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DOE OSTI2021

Editorial: Bioconversion and Biorefinery of C1 Compounds

The past decade has seen significant progress in the field of metabolic engineering and synthetic biology. The exponentially growing multi-omics data and technological advances in the development of efficient genetic manipulation tools and techniques have allowed scientists to explore and expand their understanding of microbial metabolisms and further develop sophisticated engineering strategies to realize the use of industrial "workhorses" and non-conventional microorganisms for sustainable bioconversion and biorefinery. There is of great interest for the research community in using C1 compounds (i.e., CO 2 , CO/syngas, methane, methanol) as the next generation feedstocks for microbial cell factories and biocatalysts to promote the sustainable development of a green economy (Figure 1). Considering lowering input costs is also a main consideration for successful business ventures, the use of inexpensive, abundant, and widely accessible C1 compounds is envisioned as a promising route for the sustainable production of fine chemicals, fuels, and other high-value products. Many C1 compounds are waste gases from industrial activities and may have detrimental effects on climate change upon emission into the atmosphere. Therefore, promoting the use of C1 compounds as renewable carbon feedstocks can greatly contribute to the reduction of anthropogenic emission of air pollutants.

09 BIOMASS FUELS↗

DOE OSTI2022

Editorial: Microorganisms for Consolidated 2nd Generation Biorefining

In the last few decades, lignocellulosic biomass has attracted substantial interest as a feedstock for fermentative production of fuels and other commodity chemicals due to its wide availability and low cost. However, lignocellulose has innate complexity and recalcitrance to biodegradation. In natural environments, effective plant biomass decay is obtained by synergistic activity of complex microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Editorial: Structure and mechanism of microbial membrane active transporters

Membrane active transporters play essential roles in microbial physiology. They couple energy transduction to conformational changes that drive translocation of nutrients, substrates and ions, as well as molecular communication. The structure and function of microbial membrane active transporters are highly diverse. Typical examples include the primary active transporters in the ATP-binding cassette (ABC) superfamily (Thomas and Tampé, 2020; Davidson et al., 2008; Locher et al., 2002), the secondary active transporters in the Major Facilitator Superfamily (MFS) (Drew et al., 2021; Kaback and Guan, 2019), and the ligand-gated porins in the TonB-dependent transporter (TBDT) family (Klebba et al., 2021). As structural, proteogenomic, and computational methods advance, active transporters are increasingly recognized as dynamic molecular machines whose mechanisms can now be visualized and modeled with remarkable precision, building on decades of biochemical and biophysical discovery that established the foundations of this field. The transporter studies recruited in this Research Topic provide us with new insights into the field including structure-function of sugar transporters in yeast, structural prediction and classification of ABC complexes in Bacillus subtilis, Type VI Secretion System (T6SS) in Bacteroides fragilis, amino acids uptake in Escherichia coli and bacterial spore germination.

mechanism↗

DOE OSTI2023

Editorial: Functional microcircuits in the brain and in artificial intelligent systems

Fundamental principles underlying higher-order cognitive functions remain elusive, but recent breakthroughs in neurophysiology and deep learning offer new perspectives. First, experimental studies have uncovered neural circuit motifs consisting of various neuron types; see Brain Initiative Cell Census Network (https://www.nature.com/collections/cicghheddj). For example, inhibitory neuron types expressing exclusive genes have specific targets and distinct functions (Pfeffer et al., 2013). Furthermore, diverse neuron types in cortex and their connectomes were identified in cortical columns (Jiang et al., 2015); see also Barth et al. (2016) for a debate on neuron types. Second, artificial neural networks were originally inspired by structures of the brain (McCulloch and Pitts, 1943) and could be trained to perform complex functions similar to human perception/cognition by deep learning (DL) (Lecun et al., 2015).

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Editorial: Neuroscience, computing, performance, and benchmarks: Why it matters to neuroscience how fast we can compute

At the turn of the millennium the computational neuroscience community realized that neuroscience was in a software crisis: software development was no longer progressing as expected and reproducibility declined. The International Neuroinformatics Coordinating Facility (INCF) was inaugurated in 2007 as an initiative to improve this situation. The INCF has since pursued its mission to help the development of standards and best practices. In a community paper published this very same year, Brette et al. tried to assess the state of the field and to establish a scientific approach to simulation technology, addressing foundational topics, such as which simulation schemes are best suited for the types of models we see in neuroscience. In 2015, a Frontiers Research Topic “Python in neuroscience” by Muller et al. triggered and documented a revolution in the neuroscience community, namely in the usage of the scripting language Python as a common language for interfacing with simulation codes and connecting between applications. The review by Einevoll et al. documented that simulation tools have since further matured and become reliable research instruments used by many scientific groups for their respective questions. Open source and community standard simulators today allow research groups to focus on their scientific questions and leave the details of the computational work to the community of simulator developers. A parallel development has occurred, which has been barely visible in neuroscientific circles beyond the community of simulator developers: Supercomputers used for large and complex scientific calculations have increased their performance from ~10 TeraFLOPS (10 13 floating point operations per second) in the early 2000s to above 1 ExaFLOPS (10 18 floating point operations per second) in the year 2022. This represents a 100,000-fold increase in our computational capabilities, or almost 17 doublings of computational capability in 22 years. Moore's law (the observation that it is economically viable to double the number of transistors in an integrated circuit every other 18–24 months) explains a part of this; our ability and willingness to build and operate physically larger computers, explains another part. It should be clear, however, that such a technological advancement requires software adaptations and under the hood, simulators had to reinvent themselves and change substantially to embrace this technological opportunity. It actually is quite remarkable that—apart from the change in semantics for the parallelization—this has mostly happened without the users knowing. The current Research Topic was motivated by the wish to assemble an update on the state of neuroscientific software (mostly simulators) in 2022, to assess whether we can see more clearly which scientific questions can (or cannot) be asked due to our increased capability of simulation, and also to anticipate whether and for how long we can expect this increase of computational capabilities to continue.

biophysically detailed models↗

DOE OSTI2023

Editorial: Sorption processes in nuclear waste management: data knowledge management and new methodologies for data acquisition/prediction

A fundamental approach to Nuclear Waste Repository research involves the collection of experimental data in a laboratory setting, development of empirical and/or mechanistic numerical models representing those observations, and application of these models (or Reduced Order Models) into reactive transport and performance assessment models as predictive tools for informing society of impacts and risks associated with nuclear waste repository scenarios (Stevens et al., 2020). Therefore, the assimilation and interpretation of experimental data must take advantage of both new data and the rich historical data available in the literature and apply novel modeling approaches to improve predictive tools, particularly from the standpoint of uncertainty quantification, for nuclear waste repository performance assessment (Zavarin et al., 2022).

sorption↗

DOE OSTI2025

Editorial: Applications of spectroscopy and chemometrics in nuclear materials analysis

Optical analysis techniques, including spectroscopy and image analysis, have many advantages when applied to the study of nuclear materials. They require small sample sizes, can be performed remotely, and can be proceduralized through consistent practice. Most importantly, they provide a wealth of information by generating multivariate data. For example, ultraviolet–visible–near-infrared absorbance spectroscopy of actinides in aqueous and organic solutions is dependent on the oxidation state, anionic complexation, and temperature. These variables are important for solution-based separation processes, and sensitivity to these factors, combined with online monitoring, can drive the efficiency and control of these processes. The morphology and chemical composition of actinide particles can also provide a vital clue to the mechanisms by which the particles were formed, providing forensic information on the origins of the particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Editorial: The Future of Nuclear Structure: Challenges and Opportunities in the Microscopic Description of Nuclei

The past two decades have witnessed tremendous progress in the microscopic description of atomic nuclei. The Topical Review `The Future of Nuclear Structure' aims at summarizing the current state-of-the-art microscopic calculations in Nuclear Theory and to give a useful reference for young researches who wish to learn more about this exciting discipline.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Editorial: Quantum Information and Quantum Computing for Chemical Systems

Quantum computing has emerged as an exciting inter-disciplinary research topic that cuts across the traditional fields of physics, computer science, and engineering. It is a revolutionary model of computation that has offered new insights into methods for modeling and simulation of chemical systems. Applications of quantum computing to chemistry have demonstrated rapid progress on both theoretical and experimental fronts. Past theoretical efforts have shown how to adapt quantum computation to a variety of problems including electronic structure and molecular dynamics. In addition, the development of quantum algorithms for quantum chemistry has been stimulated by the greater availability of more capable quantum computing devices. Advances in the number and quality of qubits continues to enable remarkable proof-of-concept demonstrations working towards a milestone of quantum computational advantage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Editorial: Particle interaction with afterglow plasma and non-quasi-neutral plasma

When immersed in a plasma environment, small nano-to micrometer sized solid particles undergo electrical charging by collecting charged species from the plasma. Once charged, these particles interact in peculiar ways with the surrounding plasma, triggering a widespread of interesting physical phenomena. Such systems, also known as complex or dusty plasmas, have been investigated for a few decades already.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Editorial: Generation, detection and manipulation of skyrmions in magnetic nanostructures

Due to their compact shape and small size down to a few nanometers, good thermal stability, and low driven current density, magnetic skyrmions have become promising building blocks for high-density storage and fast information processing applications. In a dozen years, this field dubbed as skyrmionics has attracted significant attention for exploring fundamental physics as well as for practical applications.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Editorial: Using high energy density plasmas for nuclear experiments relevant to nuclear astrophysics

Thermonuclear reaction rates and nuclear processes have traditionally been explored by means of accelerator experiments, which are difficult to execute at conditions relevant to nucleosynthesis. High energy density (HED) plasmas generated using lasers, such as the inertial confinement fusion (ICF) platform, more closely mimic astrophysical environments in several ways, including with thermal distributions of reacting ions as opposed to mono-energetic ions impinging on a cold target; stellar-relevant plasma temperatures and densities; and neutron flux densities not found anywhere else on earth. The most extreme conditions can currently be achieved at the National Ignition Facility (NIF) laser in the US, where densities of 10 3 g/cm 3 and neutron fluxes up to 5∙10 27 neutrons/cm/s have been demonstrated over a time period of a few tens of picoseconds. The HED platform is emerging as an interesting complement to accelerator experiments.

charged-particle-induced reactions↗

DOE OSTI2025

Editorial: Visualizing offline and live data with AI (VOLDA) workshop first edition Princeton 11-13th June 2024

The first edition of the Visualizing Offline and Live Data with AI’ (VOLDA) Workshop took place at the Princeton University Campus, Mader Hall from 11 to 13 June 2024. This annual workshop held for the first time aims at bringing together the fusion community to discuss the challenges brought by Artificial Intelligence (AI) and visualizing large datasets in fusion experiment and simulation.

artificial intelligence↗

DOE OSTI2020

Editorial: Proceedings of ICPSBBB 2018 - 2nd International Conference on Plant Synthetic Biology, Bioengineering and Biotechnology

Plant synthetic biology combines engineering principles with plant biology toward the design, construction, and testing of plants with new traits (Liu and Stewart, 2015). Synthetic biology applies engineering principles, using defined genetic parts with the aim of achieving predictable outcomes. The field aims at providing fuels, pharmaceuticals, bioactive metabolites and increased crop yield. Synthetic biology is increasingly forming a framework in genetic transformation of plants allowing us to improve traits and crop performance. The conference on Plant Synthetic Biology, Bioengineering, and Biotechnology covers broad aspects of plant synthetic biology, ranging from tools to the design of predictable functions and precision genome editing, to re-designed photosynthesis, plant bioengineering techniques, and rational design of novel plant traits. This Frontiers in Plant Science virtual issue on the “Research Topic Proceedings of ICPSBBB 2018 - 2nd International Conference on Plant Synthetic Biology, Bioengineering and Biotechnology” consists of 8 publications, including four reviews and four original research articles, which fall into the following general topics: quantitative and genetic parts, evolution, expression of transgenes and epigenetic changes, engineering of stress tolerance and bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Editorial: Plant-Soil Interactions Under Changing Climate

The health and well-being of plants and soil is crucial for all life on Earth. It is well-known that vegetation cover follows climatic zones, and plants respond to climatic drivers such as temperature and precipitation. It is also well-known that plant health depends on the properties and health of the soil, and that strong interactions among biota above and belowground dictate the functioning of both realms. Yet, soils and the processes occurring belowground are often considered a “black box,” and are treated very simplistically in our efforts to understand, quantify, and model the future of the planet. Our understanding of the interactions between plants and soils is also far from complete and offers some of the most important research frontiers in community ecology, biogeochemistry, and global change science.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Editorial: Phenylpropanoid Systems Biology and Biotechnology

Phenylpropanoids are specialized metabolites involved in several aspects of plant growth and development and in the responses of plants to environmental stimuli. These compounds are synthesized from key intermediates of the shikimate pathway, which are structurally modified by the combined activities of lyases, transferases, ligases, reductases and oxygenases, resulting in the organ- and developmental-specific synthesis and accumulation of diverse metabolites (Vogt, 2010). The phenylpropanoid pathway provides the building blocks for lignin, suberin, and condensed tannins that play a role in structural support and mechanical strength. Lignin is a major contributor to feedstock recalcitrance and negatively affects the conversion of plant biomass into downstream products in biorefineries (Liu et al., 2021). Further, this pathway is key for the production of anthocyanins for organ pigmentation, flavonols and flavones for UV protection, various flavonoids and isoflavonoids for plant-microbe interactions, and antimicrobial phytoalexins for protection against pathogens (Deng and Lu, 2017). In addition to their biological functions in planta, phenylpropanoids are economically important metabolites. They constitute important components in the human diet, acting as nutraceutical compounds with antioxidant, chemopreventive, antimitotic, neuroprotective, cardioprotective, and anti-inflammatory activities. Several phenylpropanoids are considered high-value biochemicals employed in the production of fragrances, pharmaceuticals and biopolymers (Lin and Eudes, 2020).

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Editorial: Wood Development and Physiology in a Changing Climate

Wood of forest trees is a renewable, sustainable and easily workable material and has been widely used in construction, paper making, furniture, and as a feedstock for biofuels. Wood formation is the result of a highly ordered and finely regulated process. Secondary xylem (wood) and phloem are the inner and outer derivative products of the vascular cambium, respectively. Xylem is mainly composed of dead cells with thickened cell walls rich in cellulose, hemicelluloses, and lignin, which are responsible for providing mechanical support and conducting water and minerals for the trees. Phloem transports photoassimilates and signaling molecules, including phytohormones and peptides. Wood structure varies greatly between, and within, tree species. A thorough understanding of developmental processes and metabolic pathways during wood formation would provide a basis for improving wood biomass and modifying properties in forest trees.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Editorial: Rising stars in plant ROS/redox biology under abiotic stress conditions

Plants are constantly subjected to a wide range of abiotic stresses including salinity, high temperatures, drought, or cold, among others, that negatively impact their growth and development and cause crop yield losses worldwide (Lesk et al., 2016; Bailey-Serres et al., 2019). These stress conditions induce the accumulation of reactive oxygen species (ROS) such as hydrogen peroxide (H 2 O 2 ), superoxide ($O_{2•}$$^—$), singlet oxygen ($^1O_2$), or hydroxyl radical (HO·). ROS play a key role in stress sensing and signaling, as well as in the activation of different mechanism involved in plant acclimation to different stresses (Mittler et al., 2022). However, ROS levels that are too high are cytotoxic (Mittler, 2017). To prevent cellular oxidation by ROS, an interplay between ROS production, scavenging and transport maintains ROS at controlled concentrations, as well as drives ROS signaling responses involved in plant acclimation to stress (Baxter et al., 2014; Mittler et al., 2022).

protein carbonylation↗