Event type: Seminar

Our airways are continuously exposed to potentially harmful particles like dust and viruses. The first line of defence against these pathogens is a network of millions of cilia, whip-like organelles that pump flows by beating over a thousand times per minute. In this talk, I will first discuss the connection between local ciliary architecture and the topology of the flows they generate. We image the mouse airway from the sub-cellular (nm) to the organ scales (mm), characterising quantitatively its ciliary arrangement and the resulting flows. Interestingly, we find that disorder in the ciliary alignment can actually be beneficial for this pathogen clearance [1]. Second, I would also like to discuss how systems can be driven out of equilibrium by such active carpets. Combining techniques from statistical and fluid mechanics, I will demonstrate how we can derive the diffusivity of particles near an active carpet, and how we can generalise Fick’s laws to describe their non-equilibrium transport [2]. These results may be used for designing self-cleaning materials, much like our airways. [1] Ramirez San-Juan, Mathijssen et al., “Multi-scale spatial heterogeneity enhances particle clearance in airway ciliary arrays”, Nature Physics 16, 958–964 (2020) [2] Guzman-Lastra, Löwen & Mathijssen, “Active carpets drive non-equilibrium diffusion and enhanced molecular fluxes”, in press, Nature Communications (2021) Note: We also have an informal discussion session after the seminar. Please stay in the Zoom seminar room to chat together with Professor Arnold Mathijssen!

Inherent fluctuations may play an important role in biochemical and biophysical systems when the system involves some species with low copy numbers. This talk will present the recent work on the stochastic modeling of reaction-diffusion processes in glucose metabolism. The first part of the talk introduces a compartment-based model for a simple glycolytic pathway using a continuous-time Markov jump process, which describes system features at different scales of interest. Then, we will see how the multiscale approximate method reduces the model complexity. We will briefly discuss how the compartment size in the spatial domain can affect the spatial patterns of the system. In the second part of the talk, I will show another example for glucose metabolism where we see different-sized enzyme complexes. We hypothesized that the size of multienzyme complexes is related to their functional roles. We will see two models: one using a system of differential equations and the other using the Langevin dynamics.

A multi-electrode array-based application for the long-term recording of action potentials from electrogenic cells makes possible exciting cardiac electrophysiology studies in health and disease. With hundreds of simultaneous electrode recordings being acquired over a period of days, the main challenge becomes achieving reliable signal identification and quantification. We set out to develop an algorithm capable of automatically extracting regions of high-quality action potentials from terabyte size experimental results and to map the trains of action potentials into a low-dimensional feature space for analysis. Our automatic segmentation algorithm finds regions of acceptable action potentials in large data sets of electrophysiological readings. We use spectral methods and support vector machines to classify our readings and to extract relevant features. We show that action potentials from the same cell site can be recorded over days without detrimental effects to the cell membrane. The variability between measurements 24 h apart is comparable to the natural variability of the features at a single time point. Our work contributes towards a non-invasive approach for cardiomyocyte functional maturation, as well as developmental, pathological, and pharmacological studies. This is joint work with Viviana Zlochiver, Stacie Kroboth (Advocate Aurora Research Institute), and John Jurkiewicz (graduate student at UWM).

I will discuss two mathematical problems in biological pattern formation. The first is on modeling concentric ring patterns formed in engineered bacterial colonies. I will first present a hybrid model that incorporates a detailed description of cell movement and cell signaling and explains the underlying mechanism of the ring pattern. I will then present a PDE model derived from the hybrid model that captures the biological phenomena equally well. The second concerns spatial pattern formation in reaction-diffusion systems. I will discuss a computational method that can be used to discover potentially all nonuniform steady states of the PDE system, describing the structure of the spatial patterns. The method uses techniques from numerical algebraic geometry. This talk is based on joint work with Min Tang from Shanghai Jiaotong University and Wenrui Hao from Penn State University.