Results for “pattern dependence” — Page 2

DOE OSTI2021

Exposure to an environmental mixture of polycyclic aromatic hydrocarbons induces hepatic cytochrome P450 enzymes in mice

Cytochrome P450 enzymes (CYPs) play an important role in bioactivating or detoxifying polycyclic aromatic hydrocarbons (PAHs), common environmental contaminants. While it is widely accepted that exposure to PAHs induces CYPs, effectively increasing rates of xenobiotic metabolism, dose- and time-response patterns of CYP induction are not well known. In order to better understand dose- and time-response relationships of individual CYPs following induction, we exposed B6129SF1/J mice to single or repeated doses (2-180 µmol/kg/d) of benzo[a]pyrene (BaP) or Supermix-10, a mixture of the top 10 most abundant PAHs found at the Portland Harbor Superfund Site. In hepatic microsomes from exposed mice, we measured amounts of active CYPs using activity-based protein profiling and total CYP expression using global proteomics. We observed rapid Cyp1a1 induction after 6 hr at the lowest PAH exposures and broad induction of many CYPs after 3 daily PAH doses at 72 hr following the first dose. Using samples displaying Cyp1a1 induction, we observed significantly higher metabolic affinity for BaP metabolism (Km reduced 3-fold), 3-fold higher intrinsic clearance, but no changes to the Vmax. Mice dosed with the highest PAH exposures exhibited 1.7 to 5-fold higher intrinsic clearance rates for BaP compared to controls and higher Vmax values indicating greater amounts of enzymes capable of metabolizing BaP. This study demonstrates exposure to PAHs found at Superfund Sites induces enzymes in dose- and time-dependent patterns in mice. Accounting for specific changes in enzyme profiles, and relative rates of PAH bioactivation and detoxification, and resulting risk will help translate internal dosimetry of animal models to humans and improve risk assessments of PAHs at Superfund sites.

Stoddard, Ethan G.↗

DOE OSTI2018

Cosmological signatures of a mirror twin Higgs

Here, we explore the cosmological signatures associated with the twin baryons, electrons, photons and neutrinos in the Mirror Twin Higgs framework. We consider a scenario in which the twin baryons constitute a subcomponent of dark matter, and the contribution of the twin photon and neutrinos to dark radiation is suppressed due to late asymmetric reheating, but remains large enough to be detected in future cosmic microwave background (CMB) experiments. We show that this framework can lead to distinctive signals in large scale structure and in the cosmic microwave background. Baryon acoustic oscillations in the mirror sector prior to recombination lead to a suppression of structure on large scales, and leave a residual oscillatory pattern in the matter power spectrum. This pattern depends sensitively on the relative abundances and ionization energies of both twin hydrogen and helium, and is therefore characteristic of this class of models. Although both mirror photons and neutrinos constitute dark radiation in the early universe, their effects on the CMB are distinct. This is because prior to recombination the twin neutrinos free stream, while the twin photons are prevented from free streaming by scattering off twin electrons. In the Mirror Twin Higgs framework the relative contributions of these two species to the energy density in dark radiation is predicted, leading to testable effects in the CMB. These highly distinctive cosmological signatures may allow this class of models to be discovered, and distinguished from more general dark sectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Top-Down Analysis of Proteins in Low Charge States

The impact of charging methods on the dissociation behavior of intact proteins in low charge states is investigated using HCD and 193 nm UVPD. Low charge states are produced for seven different proteins using the following four different methods: (1) proton transfer reactions of ions in high charge states generated from conventional denaturing solutions; (2) ESI of proteins in solutions of high ionic strength to enhance retention of folded native-like conformations; (3) ESI of proteins in high pH solutions to limit protonation; and (4) ESI of carbamylated proteins. Comparison of sequence coverages, degree of preferential cleavages, and types and distribution of fragment ions reveals a number of differences in the fragmentation patterns depending on the method used to generate the ions. More notable differences in these metrics are observed upon HCD than upon UVPD. The fragmentation caused by HCD is influenced more significantly by the presence/absence of mobile protons, a factor that modulates the degree of preferential cleavages and net sequence coverages. Carbamylation of the lysines and the N-terminus of the proteins alters the proton mobility by reducing the number of proton-sequestering, highly basic sites as evidenced by decreased preferential fragmentation C-terminal to Asp or N-terminal to Pro upon HCD. UVPD is less dependent on the method used to generate the low charge states and favors non-specific fragmentation, an outcome which is important for obtaining high sequence coverage of intact proteins. .

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2017

AHR and CYP1A expression link historical contamination events to modern day developmental effects in the American alligator

The aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor that initiates a transcriptional pathway responsible for the expression of CYP1A subfamily members, key to the metabolism of xenobiotic compounds. Toxic planar halogenated aromatic hydrocarbons, including dioxin and PCBs, are capable of activating the AHR, and while dioxin and PCB inputs into the environment have been dramatically curbed following strict regulatory efforts in the United States, they are still detected in the environment and exposures remain relevant today. Little is known regarding the effects that long-term chronic exposures to dioxin or dioxin-like compounds might have on the development and subsequent health of offspring from exposed individuals, nor is much known regarding AHR expression in reptilians. In this work, we characterize AHR and CYP1A gene expression in embryonic and juvenile specimen of a long-lived, apex predator, the American alligator (Alligator mississippiensis), and investigate variation in gene expression profiles in offspring collected from sites in the southeastern U.S. conveying differential exposures to environmental contaminants. Both age- and tissue-dependent patterning of AHR isoform expression was detected; receptor isoforms are highly expressed in liver, kidney, thyroid, and intestine. We then characterized two downstream transcriptional targets of the AHR, CYP1A1 and CYP1A2, and describe conserved elements of their genomic architecture. When comparisons across different sites were made, hepatic expression of CYP1A2, a direct target of the AHR, was elevated in embryos from a site associated with a dioxin point source and previously characterized PCB contamination. These effects were not persistent, as site-specific variation was absent in juveniles originating from field-collected eggs but reared under lab conditions. Our results illustrate the patterning of AHR gene expression in a long-lived environmental model species, and indicate a potential contemporary influence of historical contamination. This research presents a novel opportunity to link historical contamination events to contemporary effects on critical genetic pathways during embryonic development, and carries significant potential to inform our understanding of potential health effects in wildlife and humans.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2018

Behavioural phenotypes in mice after prenatal and early postnatal exposure to intermediate frequency magnetic fields

Highlights: • Human exposure to intermediate frequency magnetic fields (MF) is increasing. • We exposed prenatal and early postnatal male mice to 7.5 kHz MFs at 12 and 120 μT. • A behavioural teratology study focused on the developing nervous system. • No consistent adverse effects were observed. Electromagnetic fields are ubiquitous in the environment. Human exposure to intermediate frequency (IF) fields is increasing due to applications like electronic article surveillance systems, wireless power transfer, and induction heating cooking hobs. However, there are limited data on possible health effects of exposure to IF magnetic fields (MF). In the present study, we set out to assess cognitive and behavioural effects of IF MF in mice exposed during prenatal and early postnatal periods. Pregnant female mice were exposed continuously to 7.5 kHz MFs at 12 and 120 μT, from mating until weaning of pups. Sham exposed pregnant mice were used as a control group. A behavioural teratology study was conducted on the male offspring at two months of age to detect possible effects on the developing nervous system. Body weight development did not differ between the exposure groups. The exposure did not alter spontaneous motor activity when exploring a novel cage or anxiety in novelty-suppressed feeding or marble burying tests. Improved performance in the Rotarod task was observed in the 12 µT group, while the 120 μT exposure group swam more slowly than the sham exposed group in the Morris swim navigation task. However, indices of learning and memory (path length and escape latency during task acquisition and search bias during the probe test) did not differ between the exposure groups. Furthermore, the passive avoidance task did not indicate any impairment of long-term memory over a 48 h interval in the exposed groups. In a post-mortem histopathological analysis, there was no evidence for an effect of IF MF exposure on astroglial reactivity or hippocampal neurogenesis. The results suggest that the IF MF used did not have detrimental effects on spatial learning and memory or histological markers of tissue reaction. The two statistically significant findings that were observed (improved performance in the Rotarod task in the 12 µT group and decreased swimming speed in the 120 µT group) are likely to be chance findings, as they do not form an internally consistent, dose-dependent pattern indicative of specific developmental effects.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Comparative Dissolution of Iron-Bearing Minerals by Catecholate and Hydroxamate Siderophores under Oxic and Anoxic Conditions

Siderophores play a crucial role in biological iron (Fe) acquisition and mobilization by promoting Fe mineral and rock weathering. While the effects of the hydroxamate siderophore desferrioxamine B (DFOB) have been extensively studied, the role of catecholates in the dissolution of Fe mineral and rock under varying redox conditions remain limited. Moreover, despite Fe being one of the most redox-active metals, the siderophore-mediated redox transformations of solid-phase Fe and their impact on mineral dissolution are not well understood. Herein, this study systematically investigated dissolution behavior of both Fe(II) and Fe(III)-bearing minerals and rocks (Fe(II)- bearing basalt and olivine, and Fe(III)- bearing nontronite and goethite), by two structurally distinct biological siderophores, catecholate protochelin and hydroxamate DFOB, under both oxic and anoxic conditions. Batch experiments quantified Fe and transition metals (Mn, Ni, Zn, Mo) released from the tested minerals in the presence of siderophores. Throughout the dissolution experiments, siderophore concentrations and Fe-siderophore complexation in solutions were measured using UV-vis spectrometry. Fe redox changes under oxic and anoxic conditions by siderophores were determined, and mineral surface alterations following siderophore treatments were characterized through scanning electron microscopy (SEM) and time-of-flight secondary ion mass spectroscopy (ToF-SIMS). Results revealed distinct interplays of dissolution mechanisms, including ligand-exchange promoted dissolution and reductive dissolution, along with Fe(III) reduction and Fe(II) oxidation, contributing to the Fe(II)- and Fe(III)-rich mineral weathering under varying redox conditions. Under oxic conditions, both protochelin and DFOB enhanced Fe release from Fe(II)-rich basalt and olivine more effectively than from Fe(III)-rich minerals. DFOB induced greater Fe(II)-mineral dissolution than protochelin. This difference was attributed to a higher level of Fe(II) oxidation by DFOB in contrast to protochelin, as well as the protochelin oxidation with the loss of Fe binding groups (catechols). Under anoxic conditions, both siderophores significantly reduced Fe(III) in nontronite and goethite, with protochelin demonstrating substantially stronger Fe(III) reduction capacity than DFOB. However, Fe(III) reduction negatively impacted Fe release from Fe(III)-rich minerals. Instead, Fe release from Fe(II)-rich minerals was enhanced under anoxic conditions due to the absence of Fe(II) oxidation and labile Fe(II). Variations in siderophore adsorption also contributed to dissolution differences. Beyond iron, the release of transition metals from tested minerals was influenced by elemental contents, mineral compositions, and siderophore types, revealing distinct metal- and siderophore-dependent patterns. This systematic investigation highlights the roles of siderophores in Fe redox cycling and metal mobilization, enhancing our understanding of different siderophore behaviors in siderophore-mediated microbial metal acquisition within redox-dynamic environments, with implications for bioleaching industries and applications in agriculture and climate change mitigation.

Guo, Dongyi↗

DOE OSTI2021

Injectable platelet rich fibrin facilitates hair follicle regeneration by promoting human dermal papilla cell proliferation, migration, and trichogenic inductivity

Hair follicle regeneration has been successful in mice but failed in human being for years. Dermal papilla cells, a specialized mesenchymal stem cell derived from dermal papilla within hair follicles, is considered the key cells for hair follicle regeneration function as both regeneration initiator and regulator. Injectable platelet rich fibrin (i-PRF), a novel biomaterial rich in a variety of growth factors and three-dimensional scaffolds, has shown promising effects on tissue regeneration. In this study, we aimed to evaluate the application of i-PRF in human hair follicle regeneration by examining the biological effects of i-PRF on human dermal papilla cells (hDPCs). Biomaterial compatibility, cell viability, proliferation, migration, alkaline phosphatase activity and trichogenic inductivity were assessed after exposing hDPCs to different concentrations of i-PRF extracts. In addition, we investigated the ultrastructure of i-PRF with all cell components filtered. The results revealed that i-PRF possessing excellent biocompatibility and could significantly promote hDPCs proliferation, migration, and trichogenic inductivity. Furthermore, the concentration of i-PRF is able to remarkably influence hDPCs behavior in a dose-dependent pattern. Different concentrations exhibited differential effects on hDPCs behavior. In general, lower concentration promotes cell proliferation better than higher concentration, while higher concentration promotes cell function better reversely. Best concentration for hDPCs in vitro expending is 1% concentration. 20% concentration is optimal for hair follicle regeneration. In summary, our findings concluded that i-PRF facilitates hair follicle regeneration by promoting human dermal papilla cell proliferation, migration, and trichogenic inductivity.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Microtopography Matters: Belowground CH 4 Cycling Regulated by Differing Microbial Processes in Peatland Hummocks and Lawns

Water table depth and vegetation are key controls of methane (CH 4 ) emissions from peatlands. Microtopography integrates these factors into features called microforms. Microforms often differ in CH 4 emissions, but microform-dependent patterns of belowground CH 4 cycling remain less clearly resolved. Here, to investigate the impact of microtopography on belowground CH 4 cycling, we characterized depth profiles of the community composition and activity of CH 4 -cycling microbes using 16S rRNA amplicon sequencing, incubations, and measurements of porewater CH 4 concentration and isotopic composition from hummocks and lawns at Sallie's Fen in NH, USA. Geochemical proxies of methanogenesis and methanotrophy indicated that microforms differ in dominant microbial CH 4 cycling processes. Hummocks, where water table depth is lower, had higher porewater redox potential (Eh) and higher porewater δ 13 C-CH 4 values in the upper 30 cm than lawns, where water table depth is closer to the peat surface. Porewater δ 13 C-CH 4 and δD-CH 3 D values were highest at the surface of hummocks where the ratio of methanotrophs to methanogens was also greatest. These results suggest that belowground CH 4 cycling in hummocks is more strongly regulated by methanotrophy, while in lawns methanogenesis is more dominant. We also investigated controls of porewater CH 4 chemistry. The ratio of the relative abundance of methanotrophs to methanogens was the strongest predictor of porewater CH 4 concentration and δ 13 C-CH 4 , while vegetation composition had minimal influence. As microbial community composition was strongly influenced by redox conditions but not vegetation, we conclude that water table depth is a stronger control of belowground CH 4 cycling across microforms than vegetation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Intensifying Renewable Energy Droughts in the Western U.S. Amid Evolving Infrastructure and Climate

If renewable energy resources continue to become a larger part of the generation mix in the United States (U.S.), so does the potential impact of prolonged periods of low wind and solar generation, known as variable renewable energy (VRE) droughts. In such a future, naturally occurring VRE droughts need to be evaluated for their potential impact on grid reliability. This study is the first of its kind to examine the impacts of compound VRE energy droughts in the Western U.S. across a range of potential future climate and infrastructure scenarios. We find that compound VRE drought severity may increase significantly in the future, primarily due to the dramatic increase in wind and solar generation needed in some future infrastructure scenarios. We find that in our future climate scenario, the variability of energy drought severity increases, which has implications for sizing energy storage necessary for mitigating drought events. We also examine the spatial patterns of compound VRE drought events that effect multiple regions of the grid simultaneously. These co-occurring events have distinct spatial patterns depending on the season. We observed overall fewer connected events in the future with the combined effect of potential climate and infrastructure changes, although in the fall we observe a climate-induced shift toward events which impact more regions simultaneously.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

WE-DE-202-00: Connecting Radiation Physics with Computational Biology

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-DE-202-01: Connecting Nanoscale Physics to Initial DNA Damage Through Track Structure Simulations

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-DE-202-02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-DE-202-03: Modeling of Biological Processes - What Happens After Early Molecular Damage?

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Four-dimensional dynamics of multirotational transition stimulated rotational Raman scattering in air

Stimulated rotational Raman scattering in air is a powerful parasitic process that degrades high intensity laser beams and pulses propagated over significant distances. Conversely, it is used beneficially in the context of Raman lasers. Through this inelastic scattering process, laser photons are converted to higher (anti-Stokes) or lower (Stokes) energies, according to rotational mode transitions in nitrogen and oxygen diatomic molecules. The full wave-mixing problem involves numerous frequencies, and it is consistently assumed that only one rotational mode contributes to the conversion process. We instead present a dynamic 4D multirotational model that is implemented in a parallelized manner within the Virtual Beamline++ optical modeling package allowing high-resolution 4D studies. We highlight the effect that spontaneous emission plays in large and small beam-width setups, even in the highly saturating regime. The weaker transition modes play a large role in the persistent dynamics and can lead to complex spatiotemporal coupling through nonlinear competition of the modes. We highlight how and why these weaker modes persist, how the size and shape of speckle patterns depends highly on the initial beam profile, and how weaker modes can transiently become stronger as a result of such competition.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Exposure to ionizing radiation disrupts normal epigenetic aging in Japanese medaka

Alterations to the epigenome are a hallmark of biological aging and age-dependent patterning of the DNA methylome (“epigenetic aging”) can be modeled to produce epigenetic age predictors. Rates of epigenetic aging vary amongst individuals and correlate to the onset of age-related disease and all-cause mortality. Yet, the origins of epigenetic-to-chronological age discordance are not empirically resolved. Here, we investigate the relationship between aging, DNA methylation, and environmental exposures in Japanese medaka (Oryzias latipes). We find age-associated DNA methylation patterning enriched in genomic regions of low CpG density and that, similar to mammals, most age-related changes occur during early life. We construct an epigenetic clock capable of predicting chronological age with a mean error of 61.1 days (~8.4% of average lifespan). To test the role of environmental factors in driving epigenetic age variation, we exposed medaka to chronic, environmentally relevant doses of ionizing radiation. Because most organisms share an evolutionary history with ionizing radiation, we hypothesized that exposure would reveal fundamental insights into environment-by-epigenetic aging interactions. Radiation exposure disrupted epigenetic aging by accelerating and decelerating normal age-associated patterning and was most pronounced in cytosines that were moderately associated with age. These findings empirically demonstrate the role of DNA methylation in integrating environmental factors into aging trajectories.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Direct Writing of X-ray Gratings Using Zone-Plate-Array Lithography (ZPAL)

With the objective of providing the synchrotron and free-electron-laser communities with rapid turnaround and low prices for the highest quality and most advanced gratings and diffractive-focusing optics, LumArray has made specific improvements to its ZP-150 maskless photolithography system, which is based on Zone-Plate-Array Lithography (ZPAL), a technology unique to Lumarray. ZPAL’s advantages include an ability to correct in software for systematic patterning errors. Emphasis was placed on interferometric measurements of various contributors to patterning errors using Fizeau interferometry and a Mireau technique that was developed specifically for measuring errors within a micron-scale area. Average line-placement error was reduced below 20 nm using both pattern-file distortion and address-grid modification. The preferred implementation, address-grid modification, is hardware-based and requires no user intervention while also correcting more types of error. With continued iteration and refinement of the error measurements, we anticipate achieving global line-placement error below10nm. In order to investigate line-edge smoothness and high-frequency line-placement errors, a scheme for inspecting micron-sized areas was invented and implemented based on Mireau interferometry. This enabled the various contributions to be separately evaluated and measured. These included: exposure-dose variation, pattern-writing strategy and errors in the positioning of the microlenses. Deleterious crosstalk between microlenses was minimized via a pattern-dependent software modification. The impact of exposure threshold was revealed and adjustment made. The impact of address-grid fineness on line-edge roughness was likewise shown. Lastly, techniques were developed to measure and correct errors in the positioning of microlenses within the array. We expect final calibration of microlens positions to within 5nm.

42 ENGINEERING↗

DOE OSTI2018

Libera Brilliance Test with Beam Signal

The purpose of the tests described below was to estimate performance of Libera Brilliance with real circulating beam signal in the accelerator environment. Tests were performed at CESR and APS. Comprehensive test of the Libera Brilliance with real beam was performed. The obtained results are in accordance with previously obtained on the stand. Single pass capabilities of the Libera Brilliance were studied and found corresponding to the requirements. There is excellent agreement between observations of beam motion with a Libera Brilliance and APS FPGA-based receiver, with the Libera Brilliance unit having less noise in the high-frequency part of spectrum. For fill pattern dependence Libera Brilliance outperformed both the APS FPGA-based unit and the Bergoz BPM receiver.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Using machine learning to improve land use/cover characterization and projection for scenario-based global modeling

The characterization of the land surface in models is critical for robust estimation of the water cycle and associated extremes. Land use determines water demand, and land cover affects water availability. The interaction between water demand and availability is the key determinant of whether systems are resilient to variability in the overall water cycle. Furthermore, activities such as irrigation and deforestation or afforestation may influence regional to global precipitation patterns, depending on the extent of the activity. Thus this proposed work aims to address the following question: How does integrated land use/cover data and improved land use/cover projection, as informed by machine learning approaches, better resolve human-earth system resilience to water cycle variability and extremes?

54 ENVIRONMENTAL SCIENCES↗