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Tractometry of the Human Connectome Project: resources and insights

The Human Connectome Project (HCP) has become a keystone dataset in human neuroscience, with a plethora of important applications in advancing brain imaging methods and an understanding of the human brain. We focused on tractometry of HCP diffusion-weighted MRI (dMRI) data. We used an open-source software library (pyAFQ; https://yeatmanlab.github.io/pyAFQ) to perform probabilistic tractography and delineate the major white matter pathways in the HCP subjects that have a complete dMRI acquisition (n = 1,041). We used diffusion kurtosis imaging (DKI) to model white matter microstructure in each voxel of the white matter, and extracted tract profiles of DKI-derived tissue properties along the length of the tracts. We explored the empirical properties of the data: first, we assessed the heritability of DKI tissue properties using the known genetic linkage of the large number of twin pairs sampled in HCP. Second, we tested the ability of tractometry to serve as the basis for predictive models of individual characteristics (e.g., age, crystallized/fluid intelligence, reading ability, etc.), compared to local connectome features. To facilitate the exploration of the dataset we created a new web-based visualization tool and use this tool to visualize the data in the HCP tractometry dataset. Finally, we used the HCP dataset as a test-bed for a new technological innovation: the TRX file-format for representation of dMRI-based streamlines. We released the processing outputs and tract profiles as a publicly available data resource through the AWS Open Data program's Open Neurodata repository. We found heritability as high as 0.9 for DKI-based metrics in some brain pathways. We also found that tractometry extracts as much useful information about individual differences as the local connectome method. We released a new web-based visualization tool for tractometry—“Tractoscope” (https://nrdg.github.io/tractoscope). We found that the TRX files require considerably less disk space-a crucial attribute for large datasets like HCP. In addition, TRX incorporates a specification for grouping streamlines, further simplifying tractometry analysis.

59 BASIC BIOLOGICAL SCIENCES↗

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post - Bed Rest and Spaceflight

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. These alterations may disrupt crewmembers' ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual spaceflight, which crewmembers are likely to experience the greatest challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures. Our approach includes: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features, using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; and 3) assessment of genotypic markers of genetic polymorphisms in the catechol-O-methyl transferase, dopamine receptor D2, and brain-derived neurotrophic factor genes and genetic polymorphisms of alpha2-adrenergic receptors that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate that these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration spaceflight and exposure to an analog bed rest environment. We will be conducting a retrospective study, leveraging data already collected from relevant ongoing or completed bed rest and spaceflight studies. These data will be combined with predictor metrics that will be collected prospectively (as described for behavioral, brain imaging and genomic measures) from these returning subjects to build models for predicting post-mission (bed rest - non-astronauts or space flight - astronauts) adaptive capability as manifested in their outcome measures. To date we have completed a study on 15 normal subjects with all of the above measures. In this presentation we will discuss the optimized set of tests for predictive metrics to be used for evaluating post mission adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive capacity, brain structure and functional capacities, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Mulavara, A. P.↗

An Invited Preface for the Following Book: Astrobiologia, Uma Ciencia Emergente

Since the dawn of civilization, we have beheld at the beauty and wonder of the natural world around us and wondered how it came to be. We have pondered the past, and have been intrigued about the future. For this we are unique. Our ancestors looked to the vastness of space and thought surely there are others out there. We are now at a new time in human history where we can address these age-old questions with a scientific approach and study rigorously the three big questions of astrobiology: Where do we come from? Where are we going? and Are we alone? These fundamental questions of astrobiology correspond to those of humanity, and arguably, what makes us human. And so we cannot help but be drawn to the field. Unlike other scientific disciplines, Astrobiology draws on the latest advances in a multitude of fields, from evolutionary and molecular biology, to prebiotic and interstellar chemistry, from astrophysics to astronomy, with a healthy dose of earth and planetary science. Astrobiology is in reality a "metadiscipline" drawing on useful science wherever it is to be found. From a practical point of view, this endeavor requires the interaction of scientists who might not normally meet each other, much less work on a common research project. And, unlike most other scientific disciplines, Astrobiology has implications for how we see ourselves, and how we interact with the earth and beyond. "Where do we come from" touches on the "why" questions that have intrigued not just scientists but philosophers and theologians. "Where are we going" adds to these an economic and political involvement that is currently being played out with discussions of climate change. "And are we alone" will someday force us to face the fact that we as living creatures are not unique, or perhaps that we are utterly alone in the universe, the result of a chemical history that was so improbable as to result in a sample size of one. Either result will force ethical considerations of either "the other" and their relationship to us, or our solitude and thus responsibility as the only life form in our cosmos. So what is Astrobiology? Let's start with the "Where do we come from?" A biologist will approach this looking at the evolution of life on earth, using such traditional tools as comparative anatomy and paleontology and newer tools such as molecular techniques. But this doesn't address why this happened the way it did without a comprehensive understanding of the environment. What was the temperature at such and such a time? Was the earth in a snowball phase or being bombarded by meteorites -- or even just a single large, well-placed one such as struck off the Yucatan peninsula 65 million years ago. This event could not have been predicted by population genetics alone, yet it had the most profound influence on our evolution as without it, we could still be in a world dominated by dinosaurs with the mammals cowering under cover. But it is not enough to go back to LUCA, the Last Universal Common Ancestor of all extant life. One must go back to the dawn of life. How did life arise? What was the environmental backdrop that allowed it to happen? How did we happen to end up with a habitable planet? Indeed, what is the origin and evolution of our solar system, galaxy, biogenic elements all the way back to the Big Bang. The "Where are we going?" tends to be ignored in many astrobiology programs, but in fact this is of the most immediate importance to us. Whereas the past was dominated by physical and chemical processes, and organismal interactions, the future has a new major player: us. While we probably don't have the power (yet) to stop our galaxy passing through another, or even reset the sun or stop the movement of the moon away from the earth, all of these things will influence the future of life on earth. We are already proving that we have the power to visit other bodies in our solar system, either with humans or our robotic surrogates. We are changing our atmospheric composition and thus our climate. We have the power to render species extinct, including our own. But we also have the power to use these tools for the common good, to extend our lifetimes and reclaim our rivers and forests. Which will it be? And then there is the question where science fiction becomes a reality: "Are we alone?" While many people are anxious to find signs of intelligent life out there, such a creature may not share either our curiosity or values. But what if there was a beneficent alien civilization that could communicate with us, perhaps forging a mutual understanding? More likely in the forseeable future is finding a small life, less evolved, life form. Note I did not use the word "simple" as there is nothing "simple" about life, ever. Which brings us back to the question: what is life? So where does Brazil come in? For nearly a decade there has been interest in a Brazilian astrobiology program, from a small side meeting held by the Brazilian Exobiology Program (BEP) of the Brazilian National Research Council, held in Rio de Janeiro, Brazil, on August 12, 2009, in association with the IAU Assembly to subsequent workshops held in several locations and membership of the Brazilian program in the NASA Astrobiology Institute (NAI). Each time I go to Brazil, I am impressed by the enthusiasm of the community, both scientific and student, the latter an excellent omen for the future of astrobiology in Brazil. Facilities are being built to supplement the natural laboratories that Brazil is blessed to have. In my own lab I have been privileged to have a wonderful Brazilian postdoctoral fellow, Dr. Ivan Paulino-Lima, resulting in a daily reminder of the program. I am honored to have been part of the development of astrobiology in Brazil, and hope that this relationship will continue to flourish. Clearly to advance astrobiology needs new knowledge, a reorganization of that which is known, and space missions. To help the reader join on this quest, what follows is a buffet of topics that will allow the reader to nibble on the richness that is Astrobiology. And, like a fabulous meal, it should make you want more. Welcome to Astrobiology.

Are we alone?↗

Stacking sequence optimization of simply supported laminates with stability and strain constraints

An integer programming formulation for the design of symmetric and balanced rectangular composite laminates with simply supported boundary conditions subject to buckling and strain constraints is presented. The design variables that define the stacking sequence of the laminate are ply-identity zero-one integers. The buckling constraint is linear in terms of the ply-identity design variables, but strains are nonlinear functions of these variables. A linear approximation is developed for the strain constraints so that the problem can be solved by sequential linearization using the branch and bound algorithm. Examples of graphite-epoxy plates under biaxial compression are presented. Optimum stacking sequences obtained using the linear approximation are compared with global optimum designs obtained using a genetic search procedure.

Nagendra, S.↗

Deterministic Design Optimization of Structures in OpenMDAO Framework

Nonlinear programming algorithms play an important role in structural design optimization. Several such algorithms have been implemented in OpenMDAO framework developed at NASA Glenn Research Center (GRC). OpenMDAO is an open source engineering analysis framework, written in Python, for analyzing and solving Multi-Disciplinary Analysis and Optimization (MDAO) problems. It provides a number of solvers and optimizers, referred to as components and drivers, which users can leverage to build new tools and processes quickly and efficiently. Users may download, use, modify, and distribute the OpenMDAO software at no cost. This paper summarizes the process involved in analyzing and optimizing structural components by utilizing the framework s structural solvers and several gradient based optimizers along with a multi-objective genetic algorithm. For comparison purposes, the same structural components were analyzed and optimized using CometBoards, a NASA GRC developed code. The reliability and efficiency of the OpenMDAO framework was compared and reported in this report.

Coroneos, Rula M.↗

Deterministic Design Optimization of Structures in OpenMDAO Framework

Nonlinear programming algorithms play an important role in structural design optimization. Several such algorithms have been implemented in OpenMDAO framework developed at NASA Glenn Research Center (GRC). OpenMDAO is an open source engineering analysis framework, written in Python, for analyzing and solving Multi-Disciplinary Analysis and Optimization (MDAO) problems. It provides a number of solvers and optimizers, referred to as components and drivers, which users can leverage to build new tools and processes quickly and efficiently. Users may download, use, modify, and distribute the OpenMDAO software at no cost. This paper summarizes the process involved in analyzing and optimizing structural components by utilizing the framework s structural solvers and several gradient based optimizers along with a multi-objective genetic algorithm. For comparison purposes, the same structural components were analyzed and optimized using CometBoards, a NASA GRC developed code. The reliability and efficiency of the OpenMDAO framework was compared and reported in this report.

Coroneos, Rula M.↗

Development of sensory systems in zebrafish (Danio rerio)

Zebrafish possess all of the classic sensory modalities: taste, tactile, smell, balance, vision, and hearing. For each sensory system, this article provides a brief overview of the system in the adult zebrafish followed by a more detailed overview of the development of the system. By far the majority of studies performed in each of the sensory systems of the zebrafish have involved some aspect of molecular biology or genetics. Although molecular biology and genetics are not major foci of the paper, brief discussions of some of the mutant strains of zebrafish that have developmental defects in each specific sensory system are included. The development of the sensory systems is only a small sampling of the work being done using zebrafish and provides a mere glimpse of the potential of this model for the study of vertebrate development, physiology, and human disease.

Non-NASA Center↗

Biomass Quality Responses to Selection for Increased Biomass Yield in Perennial Energy Grasses

Perennial grasses are candidates for biomass cropping systems that are focused on providing a wide range of ecosystem services in addition to sustainable bioenergy production. Switchgrass (Panicum virgatum L.) and big bluestem (Andropogon gerardii Vitman) are two of the dominant grasses of the tallgrass prairie and both are candidates for development of multifunctional diverse production systems. Breeding programs for both species are aimed at increasing biomass yield as a mechanism of improving economic sustainability without increasing production costs. The objective of this study was to determine if long-term selection for increased biomass yield in these two species has had any adverse impacts on biomass quality, or the ability to convert biomass into bioenergy. Check cultivars and improved breeding populations of both species were evaluated for a wide range of biomass quality traits at 13 locations in the North Central and Northeastern USA, and a subset of these populations were also subjected to more intensive and detailed fermentation analyses. In general, lignin and ferulates either remained constant or decreased following selection for increased biomass yield in the various genetic pedigrees. These changes resulted in some increases in predicted ethanol production and in vitro digestibility. Here, the prediction of increased digestibility was confirmed by higher glucose release by pretreatment and deconstruction of an advanced lowland population. However, bioreactor fermentations with two different biofuel-producing microbes showed no differences in ethanol production. Overall, these studies indicated that the improved switchgrass and big bluestem populations had greater biomass yields without significantly reducing biomass quality or conversion efficiency into ethanol, suggesting that selection can achieve increases in biomass productivity while maintaining consistent biomass quality.

09 BIOMASS FUELS↗

Mapping of flumioxazin tolerance in a snap bean diversity panel leads to the discovery of a master genomic region controlling multiple stress resistance genes

Effective weed management tools are crucial for maintaining the profitable production of snap bean (Phaseolus vulgaris L.). Preemergence herbicides help the crop to gain a size advantage over the weeds, but the few preemergence herbicides registered in snap bean have poor waterhemp (Amaranthus tuberculatus) control, a major pest in snap bean production. Waterhemp and other difficult-to-control weeds can be managed by flumioxazin, an herbicide that inhibits protoporphyrinogen oxidase (PPO). However, there is limited knowledge about crop tolerance to this herbicide. We aimed to quantify the degree of snap bean tolerance to flumioxazin and explore the underlying mechanisms. We investigated the genetic basis of herbicide tolerance using genome-wide association mapping approach utilizing field-collected data from a snap bean diversity panel, combined with gene expression data of cultivars with contrasting response. The response to a preemergence application of flumioxazin was measured by assessing plant population density and shoot biomass variables. Snap bean tolerance to flumioxazin is associated with a single genomic location in chromosome 02. Tolerance is influenced by several factors, including those that are indirectly affected by seed size/weight and those that directly impact the herbicide's metabolism and protect the cell from reactive oxygen species-induced damage. Transcriptional profiling and co-expression network analysis identified biological pathways likely involved in flumioxazin tolerance, including oxidoreductase processes and programmed cell death. Transcriptional regulation of genes involved in those processes is possibly orchestrated by a transcription factor located in the region identified in the GWAS analysis. Several entries belonging to the Romano class, including Bush Romano 350, Roma II, and Romano Purpiat presented high levels of tolerance in this study. The alleles identified in the diversity panel that condition snap bean tolerance to flumioxazin shed light on a novel mechanism of herbicide tolerance and can be used in crop improvement.

60 APPLIED LIFE SCIENCES↗

Proliferation, differentiation and apoptosis in connexin43-null osteoblasts

Osteoblasts are highly coupled by gap junctions formed primarily by connexin43 (Cx43). We have shown that interference with Cx43 expression or function disrupts transcriptional regulation of osteoblast genes, and that deletion of Cx43 in the mouse causes skeletal malformations, delayed mineralization, and osteoblast dysfunction. Here, we studied the mechanisms by which genetic deficiency of Cx43 alters osteoblast development. While cell proliferation rates were similar in osteoblastic cells derived from calvaria of Cx43-null and wild type mice, camptothecin-induced apoptosis was 3-fold higher in mutant compared to wild type osteoblasts. When grown in mineralizing medium, Cx43-null cells were able to produce mineralized matrix but it took one week longer to reach the same mineralization levels as in normal cells. Likewise, expression of alkaline phosphatase activity per cell--a marker of osteoblast differentiation--was maximal only 2 weeks later in Cx43-null relative to wild-type cells. These observations suggest that Cx43 is important for a normal and timely development of the osteoblastic phenotype. Delayed differentiation and increase programmed cell death may explain the skeletal phenotype of Cx43-null mice.

NASA Discipline Cell Biology↗

A Full-scale Demonstration of Pressurized Water Reactor Core Design Optimization using Multi-Cycle Optimization Methodology

The U.S. nuclear sector encounters a difficulty in upholding essential safety standards while also securing economic viability for continued operation. Safety stands as a pivotal factor across all facets of operations within light-water reactor nuclear power plants. Achieving economic feasibility alongside safety can be facilitated through the utilization of a risk-informed framework, exemplified by the ongoing development within the Risk-Informed Systems Analysis Pathway under the auspices of the U.S. Department of Energy's LWRS Program. This initiative advocates for a diverse array of research and development endeavors aimed at optimizing both safety and economic efficacy within nuclear power plants, particularly pertinent as many plants contemplate second license renewals. The Risk-Informed Systems Analysis Pathway has two main goals: deploy methodologies and technologies that better represent safety margins and cost and safety factors and develop advanced applications that enable cost-effective plant operation. This report assesses the potential for resolving multi-cycle plant reload challenges through real-world scenarios utilizing the Plant ReLoad Optimization (PRLO) framework. This framework offers reactor core design developers analytic tools of reactor safety and fuel performance with the assistance of artificial intelligence (AI) to enhance core design solutions. Multi-objective genetic algorithm alongside acceleration techniques is explored as an enabling technology for improving fuel efficiency while upholding safety thresholds. The demonstration of multi-cycle core design optimization is performed. This report investigates the practical application of the PRLO platform in addressing real-world core design challenges, supporting AI efforts, and contrasting outcomes with those derived from heuristic or conventional algorithms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Exercise and pharmacological countermeasures for bone loss during long-duration space flight

Bone loss in the lower extremities and lumbar spine is an established consequence of long-duration human space flight. Astronauts typically lose as much bone mass in the proximal femur in 1 month as postmenopausal women on Earth lose in 1 year. Pharmacological interventions have not been routinely used in space, and countermeasure programs have depended solely upon exercise. However, it is clear that the osteogenic stimulus from exercise has been inadequate to maintain bone mass, due to insufficient load or duration. Attention has therefore been focused on several pharmacological interventions that have been successful in preventing or attenuating osteoporosis on Earth. Anti-resorptives are the class of drugs most commonly used to treat osteoporosis in postmenopausal women, notably alendronate sodium, risedronate sodium, zoledronic acid, and selective estrogen receptor modulators, such as raloxifene. There has also been considerable recent interest in anabolic agents such as parathyroid hormone (PTH) and teriparatide (rhPTH [1-34]). Vitamin D and calcium supplementation have also been used. Recent studies of kindreds with abnormally high bone mineral density have provided insight into the genetic regulation of bone mass. This has led to potential therapeutic interventions based on the LRP5, Wnt and BMP2 pathways. Another target is the RANK-L/osteoprotegerin signaling pathway, which influences bone turnover by regulating osteoclast formation and maturation. Trials using such therapies in space are being planned. Among the factors to be considered are dose-response relationships, bone quality, post-use recovery, and combination therapies--all of which may have unique characteristics when the drugs are used in space.

NASA Discipline Musculoskeletal↗

Demonstration of the Plant Fuel Reload Process Optimization for an Operating PWR

The United States (U.S.) nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor (LWR) nuclear power plants (NPPs) and can be achieved more economically by using a risk-informed ecosystem such as that being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program is promoting a wide range of research and development (R&D) activities with the goal to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering second license renewal. The RISA Pathway has two main goals: (1) the deployment of methodologies and technologies that enable better representation of safety margins and the factors that contribute to cost and safety; and (2) the development of advanced applications that enable cost-effective plant operation. This report summarizes the research outcomes in FY-2021, which the project progressed from the planning and methodology development phase to the early demonstration phase. The highlights of these activities are: (1) the development of a multi-objective optimization process using Genetic Algorithms (GAs); (2) the development and test of an approach for optimization process acceleration using artificial intelligence (AI) that significantly reduces the computational burden; (3) the demonstration of the fuel reload optimization framework for a generic pressurized water reactor (PWR); and (4) the demonstration of limiting design basis accident (DBA) scenarios for evaluation of the transition from deterministic to risk-informed approach for fuel reload optimization.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data from: "Lab and Field Warming Similarly Advance Germination Date and Limit Germination Rate for High and Low Elevation Provenances of Two Widespread Subalpine Conifers"

This archive contains data used to draw conclusions in “Lab and Field Warming Similarly Advance Germination Date and Limit Germination Rate for High and Low Elevation Provenances of Two Widespread Subalpine Conifers”, by Kueppers et al. 2017. Cone collection and field experiments were conducted on Niwot Ridge, Colorado, with the latter completed within the Alpine Treeline Warming Experiment (ATWE). Laboratory germination experiments were conducted at the University of California Merced. Geospatial files are also provided for additional geographical context.There are four data file formats in this package: comma-separated values (.csv), Microsoft Excel (.xlsx), keyhole markup language (.kml), and ESRI shapefile (.shp). The latter two are geospatial file formats. .csv files can be opened using any simple text editor program such as TextEdit (Mac) and Notepad (Windows), and .xlsx files can be opened using Microsoft Excel or Google Sheets. The .kml file contains coordinate data, and is compatible with Google Earth and Google Maps. ESRI shapefiles (.shp) are compatible with any geospatial software able to read the file type, such as QGIS and ESRI’s ArcGIS Suite. This data user’s guide is available in as a .pdf, and can be opened using software such as Adobe Acrobat Reader.-----------------------------------------------------------------------------------------------------------------------------------Accurately predicting upslope shifts in subalpine tree ranges with warming requires understanding how future forest populations will be affected by climate change, as these are the seed sources for new tree line and alpine populations. Early life history stages are particularly sensitive to climate and are also influenced by genetic variation among populations. We tested the climate sensitivity of germination and initial development for two widely distributed subalpine conifers, using controlled-environment growth chambers with one temperature regime from subalpine forest in the Colorado Rocky Mountains and one 5 °C warmer, and two soil moisture levels. We tracked germination rate and timing, rate of seedling development, and seedling morphology for two seed provenances separated by ~300 m elevation. Warming advanced germination timing and initial seedling development by a total of ~2 weeks, advances comparable to mean differences between provenances. Advances were similar for both provenances and species; however, warming reduced the overall germination rate, as did low soil moisture, only for Picea engelmannii. A three-year field warming and watering experiment planted with the same species and provenances yielded responses qualitatively consistent with the lab trials. Together these experiments indicate that in a warmer, drier climate, P. engelmannii germination, and thus regeneration, could decline, which could lead to declining subalpine forest populations, while Pinus flexilis forest populations could remain robust as a seed source for upslope range shifts.

54 ENVIRONMENTAL SCIENCES↗

The mGA1.0: A common LISP implementation of a messy genetic algorithm

Genetic algorithms (GAs) are finding increased application in difficult search, optimization, and machine learning problems in science and engineering. Increasing demands are being placed on algorithm performance, and the remaining challenges of genetic algorithm theory and practice are becoming increasingly unavoidable. Perhaps the most difficult of these challenges is the so-called linkage problem. Messy GAs were created to overcome the linkage problem of simple genetic algorithms by combining variable-length strings, gene expression, messy operators, and a nonhomogeneous phasing of evolutionary processing. Results on a number of difficult deceptive test functions are encouraging with the mGA always finding global optima in a polynomial number of function evaluations. Theoretical and empirical studies are continuing, and a first version of a messy GA is ready for testing by others. A Common LISP implementation called mGA1.0 is documented and related to the basic principles and operators developed by Goldberg et. al. (1989, 1990). Although the code was prepared with care, it is not a general-purpose code, only a research version. Important data structures and global variations are described. Thereafter brief function descriptions are given, and sample input data are presented together with sample program output. A source listing with comments is also included.

Goldberg, David E.↗

Multinode Multi-GPU Two-Electron Integrals: Code Generation Using the Regent Language

The computation of two-electron repulsion integrals (ERIs) is often the most expensive step of integral-direct self-consistent field methods. Formally it scales as O(N 4 ), where N is the number of Gaussian basis functions used to represent the molecular wave function. In practice, this scaling can be reduced to O(N 2 ) or less by neglecting small integrals with screening methods. The contributions of the ERIs to the Fock matrix are of Coulomb (J) and exchange (K) type and require separate algorithms to compute matrix elements efficiently. We previously implemented highly efficient GPU-accelerated J-matrix and K-matrix algorithms in the electronic structure code TeraChem. Although these implementations supported the use of multiple GPUs on a node, they did not support the use of multiple nodes. This presents a key bottleneck to cutting-edge ab initio simulations of large systems, e.g., excited state dynamics of photoactive proteins. We present our implementation of multinode multi-GPU J- and K-matrix algorithms in TeraChem using the Regent programming language. Regent directly supports distributed computation in a task-based model and can generate code for a variety of architectures, including NVIDIA GPUs. We demonstrate multinode scaling up to 45 GPUs (3 nodes) and benchmark against hand-coded TeraChem integral code. Finally, we also outline our metaprogrammed Regent implementation, which enables flexible code generation for integrals of different angular momenta.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systems-Level Modeling for CRISPR-Based Metabolic Engineering

The CRISPR-Cas system has enabled the development of sophisticated, multigene metabolic engineering programs through the use of guide RNA-directed activation or repression of target genes. To optimize biosynthetic pathways in microbial systems, we need improved models to inform design and implementation of transcriptional programs. Recent progress has resulted in new modeling approaches for identifying gene targets and predicting the efficacy of guide RNA targeting. Genome-scale and flux balance models have successfully been applied to identify targets for improving biosynthetic production yields using combinatorial CRISPR-interference (CRISPRi) programs. Here, the advent of new approaches for tunable and dynamic CRISPR activation (CRISPRa) promises to further advance these engineering capabilities. Once appropriate targets are identified, guide RNA prediction models can lead to increased efficacy in gene targeting. Developing improved models and incorporating approaches from machine learning may be able to overcome current limitations and greatly expand the capabilities of CRISPR-Cas9 tools for metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Molecular Mechanisms Regulating Muscle Fiber Composition Under Microgravity

The overall goal of this project is to reveal the molecular mechanisms underlying the selective and debilitating atrophy of specific skeletal muscle fiber types that accompanies sustained conditions of microgravity. Since little is currently known about the regulation of fiber-specific gene expression programs in mammalian muscle, elucidation of the basic mechanisms of fiber diversification is a necessary prerequisite to the generation of therapeutic strategies for attenuation of muscle atrophy on earth or in space. Vertebrate skeletal muscle development involves the fusion of undifferentiated mononucleated myoblasts to form multinucleated myofibers, with a concomitant activation of muscle-specific genes encoding proteins that form the force-generating contractile apparatus. The regulatory circuitry controlling skeletal muscle gene expression has been well studied in a number of vertebrate animal systems. The goal of this project has been to achieve a similar level of understanding of the mechanisms underlying the further specification of muscles into different fiber types, and the role played by innervation and physical activity in the maintenance and adaptation of different fiber phenotypes into adulthood. Our recent research on the genetic basis of fiber specificity has focused on the emergence of mature fiber types and have implicated a group of transcriptional regulatory proteins, known as E proteins, in the control of fiber specificity. The restriction of E proteins to selected muscle fiber types is an attractive hypothetical mechanism for the generation of muscle fiber-specific patterns of gene expression. To date our results support a model wherein different E proteins are selectively expressed in muscle cells to determine fiber-restricted gene expression. These studies are a first step to define the molecular mechanisms responsible for the shifts in fiber type under conditions of microgravity, and to determine the potential importance of E proteins as upstream targets for the effects of weightlessness. In the past year we have determined that the expression of E Proteins is restricted to specific fiber types by post-transcriptional mechanisms. By far, the most prevalent mechanism of cellular control for achieving post-transcriptional regulation of gene expression is selective proteolysis -through the ubiquitin -proteasome pathway. Steady-state levels of HEB message are similar in all fast and slow skeletal muscle fiber types, yet the protein is restricted to Type IIX fibers. HEB appears to be a nodal point for regulating fiber-specific transcription, as expression of the transcription factor is regulated at the post-transcriptional level. It is not clear at present whether the regulation is at the level of protein synthesis or degradation. We are now poised to evaluate the biological role of ubiquitination in fiber specific-gene expression by controlling the post-transcriptional expression of E Proteins. The use of metabolic labelling and pharmacological inhibitors of the ubiquitin pathway will be used to identify the mode of regulation of the Type IIX expression pattern. The potential role of specific kinases in effecting the restriction of HEB expression will be examined by using both inhibitors and activators. The results of these studies will provide the necessary information to evaluate the biological role of E proteins in controlling fiber type transitions, and in potentially attenuating the atrophic effects of microgravity conditions. We have also recently shown that ectopic expression of the HEB protein transactivates the Type IIX-specific skeletal a-actin reporter. The 218 bp skeletal a-actin promoter drives transgene expression solely in mature Type IIX fibers. A mouse also carrying the transgene MLCI/HEB (which ectopically expresses the E Protein HEB in Type IIB fibers) forces expression of the skeletal a-actin reporter gene in Type IIB fibers. We can now dissect the composition of this fiber-specific cis-element. The skeletal a-actin promoter is quite compact and has been extensively characterized in vitro for activity and binding factors. The single E box may act as a binding target of myogenic factor/HEB heterodimer to allow for IIX expression. The HEB transcription factor may recognize either the precise flanking sequences of the E Box, or perhaps interacting with other proteins bound nearby, and activating expression in Type IIX fibers. This E box will be both ablated, and alternatively, as ablation may well destroy any muscle-specific transcriptional activity, flanking sequences substituted with those surrounding the E box (El) of the myogenin promoter. Modification of fiber-specific transgene expression will be tested in transgenic mice. The results of these studies will provide basic information on the regulatory circuitry underlying fiber specificity, and will form the basis for building appropriate transgenic regulatory cassettes to effect fiber transitions in subsequent experimental manipulations on unweighted muscles.

Rosenthal, Nadia A.↗