BE Seminars & Events

Current Seminar Series: 2015-2016

Bioengineering Seminars are held on Thursdays at 10:30AM in 337 Towne Building unless otherwise noted below. For all Penn Engineering events, visit the Penn Calendar.


David A. Weitz
Mallinckrodt Professor of Physics and Applied Physics, Harvard University
"Drop-based microfluidics:  Biology a picoliter at a time"
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This talk will describe the use of microfluidic technology to control and manipulate drops whose volume is about one picoliter.  These can serve as reaction vessels for biological assays.  These drops can be manipulated with very high precision using an inert carrier oil to control the fluidics, ensuring the samples never contact the walls of the fluidic channels.  Small quantities of other reagents can be injected with a high degree of control.  The drops can also encapsulate cells, enabling cell-based assays to be carried out.  Examples of the application of these devices to the study of fundamental biology will be described.  In addition, I will describe the impact this class of microfluidics is having on biotechnology.

September 17
Jan Liphardt
Associate Professor of Bioengineering, Stanford University
"Perhaps, Abnormalities of Matrix Mechanics Can Drive Rapid EMT-like Transitions"
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One of the fundamental mysteries of biology lies in the ability of cells to convert from one phenotype to another in response to external control inputs. We have been studying the Epithelial-to-Mesenchymal Transition (EMT), which allows organized groups of epithelial cells to scatter into lone mesenchymal cells. EMT is critical for normal development and wound healing, and may be important for cancer metastasis. First, I’ll brief you on our efforts to use statistical methods to summarize about 12,500 publications on EMT. This analysis revealed interesting statistical anomalies. For example, the number of discrete factors that authors invoked to explain EMT and its regulation was bounded above by the capacity limit of the human brain to follow statistical interactions among variables. In the second part of my talk, I’ll show you our recent data on disorganizing mammary epithelial structures. We have used CRISPR to insert fluorescent tags directly into eight EMT-related genes (such as E-cadherin and Vimentin), which allows us to monitor the transition in real time, subject only to delays imposed by fluorophore folding/maturation times.


October 1
Kwabena Boahen
Professor of Bioengineering and Electrical Engineering, Stanford University
Neuromorphic Chips: Combining Analog Computation with Digital Communication

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After decreasing exponentially for the past half century, the cost of a transistor rose for the very first time this year. This increase occurred because the industry switched from planar transistors to three-dimensional ones, which are more difficult to fabricate. The switch was necessary, however, because, among other reasons, the transistor’s width had become so narrow that only ten “lanes” of electron traffic fit. With so few lanes, a single “pothole” (dopant atom) or “accident” (trapped electron) decreases traffic (electrical current) by a significant amount. Building a “double-decker freeway" made it possible to shrink the transistor’s width further while increasing—rather than decreasing—the number of lanes. In this way, the probability that traffic stops completely—due to multiple potholes and/or accidents occurring simultaneously—remains vanishingly small. If such an event occurred, the consequence would be disastrous, given the current computing paradigm (purely digital hardware and strictly deterministic operation). 


I’ll make the case for accommodating heterogeneity (potholes) and stochasticity (accidents) by combining analog computation with digital communication. It appears that the brain uses this unique mix of analog and digital techniques to deal with traffic jams in its ion-channels, biology’s single-lane transistors. To support my case, I'll present a Kalman-filter-based brain-machine interface and a three-degree-of-freedom robot-arm controller implemented on a chip that combines analog computation with digital communication much like the brain does. A formal theory for approximating arbitrary nonlinear dynamical systems with networks of spiking neurons was used to derive weights applied to synaptic inputs (analog computation) triggered by spikes that the chip’s silicon neurons receive from each other (digital communication). This neuromorphic computing paradigm was robust to heterogeneity (transistor-to-transistor dopant fluctuations) and stochasticity (randomly dropped spikes), suggesting that it may well prove to be more cost-effective than the current computing paradigm as transistors scale down to a few nanometers.


October 15
Guillermo Sapiro
Edmund T. Pratt, Jr. School Professor of Electrical and Computer Engineering, Duke University
"Image processing and machine learning helping to get advanced medicine to the masses: From brain surgery to mental health"

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Many of us are privileged and knowledgable to access advanced medicine when we unfortunately need it. A number of factors limit this access to the general population. I will demonstrate with two examples how we can brake that boundary.

First, we will show how to help deep brain stimulation (DBS), in particular for motor disorders, with advanced algorithms that permit to detect with high precision the surgical target. This opens the door to orders of magnitude expansion of DBS. From there we move to the use of technology, image processing, and machine learning to design screening tools for child mental health. We will illustrate this with Autism screening. Both examples illustrate results already in use in the OR and clinic, and exemplify both the need for the tools we develop and the value of having an incredible interdisciplinary team, all of which will be mentioned and introduced during the talk.
Ji October 22
Na Ji
Group Leader, Howard Hughes Medical Institute Janelia Research Campus
"From star to neuron - adaptive optical microscopy for deep brain imaging"
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Imaging neurons deeply buried inside a live mouse using a microscope shares many similarities with gazing at distant stars with a telescope. In both cases, imaging capacity is limited by optical aberration and scattering. Wavefront shaping using adaptive optics has revolutionized astronomy by allowing us to obtain sharp images of celestial objects through the turbulent atmosphere. Similar concepts may be applied to microscopy for optically transparent samples but not the scattering mammalian brains. In this talk, I will describe recent developments in adaptive optical microscopy, which allowed us to image both the input and output of mouse cerebral cortex with diffraction-limited resolution. By making it possible to functionally image axons and neurons deep inside the mouse brain, these techniques enabled novel discoveries on the origin of orientation selectivity in mouse primary visual cortex.
Ji October 29
 Rajanikanth Vadigepalli, Ph.D.
Associate Professor, Daniel Baugh Institute for Functional Genomics/Computational Biology,Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University
"Modeling Multiscale Control of Liver Regeneration"
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Liver regeneration is a clinically important tissue repair process, which involves the interplay of carefully orchestrated signals from different cell types integrated with systemic factors to recover functional tissue mass. At present, there is limited theoretical understanding of how the regulatory mechanisms operating at multiple scales integrate towards an overall liver response when mounting an effective regenerative program. We pursue a systems biology strategy that combines multiscale modeling with single cell scale data sets to fill this major gap in our knowledge. In this presentation, I will describe a novel computational model we developed to account for various cellular and molecular aspects of liver regeneration following partial hepatectomy. Our modeling studies led to novel predictions on how dynamic regulation of hepatic stellate cell phenotypes can control the integrated liver tissue response in health and disease, across multiple organisms. We validated the model predictions using pathway-scale single cell gene expression data sets. Our results provide new insights into how the dynamic state transitions between multiple cell phenotypes are integrated towards a coordinated control of the liver regeneration process. We are presently translating the network model to the human condition for improving liver surgery and transplant outcomes for a broader cohort of patients.

November 5
Lauren Black
Assistant Professor of Biomedical Engineering, Tufts University
Mechanotransduction and Extracellular Matrix-based signaling in Cardiac Health and Disease: Opportunities for Therapeutic Development

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Cardiovascular disease is the leading cause of death in the US and rapidly becoming the leading cause of death worldwide. While a number of therapies have sought to arrest the progression to heart failure following myocardial infarction (e.g. cell therapy and tissue engineering), these have fallen short in promoting the restoration of normal cardiac function following injury. Similarly, congenital heart defects (CHDs) are the leading cause of mortality in live-born infants and young children. Children with severe CHDs such as Hypoplastic Left Heart Syndrome and Tetralogy of Fallot require several major reconstructive surgeries starting within the first few days after birth. However, these surgeries do not replicate normal heart anatomy and function, and many patients suffer from serious secondary complications throughout life. In each of these situations there are significant changes to the mechanical environment, both in terms of the mechanical stresses presented to the cells via the normal function of the organ and in the composition and mechanical properties of the extracellular matrix (ECM). Given the growing body of evidence on the role of ECM properties in signaling cell fate and function, understanding the role of the alterations in the complex mechanical signaling environment in health and disease could be critical to the development of a new class of therapeutics aimed at altering mechanotransductive signaling in disease. In this talk I will highlight some of our work aimed at understanding the role of alterations in the properties of the complex ECM during normal and pathological development in promoting specific cell fates and/or functions.  I will also discuss how these findings may be utilized in the future to develop new therapeutic strategies for treating the injured or malformed heart.

Matthew Paszek, Ph.D.
School of Chemical and Biomolecular Engineering
Cornell University
"The mechanobiology of the cancer cell glycocalyx"

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Glycans are the most abundant and diverse of nature’s biopolymers. In the past decade, the study of glycans has entered a Renaissance fueled by the development of new analytical tools designed to probe glycan structure and biochemistry, as well as a widespread realization of glycoscience’s potential to innovate in areas of human health, bio-sustainable energy, and materials science. In addition to their recognized biochemical activities, glycans also contribute directly to the bulk physical properties of proteins, cells, and tissues. In living systems, glycans are concentrated on the cell surface in a dense, complex structure that is referred to as the glycocalyx. From a physical perspective, the glycocalyx has long been considered a simple “slime” that protects cells from mechanical disruption or against pathogen interactions, but the dramatic complexity of the structure argues for the evolution of more advanced functionality. Combining new optical imaging methodologies with approaches from computational biology and cell biology, we have now begun to dissect how changing patterns of glycosylation and glycoprotein expression alter cell surface receptor function at nanometer length scales. I will discuss these findings and describe how biophysical changes in the glycocalyx can play a role in aggressive, lethal cancers. This discussion will include our more recent findings related to the role of cancer-associated glycoproteins in vesicle biogenesis. Together, these findings emphasize the need for biophysical questioning, research and understanding in the emerging field of glycoscience.
December 3
Michael Hagan
Associate Professor of Physics, Brandeis University
Cargo encapsulation by self-assembling icosahedral containers
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The self-assembly of a protein shell around a cargo is a common mechanism of encapsulation in biology, and is inspiring development of drug delivery vehicles that form by self-assembly. However, the physics underlying such multicomponent assembly processes is incompletely understood. In this talk I will describe how minimal computational models can elucidate two biological examples in which icosahedral protein shells assemble around cargos. In each case we find that the material properties of the cargo play a key role in directing its encapsulation.

The first example concerns viruses with single-stranded RNA (ssRNA) genomes. For many ssRNA viruses, formation of an infectious virus requires the spontaneous assembly of an icosahedral protein shell (called a capsid) around the genome. I will describe simulations that investigate how this co-assembly process depends on the physical properties of RNA: its length, electrostatic charge, and 3D structure. When applied to specific virus capsids, the calculated optimal RNA lengths closely correspond to the natural viral genome lengths. This suggests that evolution of viral RNA is driven not only by the fitness of the proteins that it encodes for, but also by how its material properties favor encapsulation. We then show that assembly can proceed through two qualitatively different classes of pathways, which can be tuned by solution conditions or changing the capsid protein properties.

The second example concerns carboxysomes, which are large, roughly icosahedral protein shells that facilitate carbon fixation in cyanobacteria. Carboxysomes assemble around a cargo which is topologically different from ssRNA, a noncovalently linked, amorphous complex of the enzyme RuBisCO. Motivated by this problem, we study assembly of icosahedral shells around a fluid cargo. We find different assembly pathways and different critical control parameters as compared to assembly around RNA, and that the predominant assembly pathway depends strongly on the cargo fluidity. We discuss relationships between simulated assembly pathways and recent experiments observing assembly of individual carboxysomes in bacteria.

December 10
Konrad Kording
Associate Professor of Physical Medicine and Rehabilitation, Physiology, and Applied Mathematics, Northwestern University
"Making complicated movement out of simple ones: Chunking as a control phenomenon"

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A complex movement is optimally efficient if it is executed as one continuous optimal trajectory. However, the computational cost of optimizing movement efficiency grows exponentially with the planning horizon. Thus, for a fixed computational cost, there is a limit to how efficient a movement can be. Here we suggest that this tradeoff can explain why complex movements are executed as a string of discrete shorter movements; a phenomenon known as “chunking”.  We show that monkeys learning a reaching sequence initially improve movement efficiency by locally optimizing trajectories within chunks, and then achieve further efficiency gains by expending greater costs. This two-stage strategy results in significant cost advantages over the course of learning, relative to a strategy of learning the entire movement without chunks. Thus chunks are integral for motor learning.

January 14
Sanjay Kumar
Professor and Associate Chair of Bioengineering, University of California, Berkeley
Cells as smart materials: Dissecting and reverse-engineering mechaniobiological units

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Living cells are capable of processing a variety of mechanical signals encoded within their microenvironment, which can in turn act through the cellular structural machinery to regulate many fundamental behaviors. In this sense, cells may be regarded as "smart materials” that dynamically and locally modulate their physical properties in response to environmental stimuli. I will discuss our recent efforts to understand and control these living materials, and to create new, bio-inspired materials that mimic sequence/structure/function relationships of cytoskeletal networks. Key areas of emphasis will include: (1) Understanding and targeting biomechanical regulation of tumor infiltration in the brain; (2) Applying materials and genetic strategies to probe the timing of mechanosensitive stem cell fate decisions; and (3) Engineering stimulus-sensitive intrinsically disordered protein brushes based on neuronal cytoskeletal networks.

Mehmet Toner
Professor of Surgery, Massachusetts General Hospital and Harvard Medical School
The Power of Microfluidics to Sort Extremely Rare Cells: Quest to Isolate Circulating Tumor Cells
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Viable tumor-derived circulating tumor cells (CTCs) have been identified in peripheral blood from cancer patients and are not only the origin of intractable metastatic disease but also marker for early cancer. However, the ability to isolate CTCs has proven to be difficult due to the exceedingly low frequency of CTCs in circulation. As a result their clinical use until recently has been limited to prognosis with limited clinical utility.  More recently, we introduced several microfluidic methods to improve the sensitivity of rare event CTC isolation, a strategy that is particularly attractive because it can lead to efficient purification of viable CTCs from unprocessed whole blood. The micropost CTC-Chip (μpCTC-Chip) relies on laminar flow of blood cells through anti-EpCAM antibody-coated microposts, whereas the herringbone CTC-Chip (HbCTC-Chip) uses micro-vortices generated by herringbone-shaped grooves to efficiently direct cells toward antibody-coated surfaces. These antigen-dependent CTC isolation approaches, also called “positive selection”, led to the development of a third technology, which is tumor marker free (or antigen-independent) sorting of CTCs. We call this integrated microfluidic system the CTC-iChip, based on the inertial focusing strategy, which allows positioning of cells in a near-single file line, such that they can be precisely deflected using minimal magnetic force. The major advantage of the approach stems from the fact that it is based on “negative depletion” of blood cells and hence it is applicable to all solid tumors and does not require tagging or labeling the tumor cells.  As a result the CTCs are isolated in pristine conditions and are amenable to analysis using imaging, molecular, and other approaches.  We applied these three microfluidic platforms to blood samples obtained from lung, prostate, breast, colon, melanoma, and pancreatic cancer patients. We isolated CTCs from patients with metastatic non-small-cell-lung cancer and identified the EGFR activating mutation in CTCs. We also detected the T790M mutation, which confers drug resistance. We also applied microchip to isolate CTCs from blood specimens of patients with either metastatic or localized prostate cancer, and showed the presence of CTCs in early disease. Remarkably, the low shear design of the HBCTC-chip revealed micro-clusters of CTCs in a subset of patient samples. Microscopic CTC aggregates may contribute to the hematogenous dissemination of cancer.  More recently, we used microfluidic capture of CTCs to measure androgen receptor (AR) signaling readouts before and after therapeutic interventions using single-cell immunofluorescence analysis of CTCs. The results support the relevance of CTCs as dynamic tumor-derived biomarkers, reflecting “real time” effects of cancer drugs on their therapeutic targets, and the potential of CTC signaling analysis to identify the early emergence of resistance to therapy. We also characterized epithelial-to-mesenchymal transition (EMT) in CTCs from breast cancer patients. While a few primary tumor cells simultaneously expressed mesenchymal and epithelial markers, mesenchymal cells were highly enriched in CTCs, and most importantly, serial CTC monitoring suggested an association of mesenchymal CTCs with disease progression suggesting a role for EMT in the blood-borne dissemination of human breast cancer. We have also identified the presence of CTC clusters, which led to the development of a microchip that is designed to sort clusters of cells from whole blood without any labeling.  The propensity of CTC clusters to lead to metastasis is significantly higher than single CTCs, and underlies the importance these cells play in the metastatic cascade.  This presentation will share our integrated strategy to simultaneously advance the engineering and microfluidics of CTC-Chip development, the biology of these rare cells, and the potential clinical applications of circulating tumor cells.

Ronit Freeman
Postdoctoral Fellow, Simpson Querrey Institute for Bionanotechnology, Northwestern University
Instructing Cells with Programmable Peptide-DNA Hybrids

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The native extracellular matrix is a space in which signals can be displayed dynamically and reversibly, positioned with nanoscale precision, and combined synergistically to control cell function. Artificial forms of this matrix for tissue regeneration need to recapitulate these three characteristics in a single molecular platform. Most efforts in this area have effectively addressed only one of these three key phenomena, and focused mainly on static cell adhesion or irreversible switching of bioactivity. This talk will describe a molecular system based on peptide-DNA conjugates that can be programmed to control the dynamics, spatial positioning, and combinatorial synergies of signals in extracellular matrices. This peptide-DNA platform controls the way different signals are presented to cells and their relative spacing and confers superior reversibility by employing a set of bio-friendly stimuli. Multiple orthogonal DNA handles can be designed to allow for the selective presentation of different signals, with the ability to independently up- or down-regulate each over time. This talk will also demonstrate the formation of one-dimensional assemblies of peptide-DNA hybrids with filamentous architecture and three-dimensional hydrogel networks based on DNA- peptide amphiphiles that mimic the structure and function of the natural extracellular environment. These novel constructs will enable to elucidate how external cues direct cell behavior and orchestrate cellular processes, which may have great importance for mimicking in vivo tissue remodeling and dynamics.

January 28
Dominique Durand
Professor of Biomedical Engineering, Case Western Reserve University
Controlling the timing of single cells to prevent seizures

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Seizures are often compared to electric storms in the brain and to some extent this analogy is correct. Seizures consist of abnormal neural firing in specific parts of the brain and can often travel throughout the brain to alter the firing patterns of neurons away from the seizure. Electrical stimulation can also modulate neural firing of these cells and if applied carefully control their abnormal patterns. In this lecture I will show how electric pulses applied to the brain can control the excitability of single cells and prevent seizures in patients with temporal lobe epilepsy Short CV: Dominique M. Durand is E.L. Linsedth Professor of Biomedical Engineering and Neurosciences and Director of the Neural Engineering Center at Case Western Reserve University in Cleveland, Ohio. He received an engineering degree from Ecole Nationale Superieure d'Electronique, Hydrolique, Informatique et Automatique de Toulouse, France in 1973. In 1974, he received a M.S. degree in Biomedical Engineering from CWRU in Cleveland OH., worked several years and in 1982 received a Ph.D. in Electrical Engineering from the University of Toronto in the Institute of Biomedical Engineering. He received an NSF Young Investigator Presidential Award as well as the Diekhoff and Wittke awards for graduate and undergraduate teaching and the Mortar board top-prof awards at CWRU. He is an IEEE Fellow and also Fellow of the American Institute for Medical and Biomedical Engineering and Fellow of the Institute of Physics. He serves on many editorial boards of peer-reviewed scientific journals and he is the editor-in-chief and founding editor of the Journal of Neural Engineering. His research interests are in neural engineering and include computational neuroscience, neurophysiology and control of epilepsy, non-linear dynamics of neural systems, neural prostheses and applied magnetic and electrical field interactions with neural tissue.

Paco Robles
Postdoctoral Associate, Department of Chemistry, Duke University
Endogenous Molecular Imaging Using Linear and Nonlinear Optical Spectroscopy for Biomedical Applications

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Optical molecular imaging holds a pivotal role in biology and medicine due to its ability to provide invaluable insight into disease mechanisms at molecular and cellular levels. The rich source of molecular information available to optical methods originates from the multitude of light-matter interactions that reveal detailed biochemical and biophysical properties. However, the most widely applied strategies for optical imaging only take advantage of a small fraction of the available interactions. This has particularly limited the use of endogenous biochemical species for molecular/functional imaging.
In this talk I will discuss emerging optical spectroscopic methods (linear and nonlinear) that are able to more fully utilize the available sources of endogenous molecular and functional contrast. The application of these novel strategies to biology and medicine, particularly for melanoma detection and staging, will be discussed.
February 4
Adam Abate
Assistant Professor of Bioengineering, University of California, San Francisco
Droplet Microfluidics for High Throughput Biology
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Many questions at the forefront of biology depend on the individual properties and interactions of millions of single cells. My lab develops methods for analyzing, sorting, and engineering single cells using droplet-based microfluidics. I will describe methods in which we are using this to detect rare cells in a population and evolve new cells with enhanced properties. I will also describe how we are extending this approach to synthetic systems to generate artificial antibody-like affinity reagents.

Jukka-Pekka Onnela
Assistant Professor of Biostatistics, Harvard TH Chan School of Public Health
Digital Phenotyping

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A longstanding barrier to progress, both in clinical settings and research trials, has been the difficulty of accurately measuring the human phenotype, including but not limited to behavioral patterns, social interactions, physical mobility, gross motor activity, and speech production. Smartphones are now ubiquitous and can be harnessed to offer medicine a wealth of data on the human phenotype, and subjects can be instrumented with scientific apps that generate continuous streams of data. We have coined the term "digital phenotyping" to refer to the moment-by-moment quantification of the individual-level human phenotype, in situ, using data from personal digital devices. I’ll outline this approach, describe the Beiwe platform that we have developed for use in biomedical research, discuss methodological developments, and share some of our early results.
February 11
KC Huang
Associate Professor of Bioengineering and Microbiology and Immunology, Stanford School of Medicine
It Came as a Shock: Regulation of Bacterial Growth by Osmotic Pressure
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It has long been proposed that turgor pressure plays an essential role during bacterial growth by driving mechanical expansion of the cell wall. This hypothesis is based on analogy to plant cells, for which this mechanism has been established, and on experiments in which the growth rate of bacterial cultures was observed to decrease as the osmolarity of the growth medium was increased. To distinguish the effect of turgor pressure from pressure-independent effects that osmolarity might have on cell growth, we monitored the elongation of single Escherichia coli cells while rapidly changing the osmolarity of their media. By plasmolyzing cells, we found that cell-wall elastic strain did not scale with growth rate, suggesting that pressure does not drive cell-wall expansion. Furthermore, in response to hyper- and hypoosmotic shock, E. coli cells resumed their pre-shock growth rate and relaxed to their steady-state rate after several minutes, demonstrating that osmolarity modulates growth rate slowly, independently of pressure. Oscillatory hyperosmotic shock revealed that while plasmolysis slowed cell elongation, the cells nevertheless “stored” growth such that once turgor was re-established the cells elongated to the length that they would have attained had they never been plasmolyzed. In contrast, Bacillus subtilis cells exhibit highly regular growth oscillations in response to hypoosmotic shock that are dependent on peptidoglycan synthesis. The period of these oscillations scales linearly with the magnitude of the shock. By applying a simple mathematical theory to these data, we show that growth oscillations are initiated by mechanical-strain-induced growth arrest. This demonstrates that B. subtilis has developed an elegant system by which turgor pressure both up- and down-regulates the final steps of cell growth.

Dan Wilson
Graduate Student Researcher, Department of Mechanical Engineering, UC Santa Barbara
As Simple As Possible (But Not Simpler): Model Reduction in the Treatment of Neurological and Cardiological Disease

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As technology continues to evolve at a rapid pace, scientists are able to observe and record more and more of the underlying dynamical behavior contributing to biological diseases. With these advances in technology comes a growing interest in applying dynamical systems and control theoretic tools to provide new insight into treatment options for medically intractable diseases. My particular focus has been on the creation and utilization of mathematical tools which can reduce the dimensionality and complexity of the differential equations describing nonlinear biological systems, making them amenable for further study. Attention is given to the problem of understanding the role deep brain stimulation (DBS) as a treatment for patients with Parkinson’s disease. Model reduction strategies provide starting point for merging two competing hypotheses for the therapeutic mechanism of DBS as a treatment for Parkinson’s disease and can also be used to suggest better stimulation strategies than those currently available. In addition to neuroscience applications, model reduction techniques facilitate the development of low energy electrical stimulation methods for the elimination of cardiac arrhythmias such as alternans, tachycardia, and fibrillation; all of which are associated with the emergence of cardiac arrest, a leading cause of death in the industrialized world.
February 18
Kyle Quinn
Assistant Professor, Department of Bioengineering, University of Arkansas
Quantifying Changes in Cell Metabolism Through Label-Free Multiphoton Microscopy
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Altered cellular metabolism is commonly observed in many disease states.  Arising from early work by Britton Chance, high-resolution spectroscopic imaging approaches utilizing the natural fluorescence of metabolic cofactors (NADH and FAD) have been developed and used effectively in a number of cancer research applications.  However, the sensitivity of these imaging techniques to specific metabolic pathways and different cell functions is not well defined.  In this talk I will describe how we have obtained a more nuanced understanding of the sensitivity of NADH and FAD autofluorescence to changes in metabolism during stem cell differentiation and precancerous transformation through correlative metabolic assays. I will also discuss new applications in cutaneous wound healing for metabolic and microstructural imaging using label-free multiphoton microscopy. Through quantitative image analysis of this non-invasive depth-resolved imaging technique, we are developing a suite of optical biomarkers to evaluate wound healing therapies in vivo with the end goal of establishing real-time diagnostic readouts to evaluate wounds in the clinic.
  February 25 - Grace Hopper Distinguished Lecture - POSTPONED UNTIL FURTHER NOTICE (TO BE RESCHEDULED IN THE 2016-2017 ACADEMIC YEAR)
Clare Waterman
NIH Distinguished Investigator, Laboratory of Cell and Tissue Morphodynamics, National Institutes of Health
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Thomas Gaj

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  March 3
Hui Mao
Professor of Radiology and Imaging Sciences, Emory University School of Medicine
Title TBA
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Omar Khan

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March 10
Dan Simionescu
Associate Professor of Bioengineering, Clemson University

Heart Valve Tissue Engineering: A Tale of Scaffolds, Cells, and Stimuli

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Reconstruction or regeneration of living tissues is a daunting project for biomedical engineers and surgeons alike. Our overall aim is to bring tissue engineering closer to the patient. To reach this goal, we hypothesized that successful translational regenerative medicine requires a coherent combination of mechanically sound “niche” scaffolds, cells with the potential to regenerate and revitalize the scaffolds and adequate biological and biomechanical stimuli. Cardiac valves are the most mechanically challenged tissues in the body, and yet knowledge on cell biology, biochemistry, matrix homeostasis, genetics, mechanics, pathology, replacement and regeneration is still incomplete. Our approach combines the outstanding mechanical and biological properties of xenogeneic valves with the plasticity of autologous adult stem cells. We started by completely decellularizing porcine aortic and pulmonary roots using devices and procedures invented in our labs. Quality control tests ensured lack of porcine cells and antigens and preservation of major matrix components and mechanical characteristics. Next, adipose-derived stem cells were collected from sheep from selected anatomical sites, tested for plasticity in vitro and multiplied several passages before being seeded within the acellular valve scaffolds. Autologous stem cell-seeded valve roots were then implanted as right ventricle to pulmonary artery shunts in sheep and followed by echography for up to 10 months.

Our results showed that: 1) preservation of valve mechanical and biological properties was possible by controlled decellularization in specialized devices and bioreactors, 2) adult stem cells differentiated in vitro into valvular interstitial cells when exposed to appropriate biochemical and mechanical signals in purpose-built bioreactors, 3) successful valve implantation with minimally invasive surgery approaches was possible and yielded excellent animal recovery. To date most valves functioned properly and explant analysis is ongoing. Large animal pre-clinical testing in sheep revealed the feasibility of this approach and these promising results increase enthusiasm for the future of cardiac valve tissue regeneration.

This multidisciplinary project was made possible by contributions from several multinational research teams specialized in bioengineering, stem cell biology, biochemistry, cardiac surgery, cardiology, echography, veterinary medicine and animal care, pathology, histology and immunohistochemistry and project management.

This project was funded in part by NHLBI of the National Institutes of Health under award number RO1HL093399, by NIGMSof the National Institutes of Health under award number5P20GM103444-07, by the Harriet and Jerry Dempsey Associate Professorship in Bioengineering Award (to DS) and by a grant from the Romanian National Authority for Scientific Research, CNCS-UEFISCDI, project number PNII-ID-PCCE-2011-2-0036.

  March 17
Prashant Mali
Assistant Professor of Bioengineering, University of California, San Diego
Title TBA
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  March 31
Gerard Ateshian
Andrew Walz Professor and Chair of Mechanical Engineering, Columbia University
Title TBA
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New resting-state MRI acquisition and analysis techniques are making it possible to obtain information about network dynamics in the brain.  The patterns of changing network connectivity have been linked to fluctuations in simultaneous electrical recordings in healthy humans and anesthetized animals.  Based on these initial studies, we hypothesize that at least two independent processes contribute to the resting-state MRI signal.  The first is a quasiperiodic, large-scale spatiotemporal pattern that appears to arise from very low frequency (< 1 Hz) electrical activity and has plausible links to attention and vigilance.  The second process consists of irregular changes in the connectivity between selected areas.  It is linked to variation in the correlation of high frequency power, particularly in the beta and gamma bands, and we speculate that these changes may be more closely linked to cognitive processes.  If our hypothesis proves true, we may be able to separate out the relative contributions of these two sources to the MRI signal, with the goal of obtaining more sensitive indices of cognitive changes along with quantifiable monitoring of attention and vigilance.

April 7
Wan-Ju Li
Assistant Professor of Biomedical Engineering, University of Wisconsin-Madison
Title TBA

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April 14
Hang Lu
Professor and James R. Fair Faculty Fellow, Georgia Tech
Title TBA

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  April 21 - Herman Schwan Distinguished Lecture
Lonnie Shea
Professor of Chemical and Biological Engineering, Northwestern University
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