Skip to main content. Diagram of the process in which a stem cell line was generated for production of cardiac cells. Process makes stem-cell-derived heart cells light up. Jamie Oberdick. Share this story. Media Contacts. Jamie Oberdick jco11 psu. Work Phone:. In addition, rapid image acquisition usually within a day is needed for PET due to the short lifetime of the radioligands. By collecting 2D images using a gamma camera, 3D images can be reconstructed based on multiple 2D scans. SPECT has very high sensitivity and the tissue penetration depth is not limited but the spatial resolution is relatively low.
The object 2-D slice can then be reconstructed through computer processing. However, the use of ionizing radiation such as X-rays to a certain extent limits the application in RM. Despite a widely used clinical imaging technology offering rapid imaging solutions in clinical environment, the application of ultrasound imaging in RM is limited, due to its low image resolution and depth. In addition to the clinical imaging technologies above, there are several other important research and pre-clinical imaging modalities for RM.
As a hybrid approach, PAI has the high contrast and good specificity offered by optical methods and the high spatial resolution and deeper penetration depth provided by the ultrasound modality. In RM PAI, gold nanoparticles used to label stem cells, can be tuned to have strong plasmon resonance at the excitation wavelengths to enhance the photoacoustic signal.
Although in most applications OCT is used as a label-free imaging technology, for stem cell research, the application of OCT relies on exogenous contrast agents such as magnetic and iron oxide particles, proteins, dyes, and nanomaterials to enhance the detection sensitivity to molecular level. BLI is a low-cost approach offering both high signal-to-noise ration and sensitivity, and has been widely used in small animal studies.
The applications of BLI include tracking hematopoietic stem cell engraftment and assessing stem cell types. However, the strong scattering and absorption of the tissue limits the penetration depth of BLI. The fluorescence image can be acquired by collecting the fluorescence emissions from the fluorophores. Similar to BLI, the penetration depth of fluorescence imaging is limited as a result of the strong absorption and scattering of the fluorescent light by the mammalian tissues. For the in vivo imaging technologies reviewed above, to some extent, they are limited by a number of factors, such as the radiation hazard, the imaging depth limited by the tissue absorption and scattering, and reduced cell tracking time.
These limitations result in low sensitivity and specificity, and limited ability to monitor cell changes and therapy progresses over time. Multimodality imaging is one promising direction to address such challenges, which combines multiple imaging methods to achieve an improved imaging performance [ ].
For example, high-sensitivity and low-resolution methods such as PET can be used together with MRI to improve the image resolutions. For imaging modalities with a low penetration depth such as fluorescence imaging and PLI, one possible solution is to use implantable endoscopic imaging probes that can send down excitation light sources and at the same time to collect fluorescence emission from the fluorophores [ , , ].
Alternatively, implantable imaging sensors can be embedded in the tissue or organ to collect real-time images and communicate with an external device through wireless signals [ , ]. It is foreseeable that in vivo imaging will play an important role in future RM and may be performed routinely in clinical stem cell therapies throughout the course of treatment.
This section discusses recent opportunities that could make computational and mathematical modeling an important pillar of future RM research. It is worthwhile to first emphasize why computational and mathematical modeling is important in the field of RM. Regenerating organs requires the ability to recreate a suitable physical and biochemical environment for the cells to grow. Elements of such environment include the mechanical and geometric properties of the growth substrate, the transport properties determining the rate at which nutrients and oxygen are supplied, and waste removed, and the level of mechanical load and fluid shear [ , , ].
Without the framework provided by mathematical models, it would neither be possible to quantify and predict these properties nor to establish a link between macroscopic variables—which can be observed and controlled in an experiment—and microscopic variables that affect cell fate directly. From: Zhao F, et al. Biomechanics and Modeling in Mechanobiology.
Materials Science and Engineering: C. Reproduced from: Genzer J, Groenewold J. Reprinted from: Li B, et al. Journal of the Mechanics and Physics of Solids. Today, purely mechanical phenomena related to bioengineering scaffolds can be simulated accurately. The wide availability of software to convert CT scans into a computer mesh e. The challenge that will probably occupy computational scientists in the future is the development—and validation against experiments—of suitable models for cell growth, mobility and interaction [ , , ].
Two opportunities have emerged recently which could spur innovation in the development of substrates for cell growth and models of cell behavior. One is the growth of the discipline of soft matter physics and engineering. Such discipline, which is uniquely fitted to describe the fragile and water-filled structures where cells thrive, seeks to establish the physical principles governing the behavior of materials formed by soft macromolecular and colloidal elements, including the coupling of deformation mechanics, chemical reactions, fluid flow, physicochemical effects such as swelling, phase change, etc.
A recent example where soft matter has produced important results is the development of surface micro-patterning technique to promote cell colonization. Lithographic techniques can produce geometric features with exquisite control over microstructural geometry. However, deploying these techniques to produce cheaply and on large-scales surface micropatterns on practical scaffolds is a major challenge e. Fluidic phenomena and capillarity could offer an alternative route to micro-patterning.
For example, the capillary forces produced by evaporating liquid films can produce remarkably regular patterns in fiber mats Fig. The geometry of these patterns can be accurately predicted based on the theory of elasto-capillary coalescence, which has been the subject of increasing interest by the soft matter community recently [ ].
Patterning through wrinkling Fig. Such theories enable to predict the wavelength of the wrinkles with extraordinary precision, enabling for instance to design the spacing and stiffness of protrusion where cells can anchor themselves. A second opportunity is the realization of the importance of algorithmic mining of data as a predictive engineering tool in various areas of bioengineering [ , ].
Data analysis is not a new discipline. What is new is the availability of inexpensive sensors pressure, concentration, optical signals, etc. For example, one could conceive devices in which algorithms analyze multi-point data of cell motility from different positions in a cell monolayer and relate these to perfusion data extracted from simulations.
We believe that the convergence of cheap and robust sensing and imaging technologies, big data techniques, and physics-based computations could bring a new level of understanding of the complexity inherent in RM constructs, particularly in situations in which purely deterministic approaches have failed to provide sufficiently accurate predictive capabilities. Novel bioengineering technologies are redefining how we view and tackle key challenges in RM.
We have provided a general overview of five dynamic and increasingly evolving areas that are shaping the next generation of RM therapies aiming to provide more selective cell-material interactions, higher precision, faster monitoring, more selective delivery, and more accurate predictions. Throughout these different areas, a general theme is the continuous push to improve precision, sensitivity, and selectivity; which are bringing us closer to the development of personalized RM.
Alvaro Mata, Helena S. This article does not contain any studies with human or animal subjects performed by any of the authors. Skip to main content Skip to sections. Advertisement Hide. Download PDF. Open Access. First Online: 04 May Part of the following topical collections: Topical Collection on Artificial Tissues. Purpose of Review In this review, we provide a general overview of recent bioengineering breakthroughs and enabling tools that are transforming the field of regenerative medicine RM. Recent Findings Mechanobiology plays an increasingly important role in tissue regeneration and design of therapies.
Summary We have found that the development of these areas is not only leading to revolutionary technological advances but also enabling a conceptual leap focused on targeting regenerative strategies in a holistic manner. Introduction The increasing integration of traditional scientific disciplines such as materials science, chemistry, and biology and the emergence of research fields like synthetic biology, supramolecular chemistry, or mechanobiology continue to expand the field of bioengineering.
Today, the field of bioengineering is a testament to the possibilities of interdisciplinary research. Regenerative medicine RM is a particularly interesting target for the development and application of novel bioengineering solutions. The inherent biological and molecular complexity, multi-scale organizations, and spatio-temporal features of regenerative processes can be tackled through an ensemble of technological angles.
For example, most regenerative challenges can now be tackled through a holistic understanding of biological events, molecular design, selective monitoring or sensing, and the capacity to numerically simulate events to predict or optimize performance. This cooperative strategy is resulting in ever more integrated therapeutic approaches that are redefining the traditional view of implants, devices, drugs, or biomaterials. In this review, we attempt to provide a general overview of work being conducted in recent years in five key complementary areas of bioengineering including: mechanobiology, biomaterials and scaffolds, intracellular delivery, sensing and imaging, and computational and mathematical modeling Fig.
Open image in new window. A major goal in RM is the capacity to stimulate biological responses with temporal and spatial control while exhibiting functional physical properties. With this in mind, Yu et al. Material coatings can also provide such tissue-compatibility. For example, thin flexible perfluorocarbon layers have been developed to prevent thrombosis and formation of bacterial layers [ 36 ]. Functionality may also be enhanced not only by the properties of individual materials, but on their synergistic effect.
A strong and tough hydrogel, a major biomaterial challenge, has been developed using an interpenetrating polymer network that interacts at the molecular scale to combine stiffness and brittleness with softness and elasticity [ 37 ]. Another example integrates modified tropoelastin and graphene oxide to create a hydrogel with both enhanced mechanical properties and conductivity with potential use in muscle regeneration applications [ 38 ].
Designing at the molecular scale, using for example recombinant technologies, facilitates the integration of mechanical properties and biomolecular signaling. For example, Tejeda-Montes et al. Molecular design enables a wide variety of biomolecular signaling relevant to tissue regeneration including for example regulation of the immune system [ 42 ], presentation of bioactive peptides [ 43 ], growth factor mimetics [ 44 ], or tuneable degradation [ 45 ].
Osteoporosis drugs typically inhibit bone resorption, preventing bone loss, but they also slowdown the process of bone formation osteogenesis. Using cationic liposomes functionalized with a peptide known to bind to calcified tissues of lower crystallinity, Zhang and co-workers were able to deliver small interference RNAs siRNAs specifically to bone-forming surfaces lower crystallinity in vivo [ 87 ]. By silencing the Plekho1 gene, that encodes a protein known to be a negative regulator of bone formation [ 88 ], they were able to stimulate bone formation.
In vivo studies using osteopenic rats low bone mineral density showed enhanced bone formation with improved microarchitecture when rats were treated with CH6-siRNA-LNPs Fig. By selectively stimulating bone formation without promoting bone resorption, this therapy holds promise to treat osteoporosis.
However, further experiments are required to investigate possible off-target effects of this delivery strategy and determine the duration of the silencing effect. Imaging technologies offer a number of new opportunities in RM, for example, in the assessment of the tissue composition of organs, in transplanted cells monitoring or in cell therapy evaluation.
In this section, we will present an overview of the state-of-the-art imaging technologies in stem cell research and RM with the emphasis placed on in vivo imaging technologies that are currently being used or are likely to be adopted in clinical cell therapies Fig. An example of this link is offered by the development of bioengineering scaffolds.
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While the ambient concentration of oxygen and nutrient can be easily controlled in experiment, and the average flow rate permeating through the scaffold adjusted, the local perfusion and shear stress level experienced by each cell will depend on the microscopic geometry of the scaffold, as well as the nutrient utilization by surrounding cells [ ].
This coupled transport-mechanics phenomenon is impossible to disentangle by simple mechanicistic arguments. However, it lends itself perfectly to computer implementations Fig. Validated simulations can offer insights, and be used to establish engineering correlations, by for example, providing the local transport environment experienced by each single cell as a function of flow rate and ambient concentration. Human and Animal Rights and Informed Consent This article does not contain any studies with human or animal subjects performed by any of the authors. Matrix elasticity directs stem cell lineage specification.
Extracellular-matrix tethering regulates stem-cell fate. Interplay of matrix stiffness and protein tethering in stem cell differentiation. Mechanical regulation of cell function with geometrically modulated elastomeric substrates. Nat Methods. Degradation-mediated cellular traction directs stem cell fate in covalently crosslinked three-dimensional hydrogels.
Effect of cyclic mechanical stimulation on the expression of osteogenesis genes in human intraoral mesenchymal stromal and progenitor cells. Biomed Res Int. CrossRef Google Scholar. Chondrogenesis of periodontal ligament stem cells by transforming growth factor-[bgr]3 and bone morphogenetic protein-6 in a normal healthy impacted third molar. In J Oral Sci. Directed stem cell differentiation by fluid mechanical forces. Antioxid Redox Signal. Hydrostatic pressure-driven three-dimensional cartilage induction using human adipose-derived stem cells and collagen gels. Tissue Eng A.
Google Scholar. Dynamic compression stimulates proteoglycan synthesis by mesenchymal stem cells in the absence of chondrogenic cytokines. Geometric cues for directing the differentiation of mesenchymal stem cells. Actin and serum response factor transduce physical cues from the microenvironment to regulate epidermal stem cell fate decisions. Nat Cell Biol. J Cell Sci. Effect of cell anisotropy on differentiation of stem cells on micropatterned surfaces through the controlled single cell adhesion. Cell shape, cytoskeletal tension, and RhoA regulate stem cell lineage commitment.
Dev Cell. Cytoskeletal disassembly and cell rounding promotes adipogenesis from ES cells. Stem Cell Rev. Reevaluation of in vitro differentiation protocols for bone marrow stromal cells: disruption of actin cytoskeleton induces rapid morphological changes and mimics neuronal phenotype. J Neurosci Res. Adipogenesis of adipose-derived stem cells may be regulated via the cytoskeleton at physiological oxygen levels in vitro. Stem Cell Res Ther. Nuclear lamin-A scales with tissue stiffness and enhances matrix-directed differentiation.
Science New York, NY. Cytoskeletal to nuclear strain transfer regulates YAP signaling in mesenchymal stem cells. Biophys J. Substrate elasticity provides mechanical signals for the expansion of hemopoietic stem and progenitor cells. Nat Biotechnol. Stiffness of photocrosslinked RGD-alginate gels regulates adipose progenitor cell behavior.
Biotechnol Bioeng. Soft substrates promote homogeneous self-renewal of embryonic stem cells via downregulating cell-matrix tractions. PLoS One. Substrate modulus directs neural stem cell behavior.
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Matrix elasticity of void-forming hydrogels controls transplanted-stem-cell-mediated bone formation. Hydrogels with tunable stress relaxation regulate stem cell fate and activity. Biophysical regulation of chromatin architecture instills a mechanical memory in mesenchymal stem cells. Sci Rep.
Functional supramolecular polymers. Diffusive silicon nanopore membranes for hemodialysis applications. An elastic second skin. Designer matrices for intestinal stem cell and organoid culture. Tunable supramolecular hydrogels for selection of lineage-guiding metabolites in stem cell cultures.
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Co-assembly, spatiotemporal control and morphogenesis of a hybrid protein—peptide system. A bioinspired omniphobic surface coating on medical devices prevents thrombosis and biofouling. Toughening elastomers with sacrificial bonds and watching them break. Highly elastic and conductive human-based protein hybrid Hydrogels. Adv Mater. Engineering membrane scaffolds with both physical and biomolecular signaling.
Cole A. Therefore, the DeForest Group seeks to integrate the governing principles of rational design with fundamental concepts from material science, synthetic chemistry, and stem cell biology to conceptualize, create, and exploit next-generation materials to address a variety of health-related problems.
We are currently interested in the development of new classes of user-programmable hydrogels whose biochemical and biophysical properties can be tuned in time and space over a variety of scales.
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Our work relies heavily on the utilization of cytocompatible bioorthogonal chemistries, several of which can be initiated with light and thereby confined to specific sub-volumes of a sample. By recapitulating the dynamic nature of the native tissue through 4D control of the material properties, these synthetic environments are utilized to probe and better understand basic cell function as well as to engineer complex heterogeneous tissue. In addition, we have generated hPSC lines carrying naturally occurring or engineered mutations relevant to human kidney diseases, such as polycystic kidney disease and nephrotic syndrome.
The goal of our research is to use these new tools to model human kidney disease and identify therapeutic approaches, including kidney regeneration. Daniel G.