Registered Data

Contents

1 [CT182]

[CT182]

Session Time & Room

CT182 (1/1) : 4E @D514 [Chair: Ryan Palmer]

Classification

CT182 (1/1) : Physiological, cellular and medical topics (92C) / Mathematical biology in general (92B) / Biology and other natural sciences (92-)

[00320] Sensing the electrical world: modelling to understand aerial electroreception

Session Time & Room : 4E (Aug.24, 17:40-19:20) @D514
Type : Contributed Talk
Abstract : Bees and spiders (and other arthropods) can sense naturally occurring electrical fields. This recent discovery expands our view of how such organisms explore their environments, revealing previously unknown sensory capabilities. This talk consists of three topics: 1) the physical and biological feasibility of this sense, 2) how interactions between sensory hairs alter their sensitivity to different stimuli, and 3) the new sensory possibilities (e.g., object identification) and biological implications of this sense (e.g., decision-making).
Classification : 92C10, 92C05, 74F10, 92C42
Format : Talk at Waseda University
Author(s) :
- Ryan Palmer (University of Bristol)
- Daniel Robert (University of Bristol)
- Isaac Chenchiah (University of Bristol)

[02615] Theory of the cell motility mechanism in the absence of adhesions

Session Time & Room : 4E (Aug.24, 17:40-19:20) @D514
Type : Contributed Talk
Abstract : The existing paradigm of the cell motility cycle does not hold for in vivo cell movement in complex 3D environments. In physiologically relevant environments, cells frequently use pressure-driven round membrane protrusions for locomotion. The role of substrate adhesion is minimal, and it remains unknown if and how a cell can migrate without any adhesions. Here, we leverage modeling and computational tools to reveal the step-by-step cycle of locomotion for cells that use blebs as leading-edge protrusions in confined environments. We show that cells cannot effectively migrate when the cell cortex is a purely elastic material, even with asymmetric channel geometry. Cells migrate effectively if actin turnover is included with a viscoelastic description for the cortex. Lastly, we compare with previous experimental findings and identify the spatiotemporal force distribution during a motility cycle.
Classification : 92Bxx, 76Zxx
Format : Talk at Waseda University
Author(s) :
- Calina Anamaria Copos (Northeastern University)
- Calina Copos (Northeastern University)
- Wanda Strychalski (Case Western Reserve University)

[02158] Spatially coordinated collective phosphorylation filters spatiotemporal noises for precise circadian timekeeping

Session Time & Room : 4E (Aug.24, 17:40-19:20) @D514
Type : Contributed Talk
Abstract : The mammalian circadian clock is based on a self-sustaining transcriptional-translational negative feedback loop. This machinery is expected to suffer from the heterogeneous arrival time distribution of clock protein from the noisy intracellular environment at the nucleus; however, mammals exhibit robust daily rhythms of physiological and behavioral processes, including sleep and hormone secretion. We explore under which condition the circadian clock compensates for the heterogeneity by a modeling approach.
Classification : 92BXX, 92Cxx
Format : Talk at Waseda University
Author(s) :
- Seokjoo Chae
- Dae Wook Kim (University of Michigan)
- Seunggyu Lee (Korea University)
- Jae Kyoung Kim (KAIST)

[02529] Application of machine learning to predict dynamics of epidemiological models that incorporate human behavior

Session Time & Room : 4E (Aug.24, 17:40-19:20) @D514
Type : Contributed Talk
Abstract : In this work, we present modeling, analysis and simulation of a mathematical epidemiological model which incorporates human social, behavioral, and economic interactions. We discuss an approach based in Physics-Informed Neural Network, which is capable of predicting the dynamics of a disease described by modified compartmental models that include parameters, and variables associated with the governing differential equations. Finally, human behavior is modeled stochastically and it is included in the compartmental models.
Classification : 92Bxx, 92-04, 92-05
Format : Talk at Waseda University
Author(s) :
- Alonso Gabriel Ogueda Oliva (George Mason University)
- Padmanabhan Seshaiyer (George Mason University)

[01908] Quantifying Cytoskeletal Dynamics and Remodeling from Live-imaging Microscopy Data

Session Time & Room : 4E (Aug.24, 17:40-19:20) @D514
Type : Contributed Talk
Abstract : The shape of biological cells emerges from dynamic remodeling of the cell’s internal scaffolding, the cytoskeleton. Hence, correct cytoskeletal regulation is crucial for the control of cell behaviour, such as cell division and migration. A main component of the cytoskeleton is actin. Interlinked actin filaments span the body of the cell and contribute to a cell’s stiffness. The molecular motor myosin can induce constriction of the cell by moving actin filaments against each other. Capturing and quantifying these interactions between myosin and actin in living cells is an ongoing challenge. For example, live-imaging microscopy can be used to study the dynamic changes of actin and myosin density in deforming cells. These imaging data can be quantified using Optical Flow algorithms, which locally assign velocities of cytoskeletal movement to the data. Extended Optical Flow algorithms also quantify actin recruitment and degradation. However, these measurements on cytoskeletal dynamics may be influenced by noise in the image acquisition, by ad-hoc parameter choices in the algorithm, and by image pre-processing steps. Here, we use in silico data to understand conditions under which Optical Flow is applicable. We found the condition to guarantee the method has a good performance is that the displacement has to be in a proper proportion as the object size. We test our methods using data on actin densities in larval epithelial cells of Drosophila pupae. The development of our Optical Flow method will be a starting point for identifying differences in cytoskeletal movement and remodeling under experimental perturbations. Our method will be applicable to other datasets in which flow fields are present.
Classification : 92-10, 92-08, 92BXX, 37CXX, 76-10
Format : Online Talk on Zoom
Author(s) :
- Carey Li (University of St Andrews)