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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Development of a high-throughput method for processing sponge-stick samples to detect viable Bacillus anthracis spores

Since the national validation of the sponge-stick based method for detection of Bacillus anthracis spores in environmental samples, there have not been focused efforts to address the low throughput nature of the method, which processes only one sample at one time. Sample processing remains a serious bottleneck for rapidly analyzing large numbers of samples expected from a biological warfare attack. Therefore, we developed a high-throughput method to simultaneously process multiple sponge-stick samples to be better prepared for rapid response and recovery after wide area anthrax incidents. In this method, sponges are placed in 50 mL tubes containing 25 mL extraction buffer and shaken to release spores, after which the suspension is recovered for analysis. Here, we determined that an additional extraction step, conducted in the same tubes with 10 mL buffer, further increased spore recovery from sponge-stick by approximately 10 %. We determined that orbital shaking and multi-tube vortexing were both more effective than reciprocating shaking for recovering spores. We conducted simultaneous processing of up to 12 sponge-stick samples and demonstrated comparable spore recovery efficiencies to the traditional low-throughput stomacher-based method (approximately 60 % recovery at 10 2 -spore level and 75 % recovery at 10 4 -spore level for both methods in three replicate experiments, P > 0.05 for two-tailed t-tests for each experiment and spore level). We also demonstrated that our high-throughput method could be integrated with Rapid Viability-Polymerase Chain Reaction (RV-PCR) analysis and could detect levels as low as 40 spores per sponge even when challenged by a PCR particulate contaminant.

Anthrax↗
DOE OSTI2025

Biased degenerate ground-state sampling of small Ising models with converged quantum approximate optimization algorithm

The quantum alternating operator ansatz, a generalization of the quantum approximate optimization algorithm (QAOA), is a quantum algorithm used for approximately solving combinatorial optimization problems. QAOA typically uses the transverse field mixer as the driving Hamiltonian. One of the interesting properties of the transverse field driving Hamiltonian is that it results in nonuniform sampling of degenerate ground states of optimization problems. In this study, we numerically examine the fair sampling properties of the transverse field mixer QAOA, and Grover mixer QAOA (GM-QAOA), which provides theoretical guarantees of fair sampling of degenerate optimal solutions, up to a large enough p such that the mean expectation value converges to an optimal approximation ratio of 1. This comparison is performed with high-quality heuristically computed, but not necessarily optimal, QAOA angles, which give strictly monotonically improving solution quality as p increases. These angles are computed using the Julia based numerical simulation software JuliQAOA. Fair sampling of degenerate ground states is quantified using the Shannon entropy of the ground-state amplitudes distribution. The fair sampling properties are reported on several quantum signature Hamiltonians from previous quantum annealing fair sampling studies. Small random fully connected spin glasses are shown, which exhibit exponential suppression of some degenerate ground states with transverse field mixer QAOA. The transverse field mixer QAOA simulations show that some problem instances clearly saturate the Shannon entropy of 0 with a maximally biased distribution that occurs when the learning converges to an approximation ratio of 1 while other problem instances never deviate from a maximum Shannon entropy (uniform distribution) at any p step. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Manifold Sampling for Optimizing Nonsmooth Nonconvex Compositions

Here we propose a manifold sampling algorithm for minimizing a nonsmooth composition $f= h\circ F$, where we assume $h$ is nonsmooth and may be inexpensively computed in closed form and $F$ is smooth but its Jacobian may not be available. We additionally assume that the composition $h\circ F$ defines a continuous selection. Manifold sampling algorithms can be classified as model-based derivative-free methods, in that models of $F$ are combined with particularly sampled information about $h$ to yield local models for use within a trust-region framework. We demonstrate that cluster points of the sequence of iterates generated by the manifold sampling algorithm are Clarke stationary. We consider the tractability of three particular subproblems generated by the manifold sampling algorithm and the extent to which inexact solutions to these subproblems may be tolerated. Numerical results demonstrate that manifold sampling as a derivative-free algorithm is competitive with state-of-the-art algorithms for nonsmooth optimization that utilize first-order information about $f$.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Enhanced Monte Carlo Simulations for Electron Energy Loss Mitigation in Real-Space Nanoimaging of Thick Biological Samples and Microchips

High-resolution imaging using Transmission Electron Microscopy (TEM) is essential for applications such as grain boundary analysis, microchip defect characterization, and biological imaging. However, TEM images are often compromised by electron energy spread and other factors. In TEM mode, where the objective and projector lenses are positioned downstream of the sample, electron–sample interactions cause energy loss, which adversely impacts image quality and resolution. This study introduces a simulation tool to estimate the electron energy loss spectrum (EELS) as a function of sample thickness, covering electron beam energies from 300 keV to 3 MeV. Leveraging recent advances in MeV-TEM/STEM technology, which includes a state-of-the-art electron source with 2-picometer emittance, an energy spread of 3 × 10 -5 , and optimized beam characteristics, we aim to minimize energy spread. By integrating EELS capabilities into the BNL Monte Carlo (MC) simulation code for thicker samples, we evaluate electron beam parameters to mitigate energy spread resulting from electron–sample interactions. Based on our simulations, we propose an experimental procedure for quantitively distinguishing between elastic and inelastic scattering. The findings will guide the selection of optimal beam settings, thereby enhancing resolution for nanoimaging of thick biological samples and microchips.

36 MATERIALS SCIENCE↗
NASA NTRS2022

Un-Numbered Operational Areas PRL 229 Railroad Tie Disposal Area Pond Confirmation Sampling Report

This Confirmatory Sampling (CS) Report (CSR) was prepared for the National Aeronautics and Space Administration (NASA), Kennedy Space Center (KSC), Florida in accordance with the CS Work Plan (CSWP) (HGL, 2022a). The CSR summarizes investigation activities performed on the Railroad Tie Disposal Area (RTDA) of the Un-Numbered Operational Areas (UNOA), Potential Release Location (PRL) 229 located at KSC. HydroGeoLogic, Inc. (HGL) prepared this report under Contract Number 80KSC019D0012. The purpose of the CSR is to provide information to evaluate the level of potential contamination in surface water and sediment samples collected from the RTDA PRL 229 Pond and determine if contaminants pose unacceptable risks to ecological receptors. The CSR provides analytical data of 10 sets of surface water and sediment samples collected in 2021. Surface water samples were analyzed for volatile organic compounds (VOCs), semi-volatile organic compounds (SVOCs), polynuclear aromatic hydrocarbon (PAHs), metals, hardness, and salinity, while sediment samples were analyzed for metals, total organic carbon (TOC), SVOCs, PAHs, and total petroleum hydrocarbons (TPH). The CSR includes a Screening Level Ecological Risk Assessment (SLERA) conducted under KSC’s Resource Conservation and Recovery Act (RCRA) Corrective Action Program to determine if unacceptable risks to ecological receptors exist at PRL 229 Pond. Metals and PAHs were detected in surface water samples, including detections of antimony, arsenic, barium, calcium, copper, lead, magnesium, thallium, zinc, anthracene, benzo(a)anthracene, benzo(a)pyrene, benzo(b)fluoranthene, benzo(g,h,i)perylene, benzo(k)fluoranthene, chrysene, dibenzo(a,h)anthracene, fluoranthene, indeno(1,2,3-c,d)pyrene and pyrene. Based on measured salinity (1.03 to 1.21 parts per thousand), the pond was identified as freshwater. Sediment analytical results also contained detections of metals and PAHs, including antimony, arsenic, barium, beryllium, cadmium, chromium, copper, lead, mercury, nickel, selenium, thallium, zinc, anthracene benzo(a)anthracene, benzo(a)pyrene, benzo(b)fluoranthene, benzo(g,h,i)perylene, benzo(k)fluoranthene, chrysene, dibenzo(a,h)anthracene, fluoranthene, indeno(1,2,3-c,d)pyrene and pyrene. Potential risks to ecological receptors were evaluated in accordance with the SLERA Work Plan and the Decision Process Document for the Resource Conservation and Recovery Act (RCRA) Corrective Action Program at KSC (DPD) (Geosyntec, 2019), and using the 2021 sediment and surface water analytical results. Potential ecological receptors evaluated in the SLERA include the aquatic community, benthic invertebrates, aquatic birds, and aquatic mammals. The SLERA included Steps 2a through 2c of the Ecological Risk Assessment (ERA) process in accordance with the DPD. Using multiple lines of evidence, the SLERA concluded that many of the detected analytes are present at concentrations similar to those in background or reference locations at KSC, and/or at concentrations that would not pose a significant risk to ecological communities. There are no screening values available for the avian community, and PAHs are bioaccumulative compounds. For this reason, food web modeling was completed as a supplement to Step 2c to provide a quantitative evaluation of this exposure pathway. Food web modeling indicates that PAHs are unlikely to pose a risk to birds exposed to site sediment and surface water. Based on the results of the SLERA, the contaminants in sediment and surface water pose no to minimal risk to the ecological communities that could live or forage at the site. Based on the results of the SLERA, no further study is recommended for the RTDA Pond at PRL 229.

Confirmation Sampling↗
DOE OSTI2023

Intensity of sample processing methods impacts wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes

Wastewater SARS-CoV-2 surveillance has been deployed since the beginning of the COVID-19 pandemic to monitor the dynamics in virus burden in local communities. Genomic surveillance of SARS-CoV-2 in wastewater, particularly efforts aimed at whole genome sequencing for variant tracking and identification, are still challenging due to low target concentration, complex microbial and chemical background, and lack of robust nucleic acid recovery experimental procedures. The intrinsic sample limitations are inherent to wastewater and are thus unavoidable. Here, we use a statistical approach that couples correlation analyses to a random forest-based machine learning algorithm to evaluate potentially important factors associated with wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes, with a specific focus on the breadth of genome coverage. We collected 182 composite and grab wastewater samples from the Chicago area between November 2020 to October 2021. Samples were processed using a mixture of processing methods reflecting different homogenization intensities (HA + Zymo beads, HA + glass beads, and Nanotrap), and were sequenced using one of the two library preparation kits (the Illumina COVIDseq kit and the QIAseq DIRECT kit). Technical factors evaluated using statistical and machine learning approaches include sample types, certain sample intrinsic features, and processing and sequencing methods. The results suggested that sample processing methods could be a predominant factor affecting sequencing outcomes, and library preparation kits was considered a minor factor. Finally, a synthetic SARS-CoV-2 RNA spike-in experiment was performed to validate the impact from processing methods and suggested that the intensity of the processing methods could lead to different RNA fragmentation

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Site-specific plan-view (S)TEM sample preparation from thin films using a dual-beam FIB-SEM

To fully evaluate the atomic structure, and associated properties of materials using transmission electron microscopy, examination of samples from three non-collinear orientations is needed. This is particularly challenging for thin films and nanoscale devices built on substrates due to limitations with plan-view sample preparation. In this work, a new method for preparation of high-quality, site-specific, plan-view TEM samples from thin-films grown on substrates, is presented and discussed. Here, it is based on using a dual-beam focused ion beam scanning electron microscope (FIB-SEM) system. To demonstrate the method, the samples were prepared from thin films of perovskite oxide BaSnO 3 grown on a SrTiO 3 substrate and metal oxide IrO 2 on a TiO 2 substrate, ranging from 20–80 nm in thicknesses using molecular beam epitaxy. While the method is optimized for the thin films, it can be extended to other site-specific plan-view samples and devices build on wafers. Aberration-corrected STEM was used to evaluate the quality of the samples and their applicability for atomic-resolution imaging and analysis.

BaSnO3↗
DOE OSTI2020

Design and feasibility of a novel program of cervical screening in Nigeria: self-sampled HPV testing paired with visual triage

Background: Accelerated global control of cervical cancer would require primary prevention with human papillomavirus (HPV) vaccination in addition to novel screening program strategies that are simple, inexpensive, and effective. We present the feasibility and outcome of a community-based HPV self-sampled screening program. Methods: In Ile Ife, Nigeria, 9406 women aged 30–49 years collected vaginal self-samples, which were tested for HPV in the local study laboratory using Hybrid Capture-2 (HC2) (Qiagen). HPV-positive women were referred to the colposcopy clinic. Gynecologist colposcopic impression dictated immediate management; biopsies were taken when definite acetowhitening was present to produce a histopathologic reference standard of precancer (and to determine final clinical management). Retrospective linkage to the medical records identified 442 of 9406 women living with HIV (WLWH). Results: With self-sampling, it was possible to screen more than 100 women per day per clinic. Following an audio-visual presentation and in-person instructions, overall acceptability of self-sampling was very high (81.2% women preferring self-sampling over clinician collection). HPV positivity was found in 17.3% of women. Intensive follow-up contributed to 85.9% attendance at the colposcopy clinic. Of those referred, 8.2% were initially treated with thermal ablation and 5.6% with large loop excision of transformation zone (LLETZ). Full visibility of the squamocolumnar junction, necessary for optimal visual triage and ablation, declined from 68.5% at age 30 to 35.4% at age 49. CIN2+ and CIN3+ (CIN- Cervical intraepithelial neoplasia), including five cancers, were identified by histology in 5.9 and 3.2% of the HPV-positive women, respectively (0.9 and 0.5% of the total screening population), leading to additional treatment as indicated. The prevalences of HPV infection and CIN2+ were substantially higher (40.5 and 2.5%, respectively) among WLWH. Colposcopic impression led to over- and under-treatment compared to the histopathology reference standard. Conclusion: A cervical cancer screening program using self-sampled HPV testing, with colposcopic immediate management of women positive for HPV, proved feasible in Nigeria. Based on the collected specimens and images, we are now evaluating the use of a combination of partial HPV typing and automated visual evaluation (AVE) of cervical images to improve the accuracy of the screening program.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Robust Importance Sampling for Bayesian Model Calibration with Spatio-Temporal Data

This paper addresses two challenges in Bayesian calibration: 1) computational speed of existing sampling algorithms, and 2) calibration with spatio-temporal responses. The commonly used Markov Chain Monte Carlo (MCMC) approaches require many sequential model evaluations making the computational expense prohibitive. This paper proposes an efficient sampling algorithm: iterative importance sampling with genetic algorithm (IISGA). While iterative importance sampling enables computational efficiency, the genetic algorithm enables robustness by preventing sample degeneration and avoids getting stuck in multimodal search spaces. An inflated likelihood further enables robustness in high-dimensional parameter spaces by enlarging the target distribution. Spatio-temporal data complicate both surrogate modeling, which is necessary for expensive computational models, and the likelihood estimation. In this work, singular value decomposition is investigated for reducing the high-dimensional field data to a lower-dimensional space prior to Bayesian calibration. Then the likelihood is formulated and Bayesian inference is performed in the lower-dimension, latent space. An illustrative example is provided to demonstrate IISGA relative to existing sampling methods, and then IISGA is employed to calibrate a thermal battery model with 26 uncertain calibration parameters and spatio-temporal response data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Monte Carlo Simulation of Electron Interactions in an MeV-STEM for Thick Frozen Biological Sample Imaging

A variety of volume electron microscopy techniques have been developed to visualize thick biological samples. However, the resolution is limited by the sliced section thickness (>30–60 nm). To preserve biological samples in a hydrated state, cryo-focused ion beam scanning electron microscopy has been developed, providing nm resolutions. However, this method is time-consuming, requiring 15–20 h to image a 10 μm thick sample with an 8 nm slice thickness. There is a pressing need for a method that allows the rapid and efficient study of thick biological samples while maintaining nanoscale resolution. The remarkable ability of mega-electron-volt (MeV) electrons to penetrate thick biological samples, even exceeding 10 μm in thickness, while maintaining nanoscale resolution, positions MeV-STEM as a suitable microscopy tool for such applications. Our research delves into understanding the interactions between MeV electrons and frozen biological specimens through Monte Carlo simulations. Single elastic scattering, plural elastic scattering, single inelastic scattering, and plural inelastic scattering events have been simulated. The electron trajectories, the beam profile, and the intensity change of electrons in each category have been investigated. Additionally, the effects of the detector collection angle and the focal position of the electron beam were investigated. As electrons penetrated deeper into the specimen, single and plural elastic scattered electrons diminished, and plural inelastic scattered electrons became dominant, and the beam profile became wider. Even after 10 μm of the specimen, 42% of the MeV electrons were collected within 10 mrad. This confirms that MeV-STEM can be employed to study thick biological samples.

electron specimen interaction↗
NASA NTRS2014

The Combustion Experiment on the Sample Analysis at Mars (SAM) Instrument Suite on the Curiosity Rover

The combustion experiment on the Sample Analysis at Mars (SAM) suite on Curiosity will heat a sample of Mars regolith in the presence of oxygen and measure composition of the evolved gases using quadrupole mass spectrometry (QMS) and tunable laser spectrometry (TLS). QMS will enable detection of combustion products such as CO, CO2, NO, and other oxidized species, while TLS will enable precise measurements of the abundance and carbon isotopic composition (delta(sup 13)C) of the evolved CO2 and hydrogen isotopic composition (deltaD) of H2O. SAM will perform a two-step combustion to isolate combustible materials below approx.550 C and above approx.550 C. The combustion experiment on SAM, if properly designed and executed, has the potential to answer multiple questions regarding the origins of volatiles seen thus far in SAM evolved gas analysis (EGA) on Mars. Constraints imposed by SAM and MSL time and power resources, as well as SAM consumables (oxygen gas), will limit the number of SAM combustion experiments, so it is imperative to design an experiment targeting the most pressing science questions. Low temperature combustion experiments will primarily target the quantification of carbon (and nitrogen) contributed by SAM wet chemistry reagants MTBSTFA (N-Methyl-N-tert-butyldimethylsilyltrifluoroacetamide) and DMF (Dimethylformamide), which have been identified in the background of blank and sample runs and may adsorb to the sample while the cup is in the Sample Manipulation System (SMS). In addition, differences between the sample and "blank" may yield information regarding abundance and delta(sup 13)C of bulk (both organic and inorganic) martian carbon. High temperature combustion experiments primarily aim to detect refractory organic matter, if present in Cumberland fines, as well as address the question of quantification and deltaD value of water evolution associated with hydroxyl hydrogen in clay minerals.

Mars↗
NASA NTRS2015

Area 3 Support Buildings (A3SB) H5-0992, H5-0996 PRL 218 Confirmatory Sampling Report

The Area 3 Support Buildings site (A3SB) consists of two separate areas located on the north side of Beach Road in the northern portion of Kennedy Space Center, Florida (KSC), outside the secured perimeter of KSC. The A3SB areas are approximately 0.6 miles apart, and were developed as Shiffler's Grocery Store and Service Station (west site) and as a residence (east site) prior to acquisition by the National Aeronautics and Space Administration (NASA) in 1963. Both areas were used by the Bendix Company in support of NASA as chemical laboratories from 1963 through 1969. Both of the buildings were demolished by 1987. The west portion of the site was used by the US Fish & Wildlife Service (F&W) in support of the Merritt Island National Wildlife Refuge (MINWR) for parking at the entrance to the Hammock Trails from 1969 to the present. The east portion of the site was used for intermittent suspect materials staging in the early 1990s and is still used as an apiary location, but is otherwise no longer active. In support of the NASA HSWA permit requirements, this site was identified as Potential Release Location (PRL) 218 and a Solid Waste Management Unit (SWMU) Assessment (SA) was conducted in 2013. Confirmatory Sampling (CS) was recommended and approved by the KSC Remediation Team (KSCRT). Three locations of concern (LOCs) were identified and sampled at the site. The LOCs include two former chemical labs and a former suspect staging area. The CS was conducted in March of 2015 at three locations by means of Direct Push Technology (DPT) groundwater sampling and at one location for soil sampling. The samples were collected and analyzed in accordance with the approved CS Work Plan. There were no exceedances of criteria detected in any of the samples from the three LOCs. The results of this investigation indicate that past and/or present operations have not negatively impacted environmental media at the A3SB. Based upon no confirmed groundwater detections above GCTLs and no soil impacts above applicable screening criteria no further investigation is warranted at the A3SB. A No Further Action (NFA) status for all locations was approved by the KSCRT at the June 2015 meeting.

Confirmatory sampling↗
NASA NTRS2016

Uncertainties in Coastal Ocean Color Products: Impacts of Spatial Sampling

With increasing demands for ocean color (OC) products with improved accuracy and well characterized, per-retrieval uncertainty budgets, it is vital to decompose overall estimated errors into their primary components. Amongst various contributing elements (e.g., instrument calibration, atmospheric correction, inversion algorithms) in the uncertainty of an OC observation, less attention has been paid to uncertainties associated with spatial sampling. In this paper, we simulate MODIS (aboard both Aqua and Terra) and VIIRS OC products using 30 m resolution OC products derived from the Operational Land Imager (OLI) aboard Landsat-8, to examine impacts of spatial sampling on both cross-sensor product intercomparisons and in-situ validations of R(sub rs) products in coastal waters. Various OLI OC products representing different productivity levels and in-water spatial features were scanned for one full orbital-repeat cycle of each ocean color satellite. While some view-angle dependent differences in simulated Aqua-MODIS and VIIRS were observed, the average uncertainties (absolute) in product intercomparisons (due to differences in spatial sampling) at regional scales are found to be 1.8%, 1.9%, 2.4%, 4.3%, 2.7%, 1.8%, and 4% for the R(sub rs)(443), R(sub rs)(482), R(sub rs)(561), R(sub rs)(655), Chla, K(sub d)(482), and b(sub bp)(655) products, respectively. It is also found that, depending on in-water spatial variability and the sensor's footprint size, the errors for an in-situ validation station in coastal areas can reach as high as +/- 18%. We conclude that a) expected biases induced by the spatial sampling in product intercomparisons are mitigated when products are averaged over at least 7 km × 7 km areas, b) VIIRS observations, with improved consistency in cross-track spatial sampling, yield more precise calibration/validation statistics than that of MODIS, and c) use of a single pixel centered on in-situ coastal stations provides an optimal sampling size for validation efforts. These findings will have implications for enhancing our understanding of uncertainties in ocean color retrievals and for planning of future ocean color missions and the associated calibration/validation exercises.

Coastal ocean color↗
NASA NTRS2018

Lunar Sample Return Entry Systems Analysis

The Lunar Prospector and Clementine missions have revealed deposits of water-ice located at the South Pole-Aitken Basin of the lunar surface. Due to the scarce amount of previous successful sample return missions and the recent discovery of water-ice, the National Research Council (NRC) Decadal Survey recommended prioritizing the development of a Lunar Sample Return Mission Architecture. The NRC Decadal survey ranked the return of cryogenic samples that could potentially aid in current scientific investigations and identify sites for in-situ resource utilization to support future exploration missions. This study aims to identify the key technical challenges and operational constraints involved in returning cryogenic samples in pristine condition. A detailed classification of defined ground rules and assumptions, justification of mission events and high level functional requirements reinforces the proposed concept of operations. In support of the drafted architecture, a comprehensive analysis on design and environmental constraints are documented for the Earth return vehicle, sample container and thermal protection entry system. The design and thermal analysis is comprised of quantitative dimensions for mass and volume, flight performance parameters and thermal system performance limitations. Further refinement of the high level functional requirements is imperative for determining the optimal approach for returning cryopreserved lunar samples.

Lunar Sample Return↗
NASA NTRS2015

Dynamic Simulation Probabalistic Risk Assessment Model for an Enceladus Sample Return Mission

Enceladus, a moon of Saturn, has geyser-like jets that spray plumes of material into orbit. These jets could enable a free-flying spacecraft to collect samples and return them to Earth for study to determine if they contain the building blocks of life. The Office of Planetary Protection at NASA requires containment of any unsterilized samples and prohibits destructive impact of the spacecraft upon return to Earth, with a sample release probability of less than 1 in 1,000,000 as a recommended goal. This paper describes a probabilistic risk assessment model that uses dynamic simulation techniques to capture the physics-based, time- and state-dependent interactions between the sample return system and the environment, which drive the risk of sample release. The dynamic approach uses a Monte Carlo-style simulation to integrate the many phases and sources of risk for a sample return mission. The model is used to assess the achievability of the planetary protection reliability goal. This is accomplished by performing sensitivity studies assessing the impact of modeling assumptions to identify where uncertainties drive the risk. These results, in turn, are used to examine the feasibility of meeting key design and performance parameters that are needed to achieve the reliability goal for a given architecture with existing technologies.

Dynamic Simulation↗
NASA NTRSDate not supplied

Martian Brines in Ancient Salt Lake Beds – A High Priority Target for Mars Sample Return

Mars hosts over 600 chloride deposits as identified from orbital imagery [1-3], including deposits in settings resembling dry, evaporite lacustrine bedforms on Earth. A Mars sample return mission to one of these salt lake beds has a strong potential to directly sample present-day brines originating from ancient martian surface fluids, allowing direct laboratory investigation into fluids, atmosphere, and either potential biology or prebiological conditions on the martian surface at the Noachian through the Hesperian epochs. These sites are extraordinarily well suited for sample return missions because they are favorable for landing and for drill-based sampling, and preserve samples of parent water bodies, including dissolved atmosphere and potential well-preserved biological remains. Such a mission would provide a foundational set of reference samples for understanding Mars’ physiochemical and pre-/biological history, likely to be investigated in depth for generations to come.

brine↗
NASA NTRSDate not supplied

Sample Return and Preliminary Examination Timeline for the OSIRIS-REx Mission

NASA’s OSIRIS-REx spacecraft collected a sample of asteroid (101955) Bennu on October 20, 2020, using the Touch-and-Go Sample Acquisition Mechanism (TAGSAM) [1,2,3]. After sample acquisition, the TAGSAM collection head was stowed in the Sample Return Capsule (SRC; Fig. 1) for transport back to Earth. On September 24, 2023, the OSIRIS-Rex spacecraft will fly by Earth and release the SRC, which will land at the Utah Test and Training Range (UTTR). The sample will be transported to the OSIRIS-REx curation facility, located within NASA’s Johnson Space Center (JSC), where it will be examined, cataloged, and allocated for scientific analyses. Here we describe the timeline of operations for the return, recovery, and initial characterization of the Bennu sample.

Asteroid↗
NASA NTRSDate not supplied

Elevating the Quality of Space Omics Sequencing Data: Innovations and Methodologies from NASA GeneLab Sample Processing Laboratory

NASA’s GeneLab, part of the NASA Open Science Data Repository, is a space-related database that hosts a diverse range of transcriptomics, proteomics, epigenomics and genomics data. The NASA GeneLab Sample Processing Laboratory (SPL) generates omics data from biological experiments conducted aboard the International Space Station, Space Shuttle and space related ground experiments, this omics data then hosted on the GeneLab repository. Samples generated such experiments pose numerous technical challenges such as small experimental sample size, variance in dissection times, limited tissue preservation methods, prolonged storage time, and more. GeneLab SPL team had developed specialized expertise in nucleic acid extraction, library preparation and sequencing of such biological samples via extensive training and years of experience. In order to ensure data accuracy and consistency across experiments, SPL has developed standardized protocols for each species and tissue type. These protocols in conjunction with quality control metrics and data standards are crucial in generating of high-quality data. SPL protocols and standards have been developed in collaboration with the scientific community and had been made publicly available on the GeneLab portal, guaranteeing comparability of datasets across spaceflight experiments. To ensure reliability of data generation, SPL leverages cutting-edge innovations in laboratory automation for sample processing. By leveraging these state-of-the-art platforms, SPL achieves high levels of data reproducibility while significantly minimizing sources of bias and variability, especially across experiments with large numbers of samples. Over the past few years, the space biology investigator community has accessed SPL-generated data from the Open Science Data Repository for a myriad of data re-analysis and re-use studies. We observe a trend that in-house SPL-generated data consistently outperforms outsourced sequencing data in terms of technical standards, quality control metrics, timeliness of data delivery, and sequencing and reagent efficiency. Superior data generation has and will continue to enable discoveries in disease, diagnostic tools, and the biological effects of long duration spaceflight.

GeneLab↗