Point Particles to Capture Polarized Embryonic Cells &amp; Cold Pools in the Atmosphere
Creators: name: Nissen, Silas Boye
Publisher: name: figshare
Year: 2021
Subjects: subject: Biophysics
subject: Computational Biology
subject: 40102 Atmospheric Dynamics
subject: FOS: Earth and related environmental sciences
subject: Atmospheric Sciences
subject: 40106 Cloud Physics
subject: Geophysics
subject: Hydrology
subject: 40604 Natural Hazards
subject: 10202 Biological Mathematics
subject: FOS: Mathematics
subject: 10204 Dynamical Systems in Applications
subject: Geometry
subject: 10112 Topology
subject: Applied Physics
subject: 29901 Biological Physics
subject: FOS: Biological sciences
subject: 29902 Complex Physical Systems
subject: FOS: Physical sciences

description: This Ph.D. thesis consists of two parts: one on biophysics and one on atmospheric science.<br>Embryonic animal morphologies are incredibly robust, complex, and, at the same time, very diverse. In this Ph.D. thesis, I ask how these physical properties are compatible with each other. In the search for a few unifying developmental rules, I suggest a phenomenological model. Apical-basal polarity (defining inside-out) and planar cell polarity (differentiating one end from another) are ubiquitous in animal morphologies. Based on this knowledge, I develop a simple 3D mathematical model: Each cell represented as point particles may have zero, one, or two unit-arrows representing their polarities. I show that an aggregate of cells can self-organize into diverse and robust morphologies. By adding cell-cell communication, differential adhesion, and apoptosis, I find that these components are sufficient to capture blastocyst formation during preimplantation development. The model can further simulate sea urchin gastrulation and mammalian neurulation by adding isotropic and anisotropic cell wedging. I use this minimal, versatile toolbox to make predictions about various developmental stages, including organoid folding and tube formation. In preimplantation development, I test these predictions experimentally. In the discussion, I propose how this mathematical model may capture embryonic disc versus egg cylinder formation post-implantation. Besides, I suggest an image tool that may be used in testing hypotheses on organoid folding. Plenty mathematical, especially vertex-based, models already exist. Compared to other models, the model presented here generates fast, reproducible, and stable 3D morphologies consisting of more than 104 cells. Most importantly, only a few parameters (the strength of the two cellular polarities) go into the model. I conclude that this is a useful and easy-to-use computational tool to explore complex and diverse embryonic development.<br>Atmospheric events such as flash floods and tropical cyclones pose an increased threat to human lives. For both events, the spatial clustering of convection has been recognized as a crucial precursor. Hence, to better understand and predict these weather hazards, I ask how deep convective events spatially organize in the tropics. Searching for an underlying mechanism, I consider atmospheric cold pools (CPs) to link convective events spatiotemporally. CPs are cold and dense air pockets forming in the boundary layer below clouds when rain evaporates during thunderstorms. CPs fall to the ground and spread radially away from the rain event. By analyzing large-eddy simulations (LES), I find that new convective rain events, and thereby CPs, often form when multiple CPs collide. Based on this result, I suggest mathematically modeling CPs’ spatial organization: N points expand into circles representing CPs on a 2D domain. A new expanding circle forms where the rims of multiple circles collide. I find this model captures convective scale increase and clustering of precipitating cells as found in LES with diurnally oscillating surface temperature. To study convective self-aggregation, I add two physical parameters to the model. Based on LES, I measure a critical minimum radius, Rmin, and a critical maximal radius, Rmax, within which CPs can replicate. This extended model predicts that convective self-aggregation is accelerated in atmospheric conditions that slow the CP growth, thereby decreasing Rmax. I find this effect is achieved in LES when rain evaporation is reduced. In the discussion, I suggest several model variations and relate the model to the literature. Furthermore, I propose an idea for future work on persistently dry regions’ movements during convective self-aggregation. Using this CP model, I conclude that CPs are crucial in spatially organizing deep convective events in the tropics.<br>