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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A probabilistic creep model incorporating test condition, initial damage, and material property uncertainty

Uncertainty is prevalent in the creep resistance of alloys, where at elevated temperature and low pressure, rupture can range across logarithmic decades. In this study, a probabilistic continuum-damage-mechanics (CDM)-based model is derived to capture the uncertainty of creep resistance. To meet this objective, creep data for alloy 304 Stainless Steel is gathered. A constitutive model, “Sinh”, is calibrated deterministically to determine the statistical variability of the material properties. Three sources of uncertainty are injected into the model: test condition (stress and temperature), initial damage, and material properties. Probabilistic simulations are carried out by (a) calibrating probability distribution functions (pdfs) for each source of uncertainty (b) randomly sampling the pdfs using Monte Carlo methods and (c) executing simulations to replicate the uncertain creep behavior. A sensitivity analysis is performed to evaluate the relative effect of each source of uncertainty. In full probabilistic simulations, the cumulative uncertainty of creep behavior is evaluated. The probabilistic model accurately predicts the creep deformation and rupture of the available experiments. The probabilistic model is validated for interpolation but lacks extrapolation ability. Several future works are proposed to further improve the model.

36 MATERIALS SCIENCE↗
DOE OSTI2016

The Epigenomic Landscape of Prokaryotes

DNA methylation acts in concert with restriction enzymes to protect the integrity of prokaryotic genomes. Studies in a limited number of organisms suggest that methylation also contributes to prokaryotic genome regulation, but the prevalence and properties of such non-restriction-associated methylation systems remain poorly understood. Here, we used single molecule, real-time sequencing to map DNA modifications including m6A, m4C, and m5C across the genomes of 230 diverse bacterial and archaeal species. We observed DNA methylation in nearly all (93%) organisms examined, and identified a total of 834 distinct reproducibly methylated motifs. This data enabled annotation of the DNA binding specificities of 620 DNA Methyltransferases (MTases), doubling known specificities for previously hard to study Type I, IIG and III MTases, and revealing their extraordinary diversity. Strikingly, 48% of organisms harbor active Type II MTases with no apparent cognate restriction enzyme. These active ‘orphan’ MTases are present in diverse bacterial and archaeal phyla and show motif specificities and methylation patterns consistent with functions in gene regulation and DNA replication. Our results reveal the pervasive presence of DNA methylation throughout the prokaryotic kingdoms, as well as the diversity of sequence specificities and potential functions of DNA methylation systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Parked aeroelastic field rotor response for a 20% scaled demonstrator of a 13‐MW downwind turbine

Abstract Aeroelastic parked testing of a unique downwind two‐bladed subscale rotor was completed to characterize the response of an extreme‐scale 13‐MW turbine in high‐wind parked conditions. A 20% geometric scaling was used resulting in scaled 20‐m‐long blades, whose structural and stiffness properties were designed using aeroelastic scaling to replicate the nondimensional structural aeroelastic deflections and dynamics that would occur for a lightweight, downwind 13‐MW rotor. The subscale rotor was mounted and field tested on the two‐bladed Controls Advanced Research Turbine (CART2) at the National Renewable Energy Laboratory's Flatiron Campus (NREL FC). The parked testing of these highly flexible blades included both pitch‐to‐run and pitch‐to‐feather configurations with the blades in the horizontal braked orientation. The collected experimental data includes the unsteady flapwise root bending moments and tip deflections as a function of inflow wind conditions. The bending moments are based on strain gauges located in the root section, whereas the tip deflections are captured by a video camera on the hub of the turbine pointed toward the tip of the blade. The experimental results are compared against computational predictions generated by FAST, a wind turbine simulation software, for the subscale and full‐scale models with consistent unsteady wind fields. FAST reasonably predicted the bending moments and deflections of the experimental data in terms of both the mean and standard deviations. These results demonstrate the efficacy of the first such aeroelastically scaled turbine test and demonstrate that a highly flexible lightweight downwind coned rotor can be designed to withstand extreme loads in parked conditions.

17 WIND ENERGY↗
DOE OSTI2024

Neural network interatomic potential-driven analysis of phase stability in Ti–V alloys at the atomistic scale

The evolution of the ω phase in titanium–vanadium (Ti–V) alloys is critical for their mechanical properties, particularly in aerospace and biomedical applications. Here, this study employs a Rapid Artificial Neural Network (RANN) potential to model the ω phase evolution at the atomistic level, demonstrating a high degree of consistency with experimental observations, unlike the Modified Embedded Atom Method (MEAM), which fails to capture this phase transformation accurately. RANN simulations replicate key phenomena such as the nucleation of α precipitates at ω/β interfaces and accurate lattice orientations, enhancing our understanding of phase stability and transformation kinetics. The findings affirm that RANN potentials can significantly improve the prediction accuracy of complex material behaviors, offering a powerful tool for designing advanced materials with tailored properties such as solute effect in various stacking fault energies. This approach not only bridges the gap between theoretical predictions and empirical data but also sets a new direction for future research in materials science, emphasizing the integration of machine learning techniques in the development and optimization of new alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul↗
DOE OSTI2022

Magnitude-squared Coherence: A Powerful Tool for Disentangling Doppler Planet Discoveries from Stellar Activity

Abstract If Doppler searches for Earth-mass, habitable planets are to succeed, observers must be able to identify and model out stellar activity signals. Here we demonstrate how to diagnose activity signals by calculating the magnitude-squared coherence C ˆ xy 2 ( f ) between an activity-indicator time series x t and the radial-velocity (RV) time series y t . Since planets only cause modulation in RV, not in activity indicators, a high value of C ˆ xy 2 ( f ) indicates that the signal at frequency f has a stellar origin. We use Welch’s method to measure coherence between activity indicators and RVs in archival observations of GJ 581, α Cen B, and GJ 3998. High RV-H α coherence at the frequency of GJ 3998 b and high RV-S index coherence at the frequency of GJ 3998c, indicate that the planets may actually be stellar signals. We also replicate previous results showing that GJ 581 d and g are rotation harmonics and demonstrate that α Cen B has activity signals that are not associated with rotation. Welch’s power spectrum estimates have cleaner spectral windows than Lomb–Scargle periodograms, improving our ability to estimate rotation periods. We find that the rotation period of GJ 581 is 132 days, with no evidence of differential rotation. Welch’s method may yield unacceptably large bias for data sets with N < 75 observations and works best on data sets with N > 100. Tapering the time-domain data can reduce the bias of the Welch’s power spectrum estimator, but observers should not apply tapers to data sets with extremely uneven observing cadence. A software package for calculating magnitude-squared coherence and Welch’s power spectrum estimates is available on github.

Dodson-Robinson, Sarah E. (ORCID:0000000287964974)↗
NASA NTRS1991

Corrosion of metal particle and metal evaporated tapes

Very high coercivity metal particle (MP) and metal evaporated (ME) tapes are being used in 8mm video and digital audio tape applications, and more recently in digital data recording applications. In view of the inherent susceptibility of such media to environmental corrosion, a number of recent studies have addressed their long term stability and archivability. These studies have used an accelerated corrosion test based either on elevated temperature-humidity or polluting gas atmospheres known as Battelle tests. A comparison of the Battelle test results performed at different laboratories reveals a large variation from one location to another, presumably due to incorrect replication of the Battelle condition. Furthermore, when the Battelle tests are performed on enclosed cartridges, it is quite possible that diffusion limits the penetration of the extremely low concentration polluting gaseous species to the inner layers of the tapes during the short time of the accelerated test, whereas in real life these diffusion limitations may not apply. To avoid this uncertainty, the corrosion behavior of commercial 8mm MP and ME tapes when cassettes without their external plastic cases were exposed to 50 deg C and 80 percent RH for 7.5 weeks is investigated.

Speliotis, Dennis E.↗
NASA NTRS2013

Science Opportunity Analyzer (SOA) Version 8

SOA allows scientists to plan spacecraft observations. It facilitates the identification of geometrically interesting times in a spacecraft s orbit that a user can use to plan observations or instrument-driven spacecraft maneuvers. These observations can then be visualized multiple ways in both two- and three-dimensional views. When observations have been optimized within a spacecraft's flight rules, the resulting plans can be output for use by other JPL uplink tools. Now in its eighth major version, SOA improves on these capabilities in a modern and integrated fashion. SOA consists of five major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, and Data Output. Opportunity Search is a GUI-driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last-minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily assess the cost to science if flight rule changes occur. Data Output allows the user to compute ancillary data related to an observation or to a given position of the spacecraft along its trajectory. The data can be saved as a tab-delimited text file or viewed as a graph. SOA combines science planning functionality unique to both JPL and the sponsoring spacecraft. SOA is able to ingest JPL SPICE Kernels that are used to drive the tool and its computations. A Percy search engine is then included that identifies interesting time periods for the user to build observations. When observations are then built, flight-like orientation algorithms replicate spacecraft dynamics to closely simulate the flight spacecraft s dynamics. SOA v8 represents large steps forward from SOA v7 in terms of quality, reliability, maintainability, efficiency, and user experience. A tailored agile development environment has been built around SOA that provides automated unit testing, continuous build and integration, a consolidated Web-based code and documentation storage environment, modern Java enhancements, and a focus on usability

Witoff, Robert J.↗
NASA NTRS2011

NASA Aviation Safety Reporting System (ASRS)

The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 900,000 reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 5,500 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides de-identified report information through the online ASRS Database at http://asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation \vill discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.

Connell, Linda↗
NASA NTRS2020

Vibration-based health characterization of multiple IMUs in UAV applications

Inertial measurement units (IMUs) are vital in UAV navigation for vehicle attitude and position estimation, especially in the frequently-occurring case of temporary loss of GPS capabilities. Degradation in these units could yield inaccurate position estimates, resulting in incorrect input for vehicle control systems. A wide variety of these units exist to meet the needs of UAV operators, general aviation, and military vehicles. In recent decades, lightweight and inexpensive MEMS sensors have grown in popularity with respect to UAVs. Studies into the failure modes of MEMS devices suggest that vibration is one of the leading causes of MEMS degradation. MEMS sensors are generally encased in their own hermetic packaging, as their small size and sensitivity cause them to be particularly vulnerable to air damping and particulate contamination when exposed. Exposure to excessive vibration can cause cracking in this packaging as well as damage to connecting electronics, with recorded results that cause sensors to act outside of their specifications, potentially providing unreliable input to controllers. A prior study from the Politecnico di Torino looked into the degradation of MEMS IMUs, specifically the AXIS-AIS402, for aerospace and vibrating environments. In the study, the authors found that after exposing MEMS IMUs to simulated vibrations from working conditions of aerospace applications, the sensors showed increased noise and increased bias instability. At NASA Ames, several widely-used MEMS IMUs were selected for a new IMU degradation study, comparing accelerometer performance before and after exposure to similar levels of vibration simulating aerospace conditions. The IMUs were selected from the Pixhawk autopilot systems, hobby sUAS, or prior experimental studies at NASA. Additionally, the industrial grade VectorNav-100 IMU was selected as a ground truth reference point to which the performance of the test sensors can be compared. In the study, each sensor is exposed to functional levels of UAV vibration as replicated on a single-frequency vibratory table in the NASA Ames SHARP Laboratory, and each accelerometer is characterized for bias, drift, and noise characteristics both before and after vibratory exposure. The focus of this study is to monitor the health of the IMU sensors and determine if sensor degradation can be detected from output error and frequency spectrum analysis, rather than from microscopic examination of the sensors. In this case, sensor degradation and faulty data can be more easily detectable by non-experts hoping to use these sensors as an important piece of an integrated package. In addition, specific sensor degradation modes potentially leading to in-flight hazards could be identified, such as accelerated levels of drift and altered temperature response. The overall goal of this work is to increase levels of safety for future users of these sensors and to provide a clear analysis of sensor limitations currently lacking in most sensor specification documentation.

IMUs↗
DOE OSTI2014

A firmware-defined digital direct-sampling NMR spectrometer for condensed matter physics

We report on the design and implementation of a new digital, broad-band nuclear magnetic resonance (NMR) spectrometer suitable for probing condensed matter. The spectrometer uses direct sampling in both transmission and reception. It relies on a single, commercially-available signal processing device with a user-accessible field-programmable gate array (FPGA). Its functions are defined exclusively by the FPGA firmware and the application software. Besides allowing for fast replication, flexibility, and extensibility, our software-based solution preserves the option to reuse the components for other projects. The device operates up to 400 MHz without, and up to 800 MHz with undersampling, respectively. Digital down-conversion with ±10 MHz passband is provided on the receiver side. The system supports high repetition rates and has virtually no intrinsic dead time. We describe briefly how the spectrometer integrates into the experimental setup and present test data which demonstrates that its performance is competitive with that of conventional designs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Considerations regarding the Use of Computer Vision Machine Learning in Safety-Related or Risk-Significant Applications in Nuclear Power Plants

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Computational Prediction of Infrasound Arrival Times and Directions from Stationary and Moving Impulsive Sources

This report addresses the need to predict infrasound signal arrival times and back azimuths at monitoring stations, enabling more focused and efficient searches within recorded waveform data. The primary challenge is estimating expected signal arrival windows for stationary and moving acoustic sources, such as chemical explosions, volcanic eruptions, meteoroids, and spacecraft re-entry events. To address this challenge, a reproducible methodology is described that uses simplified propagation speeds for boundary layer, tropospheric, stratospheric, and thermospheric atmospheric waveguides. While the Python source code itself is not freely available, this document provides detailed, step-by-step instructions, and equations enabling users to replicate and adapt the method independently. The method reliably predicts signal arrival intervals and back azimuths, thereby supporting rapid detection and accurate interpretation of infrasound events. Results demonstrate that this method effectively identifies plausible signal arrival intervals and directions, facilitating faster event detection and more reliable interpretation. This methodology directly supports atmospheric monitoring, planetary defense, and forensic analysis of explosive atmospheric events.

47 OTHER INSTRUMENTATION↗
NASA NTRS2017

NASA Aviation Safety Reporting System (ASRS)

The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 million reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.

Connell, Linda J.↗
NASA NTRS2016

NASA Aviation Safety Reporting System (ASRS)

The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 M reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.

Connell, Linda↗
DOE OSTI2020

The Development of a Generalized Riser Flow Regime Map Based Upon Higher Moment and Chaotic Statistics Using Electrical Capacitance Volume Tomography (ECVT)

Dynamic analyses have been applied to the temporal signals from an Electro Capacitance Volume Tomography instrument located near mid-height on the riser of an industrial-scale cold-flow circulating fluidized bed to characterize gas-solids flow behavior in the riser. Twelve capacitance electrodes surround the cylindrical riser over a height of 1.3 m. The instrument used a neural network deconvolution algorithm to determine the spatially resolved solids fraction recorded at 52 Hz. Experiments were carried out over a range of gas and solids flows in the transport regime using a Geldart Group B bed material, high density polyethylene with mean particle size of 880 μm. The radial solids distribution was found to vary from one-time step to the next between profiles typical of laminar and turbulent flow. The duration of time spent in each of these flow profiles depended upon the operating regime – dilute, core-annular, or fast fluidized bed. The chaotic structure of the temporal data was characterized using the three conventional approaches: the first 4 moments from the distribution of signal in time, system memory parameters from the autocorrelation function and the Hurst exponent, and analysis of the correlationentropy and correlation dimension of the attractor. These signal analysis techniques were used to clearly distinguish differences between different transport operating regimes. Specifically, it was experimentally observed that a riser transitions from core annular flow profile to dilute and dense regimes via increasing the frequency of short term transients to either dilute or dense flow profiles, respectively. A regime map was generated based upon these dynamics using solids flux and gas velocity axes. Fast fluidized, core annular, and dilute each exhibited different degree of dynamic characteristics typical of fluid dominated or particle compromising behavior. It should be noted that the magnitude for the different statistics was in the same range regardless of the regime, it was the radial profile for the statistic that changed and subsequently identified that there was a change in the regime. Finally, a reduced regime map was developed consisting of plotting the gas velocity normalized by the upper transport velocity versus the solids flux normalized by the saturation carrying capacity. The use of this reduced plot allowed the data from widely different conditions to be plotted and compared on the same<p>graph. Note that in many instances, some of the statistics identified the operating point as being in one regime while others indicated that it was in another indicating a transition region between dilute or core annular regimes and between the core annular and fast fluidization regimes. This now provides a tool that can be used to optimize process performance, identify changes in operating states, or replicate process dynamics during process scaling or changing operating parameters. </p>

Breault, Ronald↗
DOE OSTI2015

RNA helicase MOV10 functions as a co-factor of HIV-1 Rev to facilitate Rev/RRE-dependent nuclear export of viral mRNAs

Human immunodeficiency virus type 1 (HIV-1) exploits multiple host factors during its replication. The REV/RRE-dependent nuclear export of unspliced/partially spliced viral transcripts needs the assistance of host proteins. Recent studies have shown that MOV10 overexpression inhibited HIV-1 replication at various steps. However, the endogenous MOV10 was required in certain step(s) of HIV-1 replication. In this report, we found that MOV10 potently enhances the nuclear export of viral mRNAs and subsequently increases the expression of Gag protein and other late products through affecting the Rev/RRE axis. The co-immunoprecipitation analysis indicated that MOV10 interacts with Rev in an RNA-independent manner. The DEAG-box of MOV10 was required for the enhancement of Rev/RRE-dependent nuclear export and the DEAG-box mutant showed a dominant-negative activity. Our data propose that HIV-1 utilizes the anti-viral factor MOV10 to function as a co-factor of Rev and demonstrate the complicated effects of MOV10 on HIV-1 life cycle. - Highlights: • MOV10 can function as a co-factor of HIV-1 Rev. • MOV10 facilitates Rev/RRE-dependent transport of viral mRNAs. • MOV10 interacts with Rev in an RNA-independent manner. • The DEAG-box of MOV10 is required for the enhancement of Rev/RRE-dependent export.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

The width of the lateral element of the synaptonemal complex is determined by a multilayered organization of its components

The synaptonemal complex (SC) is a proteinaceous structure that holds the homologous chromosomes in close proximity while they exchange genetic material in a process known as meiotic recombination. This meiotic recombination leads to genetic variability in sexually reproducing organisms. The ultrastructure of the SC is studied by electron microscopy and it is observed as a tripartite structure. Two lateral elements (LE) separated by a central region (CR) confer its classical tripartite organization. The LEs are the anchoring platform for the replicated homologous chromosomes to properly exchange genetic material with one another. An accurate assembly of the LE is indispensable for the proper completion of meiosis. Ultrastructural studies suggested that the LE is organized as a multilayered unit. However, no validation of this model has been previously provided. In this ultrastructural study, by using mice with different genetic backgrounds that affect the LE width, we provide further evidence that support a multilayered organization of the LE. Additionally, we provide data suggesting additional roles of the different cohesin complex components in the structure of the LEs of the SC. - Highlights: • The lateral element of the synaptonemal complex is a multilayered structure. • The width of the lateral element in synaptonemal complex-null mice is different. • Two cohesin complex cores plus one axial element form a wild-type lateral element. • The layers of the lateral element can be analyzed in different null mice models.

60 APPLIED LIFE SCIENCES↗