Levi B. Wood

Ensemble analysis of angiogenic growth in three-dimensional microfluidic cell cultures.

We demonstrate ensemble three-dimensional cell cultures and quantitative analysis of angiogenic growth from uniform endothelial monolayers. Our approach combines two key elements: a micro-fluidic assay that enables parallelized angiogenic growth instances subject to common extracellular conditions, and an automated image acquisition and processing scheme enabling high-throughput, unbiased quantification of angiogenic growth. Because of the increased throughput of the assay in comparison to existing three-dimensional morphogenic assays, statistical properties of angiogenic growth can be reliably estimated. We used the assay to evaluate the combined effects of vascular endothelial growth factor (VEGF) and the signaling lipid sphingoshine-1-phosphate (S1P). Our results show the importance of S1P in amplifying the angiogenic response in the presence of VEGF gradients. Furthermore, the application of S1P with VEGF gradients resulted in angiogenic sprouts with higher aspect ratio than S1P with background levels of VEGF, despite reduced total migratory activity. This implies a synergistic effect between the growth factors in promoting angiogenic activity. Finally, the variance in the computed angiogenic metrics (as measured by ensemble standard deviation) was found to increase linearly with the ensemble mean. This finding is consistent with stochastic agent-based mathematical models of angiogenesis that represent angiogenic growth as a series of independent stochastic cell-level decisions.

Low Variance Adaptive Filter for Cancelling Motion Artifact in Wearable Photoplethysmogram Sensor Signals

The photoplethysmogram (PPG) is an extremely useful wearable sensing medical diagnostic tool. However, the PPG signal becomes highly corrupted and unusable when the sensor wearer is in motion. This paper investigates how confidently Widrows Adaptive Noise Cancellation can eliminate motion artifact and recover a motion corrupted PPG signal for a wearer engaged in jogging motions. It has previously been shown that Widrows Adaptive Noise Cancellation can recover a motion corrupted PPG signal for certain data sets by using a collocated accelerometer to measure the corrupting motion. However, wearer motion is band limited, and provides little information for estimating motion-to-PPG noise transfer dynamics. This means that, without proper care, recovery results can be unreliable. In the present work, both Finite Impulse Response (FIR) and Laguerre series black box transfer dynamics models are evaluated for how confidently they can be identified. Model confidence is quantified in terms of variance of the transfer dynamics estimate at the motion frequencies. For typical jogging motion, it is found that standard deviation of the FIR model transfer dynamics is 30% of the mean value at the motion input frequency. The standard deviation of the Laguerre model transfer dynamics is only 1%. Time domain data shows how a Laguerre model outperforms a FIR model in accordance with the computed model variance.

Microfluidic Chemotaxis Platform for Differentiating the Roles of Soluble and Bound Amyloid-β on Microglial Accumulation

Progressive microglial accumulation at amyloid-β (Aβ) plaques is a well-established signature of the pathology of Alzheimers disease, but how and why microglia accumulate in the vicinity of Aβ plaques is unknown. To understand the distinct roles of Aβ on microglial accumulation, we quantified microglial responses to week-long lasting gradients of soluble Aβ and patterns of surface-bound Aβ in microfluidic chemotaxis platforms. We found that human microglia chemotaxis in gradients of soluble Aβ42 was most effective at two distinct concentrations of 23 pg.mL−1 and 23 ng.mL−1 Aβ42 in monomers and oligomers. We uncovered that while the chemotaxis at higher Aβ concentrations was exclusively due to Aβ gradients, chemotaxis at lower concentrations was enhanced by Aβ-induced microglial production of MCP-1. Microglial migration was inhibited by surface-bound Aβ42 in oligomers and fibrils above 45 pg.mm−2. Better understanding of microglial migration can provide insights into the pathophysiology of senile plaques in AD.

Active motion artifact cancellation for wearable health monitoring sensors using collocated MEMS accelerometers

This paper presents an active noise cancellation technique for recovering wearable biosensor signals corrupted by bodily motion. A finger mounted photoplethysmograph (PPG) ring sensor with a collocated MEMS accelerometer is considered. The system by which finger acceleration disturbs PPG output is identified and a means of modeling this relationship is prescribed using either FIR or Laguerre models. This means of modeling motivates the use of a recursive least squares active noise cancellation technique using the MEMS accelerometer reading as an input for a FIR or Laguerre model. The model parameters are identified and tuned in real time to minimize the power of the recovered PPG signal. Experiments show that the active noise cancellation method can recover pulse information from PPG signals corrupted with up to 2G of acceleration with 85% improvement in mean squared error.

Active Motion Artifact Reduction for Wearable Sensors Using Laguerre Expansion and Signal Separation

This paper presents an active noise cancellation technique that utilizes an accelerometry measurement to recover corrupted wearable health monitoring signals. The technique presented here requires no calibration for each patient and is computationally efficient. Also, a method of determining when the desired signal is correlated with the motion reference is presented with a means of partial signal recovery. The Laguerre basis function provides robustness against calibration as well as improvement in computational efficiency, and symmetric decorrelation accommodates the management of correlated signals. Experimentation shows that the system can produce up to an 85% reduction in wearable sensor error for accelerations up to 2G

Noise cancellation model validation for reduced motion artifact wearable PPG sensors using MEMS accelerometers.

This paper investigates the validity of utilizing Widrows Active Noise Cancellation (ANC) in the context of motion artifact reduction for photoplethysmogram (PPG) sensors. The ANC approach has previously been applied to the PPG problem, but little consideration has been given to the validity of the ANC signal corruption assumptions and in what motion range the algorithm works. The ANC validity testing is done in the form of impact (approximate impulse) testing of the physical PPG system and comparing with the modeled response for a range of motion amplitudes. The testing reveals that the identified corruption model does not generally represent the true physical system, but locally approximates the true system. Testing shows that if a similar motion amplitude is used for model tuning as the impact test, an average peak deviation of 5.2% is obtained, but if motion amplitude that is smaller than the impact amplitude by a factor of 5, the peak deviation is 15%. Finally, after ANC filtering motion corrupted data, heart rate can be estimated with less than 1.6% error

Novel Design for a Wearable, Rapidly Deployable, Wireless Noninvasive Triage Sensor

This paper presents a unique design for a low-power, continuous non-invasive sensor capable of remotely monitoring the five major vital signs of a patient. In particular, the sensor is designed for rapid attachment to the fingerbase of a patient by utilizing a clip-type mechanism and is comprised of a photoplethysmograph (PPG), a MEMS accelerometer, a temperature sensor, and a wireless node. Although hastily placed by a medic, the finger sensor will automatically find the location of a digital artery and acquire a clear, pulse signal: a micro-sensor array accommodates the location of the sensor attachment. Additionally, the PPG signal, although corrupted with the patients motion in chaotic environment, will be recovered by using the MEMS accelerometer and an active noise cancellation algorithm

Identification of neurotoxic cytokines by profiling Alzheimer’s disease tissues and neuron culture viability screening

Alzheimer’s disease (AD) therapeutics based on the amyloid hypothesis have shown minimal efficacy in patients, suggesting that the activity of amyloid beta (Aβ) represents only one aspect of AD pathogenesis. Since neuroinflammation is thought to play an important role in AD, we hypothesized that cytokines may play a direct role in promoting neuronal death. Here, we profiled cytokine expression in a small cohort of human AD and control brain tissues. We identified AD-associated cytokines using partial least squares regression to correlate cytokine expression with quantified pathologic disease state and then used neuron cultures to test whether cytokines up-regulated in AD tissues could affect neuronal viability. This analysis identified cytokines that were associated with the pathological severity. Of the top correlates, only TNF-α reduced viability in neuron culture when applied alone. VEGF also reduced viability when applied together with Aβ, which was surprising because VEGF has been viewed as a neuro-protective protein. We found that this synthetic pro-death effect of VEGF in the context of Aβ was commensurate with VEGFR-dependent changes in multiple signaling pathways that govern cell fate. Our findings suggest that profiling of tissues combined with a culture-based screening approach can successfully identify new mechanisms driving neuronal death.

A Stochastic Broadcast Feedback Approach to Regulating Cell Population Morphology for Microfluidic Angiogenesis Platforms

This paper presents a framework for controlling the development of a vascular system in an in vitro angiogenesis process. Based on online measurement of cell growth and a stochastic cell population model, a closed-loop control system is developed for regulating the process of cell migration and vascular system development. Angiogenesis is considered in a microfluidic environment, where chemical and mechanical stimuli can be applied to the cell population. A systems-level description of the angiogenesis process is formulated, and a control scheme that chooses an optimal sequence of control inputs to drive collective cell patterns toward a desired goal is presented in this paper. In response to control inputs, the k-step ahead prediction of morphologic pattern measures is evaluated, and the input that minimizes expected squared error between the future measure and its desired value is selected for the current control. Initial simulation experiments demonstrate that vascular development can be guided toward a desired morphologic pattern using this technique.

Nascent vessel elongation rate is inversely related to diameter in in vitro angiogenesis

Recent angiogenesis studies have found nascent blood vessels to take on a wide diameter distribution (5-25 μm) during the first 14 days of growth in murine explant models [Nunes S, et al., Microvascular Research, 2010, 79, 1-20], but the mechanisms determining diameter and its reported variability have not been explained. Here, we investigated the dominant mechanisms governing nascent vessel diameter by combining a 3D microfluidic angiogenesis model with a computational reaction-diffusion model. Cultured primary human endothelial cells sprouted from a monolayer into a 3D type I collagen matrix in the microfluidic model, and we found that vessel diameters were inversely correlated with their elongation rates. Several key species of matrix metalloproteinases (MMPs) are known to play important roles in matrix remodelling and vessel growth. We found that selective inhibition of soluble MMP2, but not MMPs 9 and 1, significantly reduced vessel diameters, suggesting that diameter may be MMP2 mediated. Furthermore, immunofluorescent staining for membrane bound membrane type 1 (MT1)-MMP showed that it was localized to active tip cells. Since MT1-MMP is an important activator of MMP2, these findings suggest that MMP2 produced/activated at the tip cell may be a dominant mediator of matrix proteolysis and sprout diameter. To support this hypothesis, we built a computational reaction-diffusion model involving tip cell localized expression of soluble MMPs during sprout elongation. The model, consisting of three parameters based on published values for MMP2 and one quantitatively tuned parameter, reproduced the experimentally observed inverse relationship between elongation rate and vessel diameter. Our experimental findings coupled with our computational model suggest a dominant mechanism by which elongation rate and soluble MMPs govern nascent vessel diameter.