable biomedical devices and biohybrid systems.

Characterization of neural mechanotransduction response in human traumatic brain injury organoid model.

The ability to model physiological systems through 3D neural in-vitro systems may enable new treatments for various diseases while lowering the need for challenging animal and human testing. Creating such an environment, and even more impactful, one that mimics human brain tissue under mechanical stimulation, would be extremely useful to study a range of human-specific biological processes and conditions related to brain trauma. One approach is to use human cerebral organoids (hCOs) in-vitro models. hCOs recreate key cytoarchitectural features of the human brain, distinguishing themselves from more traditional 2D cultures and organ-on-a-chip models, as well as in-vivo animal models. Here, we propose a novel approach to emulate mild and moderate traumatic brain injury (TBI) using hCOs that undergo strain rates indicative of TBI. We subjected the hCOs to mild (2 s[Formula: see text]) and moderate (14 s[Formula: see text]) loading conditions, examined the mechanotransduction response, and investigated downstream genomic effects and regulatory pathways. The revealed pathways of note were cell death and metabolic and biosynthetic pathways implicating genes such as CARD9, ENO1, and FOXP3, respectively. Additionally, we show a steeper ascent in calcium signaling as we imposed higher loading conditions on the organoids. The elucidation of neural response to mechanical stimulation in reliable human cerebral organoid models gives insights into a better understanding of TBI in humans.

Nanotopographical Cues Tune the Therapeutic Potential of Extracellular Vesicles for the Treatment of Aged Skeletal Muscle Injuries.

Skeletal muscle regeneration relies on the tightly temporally regulated lineage progression of muscle stem/progenitor cells (MPCs) from activation to proliferation and, finally, differentiation. However, with aging, MPC lineage progression is disrupted and delayed, ultimately causing impaired muscle regeneration. Extracellular vesicles (EVs) have attracted broad attention as next-generation therapeutics for promoting tissue regeneration. As a next step toward clinical translation, strategies to manipulate EV effects on downstream cellular targets are needed. Here, we developed an engineering strategy to tune the therapeutic potential of EVs using nanotopographical cues. We found that EVs released by young MPCs cultured on flat substrates (fEVs) promoted the proliferation of aged MPCs while EVs released by MPCs cultured on nanogratings (nEVs) promoted myogenic differentiation. We then employed a bioengineered 3D muscle aging model to optimize the administration protocol and test the therapeutic potential of fEVs and nEVs in a high-throughput manner. We found that the sequential administration first of fEVs during the phase of MPC proliferative expansion (i.e., 1 day after injury) followed by nEV administration at the stage of MPC differentiation (i.e., 3 days after injury) enhanced aged muscle regeneration to a significantly greater extent than fEVs and nEVs delivered either in isolation or mixed. The beneficial effects of the sequential EV treatment strategy were further validated in vivo, as evidenced by increased myofiber size and improved functional recovery. Collectively, our study demonstrates the ability of topographical cues to tune EV therapeutic potential and highlights the importance of optimizing the EV administration strategy to accelerate aged skeletal muscle regeneration.

How do control-based approaches enter into biology?

Control is intrinsic to biological organisms, whose cells are in a constant state of sensing and response to numerous external and self-generated stimuli. Diverse means are used to study the complexity through control-based approaches in these cellular systems, including through chemical and genetic manipulations, input-output methodologies, feedback approaches, and feed-forward approaches. We first discuss what happens in control-based approaches when we are not actively examining or manipulating cells. We then present potential methods to determine what the cell is doing during these times and to reverse-engineer the cellular system. Finally, we discuss how we can control the cell's extracellular and intracellular environments, both to probe the response of the cells using defined experimental engineering-based technologies and to anticipate what might be achieved by applying control-based approaches to affect cellular processes. Much work remains to apply simplified control models and develop new technologies to aid researchers in studying and utilizing cellular and molecular processes.

Defining the role of syndecan-4 in mechanotransduction using surface-modification approaches.

The ability of cells to respond to external mechanical stimulation is a complex and robust process involving a diversity of molecular interactions. Although mechanotransduction has been heavily studied, many questions remain regarding the link between physical stimulation and biochemical response. Of significant interest has been the contribution of the transmembrane proteins involved, and integrins in particular, because of their connectivity to both the extracellular matrix and the cytoskeleton. Here, we demonstrate the existence of a mechanically based initiation molecule, syndecan-4. We first demonstrate the ability of syndecan-4 molecules to support cell attachment and spreading without the direct extracellular binding of integrins. We also examine the distribution of focal adhesion-associated proteins through controlling surface interactions of beads with molecular specificity in binding to living cells. Furthermore, after adhering cells to elastomeric membranes via syndecan-4-specific attachments we mechanically strained the cells via our mechanical stimulation and polymer surface chemical modification approach. We found ERK phosphorylation similar to that shown for mechanotransductive response for integrin-based cell attachments through our elastomeric membrane-based approach and optical magnetic twisting cytometry for syndecan-4. Finally, through the use of cytoskeletal disruption agents, this mechanical signaling was shown to be actin cytoskeleton dependent. We believe that these results will be of interest to a wide range of fields, including mechanotransduction, syndecan biology, and cell-material interactions.

Microfluidics for understanding model organisms.

New microfluidic systems for whole organism analysis and experimentation are catalyzing biological breakthroughs across many fields, from human health to fundamental biology principles. This perspective discusses recent microfluidic tools to study intact model organisms to demonstrate the tremendous potential for these integrated approaches now and into the future. We describe these microsystems' technical features and highlight the unique advantages for precise manipulation in areas including immobilization, automated alignment, sorting, sensory, mechanical and chemical stimulation, and genetic and thermal perturbation. Our aim is to familiarize technologically focused researchers with microfluidics applications in biology research, while providing biologists an entrée to advanced microengineering techniques for model organisms.

Mechanostimulation of Multicellular Organisms Through a High-Throughput Microfluidic Compression System.

During embryogenesis, coordinated cell movement generates mechanical forces that regulate gene expression and activity. To study this process, tools such as aspiration or coverslip compression have been used to mechanically stimulate whole embryos. These approaches limit experimental design as they are imprecise, require manual handling, and can process only a couple of embryos simultaneously. Microfluidic systems have great potential for automating such experimental tasks while increasing throughput and precision. This article describes a microfluidic system developed to precisely compress whole Drosophila melanogaster (fruit fly) embryos. This system features microchannels with pneumatically actuated deformable sidewalls and enables embryo alignment, immobilization, compression, and post-stimulation collection. By parallelizing these microchannels into seven lanes, steady or dynamic compression patterns can be applied to hundreds of Drosophila embryos simultaneously. Fabricating this system on a glass coverslip facilitates the simultaneous mechanical stimulation and imaging of samples with high-resolution microscopes. Moreover, the utilization of biocompatible materials, like PDMS, and the ability to flow fluid through the system make this device capable of long-term experiments with media-dependent samples. This approach also eliminates the requirement for manual mounting which mechanically stresses samples. Furthermore, the ability to quickly collect samples from the microchannels enables post-stimulation analyses, including -omics assays which require large sample numbers unattainable using traditional mechanical stimulation approaches. The geometry of this system is readily scalable to different biological systems, enabling numerous fields to benefit from the functional features described herein including high sample throughput, mechanical stimulation or immobilization, and automated alignment.

Freeform 3D Ice Printing (3D-ICE) at the Micro Scale.

Water is one of the most important elements for life on earth. Water's rapid phase-change ability along with its environmental and biological compatibility also makes it a unique structural material for 3D printing of ice structures reproducibly and accurately. This work introduces the freeform 3D ice printing (3D-ICE) process for high-speed and reproducible fabrication of ice structures with micro-scale resolution. Drop-on-demand deposition of water onto a -35 °C platform rapidly transforms water into ice. The dimension and geometry of the structures are critically controlled by droplet ejection frequency modulation and stage motions. The freeform approach obviates layer-by-layer construction and support structures, even for overhang geometries. Complex and overhang geometries, branched hierarchical structures with smooth transitions, circular cross-sections, smooth surfaces, and micro-scale features (as small as 50 µm) are demonstrated. As a sample application, the ice templates are used as sacrificial geometries to produce resin parts with well-defined internal features. This approach could bring exciting opportunities for microfluidics, biomedical devices, soft electronics, and art.

Cell alignment modulated by surface nano-topography - Roles of cell-matrix and cell-cell interactions.

The propensity of cells to align in particular directions is relevant to a number of areas, including tissue engineering and biohybrid robotics. Cell alignment is modulated through various extracellular conditions including surface topographies, mechanical cues from cell-matrix interactions, and cell-cell interactions. Understanding of these conditions provides guidance for desirable cellular structure constructions. In this study, we examine the roles of surface topographies and cell-cell interactions in inducing cell alignment. We employed wavy surface topographies at the nanometer scale as a model extracellular environment for cell culture. The results show that, within a certain range of wavelengths and amplitudes of the surface topographies, cell alignment is dependent on cell confluency. This dependence on both topology and confluency suggests interplay between cell-cell and cell-matrix interactions in inducing cell alignment. Images of sparsely distributed and confluent cells also demonstrated clear differences in the structures of their focal adhesion complexes. To understand this effect, we introduced anti-N-cadherin to cell culture to inhibit cell-cell interactions. The results show that, when anti-N-cadherin was applied, cells on wavy surfaces required greater confluency to achieve the same alignment compared to that in the absence of anti-N-cadherin. The understanding of the cell alignment mechanisms will be important in numerous potential applications such as scaffold design, tissue repair, and development of biohybrid robotic systems. STATEMENT OF SIGNIFICANCE: Cell alignment plays a critical role in numerous biological functions. Advances in tissue engineering utilizes cell alignment to restore, maintain, or even replace different types of biological tissues. The clinical impact that tissue engineering has made is facilitated by advancements in the understanding of interactions between scaffolds, biological factors, and cells. This work further elucidates the role of cell-cell interactions in promoting the organization of biological tissues.

Inducing Vascular Grammars for Anomaly Classification in Brain Angiograms.

As machine learning is used to make strides in medical diagnostics, few methods provide heuristics from which human doctors can learn directly. This work introduces a method for leveraging human observable structures, such as macroscale vascular formations, for producing assessments of medical conditions with relatively few training cases, and uncovering patterns that are potential diagnostic aids. The approach draws on shape grammars, a rule-based technique, pioneered in design and architecture, and accelerated through a recursive subgraph mining algorithm. The distribution of rule instances in the data from which they are induced is then used as an intermediary representation enabling common classification and anomaly detection approaches to identify indicative rules with relatively small data sets. The method is applied to seven-tesla time-of-flight angiography MRI (n = 54) of human brain vasculature. The data were segmented and induced to generate representative grammar rules. Ensembles of rules were isolated to implicate vascular conditions reliably. This application demonstrates the power of automated structured intermediary representations for assessing nuanced biological form relationships, and the strength of shape grammars, in particular for identifying indicative patterns in complex vascular networks.

Investigating circular dorsal ruffles through varying substrate stiffness and mathematical modeling.

Circular dorsal ruffles (CDRs) are transient actin-rich ringlike structures that form on the dorsal surface of growth-factor stimulated cells. However, the dynamics and mechanism of formation of CDRs are still unknown. It has been observed that CDR formation leads to stress fibers disappearing near the CDRs. Because stress fiber formation can be modified by substrate stiffness, we examined the effect of substrate stiffness on CDR formation by seeding NIH 3T3 fibroblasts on glass and polydimethylsiloxane substrates of varying stiffnesses from 20 kPa to 1800 kPa. We found that increasing substrate stiffness increased the lifetime of the CDRs. We developed a mathematical model of the signaling pathways involved in CDR formation to provide insight into this lifetime and size dependence that is linked to substrate stiffness via Rac-Rho antagonism. From the model, increasing stiffness raised mDia1-nucleated stress fiber formation due to Rho activation. The increased stress fibers present increased replenishment of the G-actin pool, therefore prolonging Arp2/3-nucleated CDR formation due to Rac activation. Negative feedback by WAVE-related RacGAP on Rac explained how CDR actin propagates as an excitable wave, much like wave propagation in other excitable medium, e.g., nerve signal transmission.