Showing papers in "Annual Review of Biomedical Engineering in 2020"

Elastin-Like Polypeptides for Biomedical Applications.

Abstract: Elastin-like polypeptides (ELPs) are stimulus-responsive biopolymers derived from human elastin. Their unique properties-including lower critical solution temperature phase behavior and minimal immunogenicity-make them attractive materials for a variety of biomedical applications. ELPs also benefit from recombinant synthesis and genetically encoded design; these enable control over the molecular weight and precise incorporation of peptides and pharmacological agents into the sequence. Because their size and sequence are defined, ELPs benefit from exquisite control over their structure and function, qualities that cannot be matched by synthetic polymers. As such, ELPs have been engineered to assemble into unique architectures and display bioactive agents for a variety of applications. This review discusses the design and representative biomedical applications of ELPs, focusing primarily on their use in tissue engineering and drug delivery.

Layer-by-Layer Biomaterials for Drug Delivery.

Abstract: Controlled drug delivery formulations have revolutionized treatments for a range of health conditions. Over decades of innovation, layer-by-layer (LbL) self-assembly has emerged as one of the most ...

4D Flow with MRI

Abstract: Magnetic resonance imaging (MRI) has become an important tool for the clinical evaluation of patients with cardiac and vascular diseases. Since its introduction in the late 1980s, quantitative flow imaging with MRI has become a routine part of standard-of-care cardiothoracic and vascular MRI for the assessment of pathological changes in blood flow in patients with cardiovascular disease. More recently, time-resolved flow imaging with velocity encoding along all three flow directions and three-dimensional (3D) anatomic coverage (4D flow MRI) has been developed and applied to enable comprehensive 3D visualization and quantification of hemodynamics throughout the human circulatory system. This article provides an overview of the use of 4D flow applications in different cardiac and vascular regions in the human circulatory system, with a focus on using 4D flow MRI in cardiothoracic and cerebrovascular diseases.

The New Age of Cell-Free Biology.

Abstract: The cell-free molecular synthesis of biochemical systems is a rapidly growing field of research. Advances in the Human Genome Project, DNA synthesis, and other technologies have allowed the in vitro construction of biochemical systems, termed cell-free biology, to emerge as an exciting domain of bioengineering. Cell-free biology ranges from the molecular to the cell-population scales, using an ever-expanding variety of experimental platforms and toolboxes. In this review, we discuss the ongoing efforts undertaken in the three major classes of cell-free biology methodologies, namely protein-based, nucleic acids-based, and cell-free transcription-translation systems, and provide our perspectives on the current challenges as well as the major goals in each of the subfields.

Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology.

Abstract: Central nervous system (CNS) tumors come with vastly heterogeneous histologic, molecular, and radiographic landscapes, rendering their precise characterization challenging. The rapidly growing fields of biophysical modeling and radiomics have shown promise in better characterizing the molecular, spatial, and temporal heterogeneity of tumors. Integrative analysis of CNS tumors, including clinically acquired multi-parametric magnetic resonance imaging (mpMRI) and the inverse problem of calibrating biophysical models to mpMRI data, assists in identifying macroscopic quantifiable tumor patterns of invasion and proliferation, potentially leading to improved (a) detection/segmentation of tumor subregions and (b) computer-aided diagnostic/prognostic/predictive modeling. This article presents a summary of (a) biophysical growth modeling and simulation,(b) inverse problems for model calibration, (c) these models' integration with imaging workflows, and (d) their application to clinically relevant studies. We anticipate that such quantitative integrative analysis may even be beneficial in a future revision of the World Health Organization (WHO) classification for CNS tumors, ultimately improving patient survival prospects.

Hemodynamics of Cerebral Aneurysms: Connecting Medical Imaging and Biomechanical Analysis.

Abstract: In the last two decades, numerous studies have conducted patient-specific computations of blood flow dynamics in cerebral aneurysms and reported correlations between various hemodynamic metrics and aneurysmal disease progression or treatment outcomes. Nevertheless, intra-aneurysmal flow analysis has not been adopted in current clinical practice, and hemodynamic factors usually are not considered in clinical decision making. This review presents the state of the art in cerebral aneurysm imaging and image-based modeling, discussing the advantages and limitations of each approach and focusing on the translational value of hemodynamic analysis. Combining imaging and modeling data obtained from different flow modalities can improve the accuracy and fidelity of resulting velocity fields and flow-derived factors that are thought to affect aneurysmal disease progression. It is expected that predictive models utilizing hemodynamic factors in combination with patient medical history and morphological data will outperform current risk scores and treatment guidelines. Possible future directions include novel approaches enabling data assimilation and multimodality analysis of cerebral aneurysm hemodynamics.

Computer-Aided Design of Microfluidic Circuits.

Abstract: Microfluidic devices developed over the past decade feature greater intricacy, increased performance requirements, new materials, and innovative fabrication methods. Consequentially, new algorithmic and design approaches have been developed to introduce optimization and computer-aided design to microfluidic circuits: from conceptualization to specification, synthesis, realization, and refinement. The field includes the development of new description languages, optimization methods, benchmarks, and integrated design tools. Here, recent advancements are reviewed in the computer-aided design of flow-, droplet-, and paper-based microfluidics. A case study of the design of resistive microfluidic networks is discussed in detail. The review concludes with perspectives on the future of computer-aided microfluidics design, including the introduction of cloud computing, machine learning, new ideation processes, and hybrid optimization.

Three-Dimensional Single-Molecule Localization Microscopy in Whole-Cell and Tissue Specimens.

Abstract: Super-resolution microscopy techniques are versatile and powerful tools for visualizing organelle structures, interactions, and protein functions in biomedical research. However, whole-cell and tissue specimens challenge the achievable resolution and depth of nanoscopy methods. We focus on three-dimensional single-molecule localization microscopy and review some of the major roadblocks and developing solutions to resolving thick volumes of cells and tissues at the nanoscale in three dimensions. These challenges include background fluorescence, system- and sample-induced aberrations, and information carried by photons, as well as drift correction, volume reconstruction, and photobleaching mitigation. We also highlight examples of innovations that have demonstrated significant breakthroughs in addressing the abovementioned challenges together with their core concepts as well as their trade-offs.

Point-of-Care Devices to Detect Zika and Other Emerging Viruses.

Abstract: Rapid diagnostic tests (point-of-care devices) are critical components of informed patient care and public health monitoring (surveillance applications). We propose that among the many rapid diagnostics platforms that have been tested or are in development, lateral flow immunoassays and synthetic biology-based diagnostics (including CRISPR-based diagnostics) represent the best overall options given their ease of use, scalability for manufacturing, sensitivity, and specificity. This review describes the identification of lateral flow immunoassay monoclonal antibody pairs that detect and distinguish between closely related pathogens and that are used in combination with functionalized multicolored nanoparticles and computational methods to deconvolute data. We also highlight the promise of synthetic biology-based diagnostic tests, which use synthetic genetic circuits that activate upon recognition of a pathogen-associated nucleic acid sequence, and discuss how the combined or parallel use of lateral flow immunoassays and synthetic biology tools may represent the future of scalable rapid diagnostics.

Swine Disease Models for Optimal Vascular Engineering

Abstract: Swine disease models are essential for mimicry of human metabolic and vascular pathophysiology, thereby enabling high-fidelity translation to human medicine. The worldwide epidemic of obesity, meta...

Transgenic and Diet-Enhanced Silk Production for Reinforced Biomaterials: A Metamaterial Perspective.

Abstract: Silk fibers, which are protein-based biopolymers produced by spiders and silkworms, are fascinating biomaterials that have been extensively studied for numerous biomedical applications. Silk fibers often have remarkable physical and biological properties that typical synthetic materials do not exhibit. These attributes have prompted a wide variety of silk research, including genetic engineering, biotechnological synthesis, and bioinspired fiber spinning, to produce silk proteins on a large scale and to further enhance their properties. In this review, we describe the basic properties of spider silk and silkworm silk and the important production methods for silk proteins. We discuss recent advances in reinforced silk using silkworm transgenesis and functional additive diets with a focus on biomedical applications. We also explain that reinforced silk has an analogy with metamaterials such that user-designed atypical responses can be engineered beyond what naturally occurring materials offer. These insights into reinforced silk can guide better engineering of superior synthetic biomaterials and lead to discoveries of unexplored biological and medical applications of silk.

Mitigating the Consequences of Subconcussive Head Injuries.

Abstract: Subconcussive head injury represents a pathophysiology that spans the expertise of both clinical neurology and biomechanical engineering. From both viewpoints, the terms injury and damage, presented without qualifiers, are synonymously taken to mean a tissue alteration that may be recoverable. For clinicians, concussion is evolving from a purely clinical diagnosis to one that requires objective measurement, to be achieved by biomedical engineers. Subconcussive injury is defined as subclinical pathophysiology in which underlying cellular- or tissue-level damage (here, to the brain) is not severe enough to present readily observable symptoms. Our concern is not whether an individual has a (clinically diagnosed) concussion, but rather, how much accumulative damage an individual can tolerate before they will experience long-term deficit(s) in neurological health. This concern leads us to look for the history of damage-inducing events, while evaluating multiple approaches for avoiding injury through reduction or prevention of the associated mechanically induced damage.

Micromechanobiology: Focusing on the Cardiac Cell–Substrate Interface

Abstract: Engineered, in vitro cardiac cell and tissue systems provide test beds for the study of cardiac development, cellular disease processes, and drug responses in a dish. Much effort has focused on improving the structure and function of engineered cardiomyocytes and heart tissues. However, these parameters depend critically on signaling through the cellular microenvironment in terms of ligand composition, matrix stiffness, and substrate mechanical properties-that is, matrix micromechanobiology. To facilitate improvements to in vitro microenvironment design, we review how cardiomyocytes and their microenvironment change during development and disease in terms of integrin expression and extracellular matrix (ECM) composition. We also discuss strategies used to bind proteins to common mechanobiology platforms and describe important differences in binding strength to the substrate. Finally, we review example biomaterial approaches designed to support and probe cell-ECM interactions of cardiomyocytes in vitro, as well as open questions and challenges.

Physiological Modeling and Simulation-Validation, Credibility, and Application.

Abstract: In this review, we discuss the science of model validation as it applies to physiological modeling. There is widespread disagreement and ambiguity about what constitutes model validity. In areas in which models affect real-world decision-making, including within the clinic, in regulatory science, or in the design and engineering of novel therapeutics, this question is of critical importance. Without an answer, it impairs the usefulness of models and casts a shadow over model credibility in all domains. To address this question, we examine the use of nonmathematical models in physiological research, in medical practice, and in engineering to see how models in other domains are used and accepted. We reflect on historic physiological models and how they have been presented to the scientific community. Finally, we look at various validation frameworks that have been proposed as potential solutions during the past decade.

Engineering Approaches for Addressing Opioid Use Disorder in the Community

Abstract: Many communities in the United States are struggling to deal with the negative consequences of illicit opioid use. Effectively addressing this epidemic requires the coordination and support of community stakeholders in a change process with common goals and objectives, continuous engagement with individuals with opioid use disorder (OUD) through their treatment and recovery journeys, application of systems engineering principles to drive process change and sustain it, and use of a formal evaluation process to support a learning community that continuously adapts. This review presents strategies to improve OUD treatment and recovery with a focus on engineering approaches grounded in systems thinking.

Sparse Data-Driven Learning for Effective and Efficient Biomedical Image Segmentation.

Abstract: Sparsity is a powerful concept to exploit for high-dimensional machine learning and associated representational and computational efficiency. Sparsity is well suited for medical image segmentation. We present a selection of techniques that incorporate sparsity, including strategies based on dictionary learning and deep learning, that are aimed at medical image segmentation and related quantification.