Session A04: Biophysics

Combinatorial bio-inspired mixture as a novel medium for liquid/liquid extraction of ions

Nucleic acids and proteins are information containing biopolymers that carry specific genetic information. Lipids are another category of biological macromolecules but not thought of as information containing. Here we propose the idea that a group of lipid-like molecules can also detect and recognize inorganic ions as protein does. We study the extraction efficiency of small ions using a combination of lipids in oleic acid. We find that group of organic compounds shows supramolecular recognition. The effective combinations show distinct material properties, which is promising in biosensing field.   

Modeling and Analysis of COVID-19 and Dynamical Systems in Biology and Physics

In mathematics and science, dynamical systems are an area of study that describes how states of any system change over time. Their immense usefulness rises from the fact that by discovering the equations that govern such a system, we can model and predict its future behavior. In this study, we propose a new deterministic model for COVID-19 propagation. Our model should serve two purposes. First, we use it to approximate the infected and deceased individuals after a given time during the pandemic. Then, using a linearized subsystem describing infectious compartments about the disease-free equilibrium (DFE), we determine the basic reproductive number ($\mathcal{R}_0$) by the next-generation matrix method. So far, the model makes accurate predictions in short-term intervals that agree with the current data on COVID-19 and predicts that the basic reproductive number ($\mathcal{R}_0$) is 6.6208. That tells us that an infected individual, on average, infects about 6 other susceptible individuals. Hence, this study yields a mathematical model according to which we can make predictions of how COVID-19 will advance over time, and what additional measures are being overlooked in this situation. That, we believe, will be of great interest to public health.   

A new simple model for cardiac alternans~

Cardiac electrical models are designed to represent features of a system. In most cases, they will represent the dynamics of the voltage action potential (AP). Most modelling efforts are focused on accurately matching the shape of the AP signal. This approach does not guarantee that the AP will behave correctly under other parametrizations.~More specifically, these models struggle to represent the dynamics of a system in a wide range of parameter values and external perturbations (far and close of bifurcation points). In order to overcome this problem, we developed a new phenomenological cardiac electrical model that is inspired on the well-known Fitzhugh-Nagumo (FN) model for neuron excitation. The model is composed of two nonlinear polynomial equations that describe the intracellular voltage signal in a cardiac myocyte. But contrary to the FN model, ours is able to generate realistic AP signals that can be matched to experimental observations. Moreover, the model can produce alternans in an AP sequence, which is a well-known period-doubling instability that can lead to severe arrythmias. The simple and continuous nature of the equations allows for all qualitative properties to be derived analytically. More specifically, we are able to derive the action AP and the conduction velocity restitution curves, which are crucial for determining the conditions for alternans initiation. In this work we want to show the model characteristics and how they can improve our understanding of the electrophysiology of the heart.~   

Effect of crosstalk between multiple signaling pathways of a microbial quorum sensing system

An ongoing problem in biophysics is how organisms communicate using multiple signals. This has been a subject of much interest in microorganisms that use quorum sensing to regulate essential biological functions. One question that is strange and has not yet been fully explored is how the overall fitness of an organism is affected when pathways that produce and detect multiple quorum signals (autoinducers) are intertwined. As an example\textit{, Vibrio fischeri} uses two major autoinducers (C8HSL and 3OC6HSL) to regulate bioluminescence and other behavioral traits, and the signaling pathways of these autoinducers are known to exhibit significant crosstalk. We study this effect using a simplified model that consists of two signal/receiver pairs, each with its own feedback, and a tunable crosstalk between the two. By analyzing both the steady state and time dependent solutions of the underlying dynamical system we explore the effect of crosstalk on the response range of each signal/receiver, on the steady states that result, and on the trajectories taken from initial to final states. The general formulation of crosstalk in such a model is readily applicable to a variety of crosstalking quorum sensing pathways that regulate important phenotypes in the microbial communities.