Mathematical Biology Seminar - Fall 2021
Seminars are typically held on Wednesdays at 1:00PM in-person in CULM 611 or online via Zoom. Please note the location listed in the schedule below.
For questions about the seminar schedule, please contact Enkeleida Lushi.
September 8Lin Han, NanoBioMechanics Laboratory, Drexel University Location: CULM 611 Type V Collagen Regulates the Growth and Remodeling of TMJ Condylar Cartilage: A Fibrous-Hyaline Hybrid Temporomandibular joint (TMJ) disorder is marked by irreversible breakdown of condylar cartilage, and a major roadblock of regenerative medicine is the limited molecular-level understanding of its extracellular matrix (ECM). The condylar cartilage contains a unique ECM integrating a collagen I-dominated fibrous layer covering a collagen II-rich hyaline layer. Our study focuses on the role of collagen V, a primitive collagen that regulates the initial assembly of collagen I fibrils. In collagen V-deficient mice, condylar cartilage develops impaired fibril assembly and biomechanical properties in both layers. Notably, loss of collagen V also leads to reduced proliferation and canonical Wnt/β-catenin signaling in the progenitor cells of the fibrous layer. These results highlight a new role of collagen V in mediating progenitor micro-niche and mechanoregulation of TMJ growth, and establish collagen V as a new biomaterial candidate for promoting tissue regeneration. Host: Yuan-Nan Young |
September 22Danny Barash, Ben Gurion University Location: CULM 611 Efficient Numerical Methods for the Solution and Parameter Estimation in Multiscale Models of Hepatitis C Viral Kinetics Age-structured multiscale models have been developed to study viral kinetics. However, they are notoriously difficult to solve and when utilizing this type of models parameter estimation presents a challenge. Here, we investigate the numerical solutions of a multiscale model of hepatitis C virus (HCV) dynamics during antiviral treatment and compare them with analytical approximations. First, we show that considerable gain in efficiency can be achieved by using adaptive stepsize methods over fixed stepsize methods for simulating realistic scenarios when solving multiscale models numerically. We compare between several numerical schemes that are suitable and show the benefit of using the Rosenbrock method, an implicit adaptive stepsize method that is both efficient and stable. Second, we address parameter estimation by constrained optimization and show that derivative-free methods such as Powell's constrained optimization by linear approximation (COBYLA) provides an efficient procedure for this task. For simulating trajectories of viral hepatitis progression or decline in patients who are treated with antiviral drugs, we developed a simulator with a graphical user interface. Machine learning of data from patients is now being incorporated. Host: Casey Diekman and Horacio Rotstein |
October 6Ebru Demir, Mechanical Engineering in Lehigh University and Santa Clara University Location: WebEx Locomotion at Small Scale: Microswimmers for Biomedical Applications Bioinspired artificial microswimmers are promising candidates to realize coveted biomedical applications such as targeted drug delivery and minimally invasive surgery. However, swimming at small scales is a challenge onto itself, as the physics of locomotion is entirely different due to the forces and torques acting on small scale swimmers are magnified up to multiple magnitudes. At this scale, time reversible motions cannot achieve locomotion in Newtonian fluids at all. Furthermore, biological fluids are complex fluids, therefore challenges introduced by non-Newtonian fluid dynamics need to be addressed as well. One method used by researchers to address these challenges is to decipher the physics of locomotion in these challenging environments, and design physics-informed gaits and swimmers. More recently, alternative strategies that leverage machine learning techniques started to be explored to achieve locomotion by creating smart robots that learn from their interaction with the environment. This talk will address both “physics informed locomotion” and “smart locomotion” at small scale. I will present examples from my own research findings demonstrating: Host: Enkeleida Lushi |
October 20Klavdia Zemlianova, Center for Neural Science, NYU Location: WebEx Biophysical Mechanisms for Keeping Time The ability to estimate and produce appropriately timed responses is central to many behaviors including speaking, dancing, and playing a musical instrument. A classical framework for estimating or producing a time interval is the pacemaker-accumulator model in which pulses of a pacemaker are counted and compared to a stored representation. However, the neural mechanisms for how these pulses are counted remains an open question. The presence of noise and stochasticity further complicate the picture. I will present a biophysical model of how to keep count of a pacemaker in the presence of various forms of stochasticity using a system of bistable Wilson-Cowan units asymmetrically connected in a one-dimensional array; all units receive the same input pulses from a central clock but only one unit is active at any point in time. With each pulse from the clock, the position of the activated unit changes thereby encoding the total number of pulses emitted by the clock. This neural architecture maps the counting problem into the spatial domain, which in turn translates count to a time estimate. Lastly, I will show how this model fits into a larger model for keeping time in rhythmic contexts. This is joint work with Amitabha Bose at NJIT and John Rinzel at NYU. Host: Amit Bose |
November 3Nicholas Battista, Department of Mathematics, The College of New Jersey Location: Webex Exploring the Sensitivity of Jellyfish Locomotion to Variations in Scale, Frequency, and Duty Cycle Aquatic organisms use diverse mechanisms for locomotion depending on their shape and size. Some of the world's most efficient swimmers, jellyfish, swim by using jet propulsion, via contractions of their bell. Their morphology (size and shape) and kinematics place them in an interesting fluid dynamics regime - the so-called intermediate Reynolds number regime, where both inertial and viscous forces are important. The effectiveness of a jet propulsive gait is highly dependent on a number of parameters, such as the frequency and kinematics of contraction as well as its bell size and shape. In this work we will dive into exploring how variations in these parameters affect jellyfish swimming performance (forward speed and energetic cost) using global sensitivity metrics. Bio: Nicholas Battista did his undergraduate studies in math and physics at RIT. He earned a PhD in mathematics from the University of North Carolina at Chapel Hill. While at UNC he participated in a science policy program through the American Association for the Advancement of Science (AAAS), with a goal to ensure a safe, sustainable, and equitable clean water future. He's now an assistant professor in Math and Stats at The College of New Jersey, where he works with undergraduate students on a variety of problems in biomechanics, using a blend of math and computational modeling combined with physical and organismal experiments. Some areas they work on include aquatic locomotion, opioid epidemics, heart development, and bio-inspired design. Host: Enkeleida Lushi |
November 10Peter Balogh, Mechanical and Industrial Engineering, NJIT Location: CULM 611 Large-Scale Simulation of Cellular-Scale Flows in the Microcirculation In the human body, complex flow phenomena in the microcirculation play central roles in maintaining our health and facilitating growth. Blood flow through the microcirculation is responsible for transporting oxygen throughout our bodies and nutrients to our organs, while the lymphatic circulation maintains the body’s fluid-balance and circulates cells to fight infection. These systems can be hijacked by diseases like cancer which use the microcirculatory transport pathways to spread throughout our bodies. Complex flow simulations offer significant potential to provide new insights into such processes, although modeling which resolves the relevant features is highly non-trivial. In this talk I will give an overview of a method I developed for large-scale simulation of micro-scale biophysical flows using high performance computing. I will discuss some things I have been able to simulate using it, and some novel phenomena uncovered as related to microvascular network blood flow. I will also discuss modeling transport of a specific cancer’s cells with this type of approach, and plans for coupled blood and lymphatic circulation modeling to enable new insights into mechanisms of metastatic spread. Bio: Peter Balogh received his B.S. in mechanical engineering from the University of Notre Dame in 2004, and his Ph.D. in mechanical engineering from Rutgers University in 2018 working with Prosenjit Bagchi. He did a postdoc at Duke University in the biomedical engineering department, and is currently an assistant professor at NJIT in mechanical engineering. As a graduate student Peter developed a method for modeling flows of 3D biological cells through highly complex geometries, which he has used to provide new and novel insights into the microhydrodynamics of blood flow. He was awarded the 2019 Andreas Acrivos Dissertation Award in Fluid Dynamics from the American Physical Society, and the BD-STEP postdoctoral fellowship from the National Cancer Institute and VA Hospitals. His work has been featured on the cover of the Biophysical Journal, was selected as a Feature Story for the Texas Advanced Computing Center, and was featured in the press for the National Science Foundation. Peter’s research interests include computational fluid dynamics modeling of biological flows in the microcirculation, numerical methods for complex fluid-structure interfaces, and code development for high performance computing. While a mechanical engineer at heart, his research is highly multidisciplinary, and he thoroughly enjoys learning about and investigating fluid mechanical phenomena using ideas from engineering, physics, and biology via high performance computing. Host: Yuan-Nan Young |
November 17Seth H. Weinberg, Biomedical Engineering, Ohio State University Location: WebEx Modeling of Nanoscale Structure and Cell-Cell Coupling in Cardiac Tissue Cell-cell coupling between cardiac cells has a well-known and clearly defined role within cardiac tissue, both transmitting mechanical forces and electrical currents between cells. However, the underlying structures that regulate these processes are still not fully understood. The intercalated disk (ID) is a specialized subcellular region that provides electrical and mechanical connections between myocytes in the heart. Recent studies have shown that sodium (Na+) channels, the primary current responsible for cardiac excitation, are preferentially localized at the ID, and that perturbations of ID structure alter cardiac conduction. This suggests that the ID may play an important, active role in regulating conduction. However, the structures of the ID and intercellular cleft are not well characterized and, to date, no models have incorporated the influence of ID structure on conduction in cardiac tissue. In this talk, I will outline our approach to generate realistic finite element model (FEM) meshes replicating nanoscale of the ID structure, based on experimental measurements from transmission electron microscopy images. We then integrated measurements of the intercellular cleft electrical conductivity, derived from the FEM meshes, into a novel cardiac tissue model formulation. FEM-based calculations predict that the distribution of cleft conductances is sensitive to regional changes in ID structure, specifically the intermembrane separation and gap junction distribution. Tissue-scale simulations predict that ID structural heterogeneity leads to significant spatial variation in electrical polarization within the intercellular cleft. Importantly, we found that this heterogeneous cleft polarization regulates conduction by desynchronizing the activation of postjunctional Na+ currents. Further, we found that disruption of local ID nanodomains can either slow or enhance conduction, depending on gap junctional coupling strength. Our study therefore suggests that ID nanoscale structure can play a significant role in regulating cardiac conduction. Host: Victor Matveev |
December 1Hyunjoong Kim, Mathematics, University of Pennsylvania Location: CULM 611 Intercellular Communication by Direct Contact: Is it Better than Diffusion? Why do organisms utilize different mechanisms for the same intercellular communication? For example, different mechanisms are used for the same Drosophila development process. Diffusive molecule gradients are used for determining the head and tail (Bicoid) and direct contact mechanisms mediated by signaling protrusions are observed in the air-sac primordium. One hypothesis is that the efficient communication method is evolutionarily preferred, which depends on (i) the distance between a source and a target cell and (ii) the shape of the target cell. In this talk, we quantitatively compare the two representative models by the cost-benefit analysis. Especially for the direct contact model, we find an optimal protrusion initiation rate minimizing the cost-benefit ratio. Then we determine which model is evolutionarily preferred under conditions. Host: James Maclaurin |
Updated: November 29, 2021