Annual Review of Biomedical Engineering最新文献

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 versatile fabrication methods used to develop multifunctional controlled drug release coatings. The numerous advantages of LbL include its ability to incorporate and preserve biological activity of therapeutic agents; coat multiple substrates of all scales (e.g., nanoparticles to implants); and exhibit tuned, targeted, and/or responsive drug release behavior. The functional behavior of LbL films can be related to their physicochemical properties. In this review, we highlight recent advances in the development of LbL-engineered biomaterials for drug delivery, demonstrating their potential in the fields of cancer therapy, microbial infection prevention and treatment, and directing cellular responses. We discuss the various advantages of LbL biomaterial design for a given application as demonstrated through in vitro and in vivo studies.

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.

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.

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.

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.

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.

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.

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.

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, metabolic disease, and diabetes has prompted the focus on these diseases in this review. We highlight the remarkable similarity between Ossabaw miniature swine and humans with metabolic syndrome and atherosclerosis. Although the evidence is strongest for swine models of coronary artery disease, findings are generally applicable to any vascular bed. We discuss the major strengths and weaknesses of swine models. The development of vascular imaging is an example of optimal vascular engineering in swine. Although challenges regarding infrastructure and training of engineers in the use of swine models exist, opportunities are ripe for gene editing, studies of molecular mechanisms, and use of swine in coronary artery imaging and testing of devices that can move quickly to human clinical studies.