Events & Seminars

Signal transduction architectures, which control molecular information processing, frequently contain large numbers of coupled chemical conversions and complex architectural features such as redundancy, feedback and crosstalk. While this complexity ensures robustness, it also complicates signal reprogramming. The objective of our research program at Cornell is the development of physiochemical modeling tools that can be used to rationally reprogram signal flow. Our thesis is that physiochemical models could be hypotheses generation engines, which suggest targeted reprogramming strategies, despite model uncertainty. To this end we have developed computational tools to automate model generation, identification and analysis. These tools, together with our growing database of network architectural components, have allowed us to construct and test our thesis on several human signaling models on a rapid time-scale. In this study, we’ll discuss several examples, which demonstrate these tools. First, we’ll present an overview of our human coagulation modeling work. Coagulation is an ideal target for systems biology as much of the biology is known, good experimental techniques exist to measure components in the cascade and the architecture of the cascade shares many common features, such as positive feedback, with intracellular networks. Next we’ll discuss intracellular network models focused on understanding infrastructure processes such as translation and higher-level programs such as differentiation. With all these examples, we’ll show how physiochemical model populations can provide insight into the “hot-spots” of signal transduction architectures, despite model uncertainty. Understanding these “hot-spots” could be a first step in the fundamental understanding of disease progression as well as the development of new treatments for complex diseases.

Microtubule is a major component of the cytoskeleton and a key player in many essential cellular process such as mitosis, motility, morphogenesis and polarization. Microtubule associated proteins collectively control the assembly dynamics of microtubules and provide them with the necessary flexibility to fulfill their functional roles. Using a combination of automated image analysis, coarse-grained systems level models and bimolecular simulations, we strive to build an integrated understanding of these proteins from the level of the structure and dynamics of individual molecules all the way to the level of their function, regulation and interactions in living cells. Here I will present a few case studies from the process of moving towards that long term goal.

Modeling of wide sense stationary biological signals begins by estimating the signal autocorrelation function and attempting to find a linear, stationary, model the Wold theorem says exists. We use this concept and extend it to two dimensions to find the linear, stationary image model the same theorem says exists. For biological signals the model is a linear, stationary, difference equation. For images the model is a linear, stationary, partial difference equation. Continuous parameter signals and images actually have differential equation and partial differential equation models which are approximated by their discrete time and space versions. The applications we exhibit for medical images are for the purposes of finding a statistically significant model of an image that can provide medical insight for the diagnostician and also to provide a means of classifying images by disease class or progression. The SPECT (Single Photon Emission Computed Tomography) image studied is an example of the first application while the rodent and human images are of the second application. Modeling tools employed are ordinary and generalized least squares regression and Fisher linear discriminants.

Many groups have demonstrated the ability of noninvasive magnetic resonance studies to evaluate anabolic and catabolic processes in cartilage. However, although correlations of tissue status with MR parameters have been established, these analyses remain problematic, and exhibit limited sensitivity and specificity. We have therefore introduced new MR approaches for cartilage assessment and imaging, which I will describe in the context of our efforts to develop novel diagnostic and therapeutic approaches to osteoarthritis.

One of the intriguing questions in molecular evolution is the origin and development of protein structures or folds1. Are proteins trapped in a particular set of limited folds initiated by chance? Does evolution allow for structural variations (in addition to sequence mutations) that connect different fold families? We review recent experimental evidence that support the feasibility of fold changes, and discuss a computational model that account for these variations. We further provide a comprehensive computational model for sequence evolution that connects all known folds of the PDB. Implication to the evolution of fold classes and enzymes are discussed.

Deep brain stimulation of the subthalamic nucleus is an important treatment for patients with Parkinson's disease. In this presentaion, we will first review studies in which we have shown the dramatic benefit of subthalamic nucleus deep brain stimulation (STN DBS) on bradykinesia, tremor and rigidity. We will show that limb tremor is normalized, movement speed is increased, muscle activation patterns resemble those of healthy individuals, and rigidity is substantially reduced. Second, we will show that there is no difference between 90 min and greater than 3 months of STN DBS on both the UPDRS or motor control measures. This finding confirms that the treatment efficacy that is derived from a short time course of stimulation generalizes to the longer time periods of STN DBS that patients experience in their daily lives. Third, we present data showing the effects of five years of continuous STN DBS on muscle strength and movement speed. We will show that despite the fact that patients become more parkinsonian as measured by the Unified Parkinson's Disease Rating Scale, they become stronger and faster at making simple movements. These results will be discussed in the context of models of therapeutic efficacy that are predicated on the idea that that STN DBS reduces neuronal noise and thus both facilitates simple movements and the reduction of tremor. We will conclude with some recent work that tests the feasibility of using a closed loop system to activate and deactivate STN DBS depending on the amount of tremor a patient is experiencing.

Quantitative cerebral perfusion is a fundamental physiologic parameter that reflects the severity and progression of a broad range of pathologies. The Bookend MRI technique provides absolute quantification of cerebral blood flow and cerebral blood volume using dynamic susceptibility contrast MRI and T1 changes in normal white matter in relation to the changes in the blood pool after contrast injection. This technique has been shown reproducible, reliable and accurate. However, its original implementation consisted of a set of 3 consecutive MRI scans, requiring a cumulative scan time of about 4 minutes, as well as lengthy offline image postprocessing before obtaining the quantitative maps. A single MRI pulse sequence, Self-CALibrated Epi Perfusion Weighted Imaging (SCALE-PWI) sequence, allowing automatic Bookend image acquisition with inline image reconstruction has been developed and will be presented. This sequence eliminates the need for technologist training, provides the quantitative perfusion maps for physician review in a timely manner, and allows utilization of the Bookend technique in emergency settings. Several clinical applications of the Bookend technique, as well as some additional improvements, will also be discussed.

Brain Machine Interfacing (BMI) is an exciting new technology that allows direct connections to be made between the brain and a computer. While BMIs have thus far shown tremendous promise in routing brain commands around a spinal cord injury to control movement of a computer cursor or a robotic arm, our laboratory has focused on the potential of BMI to restore more natural-seeming movement directly to a paralyzed limb itself. Patients with spinal cord injury also lack proprioception, the ability to absorb information communicated very rapidly to the brain from sensors in the muscles. Even patients that are not paralyzed, who have nonetheless lost proprioception, make movements that are slow, poorly coordinated, and require great concentration. Existing BMIs rely exclusively on slower visual feedback, which may account, in part, for their as yet relatively limited performance as a practical solution for paralyzed subjects. My laboratory group, in experiments with monkeys, has developed a BMI that could allow patients with a spinal cord injury to regain voluntary control of their paralyzed muscles. We have further begun to develop an interface that will provide information to the brain, rather than extract information from it. By stimulating the brain with implanted microelectrodes, we hope to mimic normal proprioceptive feedback. Finally, we are investigating the adaptive changes that occur within the brain as the monkey adapts to these artificial interfaces. A process called Hebbian association, thought to underlie learning, normally causes the connections between neurons to be strengthened when they experience correlated patterns of activity. Relying on Hebbian association, we intend to use appropriately patterned stimulation to cause changes that would assist a monkey’s—and, we hope in the not too distant future, a human patient’s--adaptation to a BMI.

Magnetic resonance elastography (MRE) is capable of measuring the mechanical properties of living tissue by using externally introduced vibrations and phase contrast magnetic resonance imaging techniques. In conventional MRE, monofrequency shear wave excitation techniques are used. However, since biological tissue is highly dispersive due to its strong damping characteristics, the study of tissue rheology requires knowledge of wave propagation at multiple frequencies. The multifrequency-MRE method applies a superposition of multiple harmonics as the shear wave excitation signal. All vibrations are acquired simultaneously, which enables the determination of viscoelastic tissue parameters in one time-resolved MRE experiment. The viscoelastic properties of human brain and liver are determined in their in-vivo environment using several rheological models. A two-parameter fractional model demonstrates excellent stability and allows for combining the spectral information of the complex modulus acquired by multifrequency-MRE into two viscoelastic parameters that can be used for the diagnosis of various diseases such as hepatic fibrosis and MS.

Proprioception is a sense of position and movement of the body. It is constructed in the brain from inputs primarily from length and velocity receptors inside the muscles. Proprioception can be regarded as "inner vision" of the body which strongly contributes to all aspects of motor behavior. Beyond feedback response to external disturbances, it underlies inter-joint coordination, corrections to self-generated errors, motor learning and adaptation, integration of multi-sensory representations of the body and external space, and sense of agency and ownership of the body. I will review experiments that highlight the role of proprioception as corrective sensory feedback during voluntary movement and provide insight into organization of the neural control of goal-oriented arm movements. I will then discuss central proprioceptive processing in the brain and its possible disruption in Parkinson's disease.

Fractional calculus and heavy tailed stochastic processes have already proven useful to model anomalous diffusion/dispersion on the earth surface. Many open problems remain, including experimental efforts to verify power law statistics, incorporation of waiting times between particle movements, development of fractional models to explain multifractal behavior, tempered or truncated power laws, and other alternative models between Gaussian and power law.

Typical approaches in pharmacometric PK/PD modeling involve a step-wise evaluation of model structural elements. This approach ignores the potential for interaction across multiple levels in these types of models. Specifically, mathematical structural forms selected to represent the fixed effects components of these models can affect the selection of random effects structures and vice-versa. Our laboratory has evaluated two multi-objective genetic algorithm approaches to explore a more complete method for evaluating potential model structures and the typical fitness parameters used to judge model robustness. The first example utilizes a composite function for model "fitness" that is based on the -2 log likelihood function with penalties added. This global search is coupled with a local downhill search algorithm to enhance the possibility of identifying the best single solution in this space. The second example utilizes a non-dominated sorted genetic algorithm that optimizes along each of a number of objectives individually and identifies the non-dominated solutions that exist along Pareto-optimal fronts. The key objectives of interest can then be assessed by the "expert" individual to judge what model is preferable. This second approach permits more qualitative assessment of the outcomes of the model search strategy. Several examples from the population pharmacokinetic field are presented utilizing these approaches and are compared with the published results achieved using the standard methodologies.

David N. Ruzic is the Director of the Center for Plasma Material Interactions at the University of Illinois at Urbana-Champaign and was recently named as the Bliss Professor of Engineering by the College of Engineering. He is a professor in the Department of Nuclear, Plasma, and Radiological Engineering and affiliated with the Department of Electrical and Computer Engineering and the Department of Physics. He joined the faculty in 1984 after spending six months on the research staff at the Princeton Plasma Physics Laboratory. Prof. Ruzic has also served as an Assistant Dean and Associate Vice President at Illinois.
His current research interests’ include plasma processing for the microelectronics industry (deposition, etching, EUV lithography and particle removal), atmospheric-pressure plasmas for industrial applications (microwave and DBD discharges), and fusion energy research (liquid lithium for use as a plasma-facing component). His research group currently consists of 3 post-docs, 12 graduate students, and over 20 undergraduate research assistants as well as a technician and an administrative assistant. Combined government and industrial funding received in 2010 exceeded $1.5 million.
Prof. Ruzic is a Fellow of the American Nuclear Society and of the American Vacuum Society (AVS). He also serves as the Scientific Director for the International Union of Vacuum Congresses. He is the author of the AVS monograph, Electric Probes for Low Temperature Plasmas, numerous book chapters, patents, and over 130 refereed journal articles. He obtained his PhD and MS in Physics from Princeton University, and his BS degree in Physics and Applied Math from Purdue University. He really enjoys teaching and tries to blow something up during every lecture. He has been recognized as the most outstanding instructor in his Department, in his College and on the Campus through the years.

Protein evolution has most commonly been studied either theoretically, by analyzing the sequence of the protein, or experimentally, by resurrecting ancestral proteins in the lab and performing ligand binding studies to determine function. Thus far, structural and dynamic evolution have largely been left out of molecular evolution studies. Here we incorporate both structure and dynamics to elucidate the molecular principles behind the divergence in the evolutionary path of the steroid receptor proteins. We begin by determining the likely structure of three evolutionary diverged, ancestral steroid receptor proteins using the Zipping and Assembly Method with FRODA (ZAMF). Ourpredictions are within 1.9Å RMSD of the crystal structure of ancestral corticoid steroid receptor. Beyond comparing static structure prediction, the main advantage of ZAMF is that it allows us to observe protein dynamics. Therefore we can investigate differences in the diverged proteins’ available dynamic space. This dynamic analysis enables us to identify critical mutations that most affect dynamics, therefore it shows the critical mutations leading to a divergence in function. We observe evolutionary diverged proteins do not share the same dynamic subspace. In the second part of the talk we will discuss how to predict the foldable sequence from unfoldable ones through searching local nucleation sites using ZAMF. We analyze the designed WW sequences and predict the foldable sequences based on local contact probabilities with 75 % accuracy.

The Biomedical Imaging Center is a unit of the <http://www.beckman.illinois.edu>Beckman Institute for Advanced Science and Technology of the <http://illinois.edu>University of Illinois at Urbana-Champaign. The Center traces its heritage to the Biomedical Magnetic Resonance Laboratory founded at UIUC by Professor Paul Lauterbur, 2003 winner of the Nobel Prize in Medicine. The Center's goal is to conduct research and develop MRI technology that addresses questions ranging from the single cell to the complex inter-dependent systems. The 14.1T Varian microimaging system available in the BIC is one of only seven such magnets in operation in the world. Technical characteristics and capabilities of 14.1T MRI scanner, new accessories and developments will be discussed. The information about new design of RF coils, research objects and selected current projects will be presented.

We present a computationally efficient replicate optimizer (ReplicOpter ) method for flexible refinement of docking predictions that reflects observed motions within a protein's structural class. Using structural homologs, we derive deformation models that capture likely motions. The models or "replicates" typically align along a rigid core, with a handful of flexible loops, linkers and tails. A few replicates can generate a much larger number of conformers, by exchanging each flexible region independently of the others. In this way, 10 replicates of a protein having 6 flexible regions can be used to generate a million conformations of a molecule. While this has obvious advantages in terms of, the cost of assessing energies at every conformer is prohibitive, particularly when both molecules are flexible. Our approach addresses this combinatorial explosion, using key assumptions to compress the sampling by many orders of magnitude. In addition, we present a knowledge-based statistical model for allostery. Using experimental mutagenesis data on sidechain substitutions observed to disrupt cooperative binding, a predictive model is created based on the structures of effector bound and unbound proteins. Changes observed by Daily and Gray in solvent accessibility patterns between bound and unbound structures are observed to have predictive value. Interestingly, the most highly predictive features relate to structural stability and packing density, suggesting that long-range effects may result from a lack of local plasticity and an inability to accomodate effector binding locally. This hypothesis coincides and is consistent with observations made by Lu and Liang using structure-based perturbation techniques.

Bilateral (force reflecting) teleoperation allows human operators to determine the motion of a remote slave robot by moving a local master robot and feeling the forces reflected from the slave to the master. Such systems could be most useful for various applications, however, the unavoidable delay prevents truly transparent channel. We assert that understanding the human perception and control of delayed environment could facilitate the design of perceptually transparent telemanipulation. In this talk I will review our recent findings about perception of delayed stiffness and our human centered approach to transparency in teleoperation. I will start with a short introduction to computational motor control, and a brief overview of the studies in my laboratory, about predictive control in lifting task and about reverse-hysteresis in cyclic movements. I will then concentrate on a series of psychophysical experiments and computational modeling accounting for perception of delayed stiffness under various probing conditions. Finally, I‚lldescribe our three dimensional measure of transparency which considers perception as well as local and remote action. I‚ll conclude with a challenge called theTuring-like handshake test for motor intelligence.The studies in the computational motor control laboratory are supported by the United States-Israel Binational Science Foundation (BSF); by the National Institute for Psychobiology in Israel (NIPB); by the ministry of science (MOS);and by the Israel Science Foundation (ISF).

Rheumatoid arthritis (RA) is a chronic, debilitating autoimmune disease that afflicts ~1% of the general population. Despite recent advances in medical therapeutics, treatment of rheumatoid arthritis still represents an unmet medical need because of safety and efficacy concerns with currently prescribed drugs. In my talk I will describe two novel nanomedicines that are composed of phospholipid nanomicelles (SSM) incorporating campthotecin (C) and vasoactive intestinal peptide (VIP) as anti inflammatory drugs. Our results using these nanomedicines on a collagen induced mice RA animal model demonstrated that the drugs are targeted to the inflamed tissues to show enhanced anti inflammatory effects with hardly any toxicity. Therefore, we propose that CPT-SSM-(VIP) and SSM-VIP are promising targeted nanomedicines and should be further evaluated as safe, long-acting, disease-modifying agents for RA.

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Several different culture systems are available to study factors with potential therapeutic usefulness in the treatment of degenerative joint disease. Each has advantages and limitations. Cartilage explant culture for example, most resembles in vivo conditions and provides a system with fully development matrix. However, there is a high degree of variability between donor tissues and even within the same donor that make explant culture systems difficult to work with. An ideal system would retain cartilage characteristics, yet be capable of data with low intra- and intervariability. Tissue engineering combines the field of Engineering, Biology and Medicine to direct cell populations to form biological tissue substitutes. Such engineered tissues are specifically designed to restore normal function of injured or pathological tissues and thus provides a source of well-defined, homogenous tissue. Recent studies in our lab demonstrate that the patented alginate recovered chondrocyte (ARC) technology can be used to form in vitro a cartilaginous tissue that is viable and has good physicochemical properties. In addition to its use as an implant for repair of damaged and /or diseased cartilage, tissue produced using the ARC technology may have a role in the study of factors with the potential to modulate matrix metabolism and in drug discovery.

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Pancreatic adenocarcinoma is the 4th leading cause of cancer death in the United States, with a 5-year survival rate of only 5%. The inability of current clinical methods to accurately detect pancreatic cancer in its early stages leads to this dismal prognosis. To investigate whether tissue optical spectroscopy could potentially aid in early diagnosis and improve survival rates, a prototype clinical fluorescence and reflectance spectrometer was developed and employed in a pilot study to probe freshly excised human pancreatic tissues. Significant differences were observed in the optical responses of normal tissues, pancreatitis, and adenocarcinoma. Quantitative tissue-photon interaction models and tissue classification algorithms were developed and applied to successfully distinguish among these pancreatic tissue types. These studies suggest that multi-modal optical spectroscopy holds promise as a clinical method to differentiate among diseased and normal pancreatic tissues.

Our goal is to delineate the role of mechanical forces and oxidative stress in endothelial cell (EC) intracellu­lar signaling and gene expression. Our group discovered that cultured EC expo­sure to fluid shear stress repro­duces certain aspects of the reperfusion (RP)-induced endothelial injury, namely the nitric oxide (NO)/peroxynitrite-mediated inhibition of respiration and mitochondrial production of reactive oxygen species (ROS). Current work concentrates on the mitochondrial changes during hypoxia/reoxygena­tion (H/RO) or simulated ische­mia/re­per­fusion (I/RP), in order to better understand the mechanisms that lead to the EC dysfunction following I/RP of the heart. Following treatment, cultured ECs are stained with mitotracker and digital fluores­cent images are obtained. Morphologi­cal parameters are determined and used for quantitative compari­sons of the mitochon­drial network between treatments. We found that both H/RO- and I/RP-exposed ECs undergo changes in mito­chondrial morphology, and ROS and NO are responsi­ble for the I/RP-induced increase in mitochondrial fission. Since mitochondrial fission has been implicated in the induc­tion of cell apopto­sis, our studies suggest that, by controlling mitochon­drial network morphology, we may be able to lessen the EC injury following cardiac I/RP.

Spatial and temporal resolution and image quality in dynamic MRI are severely limited by physical constraints on the rate of acquisition. Perhaps the most challenging example and important dynamic MRI application, is cardiac MR (CMR) imaging. While CMRI is already a clinical tool, it does not offer sufficient temporal resolution, its spatial resolution is insufficient to discern small blocked arteries, and it requires long breath-holds that cannot be performed by infants or the sick. Similar challenges arise in functional brain imaging, in the imaging of the vocal tract during speech, and the imaging of joints during movement. Acquisition of additional dimensions of information in the presence of motion -- such as spectral, or diffusion tensor, further exacerbates the problem. We describe an explicit model-based methodology enabling more than an order-of-magnitude reduction in the acquisition requirements in both single and multiple-channel MRI, and providing guarantees on the quality of reconstruction subject to the modeling assumptions. Based on time-sequential sampling theory, the approach uses the models to (i) design a minimum redundancy acquisition sequence; and (ii) reconstruct a movie (cine) of the object. By adapting the model to the imaged subject, both acquisition and reconstruction are adaptive. Phantom studies with known ground truth, and in-vivo CMR experiments demonstrate unprecedented spatial and temporal resolutions.

The age-old awe that man has had for the heavens has driven almost all aspects of human culture and knowledge and resulted in technologies with generally positive, though occasionally negative effect. Arguably the most positive have taken place since Galileo recognized that the phases of Venus provided the evidence that confirmed the Copernican heliocentric system and cemented his position firmly as the “Father of Science”. From this moment on we had, at long last, a straightforward philosophical construct and language which enabled mankind to determine what is and is not “True”. Particularly important truths have resulted from the curiosity that humans have had for a detailed understanding of the way Universe works. This led to the development of astrophysics and the associated technologies that have been spun-off. Not least of these has been the telescope – from Galileo’s beautiful original design to the fantastic satellite-born devices put up by NASA. These have not only enabled us to observe the planets and stars more clearly but we have been able to see to the very edge of the Universe and make a plethora of discoveries about all aspects of the Universe from the occupants of the space between stars to the processes occurring deep inside stars. Perhaps the most fundamental advance based on space observations led to the development of Classical Mechanics in order to understand the motions of the planets and comets and concommitantly the development Calculus, one of the greatest of Mathematical achievements. As Quantum Mechanics developed along with Spectroscopy it was inevitable that we should start to study the atomic and molecular composition of heavenly bodies - first hot stars as well as cool comets. With the development of radiotelescopes, the very cold interstellar medium was found to be a veritable Pandora's Box, full to the brim with fascinating and exotic molecules, dust particles and also some highly puzzling material responsible for some as yet unidentified spectroscopic features. These latter are known as the Diffuse Interstellar Bands (DIBs) first observed in the 1920s.

Particularly fascinating, curious and crucial has been the role that the element carbon has played in almost every aspect of the development of our understanding of both the physical and natural sciences. The fact that the element is at all abundant is due to a curious set of coincidences involving its nucleosynthesis from helium in stars. If one furthermore adds into the overall carbon equation its uniquely profuse chemistry, ie Organic Chemistry, it is hard to conceive that life could be based on any other element. The most recent big surprise that the element had up its sleeve was the existence of C60, Buckminsterfullerene, the third well-defined form of carbon. The discovery was made serendipitously in 1985 during laboratory experiments which attempted to explain the chemical synthesis of some unusually long linear carbon chain molecules detected in the interstellar medium in the 1970’s. A second aim of these experiments involved curiosity as to whether the carriers of the DIBs might be long linear carbon chains. Interestingly the extraction of C60 in 1990 by Kraetschmer and Huffman resulted from experiments aimed at understanding another mysterious feature known as the 217nm hump and conjectured to also involve carbon – perhaps carbonaceous dust particles. The fact that this third, well-defined, form of carbon had been hiding in the shadows since time immemorial brings to mind the mysterious character lurking in the dark streets of Vienna, made famous by Orson Welles in the classic movie “The Third Man”. In fact we now know that the molecule forms fleetingly within sooting flames but is immediately destroyed as it passes through the flame barrier into an oxygen atmosphere. On the basis of such revelations the suggestion that C60 might exist in space and be responsible for the DIBs (Kroto & Jura) seemed an as good, if not a better, possibility than most other ideas that had heretofore been proposed. Especially compelling support for the idea that C60 existed in space lay in the fact that the original discovery was made serendipitously during laboratory experiments designed to simulate the atmospheric conditions in cool red giant carbon stars. This conjecture has just been confirmed by Cami et al who have found infra red bands in the spectra obtained by NASA’s Spitzer satellite telescope. The discovery also makes some recent work here at FSU on endohedral fullerenes, in which atoms are trapped inside the carbon cage, extremely relevant to certain anomalous isotope ratios observed in meteorites, in particular carbonaceous chondrites. This is yet another example of the remarkably synergistic relationship between terrestrial and space science. In these difficult times it lends useful support for the fundamental value of "Blue Skies" or perhaps more accurately “Black Skies” cross-disciplinary research. All these results taken together suggest that the 90 year-old mystery of the carrier of the DIBs might be close to being resolved at long last.

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Biological materials have incredible mechanical properties resulting from the complex arrangement of their structural constituents. Understanding the relationship between the structure and mechanical properties of these materials is crucial for developing new medical tools for the prevention and treatment of injuries and diseases. In this talk, I will give a brief survey of my experimental and theoretical research aimed at describing the mechanical behavior of collagenous tissues in vertebrates and chitin-based tissues in invertebrates by accounting for their structure. I will then present my modeling strategies for evaluating deformations of planar lipid bilayers, which represent the basic structures in cell membranes. The models are derived within a new theoretical framework for smectic A liquid crystals in which the usual director, which defines the average orientation of the lipid molecules, is not constrained to be normal to the layers. These models account for bending, compression, splay, tension of the lipid bilayers and their anchoring to substrates. The predictions agree qualitatively with experimental data; they suggest that the deformations of the lipid layers and the tilting of the lipid molecules are pronounced in regions close to the boundary of the supporting substrates. The deformations increase with increasing anchoring strength and decreasing surface tension.

12 -12:05pm - (Intro) Andreas Linninger
12:05 - 12:15pm - David Eddington
12:15 - 12:30pm - G Ali Mansoori
12:30 - 12:45pm - Jun Cheng
12:45 - 1pm - Larisa Adamian
1 - 1:15pm - Thomas Royston
1:15 - 1:30pm - Andreas Linninger

The goal of this talk is to provide an update on progress in the use of robotic devices in rehabilitation to enhance motor and unctional recovery in individuals following neurological injury. Surprisingly little technology is currently available to treat motor impairments following stroke and spinal cord injury, although many rehabilitation techniques are mechanical in nature and amenable to automation. An overview into the rationale underlying the use of such devices in rehabilitation will be presented, followed by a presentation of completed research on the use of specific robotic devices developed to enhance locomotor function following stroke or spinal cord injury. Based on current evidence, a re-examination of factors which maximize motor learning and neural recovery may be warranted to facilitate future development of robotic technology to enhance delivery of locomotor training.

A bit of history. Some most useful definitions. Approximation and the short-memory principle. Fractional differential equations (FDEs) and some methods of their analytical solution. Numerical solution: matrix approach to discretization of FDEs. Outline of some new fields of applications, including fractional-order systems and fractional-order controllers. Geometric and physical interpretations. Concluding remarks.

In this talk I will give an overview of a new approach to process control which is based on integrating the information system more closely with the physics of the process than what is done in typical process control applications. The theory combines the formalism of irreversible thermodynamics with the passivity theory of nonlinear control. This theory applies equally well a single process or a complex network of processes which results when groups of processes are combined. We show that in such complex systems we actually only need to control a very small subset inventories and flows to stabilize the entire network. The second law of thermodynamics is used to show that variables we do not control, the so-called zero-dynamics, stabilize due to viscous dissipation (friction) as long as the control and communication systems are properly designed. The minimum dissipation principle of thermodynamics is furthermore used to relate process control theory to optimization. Applications a glass production process and a fluid bed reactor for aking solar grade silicon will be discussed.

Blood flow in the brain is an important physiological quantity relating to vitality of brain tissue and performance of cognitive tasks. Current non-invasive methods to measure cerebral blood flow with magnetic resonance imaging (MRI) allow for the measurement of delivery of blood from feeding arteries and may be sensitive to disruptions in flow in pathways between where blood is tagged and where it is measured. Recently we have revived old techniques and developed new techniques for localized imaging of microvascular blood flow in the brain. In addition to flow quantification, our techniques allow for measurement of structural arrangement of microvasculature. In this talk, we will show how microvascular blood flow can be quantified in brain tissues using non-invasive methods of FENSI and diffusion weighted imaging.

Endothelial cells (ECs) are integral to the characteristically dense vasculature of pancreatic islets. This vasculature enables accurate blood-glucose sensing and rapid secretion of insulin into the blood stream. How EC and beta cells interact to affect glucose-stimulated insulin secretion is an actively debated topic. However, long-term studies in the ex vivo tissue are limited by the loss of the ECs over a period of days in traditional culture. We postulate that the ECs die in part from an absence of media exchange normally provided by blood flow. To test the role of media exchange on ECs, we created microfluidic devices capable of supplying a range of fluid flow-rates to ex vivo islets. Our protocol controls temperature, pH and bubble formation using two hot plates and a syringe pump for long-term desk top experimentation. We show that Islets in these devices experience enhanced exchange of media to the center of the islet due to a flow-dependent pressure differential across the tissue. We further examined the morphological response of islet-ECs to a variety of flow-rates for 24 and 48 hours using these devices combined with immunofluorescence imaging. Our results show more than twice the average percent area and connectivity of the ECs in islets treated in the device as compared to no-flow controls stored in traditional cell culture. Using flow of media with different viscosities, we also show that the differences in morphology are due to media exchange and not shear-activated survival. We are currently determining the effect of fluid-flow on the survival of beta cells by measuring the glucose stimulated calcium and insulin responses. Overall, our data indicate that flow in a microfluidic device provides a reliable co-culture environment enabling the long-term study of cell biology in the pancreatic islet. Our data also illustrate the utility of microfluidic devices for combined long-term culture and assessment using quantitative fluorescence microscopy of the tissue.

Our lab's goal is to understand cell signaling and information processing in biological cellular neural networks in the brain, and how the break down of these processes contribute to neurological disorders. A broad goal is understanding how the complex dynamics of the brain at a systems level emerge from (often stereotyped and ubiquitous) molecular and cellular foundational processes. We approach these questions by developing and using experimental and computational methods in order to reverse engineer how the nervous system is built, so that we can understand how it functions. Our lab operates at the interface between experiment, theory, and computation. Experimentally we rely on optical imaging methods, as well as traditional molecular and cellular neurobiology methods. More technologically intensive, we are very engaged in the development of nanotechnologies as biosensors for neural cells in order to study both individual cells and neural circuits and networks. Theoretically and computationally we are developing mathematical and physical models for identifying and mapping functional signaling and information propagation in biological neural networks, and neurophysiological and biophysical models that provide mechanistic insights. Computer science and engineering comes into all of this by providing the theory and tools necessary to computationally implement the models, and our lab is engaged in using and pushing the limits of graphics processing unit (GPU) computing in systems neuroscience. This talk will discuss some of the challenges associated with these goals, and provide an update on the development of our methods and scientific progress to date.

The nominal contact stresses in so-called ultramild wear tribosystems (< 1 nm/h) like head/cup-combinations of artificial hip joints, hip resurfacings or spine discs might have several maxima at some tens of MPa. Even though for hip joints anz suboptimal positioning could increase these stresses by an order of magnitude they are still too small to relate directly to the marked alterations of microstructures found on and under worn surfaces. Now the above tribosystems are characterized by differing lubrication regimes within either the boundary- or the mixed-regime. Thus the interaction of contacting sliding bodies is characterized by solid-solid contacts resulting in the fact that contact loads are taken predominantly by asperities covered with the remains of fluid films, absorbed molecules, tribochemical reaction layers and/or agglomerates of wear particles. This chaotic surface structure from the constituents of head, cup, pseudosynovia and the human body itself is called "tribomaterial" and differs for each tribosystem. This contribution shows that one can understand the dynamics of such contacts and the omplicated interaction of wear mechanisms under ultramild sliding wear by means of experimental work and simple computer simulations.

Human mesenchymal stem cells (hMSCs) are a promising cell source for cartilage therapies and tissue engineering. To prepare hMSCs ex vivo for cartilage regeneration applications, a great deal of research effort has been focused on maintaining the multi-potency of hMSCs and improving hMSC chondrogenesis. Physical and chemical cues in ex vivo culture instruct hMSC activities, and the biological response of hMSCs in pre-differentiation culture, instructed by the environmental cues, affects the regulation of subsequent cell differentiation. We culture hMSCs in polymeric nanofibrous matrix that is structurally similar to collagen fibers, and the cells cultured in the matrix show their MSC phenotype and the enhanced multi-differentiation capability. In addition, we study the effect of fibroblast growth factor-2 (FGF-2) and glucose on the chondrogenic potential of pre-differentiation hMSCs. Our result shows that FGF-2 and glucose are able to prime pre-differentiation hMSCs for enhanced chondrogenesis through modulating the activity of SOX-9 transcription factor, and up-regulating protein kinase C (PKC) and the transforming growth factor-beta (TGF - beta) signaling pathway, respectively.

Other lectures in this series will be given on Dec 1 on epilepsy.

Our research is focused on tumor oxygenation as a prognostic factor for radiation treatment outcome. We use pulse EPR imaging to define tissue oxygenation and MRI for tumor localization. In the future we see oxygen imaging as a common tool in hospitals used for image guided therapy.

Increasing evidence suggests that mechanics of an adherent cell plays a critical role in its biological functions. However, it is not clear if, downstream from the initial site of activation on the cell surface, mechanical signaling is similar to or different from a growth factor induced signaling. Recent findings from our laboratory demonstrate that integrin-mediated rapid mechanochemical transduction in the cytoplasm is substantially different from growth factor induced signaling. In addition, we show that in the absence of soluble factor stimulation, cyclic loading of the same amplitude can induce cell spreading in mouse embryonic stem cells but not in differentiated cells. The sensitivity of spreading to force was dictated by cell softness, since embryonic stem cells are ~10 fold softer than their differentiated counterparts, suggesting that it is the stress-induced intracellular deformation of the cytoskeleton that dictates cell spreading response. A local stress via focal adhesions alone can induce embryonic stem cells to differentiate, in the absence of soluble differentiation factors. We also show that pluripotency and differentiation of embryonic stem cells are intimately dependent on substrate stiffness. Both tractions and stiffness of the embryonic stem cell colonies increase with substrate stiffness, accompanied by downregulation of Oct3/4 expression, a pluripotency marker. In sharp contrast to the mouse embryonic stem cells seeded on rigid substrates, the cells cultured on the soft substrates that match the intrinsic stiffness of the mouse embryonic stem cells and in the absence of exogenous Leukemia Inhibitory Factor, can generate homogeneous undifferentiated colonies, maintain high levels of Oct3/4, Nanog, and Alkaline Phosphatase activities, and efficiently form embryoid bodies and teratomas. Our findings demonstrate that mouse embryonic stem cell self-renewal and pluripotency are maintained on soft substrates via the biophysical mechanism of facilitating generation of low cell-matrix tractions. These results suggest that mechanics and mechanotransduction of anchorage-dependent cells are indispensable in physiological functions of living cells.