Biomedical Modeling Research Overview

Benveniste, Helene

Chair, Medical Department

Benveniste@bnl.gov

Summary : Benveniste's Laboratory focuses on (1) exploring, characterizing and understanding diagnostic MR contrast parameters suitable to visualize neuro-pathology in neurodegenerative diseases; (2) investigate transgenic animal models were specific genes are modified to understand mechanism(s) and treatment of addiction and of drug-induced neurotoxicity using high resolution MR imaging, (3) advance technologies in molecular MR imaging.

Bluestein, Danny

Professor

Danny.Bluestein@sunysb.edu

Summary : Despite major progress, cardiovascular diseases remain the leading cause of death in the western world. One of the major culprits in cardiovascular disease and in devices designed to treat or restore impaired cardiovascular function is the non-physiologic flow pattern that enhances the hemostatic response mainly through platelet activation. Platelets have long been regarded as the preeminent cell involved in physiologic hemostasis and pathologic thrombosis. An innovative technique for measuring flow induced platelet activation has been developed, and its utility demonstrated in experiments conducted in recirculation devices (models of arterial stenosis, Left Ventricular Assist Device (LVAD), and mechanical heart valves). The mechanisms by which the non-physiologic flow patterns induce platelet activation and generate free emboli, that enhance the risk of cardioembolic stroke, was demonstrated in vivo with mechanical heart valves implanted in the sheep model. The results of this research will aid in elucidating physical forces that regulate cellular function in flowing blood, and may be applied to improve the design of blood recirculating devices and to develop more potent drugs for treating cardiovascular diseases.

Carlson, Josh

Research Assistant Professor

carlsonjm79@gmail.com

Summary : The human brain is highly tuned for detecting salience within one’s environment. In particular, social signals of threat such as fearful facial expressions are preferentially processed and automatically capture observers’ attention. Indeed, these social signals are so powerful that they can influence behavior even when subliminally processed. Much of my research is aimed at understanding the neural mechanisms underlying salience detection within low signal-to-noise environments including subliminal processing conditions. Furthermore, my research examines how differences in brain activity relate to individual differences in one’s ability to detect salience. The hope is that by understanding the brain mechanisms underlying individual differences in human behavior clinicians will be able to better focus treatment efforts for psychopathological behaviors. Functional magnetic resonance imaging (fMRI), structural MRI, electroencephalogram event-related potentials (EEG/ERP), genetics, and peripheral physiology (e.g., cortisol and heart rate) are all utilized in this research.

Chon, Ki

Professor

Ki.Chon@sunysb.edu

Summary : The cardiac autonomic nervous system is responsible for maintaining proper homeostasis, or balance, of the cardiovascular system. One of our major areas of research is to detect, quantify, and interpret differences in dynamic characteristics of the cardiac autonomic nervous system between normal and diseased subjects, in an attempt to find a marker for increased risk of sudden cardiac death. Identifying and quantifying differences in the dynamic characteristics of autonomic function between normal and diseased conditions may lead to a better understanding of the role of autonomic function imbalance in diseased conditions, and should have important clinical diagnostic and prognostic applications. Another active research area is the development of computational modeling approaches to understand differences in dynamics of renal autoregulatory mechanisms between normotensive and hypertensive conditions. For both areas of research, we are developing novel linear and nonlinear signal processing techniques that can be successfully applied to achieve the research objectives.

Einav, Shmuel

Professor

seinav@sunysb.edu

Summary : The primary role of this laboratory is to study basic physiological flow phenomena, both experimentally and numerically, as well as cellular and tissue engineering as applied to the vascular system. and to suggest ways of improving the functioning of cells, tissues and organs in the body. These physiological flows include blood flow in the heart, blood flow in arteries, veins and the microcirculation, air flow in the respiratory airways, and urine flow in the kidney and urethra. This laboratory simulates systems through the use of computers, assisting life scientists to better understand physiological functions without having to rely entirely on living systems as experimental models. The use of mathematical analysis helps minimize animal experimentation. Other projects are the investigation of hemodynamics as a regulator of vascular biology, the mathematical modeling of the dynamic response of mammalian cells, the role of flow and the associated shear stress on vascular endothelial biology, prosthetic circulatory devices and the tissue engineering of blood vessel substitutes. The laboratory is also engaged in the evaluation of critical conditions that lead to failure of biological organs, such as the heart and the coronary circulation, failure of circulatory prosthetic devices as stents, heart valves and grafts. To facilitate in vitro and in vivo studies, the laboratory develops new investigative techniques, noninvasive diagnostic methods, and advance, multi-dimensional numerical modeling.

Judex, Stefan

Professor

Stefan.Judex@sunysb.edu

Summary : Research in this laboratory focuses on the identification of precise parameters that define skeletal tissue quantity and quality and their perturbation to applied physical stimuli. To this end, state of the art imaging techniques (e.g., microCT or synchrotron infrared spectroscopy) are combined with molecular (e.g., RT-PCR), genetic (e.g., QTL), and engineering techniques (e.g., finite element modeling) to determine genes, molecules, forces, as well as chemical and structural matrix properties. An example for a recent study includes the demonstration that extremely small amplitude oscillatory motions (~ 100µm), inducing negligible deformation in the matrix, can serve as an anabolic stimulus to osteoblasts in vivo, producing a structure that is mechanical stronger and more efficient to withstand forces. Recent results also indicate that there is not only a genetic basis for bone architecture, but also that the sensitivity of bone tissue to both anabolic and catabolic stimuli is influenced by subtle genetic variations. The identification of the specific chromosomal regions that modulate this differential sensitivity is in progress. Clinically, our studies may lead to the development of effective prophylaxes and interventions for osteoporosis, without side-effects and tailored towards the genetic make-up of an individual.

Kaufman, Arie E.

Professor

Arie.Kaufman@sunysb.edu

Summary : Arie Kaufman is the director of the Center of Visual Computing (CVC) and the director of the Cube project for volume visualization supported by the National Science Foundation, Department of Energy, Office of Naval Research, Hughes Aircraft Company, Hewlett-Packard Company, Silicon Graphics Company, Howard Hughes Medical Institute, and many others. His research interests include computer graphics and specifically computer graphics architectures, algorithms, and languages; visualization including volume visualization and scientific visualization; user interfaces; virtual reality; and multimedia. Kaufman is the editor-in-chief of the IEEE Transaction on Visualization and Computer Graphics. He has lectured widely and published numerous technical papers in these areas, including the IEEE tutorial book on Volume Visualization. He has been the papers chair and program cochair for Visualization 1990-1994 and the chairman of the IEEE CS Technical Committee on Computer Graphics.

Mitra, Partha

Professor

mitra@cshl.edu

Summary : I am interested in gaining a fundamental understanding of the behavior of complex biological systems, both from a mechanistic, physico-chemical perspective, and from an engineering perspective emphasizing function. I am also interested in applying this knowledge to help improve therapies for brain disorders. My research combines a number of approaches, including theoretical work, informatics, and experimental work. My theoretical interests are primarily in formalizing the treatment of biological function using ideas and methods from engineering. The informatics component of my research is devoted to the development of computational tools for analyzing neurobiological data, particularly electrophysiological data from experiments designed to probe cognitive phenomena. In addition, I am working on building knowledge bases to integrate information from the neuroscientific literature, both for the research and medical communities. I have an experimental research program studying memory formation in the fruitfly, integrating information across genetic, neural and behavioral levels. In collaborative research, I study song development in the zebra finch. My research is highly interdisciplinary and has a broad scope. I am also interested in the communication of science to a general audience.

Mueller, Klaus

mueller@cs.sunysb.edu

Summary : Klaus Mueller's areas of interest are medical, scientific and information visualization, visual analytics, medical imaging, computer graphics, virtual and augmented reality, and high-performance computing. He has pioneered the use of programmable commodity graphics hardware boards (GPUs) for the acceleration of a wide variety of computer tomographic (CT) reconstruction algorithms and medical physics phenomena. Applications include diagnostic imaging, radiotherapy, electron microscopy, ultrasound tomography for breast mammography, and others. In the visual analytics area he works on devising new high-dimensional data visualization frameworks and combining them with statistical pattern recognition and machine learning to create intuitive interactive analytical reasoning environments for medical professionals. He is also working towards a comprehensive visual data mining environment for neuroscientists, called BrainMiner, to enable a more targeted and experiential derivation of brain functional models from large collections of knowledge and data.

Qin, Yi-Xian

Professor

Yi-Xian.Qin@sunysb.edu

Summary : Early diagnostic of osteoporosis allows for accurate prediction of fracture risk and effective options for early treatment of the bone disease. A new ultrasound technology, based on focused transmission and reception of the acoustic signal, has been developed by Dr. Qin and his team which represents the early stages of development of a unique diagnostic tool for the measure of both bone quantity (density) and quality (strength). These data show a strong correlation between non-invasive ultrasonic prediction and micro-CT determined bone mineral density (r>0.9), and significant correlation between ultrasound and bone stiffness (r>0.8). Considering the ease of use, the non-invasive, non-radiation based signal, and the accuracy of the device, this work opens an entirely new avenue for the early diagnosis of metabolic bone diseases.

Rizzo, Robert

Assistant Professor

rizzorc@gmail.com

Summary : Rob Rizzo works in Computational Structural Biology. His research group seeks to understand the atomic basis for molecular recognition for specific biological systems involved in human disease such as HIV/AIDS, cancer, and influenza with the ultimate goal of developing new and improved drugs. Computational methods are used to model how molecules interact at the atomic level with a given drug target. The resultant 3D structural and energetic information is used to quantify and rationalize drug-binding for known systems and to make new predictions.

Rubin, Clinton

Distinguished Professor & Chair

Clinton.Rubin@sunysb.edu

Summary : Encouraging results show that the application of extremely low level strains to animals and humans will increase bone formation, and thus may represent the much sought after "anabolic" stimulus in bone. More than 15 years of research into non-invasive, non-pharmacological intervention to control osteoporosis, was referenced in Dr. Rubin's paper published in the journal Nature (August 9, 2001; 412:603-604). Dr. Rubin's studies suggest that gentle vibrations on a regular basis will help strengthen the bones in osteoporosis sufferers and increase bone formation. In his study, adult female sheep treated with gentle vibration to their hind legs for 20 minutes daily showed almost 35% more bone density. Clinical trials have been completed on post-menopausal women, children with cerebral palsy, and young women with osteoporosis, all with encouraging results. In expanding the research platform into other physiologic systems, current work demonstrates that these low-level signals influence mesenchymal stem cell differentiation, such that their path to adipocytes is suppressed, and markedly reduces adipose tissue.

Skiena, Steven

Professor

skiena@cs.sunysb.edu

Summary : computational biology, combinatorial computing environments, and combinatorial algorithms and data structures

Strey, Helmut

Associate Professor & Graduate Program Director

Helmut.Strey@sunysb.edu

Summary : Nature's ability to assemble simple molecular building blocks into highly ordered materials, such as those found in cell membranes, cell nuclei, cytoskeleton, cartilage, or bone presents many fascinating and unanswered questions. We are interested in how to tune the interactions of water-soluble building blocks so as to induce their self-assembly into useful microstructures much needed for the next generation of controlled drug delivery, biosensors and DNA sequencing applications. In particular, we are working on long-range ordered polyelectrolyte-surfactant microemulsions that are used as templates for solid nanoporous materials using polymerization and/or cross-linking strategies. Such materials, because of their well-ordered porous structure, will allow more efficient molecular separation and drug delivery. In addition, we are developing biosensors that are based on biopolymer chiral liquid crystals and quantum dot colloidal crystals. In both cases the softness of the systems allows the induction of a strong optical response to external stimuli. Such sensors should be able to quantitatively detect and measure analyte concentrations at hormonal levels.

Vaska, Paul

Professor and Scientist

vaska@bnl.gov

Summary : Medical imaging techniques have undergone substantial growth in recent years, in both the research and clinical arenas. The standard anatomical imaging modalities of computed tomography (CT) and magnetic resonance imaging (MRI) have been complemented by quantitative functional approaches like positron emission tomography (PET) and single photon emission computed tomography (SPECT). Our lab develops new instrumentation and processing techniques not only to enhance the functional capabilities of PET, but also to combine it with synergistic modalities such as MRI to provide unprecedented, multidimensional information for cancer diagnosis, brain research, and many other applications. We have developed a miniaturized brain scanner for rodents (RatCAP) which avoids the potentially confounding effects of general anesthesia in rat brain studies, and even allows for the simultaneous study of behavior along with neurochemistry by PET. We have also developed new approaches for very high spatial resolution in PET, including a solid-state imager using cadmium zinc telluride (CZT) which achieves sub-mm resolution, and a monolithic scintillator detector with depth-encoding capability via a novel maximum likelihood positioning algorithm. And we have developed multiple imaging systems for simultaneous imaging with PET and high-field MRI, including a rodent brain scanner, a whole-body rodent system, and a prototype clinical breast imager. The research encompasses the development of new detector materials and concepts, low-noise microelectronic signal processing, high-throughput data acquisition methods, Monte Carlo simulation, and new data processing techniques to optimize the extraction of quantitative information from the PET data.