Event type: Seminar

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25
Oct

Sean Sun
(John Hopkins University)

Water Dynamics in Cells and Tissues
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The mammalian cell surface is highly permeable to water. The cell can also actively control the water flux across the cell surface by pumping solutes (mostly ions), and thereby controlling the cell water content and the cell volume. In this talk, we will explore how the cell also uses active water fluxes to move and change cell shape. The same players in the cell volume control system are involved in driving cell movement, especially in high viscosity environments. Mathematical modeling shows that the water-driven cell movement is energetically costly, but is necessary when the hydraulic environment is viscous. Finally, we will discuss how epithelial cell layers such as the kidney tubule pump water and generate mechanical force.
Oct 25, 2019 Online Seminar
Next Event
10
Nov

Jasmine Foo
(University of Minnesota)

Understanding the role of phenotypic switching in cancer drug resistance
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Recent findings suggest that cancer cells can acquire transient resistant phenotypes via epigenetic modifications and other non-genetic mechanisms. Although these resistant phenotypes are eventually relinquished by individual cells, they can temporarily ’save’ the tumor from extinction and enable the emergence of more permanent resistance mechanisms. These observations have generated interest in the potential of epigenetic therapies for long-term tumor control or eradication. In this talk, I will discuss some mathematical models for exploring how phenotypic switching at the single-cell level affects resistance evolution in cancer. As an example, we will explore the role of MGMT promoter methylation in driving resistance to temozolomide in glioblastoma.
Nov 10, 2020 Online Seminar
Next Event
15
Nov

Samuel Isaacson
(Boston University)

Control of membrane-bound tethered signaling reactions
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Many membrane-bound T cell receptors have long, unstructured cytoplasmic tails that contain tyrosine sites. These sites can serve as regulators of receptor activation when phosphorylated or dephosphorylated, while also serving as docking sites for cytosolic enzymes. Interactions between receptors then involve the in-membrane diffusion of the receptor proteins, and reactions between proteins tethered to the receptors’ tails (and hence diffusing within the three-dimensional cytosolic space near the membrane). We develop a particle-based stochastic reaction-diffusion model based on the Convergent Reaction-Diffusion Master Equation to study the combined diffusion of individual receptors within the cell membrane, and chemical reactions between proteins bound to receptor tails. The model suggests a switch-like behavior in the dependence of the fraction of activated receptors on both receptor diffusivity, and on the molecular reach at which two receptor tails can interact. A simplified, analytically solvable model is developed to approximate the more complicated multi-particle system, and used to illustrate how the switch-like behavior arises.
Nov 15, 2019 Online Seminar
Next Event
17
Nov

Mark Lewis
(University of Alberta)

Population Dynamics in Changing Environments
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Classical population dynamics problems assume constant unchanging environments. However, realistic environments fluctuate in both space and time. My lecture will focus on the analysis of population dynamics in environments that shift spatially, due either to advective flow (eg., river population dynamics) or to changing environmental conditions (eg., climate change). The emphasis will be on the analysis of nonlinear advection-diffusion-reaction equations and related models in the case where there is strong advection and environments are heterogeneous. I will use methods of spreading speed analysis, net reproductive rate and inside dynamics to understand qualitative outcomes. Applications will be made to river populations and to the genetic structure of populations subject to climate change.
Nov 17, 2020 Online Seminar
Next Event
22
Nov

Alexander Mogilner
(New York University)

Many-body problem of classical mechanics in cell biology
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Many-body problem of celestial mechanics revolutionized applied mathematics and continues to provide inspiration. Math/physical communities are much less aware that there are numerous example of fascinating many-body problems of classical mechanics arising in live cells at drastically different scales: instead of years and millions of kilometers, in the cell we deal with minutes and microns. Another big difference is: rather than Newtonian mechanics in empty space, when acceleration is proportional to force, in the cells filled with viscous cytoplasm, we deal with Aristotelian mechanics, in which velocity is proportional to force. Yet another difference is a great diversity of complex inter-body forces in the cell, compared to pleasingly simple gravitational force of celestial mechanics. Because of this diversity, in cell biology we often need to solve the ill-posed inverse problem – reverse-engineering forces from the observed patterns and movements – contrasted with the well-posed direct problem of predicting patterns and movements from known forces. I will discuss two many-body problems of cell biology – assembly of mitotic spindle from two centrosomes and tens of chromosomes, and nuclei positioning in multi-nucleated muscle cells. Three approaches – solutions of ODEs of ‘particle’ models, solutions of PDEs of continuous approximation, and energy minimization, complemented by computer screening – shed light on the molecular origins of the intracellular forces that ensure proper and robust cellular architecture.
Nov 22, 2019 Online Seminar
Next Event
24
Nov

Qing Nie
(University of California, Irvine)

Multiscale inference and modeling of cell fate via single-cell data
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Cells make fate decisions in response to dynamic environmental and pathological stimuli as well as cell-to-cell communications. Recent technological breakthroughs have enabled to gather data in previously unthinkable quantities at single cell level, starting to suggest that cell fate decision is much more complex, dynamic, and stochastic than previously recognized. Multiscale interactions, sometimes through cell-cell communications, play a critical role in cell decision-making. Dissecting cellular dynamics emerging from molecular and genomic scale in single-cell demands novel computational tools and multiscale models. In this talk, through multiple biological examples we will present our recent effort to use single-cell RNA-seq data and spatial imaging data to uncover new insights in development, regeneration, and cancers. We will also present several new computational tools and mathematical modeling methods that are required to study the complex and dynamic cell fate process through the lens of single cells. Zoom
Nov 24, 2020 Online Seminar
Next Event
17
Jan

HyunJoong Kim
(University of Utah)

Communicating by touch
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During development, cells figure out their location and fate through morphogen concentration gradients. The most commonly accepted mechanism for morphogen gradient formation is diffusion from a local source combined with degradation. Recently, however, there has been growing experimental evidence for an alternative mechanism, based on the direct delivery of morphogens via thin and long cellular protrusions known as cytonemes. In this talk, we will address the effects of various cytoneme transport mechanisms. We then explore the stochasticity from the discrete nature of transport. To deal with the complex nature of the stochastic process, we introduce the strong Markov property and queuing theory.
Jan 17, 2020 Online Seminar
Next Event
23
Jan

Eduardo Garcia-Juarez
(University of Pennsylvania)

Analysis of Moving Interfaces in Incompressible Flows
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Interfaces that evolve with a fluid flow abound in nature and engineering. They are subject to intense research in many different fields, from meteorology to medical sciences or the petroleum industry. However, the mathematical analysis of these free boundary problems is still emerging, which impedes a deeper understanding necessary for accurate numerical methods. In this talk, we will give an overview of certain fluid-fluid and fluid-structure interfaces problem (inhomogeneous Navier-Stokes, Boussinesq, Muskat and Peskin models). The focus is placed on global-in-time results (versus finite-time singularities), with initial interfaces that are not just small perturbations. The analysis is thus purely nonlinear. Particular attention is given to initial data in critical spaces and the challenging non-local effects of viscosity contrasts.
Jan 23, 2020 Online Seminar
Next Event
24
Jan

Daniel Cooney
(Princeton University)

PDE Models of Multilevel Selection
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Here we consider a game theoretic model of multilevel selection in which individuals compete based on their payoff and groups also compete based on the average payoff of group members. Our focus is on the Prisoners’ Dilemma: a game in which individuals are best off cheating, while groups of individuals do best when composed of many cooperators. We analyze the dynamics of the two-level replicator dynamics, a nonlocal hyperbolic PDE describing deterministic birth-death dynamics for both individuals and groups. Comparison principles and an invariant property of the tail of the population distribution are used to characterize the threshold level of between-group selection dividing a regime in which the population converges to a delta function at the equilibrium of the within-group dynamics from a regime in which between-group competition facilitates the existence of steady-state densities supporting greater levels of cooperation. In particular, we see that the threshold selection strength and average payoff at steady state depend on a tug-of-war between the individual-level incentive to be a defector in a many-cooperator group and the group-level incentive to have many cooperators over many defectors. We also find that lower-level selection casts a long shadow: if groups are best off with a mix of cooperators and defectors, then there will always be fewer cooperators than optimal at steady state, even in the limit of infinitely strong competition between groups.
Jan 24, 2020 Online Seminar
Next Event
27
Jan

Daniel Gomez
(University of British Columbia)

Localized Patterns in Bulk-Membrane Coupled Models
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Turing instabilities in reaction diffusion systems describe potential mechanisms for pattern formation in qualitative models of microbiological processes. A recent direction of research has been to incorporate bulk-membrane coupling (BMC) into these models which introduces a process of attachment and detachment to and from the cell membrane. In these models chemical species can therefore undergo periods of bulk- and membrane-bound diffusion in addition to prescribed kinetics. Linear stability analysis and numerical simulations have revealed that differences between membrane and cytosol diffusivities can trigger Turing-like pattern-forming instabilities in BMC models. We further investigate the role of bulk-membrane coupling by analyzing its effect in a singularly perturbed model where the diffusivity of one membrane-bound species is asymptotically small. In this context, localized solutions are known to exist and can be approximated using asymptotic methods. Additionally, the linear stability and long time dynamics of these localized solutions leads to novel non-local eigenvalue problems and differential-algebraic systems. In this talk we will outline this asymptotic framework and highlight the role of bulk-membrane coupling in the stability properties of localized solutions.
Jan 27, 2020 Online Seminar
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