Global morphogenetic flow is accurately predicted by the spatial distribution of myosin motors.

During embryogenesis tissue layers undergo morphogenetic flow rearranging and folding into specific shapes. While developmental biology has identified key genes and local cellular processes, global coordination of tissue remodeling at the organ scale remains unclear. Here, we combine in toto light-sheet microscopy of the Drosophila embryo with quantitative analysis and physical modeling to relate cellular flow with the patterns of force generation during the gastrulation process. We find that the complex spatio-temporal flow pattern can be predicted from the measured meso-scale myosin density and anisotropy using a simple, effective viscous model of the tissue, achieving close to 90% accuracy with one time dependent and two constant parameters. Our analysis uncovers the importance of a) spatial modulation of myosin distribution on the scale of the embryo and b) the non-locality of its effect due to mechanical interaction of cells, demonstrating the need for the global perspective in the study of morphogenetic flow

Active cellular mechanics and its consequences for animal development

A central goal of developmental biology is to understand how an organism shapes itself, a process referred to as morphogenesis. While the molecular components critical to determining the initial body plan have been well characterized, the control of the subsequent dynamics of cellular rearrangements which ultimately shape the organism are far less understood. A major roadblock to a more complete picture of morphogenesis is the inability to measure tissue-scale mechanics throughout development and thus answer fundamental questions: How is the mechanical state of the cell regulated by local protein expression and global pattering? In what way does stress feedback onto the larger developmental program?In this dissertation, we begin to approach these questions through the introduction and analysis of a multi-scale model of epithelial mechanics which explicitly connects cytoskeletal protein activity to tissue-level stress. In Chapter 2, we introduce the discrete Active Tension Network (ATN) model of cellular mechanics. ATNs are tissues that satisfy two primary assumptions: that the mechanical balance of cells is dominated by cortical tension and that myosin actively remodels the actin cytoskeleton in a stress-dependent manner. Remarkably, the interplay of these features allows for angle-preserving, i.e. `isogonal', dilations or contractions of local cell geometry that do not generate stress. Asymptotically this model is stabilized provided there is mechanical feedback on expression of myosin within the cell; we take this to be a strong prediction to be tested. The ATN model exposes a fundamental connection between equilibrium cell geometry and its underlying force network. In Chapter 3, we relax the tension-net approximation and demonstrate that at equilibrium, epithelial tissues with non-uniform pressure have non-trivial geometric constraints that imply the network is described by a weighted `dual' triangulation. We show that the dual triangulation encodes all information about the mechanical state of an epithelial tissue. Utilizing the stress-geometry ‘duality’, we formulate a local "Mechanical Inference" of cellular-level stress using solely cell geometry that dramatically improves over past image-based inference techniques.In Chapter 4, we generalize the ATN model to explore the controlled re-arrangement of cells within epithelial tissues. This requires us to explicitly consider the effects of cadherin mediated adhesion, and its regulation, on tissue morphogenesis. We find that positive feedback between myosin and cortical tension, along with traction-dependent depletion of cytoskeletal cadherin is sufficient to recapitulate the morphogenetic movement of cells observed during convergent extension of the lateral ectoderm during Drosophila embryogenesis. Statistical analyses of live-imaging data supports the fundamentals of the model.Chapter 5 focuses on morphogenesis at a mesoscopic scale by coarse-graining the cellular ATN model. Under this limit, we expect an epithelial tissue should behave as an effective viscous, compressible fluid driven by myosin gradients on intermediate time-scales. Theoretical predictions are empirically tested against in-toto microscopy data obtained during early Drosophila embryogenesis

Rotational properties of the Haumea family members and candidates: Short-term variability

Haumea is one of the most interesting and intriguing transneptunian objects (TNOs). It is a large, bright, fast rotator, and its spectrum indicates nearly pure water ice on the surface. It has at least two satellites and a dynamically related family of more than ten TNOs with very similar proper orbital parameters and similar surface properties. The Haumean family is the only one currently known in the transneptunian belt. Various models have been proposed but the formation of the family remains poorly understood. In this work, we have investigated the rotational properties of the family members and unconfirmed family candidates with short-term variability studies, and report the most complete review to date. We present results based on five years of observations and report the short-term variability of five family members, and seven candidates. The mean rotational periods, from Maxwellian fits to the frequency distributions, are 6.27+/-1.19 h for the confirmed family members, 6.44+/-1.16 h for the candidates, and 7.65+/-0.54 h for other TNOs (without relation to the family). According to our study, there is a suggestion that Haumea family members rotate faster than other TNOs, however, the sample of family member is still too limited for a secure conclusion. We also highlight the fast rotation of 2002 GH32. This object has a 0.36+/-0.02 mag amplitude lightcurve and a rotational period of about 3.98 h. Assuming 2002 GH32 is a triaxial object in hydrostatic equilibrium, we derive a lower limit to the density of 2.56 g cm^-3. This density is similar to Haumea's and much more dense than other small TNO densities.Comment: Accepted for publication, A

Priming Effects in Switching Attention Between Working Memory and Visual Perception

The following series of experiments explored factors which influence the time required to shift attention between working memory and visual perception. I believe it is important for psychology to study switching time, as it gives one a unique empirical method for assessing the capabilities of human information processing. This study makes use of the switching time paradigm originated by Dr. Robert Weber. This paradigm is a promising means of studying attention switching and may have practical as well as scholarly value.Psycholog

PanGraph: scalable bacterial pan-genome graph construction

The genomic diversity of microbes is commonly parameterized as SNPs relative to a reference genome of a well-characterized, but arbitrary, isolate. However, any reference genome contains only a fraction of the microbial pangenome, the total set of genes observed in a given species. Reference-based approaches are thus blind to the dynamics of the accessory genome, as well as variation within gene order and copy number. With the widespread usage of long-read sequencing, the number of high-quality, complete genome assemblies has increased dramatically. In addition to pangenomic approaches that focus on the variation in the sets of genes present in different genomes, complete assemblies allow investigations of the evolution of genome structure and gene order. This latter problem, however, is computationally demanding with few tools available that shed light on these dynamics. Here, we present PanGraph, a Julia-based library and command line interface for aligning whole genomes into a graph. Each genome is represented as a path along vertices, which in turn encapsulate homologous multiple sequence alignments. The resultant data structure succinctly summarizes population-level nucleotide and structural polymorphisms and can be exported into several common formats for either downstream analysis or immediate visualization

COVID-19 Scenarios: an interactive tool to explore the spread and associated morbidity and mortality of SARS-CoV-2

The ongoing SARS-CoV-2 pandemic has caused large outbreaks around the world and every heavily affected community has experienced a substantial strain on the health care system and a high death toll. Communities therefore have to monitor the incidence of COVID-19 carefully and attempt to project the demand for health care. To enable such projections, we have developed an interactive web application that simulates an age-structured SEIR model with separate compartments for severely and critically ill patients. The tool allows the users to modify most parameters of the model, including age specific assumptions on severity. Infection control and mitigation measures that reduce transmission can be specified, as well as age-group specific isolation. The simulation of the model runs entirely on the client side in the browser; all parameter settings and results of the simulation can be exported for further downstream analysis. The tool is available at covid19-scenarios.org and the source code at github.com/neherlab/covid19_scenarios

Rubble Pile Characterization Model

Rubble piles created following the collapse of a building in a combat situation can significantly impact mission accomplishment, particularly in the area of movement and maneuver. Rubble characteristics must be known, for example, in order to predict the ability of a vehicle to override the collateral damage from weapon effects in urban areas. Two types of models are developed: a first-order model and a first-principles-based model. In both models, we assume complete rubblization of the building and develop a rubble profile model using the size and composition of the collapsed structure to predict the rubble volume. In both cases, this profile model includes the size of the footprint area surrounding the original building assuming that the rubble is free to expand horizontally as well as the resulting height of such a rubble pile. Empirical data is now needed to verify the predictive capabilities of these models