Bioengineered Vascular Model of Foam Cell Formation.

Foam cell formation is a complex blood vessel pathology, which is characterized by a series of events, including endothelium dysfunction, inflammation, and accumulation of immune cells underneath the blood vessel walls. Novel bioengineered models capable of recapitulating these events are required to better understand the complex pathological processes underlying the development of foam cell formation and, consequently, advanced bioengineered platforms for screening drugs. Here, we generated a microfluidic blood vessel model, incorporating a three-dimensional (3D) extracellular matrix coated with an endothelial layer. This system enables us to perform experiments under a dynamic microenvironment that recapitulates the complexities of the native vascular regions. Using this model, we studied the effectors that regulate monocyte adhesion and migration, as well as foam cell formation inside vessel walls. We found that monocyte adhesion and migration are regulated by both the endothelium and monocytes themselves. Monocytes migrated into the extracellular matrix only when endothelial cells were cultured in the vessel model. In addition, the exposure of an endothelial layer to tumor necrosis factor α (TNF-α) and low shear stress both increased monocyte migration into the subendothelial space toward the matrix. Furthermore, we demonstrated the process of foam cell formation, 3 days after transmigration of peripheral blood mononuclear cells (PBMCs) into the vessel wall. We showed that pre-exposure of PBMCs to high shear rates increases their adhesion and migration through the TNF-α-treated endothelium but does not affect their capacity to form foam cells. The versatility of our model allows for mechanistic studies on foam cell formation under customized pathological conditions.

Evaluation of quantitative biomarkers of aging in human PBMCs.

Functional decline with age contributes significantly to the burden of disease in developed countries. There is growing interest in the development of therapeutic interventions which slow or even reverse aging. Time and cost constraints prohibit the testing of a large number of interventions for health and lifespan extension in model organisms. Cell-based models of aging could enable high throughput testing of potential interventions. Despite extensive reports in the literature of cell properties that correlate with donor age, few are robustly observed across different laboratories. This casts doubt on the extent that aging signatures are captured in cultured cells. We tested molecular changes previously reported to correlate with donor age in peripheral blood mononuclear cells (PBMCs) and evaluated their suitability for inclusion in a panel of functional aging measures. The tested measures spanned several pathways implicated in aging including epigenetic changes, apoptosis, proteostasis, and intracellular communication. Surprisingly, only two markers correlated with donor age. DNA methylation age accurately predicted donor age confirming this is a robust aging biomarker. Additionally, the apoptotic marker CD95 correlated with donor age but only within subsets of PBMCs. To demonstrate cellular rejuvenation in response to a treatment will require integration of multiple read-outs of cell function. However, building a panel of measures to detect aging in cells is challenging and further research is needed to identify robust predictors of age in humans.

Magnetic resonance imaging RAMRIS-SAFE score-A low-risk effective measure of rapid response to therapy in rheumatoid arthritis clinical trials.

AIM: To assess the rapidity of magnetic resonance imaging (MRI) measured synovitis (as measured by synovial thickening using the RAMRIS-SAFE score) and bone edema in active rheumatoid arthritis (RA) subjects treated with golimumab. Secondary aims: to correlate MRI measures with disabilities of the arm, shoulder, and hand (DASH), physician global (PhysG) and patient global (PatG) assessments. METHODS: Patients with active RA and inadequate response to methotrexate were recruited. Active RA was defined as RA with a Disease Activity Score of 28 joints - C-reactive protein ≥4.2 at screening AND active disease (synovitis and edema) of the chosen hand or wrist on MRI at screening, as determined by the central blinded MRI reader (PB). Outcomes measures were assessed at baseline, 2, 6, and 12 weeks. MRI results were interpreted by one experienced observer (PB), blinded to clinical measures. Pearson's correlation co-efficient (SPSS) was used to express the relationship between DASH, PhysG, PatG and MRI measures. RESULTS: Eighteen patients were included in the study. All subjects completed follow-up visits and MRI assessment. Mean age was 60.6 years (range 22-72), and 10 were female, 8 male, and disease duration was mean 4.72 years (range 1-28); all patients were taking background methotrexate. The changes in MRI synovial volume were evident by visit 2. The strongest correlations with the DASH for MRI parameters were total synovial thickening (0.923) and edema (0.921). CONCLUSION: Golimumab was associated with rapid improvement in clinical measures and patient-reported outcome measures. Mean synovial thickening demonstrated early rapid improvement. MRI synovial thickening demonstrated a strong correlation with DASH, PatG and PhysG.

Recent developments in modeling, imaging, and monitoring of cardiovascular diseases using machine learning.

Cardiovascular diseases are the leading cause of mortality, morbidity, and hospitalization around the world. Recent technological advances have facilitated analyzing, visualizing, and monitoring cardiovascular diseases using emerging computational fluid dynamics, blood flow imaging, and wearable sensing technologies. Yet, computational cost, limited spatiotemporal resolution, and obstacles for thorough data analysis have hindered the utility of such techniques to curb cardiovascular diseases. We herein discuss how leveraging machine learning techniques, and in particular deep learning methods, could overcome these limitations and offer promise for translation. We discuss the remarkable capacity of recently developed machine learning techniques to accelerate flow modeling, enhance the resolution while reduce the noise and scanning time of current blood flow imaging techniques, and accurate detection of cardiovascular diseases using a plethora of data collected by wearable sensors.

Dynamic Vortex Generation, Pulsed Injection, and Rapid Mixing of Blood Samples in Microfluidics Using the Tube Oscillation Mechanism.

Here, we describe the generation of dynamic vortices in micro-scale cavities at low flow rates. The system utilizes a computer-controlled audio speaker to axially oscillate the inlet tube of the microfluidic system at desired frequencies and amplitudes. The oscillation of the tube induces transiently high flow rates in the system, which facilitates the generation of dynamic vortices inside the cavity. The size of the vortices can be modulated by varying the tube oscillation frequency or amplitude. The vortices can be generated in single or serial cavities and in a wide range of cavity sizes. We demonstrate the suitability of the tube oscillation mechanism for the pulsed injection of water-based solutions or whole blood into the cavity. The injection rate can be controlled by the oscillation characteristics of the tube, enabling the injection of liquids at ultralow flow rates. The dynamic vortices facilitate the rapid mixing of the injected liquid with the main flow. The controllability and versatility of this technology allow for the development of programmable inertial microfluidic systems for performing multistep biological assays.

Studying the Synergistic Effect of Substrate Stiffness and Cyclic Stretch Level on Endothelial Cells Using an Elastomeric Cell Culture Chamber.

Endothelial cells lining blood vessels are continuously exposed to biophysical cues that regulate their function in health and disease. As we age, blood vessels lose their elasticity and become stiffer. Vessel stiffness alters the mechanical forces that endothelial cells experience. Despite ample evidence on the contribution of endothelial cells to vessel stiffness, less is known about how vessel stiffness affects endothelial cells. In this study, we developed a versatile model to study the cooperative effect of substrate stiffness and cyclic stretch on human aortic endothelial cells. We cultured endothelial cells on elastomeric wells covered with fibronectin-coated polyacrylamide gel. Varying the concentrations of acrylamide and bis-acrylamide enabled us to produce soft and stiff substrates with elastic modules of 40 and 200 kPa, respectively. Using a customized three-dimensional (3D) printed cam-driven system, the cells were exposed to 5 and 10% cyclic stretch levels. This enabled us to mimic the stiffness and stretch levels that endothelial cells experience in young and aged arteries. Using this model, we found that endothelial cells cultured on a soft substrate had minimal cytoskeletal alignment to the direction of the stretch compared to the ones cultured on the stiff substrate. We also observed an increase in the cellular area and aspect ratio in cells cultured on the stiff substrate, both of which are positively regulated by cyclic stretch. However, neither cyclic stretch nor substrate stiffness significantly affected the nuclear circularity. Additionally, we found that the accumulation of NF-κB in the nucleus, endothelial proliferation, tube formation, and expression of IL1ß depends on the stretch level and substrate stiffness. Our model can be further used to investigate the complex signaling pathways associated with vessel stiffening that govern the endothelial responses to mechanical forces.

Generation of dynamic vortices in a microfluidic system incorporating stenosis barrier by tube oscillation.

Microfluidic systems incorporating sudden expansions are widely used for generation of vortex flow patterns. However, the formation of vortices requires high flow rates to induce inertial effects. Here, we introduce a new method for generating dynamic vortices in microfluidics at low static flow rates. Human blood is driven through a microfluidic channel incorporating a semi-circular stenosis barrier. The inlet tube of the channel is axially oscillated using a computer-controlled audio-speaker. The tube oscillation induces high transient flow rates in the channel, which generates dynamic vortices across the stenosis barrier. The size of the vortices can be modulated by varying the frequency and amplitude of tube oscillation. Various vortex flow patterns can be generated by varying the flow rate. The formation and size of the vortices can be predicted using the Reynolds number of the oscillating tube. We demonstrate the potential application of the system for investigating the adhesion and phagocytosis of circulating immune cells under pathologically high shear rates induced at the stenosis. This approach facilitates the development of versatile and controllable inertial microfluidic systems for performing various cellular assays while operating at low static flow rates and low sample volumes.

Studying the Mechanobiology of Aortic Endothelial Cells Under Cyclic Stretch Using a Modular 3D Printed System.

Here, we describe a motorized cam-driven system for the cyclic stretch of aortic endothelial cells. Our modular design allows for generating customized spatiotemporal stretch profiles by varying the profile and size of 3D printed cam and follower elements. The system is controllable, compact, inexpensive, and amenable for parallelization and long-term experiments. Experiments using human aortic endothelial cells show significant changes in the cytoskeletal structure and morphology of cells following exposure to 5 and 10% cyclic stretch over 9 and 16 h. The system provides upportunities for exploring the complex molecular and cellular processes governing the response of mechanosensitive cells under cyclic stretch.

Reconfigurable, Self-Sufficient Convective Heat Exchanger for Temperature Control of Microfluidic Systems.

Here, we demonstrate a modular, reconfigurable, and self-sufficient convective heat exchanger for regulation of temperature in microfluidic systems. The heat exchanger consists of polymer tubes wrapped around a plastic pole and fully embedded in an elastomer block, which can be easily mounted onto the microfluidic structure. It is compatible with various microfluidic geometries and materials. Miniaturized, battery-powered piezoelectric pumps are utilized to drive the heat carrying liquid through the heat exchanger at desired flow rates and temperatures. Customized temperature profiles can be generated by changing the configuration of the heat exchanger with respect to the microfluidic structure. Tailored dynamic temperature profiles can be generated by changing the temperature of the heat carrying liquid in successive cycles. This feature is used to study the calcium signaling of endothelial cells under successive temperature cycles of 24 to 37 °C. The versatility, simplicity, and self-sufficiency of the heat exchanger makes it suitable for various microfluidic based cellular assays.

Toward priorities for aging research.

The global population is aging, and although age remains the primary risk factor for all major causes of death, no priorities for aging research exist. After reviewing the literature on mortality modeling, we found that different chronic processes underlie mortality before and after reproductive age. To identify priorities in aging research, we propose a simple ranking method that uses the percentage of deaths attributable to each disease for the over 60 population on the basis that, rather than being the result of individual risk factors, these deaths are largely due to underlying senescent processes. Our ranking suggests that vascular aging, led by ischemic heart disease and stroke, is the most important focus for aging research. The availability of funding, however, is not currently aligned with health priorities, and we believe that rectifying this disconnect may improve societal health outcomes.