All are welcome, (attendance required for graduate students). Lunch is provided.

Contact: Prof. Qi Wang.

Day/Time/Location: Fridays 11-12 noon, 614 Schermerhorn Building (unless otherwise noted)

Spring 2018 Departmental Seminar Schedule

    Curtis Johnson, University of Delaware
    High-Resolution Magnetic Resonance Elastography of the Human Hippocampus

    Magnetic resonance elastography (MRE) is an emerging technique for noninvasively characterizing the quantitative mechanical properties of tissues in vivo. These mechanical properties are highly sensitive to the structural integrity of tissue, and MRE has shown promise in diagnosing and staging neurological conditions in the brain. However, the ability to reliably characterize properties of specific neuroanatomical structures, such as the hippocampus, has been limited by poor spatial resolution and the need for high signal-to-noise ratio in reasonable scan times. In this talk I will discuss the work of my group in developing high-resolution MRE techniques to target the hippocampus, and our studies in examining mechanical integrity of the hippocampus in health and disease. Specifically, I will present our finding of structure-function relationships between hippocampal viscoelasticity and memory performance, and the characterization of hippocampal tissue in medial temporal lobe epilepsy.

    Wilson Wong, Boston University
    Synthetic Biology in Cancer Immunotherapy

    Genetically engineered cells hold great promise for improving therapeutics, diagnostics, animal models, and industrial biotechnological processes. Here I will describe our Universal Chimeric Antigen Receptors (CAR) for customizable control of T cell responses. This Universal CAR system could improve the safety and efficacy of cellular cancer immunotherapy. I will also discuss our Boolean and Arithmetic through DNA Excision (BLADE) system for designing genetic circuits with multiple inputs and outputs in mammalian cells. BLADE enables execution of sophisticated cellular computation, with applications in cell and tissue engineering. Together, the Universal CAR and BLADE systems highlight an expanding toolset for flexibly controlling mammalian cell functions.

    Kandice Tanner, NIH/NCI
    Engineering the Physical Properties of the Tumor Microenvironment

    Transformation of the physical microenvironment including changes in mechanical stiffness of the extracellular matrix (ECM) may be one of the crucial factors that drives cancer progression. In addition to tissue mechanics, the surface topography of the ECM microenvironment has been shown to modulate gene expression. Simply put, how do changes in the physical microenvironment drive cancer progression? 3D culture models can approximate in vivo architecture and signaling cues, allowing for real time characterization of cell-ECM dynamics. We developed tissue mimetics that recreate the complex in vivo geometries while independently controlling bulk stiffness and ECM ligand density. We also developed tools that allow us to resolve and quantitate minute forces that cells sense in the local environment (on the order of microns) within thick tissue (in mm). Using these methods, we are able to dissect the contributions of the physical properties from those due to chemical properties on cell fate as it relates to malignancy and normal tissue homeostasis. Finally, we validated our in vitro findings in an in vivo model using zebrafish as our model for metastasis.

    Rashid Bashir, University of Illinois
    BioMEMS and Biomedical Nanotechnology: From Lab on Chip to Printing Cellular Machines

    Integration of biology, medicine, and fabrication methods at the micro and nano scale offers tremendous opportunities for solving important problems in biology and medicine and to enable a wide range of applications in diagnostics, therapeutics, and tissue engineering. Microfluidics and Lab-on-Chip can be very beneficial to realize practical applications in detection of disease markers, counting of specific cells from whole blood, and for identification of pathogens, at point-of-care. The use of small sample size and electrical methods for sensitive analysis of target entities can result in easy to use, one-time-use assays that can be used at point-of-care. In this talk, we will present our work on detection of T cells for diagnostics of HIV AIDs for global health, development of a CBC (Complete Blood Cell) analysis on a chip, electrical detection of multiplexed nucleic acid amplification reactions, and detection of epigenetic markers on DNA at the single molecule level. While the above mentioned devices are built with PDMS or silicon using microfabrication approaches, bio-printing with stereolithography can be a very powerful technology to produce bio-hybrid devices made of polymers and cells such as biological machines and soft robotics. Such complex cellular systems will be a major challenge for the next decade and beyond, requiring knowledge from tissue engineering, synthetic biology, micro-fabrication and nanotechnology, systems biology, and developmental biology. As these “biological machines” increase in capabilities, exhibit emergent behavior, and potentially reveal the ability for self-assembly and self-repair, questions can arise about the ethical implications of this work. These devices could have potential applications in drug delivery, power generation, and other biomimetic systems.

    Lili Deligianni, IBM Research
    New Tools for Brain Research

    At the system level neuroscience is trying to understand how neural circuits work in learning, memory, multisensory integration, motor coordination and how the electrochemical function of these circuits is compromised in the case of disease. Diseases that involve the nervous system are highly complex and mostly not well understood. The Global Burden of Disease Study 2010 (GBD 2010), estimated that a substantial proportion of the world’s disease burden came from mental, neurological and substance use disorders. We need new tools and methods at the system level to effectively tackle these conditions and to better understand brain function and disease. One such tool is a cognitive computing platform, IBM's TrueNorth chip that enables the use of deep learning techniques in an ultra- low power environment. We have used deep learning with a convolutional neural network (CNN) and TrueNorth technologies for real-time analysis of brain-activity data at the point of sensing. Neurotransmitters are small proteins secreted between neurons to facilitate neural communication. These compounds are key to information processing during behavior. However, until recently, this chemical communication had not been characterized because biosensors suitable to monitor sub-second chemical events in micron dimensions were unavailable. Fast scan cyclic voltammetry at carbon-fiber microelectrodes provides measurements with sub-second time resolution and has been used to examine the dynamics of neurotransmitter concentrations. To enhance the sensitivity a n d the selectivity of these measurements, we have developed polymeric coatings for bare carbon electrodes. Dopamine, serotonin and adenosine are neurotransmitters that were measured with this methodology. Another tool that we have developed is a nanoscale electrode array with superior sensitivity and improved spatial resolution which can be used in the future to gain improved understanding of dopamine dysregulation. The scalable fabrication strategy offers the potential to integrate these nanoscale rods with an integrated circuit control system, with other sensors and with different modalities of neural activation.

    Susannah Fritton, CCNY
    Alterations in Bone Microstructure and Interstitial Fluid Flow during Osteoporosis

    In this seminar I will highlight recent investigations from my lab that have assessed how reduced estrogen levels and disuse conditions affect bone microstructure and interstitial fluid flow. Using high- resolution microscopy and micro-CT imaging, we have assessed changes in the lacunar-canalicular porosity surrounding osteocytes, as well as the vascular porosity that houses the bone vasculature, in animal models of postmenopausal osteoporosis and disuse osteoporosis. We have combined the microstructural assessments with poroelastic finite element modeling to assess interstitial fluid flow through the osteocyte lacunar-canalicular network. Results of the models demonstrate reduced interstitial fluid velocities in both estrogen-deficient and disuse conditions and suggest that a reduced mechanical input could contribute to the bone degradation that leads to osteoporosis.

    The seminar for 3/9
    has been canceled

    Creation of highly organized multicellular constructs, including tissues and organoids, will revolutionize tissue engineering and regenerative medicine. The development of these technologies will enable the production of individualized organs for patient-tailored organ transplantation or individualized tissues for cell-based therapy. These lab-produced high order tissues and organs can serve as disease models for pathophysiological study and drug screening. We have developed tissue assembly technologies for generating pancreatic islets from human pluripotent stem cells (HPSCs). These islets exhibited a tissue architecture similar to human pancreatic islets, consisting of pancreatic α, β, d, and pancreatic polypeptide (PP) cells. We discovered that tissue scaffolding is critical to the generation of pancreatic endoderm and the assembly of islet architectures. The organoids formed co-expressed PDX1, NKX6.1, and NGN3, suggesting the characteristics of pancreatic β cells. More importantly, most insulin-secreting cells generated did not express glucagon, somatostatin, or PP. The expression of mature β cell marker genes such as Pdx1, Ngn3, Insulin, MafA, and Glut2 was detected in generated islet organoids. A high-level expression of C-peptide confirmed the de novo endogenous insulin production in these organoids. Insulin-secretory granules, an indication of β cell maturity, were detected. Glucose-challenging experiments suggested that these organoids are sensitive to glucose levels due to their elevated maturity. Exposing the organoids to a high concentration of glucose induced a sharp increase in insulin secretion, whereas glucagon was released when they were exposed to a low glucose, indicating the glucose-responsive insulin release and glucagon secretion, a characteristic physiological metabolism of the human islets.

    Susan S. Margulies, Georgia Tech
    Pediatric Biomechanics: What We Need to Know

    Concussions are diagnosed based on symptoms, and most assessments are influenced by the patients’ awareness of or willingness to report their symptoms, which undermines our ability to identify biomechanical thresholds associated with concussion using instrumented volunteers. In addition, the biomechanical environment, occasionally captured by sensors in helmets, patches and mouthguards, often report limited information about the rotational movements of the head associated with concussion. Animal models can provide a controlled laboratory setting to investigate the relationships between the risk of concussion and the rapid head rotation magnitude and direction, as well has the contributions of age, sex, and previous concussions in the biomechanical thresholds for concussion. Most animal models for traumatic brain injury typically exhibit loss of consciousness, axonal damage, and hemorrhage, often with focal contusions. These animal models are representative of moderate to severe traumatic brain injuries (TBIs), but few mimic the more subtle cognitive and neurofunctional alterations without pathology that are found in concussion. Thus, animal model-derived biomechanical thresholds are typically for more severe brain injuries than concussion. Regardless, animal models offer insight into how head impacts and sudden head movements produce brain deformations and how brain deformations result in a spectrum of brain injuries, from mild to severe TBI. Emerging research in objective, involuntary neurofunctional metrics and biomarkers can bridge the gap between human and animal research, and provide important insight into the biomechanics of concussion, to provide a rational foundation for injury prevention and treatment.

    Neel S. Joshi, Harvard
    Biologically fabricated materials composed of engineered biofilm matrix proteins

    The intersection between synthetic biology and materials science is an underexplored area with great potential to positively affect our daily lives, with applications ranging from manufacturing to medicine. My group is interested in harnessing the biosynthetic potential of microbes, not only as factories for the production of raw materials, but as fabrication plants that can orchestrate the assembly of complex functional materials. We call this approach “biologically fabricated materials”, a process whose goal is to genetically program microbes to assemble materials from protein-based building blocks without the need for time consuming and expensive purification protocols or specialized equipment. Accordingly, we have developed Biofilm Integrated Nanofiber Display (BIND), which relies on the biologically directed assembly of biofilm matrix proteins of the curli system in E. coli. We demonstrate that bacterial cells can be programmed to synthesize a range of functional materials with straightforward genetic engineering techniques. The resulting materials are highly customizable and easy to fabricate, and we are investigating their use for practical uses ranging from bioremediation to engineered therapeutic probiotics.

    Ryan Gilbert, RPI
    Translation of Biomaterial Approaches for Treatment of the Injured Spinal Cord

    Following spinal cord injury (SCI), an astrocytic glial scar restricts regenerating axons from migrating through the lesion site. Our laboratory focuses on the development of fibrous materials that can guide axons through spinal cord lesions. In this talk, the response of astrocytes to fibrous materials will be examined. In particular, we assessed how fiber physical properties (diameter and nanotopography) influenced astrocyte elongation, glial fibrillary acidic protein (GFAP) production, and GLT-1 (glutamate transporter) expression. Our results indicate the ability of astrocytes to sense differences in fiber physical characteristics through differential elongation and increased GLT-1 expression. The second part of the talk will highlight our attempts to translate fibrous technologies for contusive spinal cord injury. Specifically, we added superparamagnetic iron oxide nanoparticles (SPIONs) into fibrous materials and studied the ability of these fibers to move within viscous solutions using magnetic fields. Furthermore, we reveal their capability of directing the extension of neurites from dorsal root ganglia embedded in a hydrogel matrix. Collectively, these results highlight our pursuit of developing translatable biomaterial approaches for the treatment of spinal cord injury.

    Philip Alderson, Saint Louis University
    Machine Learning for Precision Medicine

    The first sequencing of the human genome in April of 2003 set the stage for great progress in biomedicine. The large data sets that were created, however, required computational solutions for curation and analysis. Within a few years, genomic analysis became faster and much less expensive using next generation sequencing. Similar impacts came in data processing by the development of unified CPU/GPU architecture and deep neural networks. By 2012 it was shown that dense and deep nodal connectivity allowed network outputs to improve via repetitive data cycles, i.e., the systems seemed to “learn”. Feed forward deep networks, recurrent network and other specialized configurations were developed including convolutional networks to support graphic data configurations, i.e., computer vision. Algorithm-driven versions of these various systems now are being applied broadly in medicine. “Precision medicine” is a major goal. This is the attempt to match an individual’s medical treatment to their genomic receptivity as impacted by their environment. Applications to patients with cancer and with many other medical problems will require continued development of big data approaches. In addition, broad educational efforts including better integration of genomic and computational education should be pursued to reach the full potential of precision genomic medicine.

    John White, Boston University
    The Unbalanced State of Resting Cortical Networks

    Summary. High statistical variability is a hallmark of neuronal firing patterns in neocortex. This variable activity is hypothesized to be driven by input that is balanced, with membrane potential held near spike threshold by equally weighted, and fluctuating, excitation and inhibition. Models with balanced activity express voltage-dependent statistical and spectral properties that can be used to test for the presence of balanced activity. Using visually-guided intracellular recordings of layer 2/3 somatosensory neurons in awake mice, we compared the properties of spontaneous voltage fluctuations with those generated in balanced models. In both pyramidal cells and interneurons, our data contrast with balanced-model predictions in two crucial regards. First, the power in the inputs does not obey the nonmonotonic relationship that is necessary for balanced inputs. Second, the skew in the distributions of measured voltages, unlike those from the models, is voltage-independent. In the data, inputs appear electrotonically distant from the soma, but evoke voltage-dependent changes in apparent postsynaptic input resistance that amplify depolarizations nonlinearly. We speculate that such unbalanced inputs give rise to more flexible network responses under awake but unstimulated conditions.

    Norbert Pelc, Stanford
    Perspectives for Future Developments in CT Imaging

    Computed tomography (CT) has made enormous technical advances since its introduction into clinical use. The engineering improvements have led to important clinical applications and large impact in patient care. Expanded clinical use has in turn led to concerns about population ionizing radiation dose from CT. Even after more than 45 years of progress, important developments are in the lab bench and on the horizon, including a new generation of x-ray detectors. This lecture reviews the technology development trends in CT since its introduction. Then, using these historical trends as well as physics and engineering limits, we will explore likely directions of future technical progress. This analysis suggests that significant further improvements in speed, spatial resolution and dose efficiency can be expected in the next decade.


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