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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Aerosol-Water Cycle Interaction: A New Challenge in Monsoon Climate Research

Long recognized as a major environmental hazard, aerosol is now known to have strong impacts on both regional and global climate. It has been estimated that aerosol may reduce by up to 10% of the seasonal mean solar radiation reaching the earth surface, producing a global cooling effect that opposes global warming (Climate Change 2001). This means that the potential perils that humans have committed to global warming may be far greater than what we can detect at the present. As a key component of the Earth climate system, the water cycle is profoundly affected by the presence of aerosols in the atmosphere. Through the so-called direct effect , aerosol scatters and/or absorbs solar radiation, thus cooling the earth surface and changing the horizontal and vertical radiational heating contrast in the atmosphere. The heating contrast drives anomalous atmospheric circulation, resulting in changes in convection, clouds, and rainfall. Another way aerosol can affect the water cycle is through the so-called indirect effects, whereby aerosol increases the number of cloud condensation nuclei, prolongs life time of clouds, and inhibits the growth of cloud drops to raindrops. This leads to more clouds, and increased reflection of solar radiation, and further cooling at the earth surface. In monsoon regions, the response of the water cycle to aerosol forcing is especially complex, not only because of presence of diverse mix of aerosol species with vastly different radiative properties, but also because the monsoon is strongly influenced by ocean and land surface processes, land use, land change, as well as regional and global greenhouse warming effects. Thus, sorting out the impacts of aerosol forcing, and interaction with the monsoon water cycle is a very challenging problem. In this talk, I will offer some insights into how aerosols may impact the Asian monsoon based on preliminary results from satellite observations and climate model experiments. Specifically, I will discuss the elevated heat pump hypothesis, involving atmospheric heating by absorbing aerosols (dust and black carbon) over the southern slopes of the Himalayas, and feedback with the deep convection, in modifying monsoon water cycle over South .and East Asia. The role of aerosol forcing relative to those due to sea surface temperature and land surface processes, as well as observation requirements to verify such a hypothesis will also be discussed.

Lau, William K. M.↗
NASA NTRS2006

Aerosol-Water Cycle Interaction: A New Challenge in Monsoon Climate Research

Long recognized as a major environmental hazard, aerosol is now known to have strong impacts on both regional and global climate. It has been estimated that aerosol may reduce by up to 10% of the seasonal mean solar radiation reaching the earth surface, producing a global cooling effect that opposes global warming (Climate Change 2001). This means that the potential perils that humans have committed to global warming may be far greater than what we can detect at the present. As a key component of the Earth climate system, the water cycle is profoundly affected by the presence of aerosols in the atmosphere. Through the so-called "direct effect", aerosol scatters and/or absorbs solar radiation, thus cooling the earth surface and changing the horizontal and vertical radiational heating contrast in the atmosphere. The heating contrast drives anomalous atmospheric circulation, resulting in changes in convection, clouds, and rainfall. Another way aerosol can affect the water cycle is through the so-called "indirect effects", whereby aerosol increases the number of cloud condensation nuclei, prolongs life time of clouds, and inhibits the growth of cloud drops to raindrops. This leads to more clouds, and increased reflection of solar radiation, and further cooling at the earth surface. In monsoon regions, the response of the water cycle to aerosol forcing is especially complex, not only because of presence of diverse mix of aerosol species with vastly different radiative properties, but also because the monsoon is strongly influenced by ocean and land surface processes, land use, land change, as well as regional and global greenhouse warming effects. Thus, sorting out the impacts of aerosol forcing, and interaction with the monsoon water cycle is a very challenging problem. In this talk, I will offer some insights into how aerosols may impact the Asian monsoon based on preliminary results from satellite observations and climate model experiments. Specifically, I will discuss the "elevated heat pump" hypothesis, involving atmospheric heating by absorbing aerosols (dust and black carbon) over the southern slopes of the Himalayas, and feedback with the deep convection, in modifying monsoon water cycle over South and East Asia. The role of aerosol forcing relative to those due to sea surface temperature and land surface processes, as well as observation requirements to verify such a hypothesis will also be discussed.

Lau, William K. M.↗
DOE OSTI2020

Ecological Assembly Processes Are Coordinated between Bacterial and Viral Communities in Fractured Shale Ecosystems

The ecological drivers that concurrently act upon both a virus and its host and that drive community assembly are poorly understood despite known interactions between viral populations and their microbial hosts. Hydraulically fractured shale environments provide access to a closed ecosystem in the deep subsurface where constrained microbial and viral community assembly processes can be examined. Here, we used metagenomic analyses of time-resolved-produced fluid samples from two wells in the Appalachian Basin to track viral and host dynamics and to investigate community assembly processes. Hypersaline conditions within these ecosystems should drive microbial community structure to a similar configuration through time in response to common osmotic stress. However, viral predation appears to counterbalance this potentially strong homogeneous selection and pushes the microbial community toward undominated assembly. In comparison, while the viral community was also influenced by substantial undominated processes, it assembled, in part, due to homogeneous selection. When the overall assembly processes acting upon both these communities were directly compared with each other, a significant relationship was revealed, suggesting an association between microbial and viral community development despite differing selective pressures. These results reveal a potentially important balance of ecological dynamics that must be in maintained within this deep subsurface ecosystem in order for the microbial community to persist over extended time periods. More broadly, this relationship begins to provide knowledge underlying metacommunity development across trophic levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Deep learning-based noise filtering toward millisecond order imaging by using scanning transmission electron microscopy

Application of scanning transmission electron microscopy (STEM) to in situ observation will be essential in the current and emerging data-driven materials science by taking STEM’s high affinity with various analytical options into account. As is well known, STEM’s image acquisition time needs to be further shortened to capture a targeted phenomenon in real-time as STEM’s current temporal resolution is far below the conventional TEM’s. However, rapid image acquisition in the millisecond per frame or faster generally causes image distortion, poor electron signals, and unidirectional blurring, which are obstacles for realizing video-rate STEM observation. Here we show an image correction framework integrating deep learning (DL)-based denoising and image distortion correction schemes optimized for STEM rapid image acquisition. By comparing a series of distortion corrected rapid scan images with corresponding regular scan speed images, the trained DL network is shown to remove not only the statistical noise but also the unidirectional blurring. This result demonstrates that rapid as well as high-quality image acquisition by STEM without hardware modification can be established by the DL. The DL-based noise filter could be applied to in-situ observation, such as dislocation activities under external stimuli, with high spatio-temporal resolution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Exemption of lattice collapse in Ni–MnO 2 birnessite regulated by the structural water mobility

Lattice collapse and associated mechanical fracture frequently occur in Li-intercalated metal oxide cathodes at the deep charge state upon Li-ion removal, governed by chemical compositions and the resulting electron density of the oxygen atoms. However, similar lattice collapse for metal oxide electrodes in aqueous storage and its mitigation have not been well studied. In this work, we reported the lattice collapse of MnO 2 layered birnessite during the aqueous de-sodiation process at high voltage due to the structural water motion, as evidenced by in situ XRD. Unlike non-aqueous Li-intercalated electrodes, Ni-dopants mitigated the lattice collapse of birnessite at deep charge states. Moreover, density functional theory (DFT) calculations showed that Ni doping induces charge depletion of lattice oxygen due to its higher electronegativity than Mn. This charge reduction, in turn, yields a significant decrease in electrostatic repulsion between the oxygens belonging to lattice and structural water. Classical molecular dynamics simulations based on atomic charges obtained from DFT elucidate that Ni-doping facilitates immobilization of structural water in (Ni)MnO 2 and prevents lattice collapse upon Na-ion removal. (Ni)MnO 2 exempted from lattice collapse shows an improved storage capacity relative to MnO 2 while maintaining similar cycling stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

NRAP-Open-IAM Multisegmented Wellbore Reduced-Order Model: Improvement and Quality Assurance

The multisegmented wellbore model (MSW) semi-analytically estimates the amount of CO 2 and brine leakage from a leaking legacy well by segmenting it into intervals to simulate site-specific stratigraphic and hydrogeologic properties. The model is a component of the National Risk Assessment Partnership Open-Source Integrated Assessment Model (NRAP-Open-IAM), which was developed to perform risk assessment for geologic CO 2 storage. The new wellbore leakage model, which uses deep learning networks for a caprock segment, was developed to enhance the analytical MSW. The model was trained and validated using a synthetic data set of Subsurface Transport Over Multiple Phases (STOMP) multiphase flow simulations from various geological, well attribute, and operational conditions to ensure its quality. The results demonstrate that the model is more accurate than the existing model in predicting the transport of two-phase fluids (brine and injected CO 2 ) through the well. This report provides a detailed explanation of the model development and quality assurance.

58 GEOSCIENCES↗
NASA NTRS1994

Improved Bounds on Non-Luminous Matter in Solar Orbit

We improve, using a larger set of observations including Voyager 2 Neptune flyby data, previous bounds on the amount of dark matter (DM) trapped in a spherically symmetric distribution about the sun. We bound DM by noting that such a distribution would increase the effective mass of the sun as seen by the outer planets and by finding the uncertainty in that effective mass for Uranus and Neptune in fits to the JPL Developmental Ephermeris residuals, including optical data and those two planets' Voyager 2 flybys. We extend our previous procedure by fitting more parameters of the developmental ephemerides. Additionally, we present here the values for Pioneer 10 and 11 and Voyager 1 and 2 Jupiter ranging normal points (and incorporate these data as well).

dark matter Deep Space Network DSN Voyager Neptune↗
NASA NTRS2017

A Consistent EPIC Visible Channel Calibration using VIIRS and MODIS as a Reference

The Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) satellite constantly images the sunlit disk of Earth from the Lagrange-1 (L1) point in 10 spectral channels spanning the UV, VIS, and NIR spectrums. Recently, the DSCOVR EPIC team has publicly released version 2 dataset, which has implemented improved navigation, stray-light correction, and flat-fielding of the CCD array. The EPIC 2-year data record must be well-calibrated for consistent cloud, aerosol, trace gas, land use and other retrievals. Because EPIC lacks onboard calibrators, the observations made by EPIC channels must be calibrated vicariously using the coincident measurements from radiometrically stable instruments that have onboard calibration systems. MODIS and VIIRS are best-suited instruments for this task as they contain similar spectral bands that are well-calibrated onboard using solar diffusers and lunar tracking. We have previously calibrated the EPIC version 1 dataset by using EPIC and VIIRS angularly matched radiance pairs over both all-sky ocean and deep convective clouds (DCC). We noted that the EPIC image required navigations adjustments, and that the EPIC stray-light correction provided an offset term closer to zero based on the linear regression of the EPIC and VIIRS ray-matched radiance pairs. We will evaluate the EPIC version 2 navigation and stray-light improvements using the same techniques. In addition, we will monitor the EPIC channel calibration over the two years for any temporal degradation or anomalous behavior. These two calibration methods will be further validated using desert and DCC invariant Earth targets. The radiometric characterization of the selected invariant targets is performed using multiple years of MODIS and VIIRS measurements. Results of these studies will be shown at the conference.

Haney, C. O.↗
NASA NTRS2020

NASA’s Space Launch System: Launch Capability for Lunar Exploration and Transformative Science

Excitement is building for the first launch of NASA’s Space Launch System (SLS), a unique exploration asset for the agency’s Artemis lunar program as well as for a new generation of science missions. SLS is designed for an array of missions beyond Earth’s orbit. The flexible system, which can be configured for Orion, cargo or Orion with co-manifested payload missions, offers high escape velocities to send more mass to deep space destinations. When configured with an 8.4 m-diameter fairing, SLS offers unmatched payload volume for human exploration and science missions. The initial Block 1 variant will insert at least 26 metric tons (t) to trans-lunar injection (TLI) and the more powerful Block 1B vehicle will launch 34-37 t to TLI using a new-development upper stage. Much of the initial SLS Block 1 vehicle is complete, including the upper stage and payload section, the core stage, engines and the solid rocket boosters. The first mission, Artemis I, launching from modernized and upgraded facilities at Kennedy Space Center (KSC), will be an uncrewed test flight of SLS, Orion and ground processing, with a primary objective of testing Orion’s heat shield at lunar re-entry velocity. Artemis I will have accommodations for 13 6U CubeSat payloads. These CubeSat missions will be deployed along the upper stage disposal trajectory after Orion separates from the vehicle. A rare opportunity for CubeSats to be deployed beyond low Earth orbit (LEO), Artemis I CubeSat missions range from searching for hydrogen and other volatiles on the lunar South Pole to studying the acceleration mechanisms of solar and interplanetary particles from a heliocentric trajectory. With manufacturing of the initial vehicle complete, fabrication and procurement is progressing for the second flight of SLS and Orion, Artemis II. Also an SLS Block 1 and Orion flight launching from KSC, Artemis II will mark the return of American astronauts to deep space with a lunar flyby-free return trajectory mission. With the Artemis III flight, NASA has the goal to land the first woman and the next man on the Moon. Infrastructure beyond SLS will be required for this effort, including elements of the lunar Gateway as well as lunar rovers, landers and additional commercially supplied launch services. SLS, as the only vehicle with the capability to lift 26 t of mass to TLI in its initial Block 1 variant, will remain a key component of this new-era exploration program. Future variants – Block 1B and Block 2 –will lift 34-45 t to TLI. This paper will discuss the status of testing and integration for the Artemis I vehicle, manufacturing progress for the second vehicle and the manifest outlook for primary, co-manifested and secondary payloads in the current deep space exploration environment.

Creech, Stephen D.↗
DOE OSTI2021

TEMImageNet training library and AtomSegNet deep-learning models for high-precision atom segmentation, localization, denoising, and deblurring of atomic-resolution images

Abstract Atom segmentation and localization, noise reduction and deblurring of atomic-resolution scanning transmission electron microscopy (STEM) images with high precision and robustness is a challenging task. Although several conventional algorithms, such has thresholding, edge detection and clustering, can achieve reasonable performance in some predefined sceneries, they tend to fail when interferences from the background are strong and unpredictable. Particularly, for atomic-resolution STEM images, so far there is no well-established algorithm that is robust enough to segment or detect all atomic columns when there is large thickness variation in a recorded image. Herein, we report the development of a training library and a deep learning method that can perform robust and precise atom segmentation, localization, denoising, and super-resolution processing of experimental images. Despite using simulated images as training datasets, the deep-learning model can self-adapt to experimental STEM images and shows outstanding performance in atom detection and localization in challenging contrast conditions and the precision consistently outperforms the state-of-the-art two-dimensional Gaussian fit method. Taking a step further, we have deployed our deep-learning models to a desktop app with a graphical user interface and the app is free and open-source. We have also built a TEM ImageNet project website for easy browsing and downloading of the training data.

25 ENERGY STORAGE↗
DOE OSTI2023

Mesoscale Convective Systems in DYAMOND Global Convection‐Permitting Simulations

Abstract This study examines the deep convection populations and mesoscale convective systems (MCSs) simulated in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) winter project. A storm tracking algorithm is applied to six DYAMOND simulations and a global high‐resolution satellite cloud and precipitation data set for comparison. The simulated frequencies of tropical deep convection and organized convective systems vary widely among models and regions, although robust MCSs are generally underestimated. The diurnal cycles of MCS initiation and mature stages are well simulated, but the amplitudes are exaggerated over land. Most models capture the observed MCS lifetime, cloud shield area, rainfall volume and movement speed. However, cloud‐top height and convective rainfall intensity are consistently overestimated, and stratiform rainfall area and amount are consistently underestimated. Possible causes for the model differences compared to observations and implications for future model developments are discussed.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Neurovascular Outcomes of Ionizing Radiation in Human Blood-Brain Barrier Models

One of the main health risks in human deep space exploration is central nervous system (CNS) damage by ionizing radiation due to exposure to galactic cosmic rays (GCRs). In animal models, irradiation with simulated GCRs or their components has been shown to cause neurodegeneration and neuroinflammation associated with cognitive and behavioral dysfunction. The extent of CNS damage is partially mediated by the blood-brain barrier (BBB), which regulates the interaction between CNS and systemic responses to stressors in the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuronal death, neuroinflammation and oxidative stress. However, studies on BBB and astrocyte functions in regulating CNS responses to ionizing radiation have been limited, especially in human tissue/organ analogs. Therefore, we developed a high-throughput 3D organ-on-a-chip system to study human CNS and BBB impairments caused by deep space radiation. We investigated both immediate and delayed CNS responses to major GCR components: 0.15-0.5Gy 250MeV/n 4He and 0.3-0.8Gy 600MeV/n 56Fe; as well as to 0.5-1Gy X-rays. We observed ionizing radiation-mediated increases in BBB permeability that was exacerbated by astrocyte presence and accompanied by damage to endothelial cells and tight junctions, altered cytokine expression including TNFalpha upregulation, and increased oxidative stress. In particular, 600MeV/n 56Fe particle irradiation selectively induced astrocyte damage and blood-brain barrier permeability only in models that contained astrocytes in addition to endothelial cells, indicating astrocytes as a particularly radiosensitive component of the CNS that could therefore be a suitable a target for neuroprotection. Future studies will compare human and mouse CNS model responses to simulated GCRs and evaluate the induction of an anti-inflammatory phenotype in astrocytes as a potential countermeasure. Ultimately, we aim to expand upon these results to uncover novel cellular and mechanistic targets for countermeasure development to mitigate human CNS damage in deep space exploration.

space radiation↗
NASA NTRSDate not supplied

Neurovascular Outcomes of Space Radiation in Human Blood-Brain Barrier Models

One of the main health risks in human deep space exploration is central nervous system (CNS) damage by ionizing radiation due to exposure to galactic cosmic rays (GCRs). In animal models, irradiation with simulated GCRs or their components has been shown to cause neurodegeneration and neuroinflammation associated with cognitive and behavioral dysfunction. The extent of CNS damage is partially mediated by the blood-brain barrier (BBB), which regulates the interaction between CNS and systemic responses to stressors in the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuronal death, neuroinflammation and oxidative stress. However, studies on BBB and astrocyte functions in regulating CNS responses to ionizing radiation have been limited, especially in human tissue/organ analogs. Therefore, we developed a high-throughput 3D organ-on-a-chip system to study human CNS and BBB impairments caused by deep space radiation. We investigated both immediate and delayed CNS responses to major GCR components: 0.15-0.5Gy 250MeV/n 4He and 0.3-0.8Gy 600MeV/n 56Fe; as well as to 0.5-1Gy X-rays. We observed ionizing radiation-mediated increases in BBB permeability that was exacerbated by astrocyte presence and accompanied by damage to endothelial cells and tight junctions, altered cytokine expression including TNFalpha upregulation, and increased oxidative stress. In particular, 600MeV/n 56Fe particle irradiation selectively induced astrocyte damage and increased blood-brain barrier permeability only in models that contained astrocytes in addition to endothelial cells, indicating astrocytes as a particularly radiosensitive component of the CNS that could therefore be a suitable a target for neuroprotection. Future studies will compare human and mouse CNS model responses to simulated GCRs and evaluate the induction of an anti-inflammatory phenotype in astrocytes as a potential countermeasure. Ultimately, we aim to expand upon these results to uncover novel cellular and mechanistic targets for countermeasure development to mitigate human CNS damage in deep space exploration.

centrat nervous system↗
NASA NTRS2004

Microphysics of Pyrocumulonimbus Clouds

The intense heat from forest fires can generate explosive deep convective cloud systems that inject pollutants to high altitudes. Both satellite and high-altitude aircraft measurements have documented cases in which these pyrocumulonimbus clouds inject large amounts of smoke well into the stratosphere (Fromm and Servranckx 2003; Jost et al. 2004). This smoke can remain in the stratosphere, be transported large distances, and affect lower stratospheric chemistry. In addition recent in situ measurements in pyrocumulus updrafts have shown that the high concentrations of smoke particles have significant impacts on cloud microphysical properties. Very high droplet number densities result in delayed precipitation and may enhance lightning (Andrew et al. 2004). Presumably, the smoke particles will also lead to changes in the properties of anvil cirrus produces by the deep convection, with resulting influences on cloud radiative forcing. In situ sampling near the tops of mature pyrocumulonimbus is difficult due to the high altitude and violence of the storms. In this study, we use large eddy simulations (LES) with size-resolved microphysics to elucidate physical processes in pyrocumulonimbus clouds.

Jensen, Eric↗
DOE OSTI2020

Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2

Motion-activated wildlife cameras (or “camera traps”) are frequently used to remotely and noninvasively observe animals. The vast number of images collected from camera trap projects has prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter-out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. We used 3 million camera trap images from 18 studies in 10 states across the United States of America to train two deep neural networks, one that recognizes 58 species, the “species model,” and one that determines if an image is empty or if it contains an animal, the “empty-animal model.” Our species model and empty-animal model had accuracies of 96.8% and 97.3%, respectively. Furthermore, the models performed well on some out-of-sample datasets, as the species model had 91% accuracy on species from Canada (accuracy range 36%–91% across all out-of-sample datasets) and the empty-animal model achieved an accuracy of 91%–94% on out-of-sample datasets from different continents. Our software addresses some of the limitations of using machine learning to classify images from camera traps. By including many species from several locations, our species model is potentially applicable to many camera trap studies in North America. We also found that our empty-animal model can facilitate removal of images without animals globally. We provide the trained models in an R package (MLWIC2: Machine Learning for Wildlife Image Classification in R), which contains Shiny Applications that allow scientists with minimal programming experience to use trained models and train new models in six neural network architectures with varying depths.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Electrical Conductivities and Association Constants in Dilute Aqueous NdCl 3 Solutions from 298 to 523 K along an Isobar of 25 MPa

Here, electrical measurements were performed in dilute aqueous NdCl 3 solutions from 298 to 523 K along the 25 MPa isobar to obtain limiting conductivities and association constants. The specific conductivity data were estimated using a continuous flow cell and a Markov Chain Monte Carlo (MCMC) correction algorithm. The limiting conductivities for the salts in water were derived by regressing the mean spherical approximation model and speciation analyses based on the MCMC algorithm and the deep earth water model. The limiting conductivities derived from the experimental data were correlated using the Zimmerman-Arcis-Tremaine correlation and agreed well with a predictive correlation proposed by Smolyakov, Anderko, and Lencka. Only the first association constant between neodymium and chloride could be derived at low temperatures (<373 K) due to the apparent large statistical uncertainty of the second association constant. Above 373 K, both association constants could be derived and show a reasonable agreement with Migdisov and Williams-Jones and Gammons et al.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Exploring decarbonization pathways for USA passenger and freight mobility

Abstract Passenger and freight travel account for 28% of U.S. greenhouse gas (GHG) emissions today. We explore pathways to reduce transportation emissions using NREL’s TEMPO model under bounding assumptions on future travel behavior, technology advancement, and policies. Results show diverse routes to 80% or more well-to-wheel GHG reductions by 2050. Rapid adoption of zero-emission vehicles coupled with a clean electric grid is essential for deep decarbonization; in the median scenario, zero-emission vehicle sales reach 89% for passenger light-duty and 69% for freight trucks by 2030 and 100% sales for both by 2040. Up to 3,000 terawatt-hours of electricity could be needed in 2050 to power plug-in electric vehicles. Increased sustainable biofuel usage is also essential for decarbonizing aviation (10–42 billion gallons needed in 2050) and to support legacy vehicles during the transition. Managing travel demand growth can ease this transition by reducing the need for clean electricity and sustainable fuels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Low dose rate γ-irradiation protects fruit fly chromosomes from double strand breaks and telomere fusions by reducing the esi-RNA biogenesis factor Loquacious

Abstract It is still continuously debated whether the low-dose/dose-rate (LDR) of ionizing radiation represents a hazard for humans. Model organisms, such as fruit flies, are considered valuable systems to reveal insights into this issue. We found that, in wild-type Drosophila melanogaster larval neuroblasts, the frequency of Chromosome Breaks (CBs), induced by acute γ-irradiation, is considerably reduced when flies are previously exposed to a protracted dose of 0.4 Gy delivered at a dose rate of 2.5 mGy/h. This indicates that this exposure, which is associated with an increased expression of DNA damage response proteins, induces a radioadaptive response (RAR) that protects Drosophila from extensive DNA damage. Interestingly, the same exposure reduces the frequency of telomere fusions (TFs) from Drosophila telomere capping mutants suggesting that the LDR can generally promote a protective response on chromatin sites that are recognized as DNA breaks. Deep RNA sequencing revealed that RAR is associated with a reduced expression of Loquacious D (Loqs-RD) gene that encodes a well-conserved dsRNA binding protein required for esiRNAs biogenesis. Remarkably, loss of Loqs mimics the LDR-mediated chromosome protection as it decreases the IR-induced CBs and TFs frequency. Thus, our molecular characterization of RAR identifies Loqs as a key factor in the cellular response to LDR and in the epigenetic routes involved in radioresistance.

Porrazzo, A.↗