In Vivo and In Vitro Dynamics of Undifferentiated Embryonic Cell Transcription Factor 1

Summary Pluripotent stem cells retain the ability to differentiate into the three germ layers and germline. As a result, there is a major interest in characterizing regulators that establish and maintain pluripotency. The network of transcription factors continues to expand in complexity, and one factor, undifferentiated embryonic cell transcription factor 1 (UTF1), has recently moved more into the limelight. To facilitate the study of UTF1, we report the generation and characterization of two reporter lines that enable efficient tracking, mapping, and purification of endogenous UTF1. In particular, we include a built-in biotinylation system in our targeted locus that allows efficient and reliable pulldown. We also use this reporter to show the dynamic regulation of Utf1 in distinct stem cell conditions and demonstrate its utility for reprogramming studies. The multipurpose design of the reporter lines enables many directions of future study and should lead to a better understanding of UTF1’s diverse roles

EikoNet: Solving the Eikonal Equation With Deep Neural Networks

The recent deep learning revolution has created enormous opportunities for accelerating compute capabilities in the context of physics-based simulations. In this article, we propose EikoNet, a deep learning approach to solving the Eikonal equation, which characterizes the first-arrival-time field in heterogeneous 3-D velocity structures. Our grid-free approach allows for rapid determination of the travel time between any two points within a continuous 3-D domain. These travel time solutions are allowed to violate the differential equation--which casts the problem as one of optimization--with the goal of finding network parameters that minimize the degree to which the equation is violated. In doing so, the method exploits the differentiability of neural networks to calculate the spatial gradients analytically, meaning that the network can be trained on its own without ever needing solutions from a finite-difference algorithm. EikoNet is rigorously tested on several velocity models and sampling methods to demonstrate robustness and versatility. Training and inference are highly parallelized, making the approach well-suited for GPUs. EikoNet has low memory overhead and further avoids the need for travel-time lookup tables. The developed approach has important applications to earthquake hypocenter inversion, ray multipathing, and tomographic modeling, as well as to other fields beyond seismology where ray tracing is essential

2021-2022 Statewide Utah Angler Survey Report

Continuing an effort that dates to 1967, we collected data through a statewide survey of licensed anglers in an effort to understand their preference and behaviors. Anglers were surveyed across the state of Utah, as well as nonresident anglers who purchased a Utah fishing license. This research was guided by objectives developed by the Division of Wildlife Resources (DWR) as and our research team at the Institute of Outdoor Recreation and Tourism at Utah State University. In the report, we provide statewide statistics and comparisons between the DWRs five management regions. The objectives and key findings are:Objective 1. Define the characteristics of Utah anglersObjective 2. Produce a snapshot of angling in Utah over a 12-month periodObjective 3. Identify what motivates Utah anglersObjective 4. Identify what fish species anglers expected to catch, caught, and prefer to catchObjective 5. Gauge anglers’ perceptions and knowledge of native and nonnative fish species in UtahObjective 6. Explore Utah anglers’ perceptions of, and experiences with, crowdingObjective 7. Identify potential areas where managers can create or promote opportunities for Utah anglers to combine recreational activities to enhance the angling experienceThe report provides tables and figures and explanations pertaining to each of the research objectives outlined above. In addition, statewide and regional statistics are provided to showcase the unique trends associated with Utah anglers and angling resources in Utah

Mouse Ooplasm Confers Context-Specific Reprogramming Capacity

Enucleated oocytes have the remarkable ability to reprogram somatic nuclei back to totipotency. Here we investigate genome-scale DNA methylation patterns after nuclear transfer and compare them to the dynamics at fertilization. We identify specific targets for DNA demethylation after nuclear transfer such as germ-line associated promoters, as well as unique limitations that include certain repetitive element classes.Stem Cell and Regenerative Biolog

3D fault architecture controls the dynamism of earthquake swarms

The vibrant evolutionary patterns made by earthquake swarms are incompatible with standard, effectively two-dimensional (2D) models for general fault architecture. We leverage advances in earthquake monitoring with a deep-learning algorithm to image a fault zone hosting a 4-year-long swarm in southern California. We infer that fluids are naturally injected into the fault zone from below and diffuse through strike-parallel channels while triggering earthquakes. A permeability barrier initially limits up-dip swarm migration but ultimately is circumvented. This enables fluid migration within a shallower section of the fault with fundamentally different mechanical properties. Our observations provide high-resolution constraints on the processes by which swarms initiate, grow, and arrest. These findings illustrate how swarm evolution is strongly controlled by 3D variations in fault architecture

Diverse epigenetic mechanisms maintain parental imprints within the embryonic and extraembryonic lineages

Genomic imprinting and X chromosome inactivation (XCI) require epigenetic mechanisms to encode allele-specific expression, but how these specific tasks are accomplished at single loci or across chromosomal scales remains incompletely understood. Here, we systematically disrupt essential epigenetic pathways within polymorphic embryos in order to examine canonical and non-canonical genomic imprinting as well as XCI. We find that DNA methylation and Polycomb group repressors are indispensable for autosomal imprinting, albeit at distinct gene sets. Moreover, the extraembryonic ectoderm relies on a broader spectrum of imprinting mechanisms, including non-canonical targeting of maternal endogenous retrovirus (ERV)-driven promoters by the H3K9 methyltransferase G9a. We further identify Polycomb-dependent and -independent gene clusters on the imprinted X chromosome, which appear to reflect distinct domains of Xist-mediated suppression. From our data, we assemble a comprehensive inventory of the epigenetic pathways that maintain parent-specific imprinting in eutherian mammals, including an expanded view of the placental lineage

3D fault architecture controls the dynamism of earthquake swarms

The vibrant evolutionary patterns made by earthquake swarms are incompatible with standard, effectively two-dimensional (2D) models for general fault architecture. We leverage advances in earthquake monitoring with a deep-learning algorithm to image a fault zone hosting a 4-year-long swarm in southern California. We infer that fluids are naturally injected into the fault zone from below and diffuse through strike-parallel channels while triggering earthquakes. A permeability barrier initially limits up-dip swarm migration but ultimately is circumvented. This enables fluid migration within a shallower section of the fault with fundamentally different mechanical properties. Our observations provide high-resolution constraints on the processes by which swarms initiate, grow, and arrest. These findings illustrate how swarm evolution is strongly controlled by 3D variations in fault architecture