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At least 487 records · Page 27

Altered Immune Differentials Between Male and Female Mice Independent of Ionizing Irradiation

As upcoming exploratory missions to the Lunar surface and Mars during the Artemis Program will send both female and male crewmembers, studies identifying sex-specific effects are necessary. It is well-documented that the immune system engages different responses between females and males following exposures to infectious challenge, tumors surveillance, and autoimmune development. Yet, the immune effects of spaceflight-like exposures between the sexes are limited. Therefore, this study sought to address the effects of spaceflight-like conditions on immune differentials in female and male mice. We hypothesized that the spaceflight factor, ionizing radiation, will have sex-specific effects on immune differentials. To test this, singly-housed, 12-month old female and male wildtype (Wt) mice were exposed to acute ionizing gamma irradiation (50 cGy), followed by retro-orbital blood collections at 7-days post-irradiation. Leukocytes were analyzed by flow cytometry characterizing, granulocytes, monocytes, lymphocytes (cytotoxic/helper T cells and B cells), neutrophils, eosinophils, and NK/NKT cells. Briefly, minimal sex-specific effects were observed across the cell types listed at this time point, including changes in granulocyte and lymphocyte populations. The results revealed females displayed elevated granulocytes and reduced lymphocytes compared to their male counterparts, independent of irradiation exposure. These results suggest female mice may be more capable to produce innate inflammatory mediators but may be adaptively immune compromised. In brief, this study provides insight into the sex-specific immune risks following ionizing radiation that may be experienced during spaceflight, which is relevant for future countermeasure development.

spaceflight stressors↗

An upgraded G-band differential absorption radar system for future airborne studies

A proof-of-concept, 170 GHz frequency-modulated, continuous-wave (FMCW) radar has been developed for measuring water vapor profiles within the cloudy boundary layer from an airborne platform. The measurement concept exploits the differential absorption accrued by two or more transmitted frequencies in the vicinity of the 183 GHz water absorption line to retrieve range-resolved humidity profiles, so-called differential absorption radar (DAR). The upgraded system design includes important considerations for monostatic radar operation with an open fuselage viewport (i.e. no radome). The radar features an all-solid-state tansmitter with > 0:4 W continuous transmit power, a 60 cm primary aperture and corresponding 58 dB antenna gain, and more than 80 dB transmit/receive isolation, enabling near thermal-noise-limited sensitivity with a 8 dB noise figure receiver. Ice-cloud radar returns are detected beyond 8 km in height from the ground, demonstrating the high sensitivity of the system. In addition to in-cloud humidity profiling capabilities, deployment of a water vapor DAR from an airborne platform enables measurements of total column water vapor (TCWV) for all weather and surface scenarios. Precision estimates and potential biases for future TCWV measurements are discussed.

Monje, Raquel↗

Mars 2020 Center Differential Pivot Restraint: Flexurized Spring System Providing Compliance for Rover Mobility Deployment Prior to Landing

The Center Differential Pivot Restraint (CDPR) for the Mars 2020 mission is designed to constrain motion of the rover differential and to dampen out the load response of during rover’s mobility deployment event in Entry, Descent, and Landing (EDL) phase of the mission. For Mars 2020, it was required to redesign the mechanism to save minimum 33% of the mass from the previous Mars Science Laboratory (MSL) design. The new mechanism architecture used a monolithic spring-like flexure to act as the system compliance, resulting in 50% mass savings from the MSL design. Along the design and prototype testing process, several mechanism design principles were re-affirmed as well as lessons learned about potential race conditions.

Cameron, Matthew↗

Adaptive Optimization for System Performance and Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

The emerging urban air mobility (UAM) sector in aerospace is driving development of unconventional multi-modal vehicle configurations and autonomous flight. The combination of multi-modal vehicle dynamics, complex environment, requirements to deal with flight contingencies in an efficient and safe manner, as well as necessity for precise trajectory following and performance, are the driving influence behind adaptive optimization for system performance. We are interested in trajectory optimization algorithm that would system parameter estimation and identifying the optimal switching time between modes of hybrid dynamical systems. This presentation discusses a parameterized optimal control trajectory optimization algorithm that is an extended and generalized version of Differential Dynamic Programming (DDP), titled Parameterized Differential Dynamic Programming (PDDP). DDP is an efficient trajectory optimization algorithm relying on second order approximations of a system’s dynamics and cost function and has recently been applied to optimize systems with time invariant parameters. Experiments are presented applying PDDP to solve model predictive control (MPC) and moving horizon estimation (MHE) tasks simultaneously. In particular, PDDP is used to determine the optimal transition point between flight regimes of a complex urban air mobility (UAM) class vehicle exhibiting multiple phases of flight and to identify and compensate for actuation faults.

optimization↗

Constrained Reference Star Differential Imaging: Enabling High-fidelity Imagery of Highly Structured Circumstellar Disks

High-contrast imaging presents us with the opportunity to study circumstellar disks and the planets still embedded within them, providing key insights into the formation and evolution of planetary systems. However, the postprocessing techniques that are often needed to suppress stellar halo light typically result in significant and variable loss of circumstellar light, even when using relatively conservative approaches like reference star differential imaging (RDI). We introduce “constrained reference star differential imaging” (constrained RDI), a new class of RDI point-spread-function (PSF) subtraction techniques for systems with circumstellar disks. Constrained RDI utilizes either high-resolution polarized-intensity (PI) images or disk models to severely limit or even eliminate the signal loss due to oversubtraction that is common to RDI. We demonstrate the ability of constrained RDI utilizing polarimetric data to yield an oversubtraction-free detection of the AB Aurigae protoplanetary disk in total intensity. PI-constrained RDI allows us to decisively recover the spectral signature of the confirmed, recently discovered protoplanet, AB Aurigae b. We further demonstrate that constrained RDI can be a powerful analysis tool for soon-to-be-acquired James Webb Space Telescope coronagraphic imaging of disks. In both cases, constrained RDI provides analysis-ready products that enable more detailed studies of disks and more robust verification of embedded exoplanets.

Kellen Lawson↗

T-Cell Shenanigans: The Impact of MHC Pathway & Lipid Metabolism Genes on T-Cell Differentiation in the Thymus

Astronaut health and proper immune function are key to the success and sustainability of long term missions in space. While previous studies have observed adaptive immune dysfunction such as diminished WBC counts and cytokine production during spaceflight, the underlying mechanisms behind why immune function worsens are poorly understood. Using transcriptomic data analyzed from mouse thymus tissues available from the GLDS-421 experiment on the Rodent Research-9 mission, we used the GeneLab standardized RNA-Seq pipeline and identified four genes that were largely dysregulated (p<0.05): lipid metabolic genes Hpgd and Pgr and cell cycle regulator genes Cenpe and Kif11. We analyzed how these genes regulate the MHC-TCR interaction, and used this understanding to propose a novel mechanism for alterations to T-cell differentiation. In our experimental methodology, we propose to use 36 transgenic CD4-CD8 mice and 12 wild-type mice from the Jackson Lab to create a microgravity-simulating hindlimb unloading model and test our hypothesis. By silencing the aforementioned genes using custom siRNA based primers, we will use flow cytometry and RNA-Seq to quantify Treg counts in comparison to naive CD4+ cells, Alamar Blue assay for observing the metabolic activity in T-cells, and Enzyme-Linked Immunosorbent Assay (ELISA) to observe the general immune response in terms of T-cell differentiation. We hope this methodology will improve our knowledge of MHC-TCR interaction, contribute to a better understanding of the mechanisms of autoimmune diseases such as lupus, and improve the success rate of newer cancer treatments such as CAR-T cell therapy.

GL4HS↗

Differential Gene Expression in A Cross-Feeding Two-Species Model Microbial Community Under Simulated Microgravity and Deep-Space Radiation

A long-term goal of space biology is to understand interspecies microbial interactions in space. Presently, little is known about the combined effect of microgravity and ionizing radiation on bacterial community response when species are interdependent through exchange of metabolites in fluid medium (cross-feeding). Microgravity is expected to slow interspecies mass transfer and growth in cross-feeding communities in the low-shear, diffusion-limited environment, while ionizing radiation may influence stress response to direct (DNA damage) and indirect damage (ROS). Using a well-understood, two-species (Escherichia coli and Salmonella enterica) microbial community engineered to be a model for studying cross-feeding, we simulated galactic cosmic rays (GCRsim) and microgravity to test the hypothesis: exposure to ionizing radiation causes cell damage or stress, altering transcriptomic community responses in metabolically interdependent cells, which is exacerbated by microgravity. We expect to see differential gene expression between cross-feeding and non-cross-feeding communities. We measured GCRsim effects on growth and gene expression in well-mixed versus simulated-microgravity conditions and in cross-feeding and non-cross-feeding medium. Microbial cultures were inoculated into liquid medium in rotating wall vessels (RWV) with different rotation rates: 5 RPM (simulated microgravity) and 50 RPM (well-mixed). The E. coli-S. enterica consortium, under simulated microgravity, were exposed to 500 mGy of Simplified 5-ion Galactic Cosmic Ray Simulation for 2 hours at Brookhaven National Lab. We harvested samples 40 minutes after irradiation for extraction and sequencing (NASA GeneLab). Here we present the differential gene expression analysis results, which reveal altered transcriptomic community responses, even where growth rate differences are not observed. Gene expression of these actively metabolizing microbial communities in GCRsim may illuminate molecular mechanisms of microbial interactions in space. Understanding how microbial community gene expression, metabolism, and other cellular processes are influenced by spaceflight stressors can inform the use of microbes in human life support for low Earth orbit missions and beyond.

microgravity↗

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface. In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha-Ray↗

Calcium and Magnesium Distribution Between Sulfide and Silicate Melts: Thermodynamic Modeling and Insights into Mercury's Mantle-Crust Differentiation

Mercury stands out as the terrestrial planet with the lowest degree of oxidation among all planets of our solar system. It is characterized by a high abundance of sulfur, which is expected to replace oxygen in silicate melts. This sulfur enrichment could lead to sulfide saturation in its mantle, potentially resulting in the formation of sulfides rich in calcium and magnesium. Utilizing experimental data from the literature, we constructed a thermodynamic model to explore the partitioning of calcium and magnesium between sulfide and silicate melts. This model aims to improve our comprehension of the chemical equilibria driving the process of mantle-crust differentiation on Mercury. Our models indicate that increased temperature, decreased pressure, and low concentrations of iron, oxygen, and carbon within the sulfide phase, along with low sulfur concentrations in the silicate phase, favor calcium’s partitioning into the sulfide. Additionally, magnesium partitioning into the sulfide melt is favored with decreased pressure, decreased temperature, low concentrations of iron and calcium within the sulfide, and low concentrations of sulfur within the silicate. Our results suggest that up 9.4% and 5.6% Ca and Mg, respectively, can be present in sulfides equilibrated with sulfide-saturated silicate melts during mantle-crust differentiation. Further investigation will focus on the distribution of sulfide phases within the mantle and crust to better constrain Mercury’s internal structure.

Taylor McCombs↗

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

Q-Law for Rapid Assessment of Low Thrust Cislunar Trajectories Via Automatic Differentiation

Q-Law is a Lyapunov-based control law used to determine optimal controls for a low thrust trajectory. One major issue with its use is the difficult derivatives re-quired for calculating optimal controls at a given time. In this paper, an implementation of Q-Law with automatic differentiation via a Python package called JAX is applied. With automatic differentiation, the difficult derivatives for Q-Law’s optimal controls are calculated with ease, and derivatives of final states with respect to Q-Law’s weights are found enabling gradient-based optimization of Q-Law for the first time. Different search and optimization methods for finding optimal weights are then compared using the LEO to GEO problem, and it was found that gradient-free methods like design of experiments and genetic algorithm produced the best results, but they took the longest time to get a solution, while the gradient-based method found a locally optimal result in a much faster time. Overall, the run time for a single propagation is manageable and well-suited for a mission designer to use as an initial guess generator for trajectory optimization, or for simple orbit transfer analysis.

Nathan Steffen↗