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At least 1,639 records · Page 91

WetLab-2: Providing Quantitative PCR Capabilities on ISS

The objective of NASA Ames Research Centers WetLab-2 Project is to place on the ISS a system capable of conducting gene expression analysis via quantitative real-time PCR (qRT-PCR) of biological specimens sampled or cultured on orbit. The WetLab-2 system is capable of processing sample types ranging from microbial cultures to animal tissues dissected on-orbit. The project has developed a RNA preparation module that can lyse cells and extract RNA of sufficient quality and quantity for use as templates in qRT-PCR reactions. Our protocol has the advantage that it uses non-toxic chemicals, alcohols or other organics. The resulting RNA is transferred into a pipette and then dispensed into reaction tubes that contain all lyophilized reagents needed to perform qRT-PCR reactions. These reaction tubes are mounted on rotors to centrifuge the liquid to the reaction window of the tube using a cordless drill. System operations require simple and limited crew actions including syringe pushes, valve turns and pipette dispenses. The resulting process takes less than 30 min to have tubes ready for loading into the qRT-PCR unit.The project has selected a Commercial-Off-The-Shelf (COTS) qRT-PCR unit, the Cepheid SmartCycler, that will fly in its COTS configuration. The SmartCycler has a number of advantages including modular design (16 independent PCR modules), low power consumption, rapid thermal ramp times and four-color detection. The ability to detect up to four fluorescent channels will enable multiplex assays that can be used to normalize for RNA concentration and integrity, and to study multiple genes of interest in each module. The WetLab-2 system will have the capability to downlink data from the ISS to the ground after a completed run and to uplink new programs. The ability to conduct qRT-PCR on-orbit eliminates the confounding effects on gene expression of reentry stresses and shock acting on live cells and organisms or the concern of RNA degradation of fixed samples. The system can be used to validate terrestrial analyses of samples returned from ISS by providing on-orbit gene expression benchmarking prior to sample return. The ability to get on-orbit data will provide investigators with the opportunity to adjust experimental parameters in real time for subsequent trials, without the need for sample return and re-flight to sample multigenerational changes. The system can also be used for analysis of air, surface, water, and clinical samples to monitor environmental contaminants and crew health. The verification flight of the instrument is scheduled to launch on SpaceX-7 in June 2015. The WetLab-2 Project is supported by NASAs ISS Program at JSC, Code OZ.

ISS tools↗

Catalyst-Vision (PEM Catalyst Layer Image Analysis Tool) [SWR-25-100]

Catalyst-Vision (PEM Catalyst Layer Image Analysis Tool) provides an advanced Python-based tool, primarily designed for use in a Jupyter/Colab notebook, for the quantitative morphological analysis of pre-segmented shapes. While developed for analyzing PEM catalyst layers from microscopy, its methodology is suitable for characterizing any grayscale object provided on a uniform white background. The tool uses a robust computer vision pipeline based on the Euclidean Distance Transform and skeletonization to accurately measure local thickness and tortuosity, providing a comprehensive characterization of an object's geometry and internal texture. If you find this code useful, please cite our preprint as: Chan, Ai-Lin and Hayden, Steven and Harvey, Steven P. and Smeaton, Michelle and Okrucky, Caleb and Watt, John and Ulična, Soňa and Spurgeon, Steven and Jungjohann, Katherine and Alia, Shaun, Mechanism-informed breakdown: understanding degradation by controlling voltage hold patterns in PEM water electrolyzers. Preprint (2025).

Spurgeon, Steven [National Laboratory of the Rocki↗

MAUD Interface Tool Kit (MILK)

Materials Analysis Using Diffraction (MAUD) is an open source Rietveld refinement program which fits diffraction models to diffraction spectra allowing quantitative diffraction analysis. The scripting interface developed here using python facilitates the choice of parameters to refine during the Rietveld fitting process and provides a simple MPI framework for running MAUD instances in parallel. The scripting language facilitates batch, custom, and reproducible Rietveld refinements of large datasets.

Savage, Daniel↗

Three-dimensional imaging of grain boundaries via quantitative fluorescence X-ray tomography analysis

Abstract Three-dimensional visualization of material composition within multiple grains and across complex networks of grain boundaries at nanoscales can provide new insight into the structure evolution and emerging functional properties of the material for diverse applications. Here, using nanoscale scanning X-ray fluorescence tomography, coupled with an advanced self-absorption correction algorithm developed in this work, we analyze the three-dimensional gain distributions and compositions in a Ce 0.8 Gd 0.2 O 2-δ -CoFe 2 O 4 mixed ionic-electronic conductor system with high accuracy and statistical significance. Our systematic investigation reveals an additional emergent phase and uncovers highly intriguing composition stability ranges for the multiple material phases within this system. The presented visualization of composition variations across complex interfaces, supported by our quantitative composition analysis, discloses mechanistic pathways of the diverse phase transformations occurring in the material synthesis, providing insights for the optimization of transport properties in the mixed ionic-electronic conductor system.

36 MATERIALS SCIENCE↗

Effect of quantum nuclear motion on hydrogen bonding

This work considers how the properties of hydrogen bonded complexes, X–H⋯Y, are modified by the quantum motion of the shared proton. Using a simple two-diabatic state model Hamiltonian, the analysis of the symmetric case, where the donor (X) and acceptor (Y) have the same proton affinity, is carried out. For quantitative comparisons, a parametrization specific to the O–H⋯O complexes is used. The vibrational energy levels of the one-dimensional ground state adiabatic potential of the model are used to make quantitative comparisons with a vast body of condensed phase data, spanning a donor-acceptor separation (R) range of about 2.4 − 3.0 Å, i.e., from strong to weak hydrogen bonds. The position of the proton (which determines the X–H bond length) and its longitudinal vibrational frequency, along with the isotope effects in both are described quantitatively. An analysis of the secondary geometric isotope effect, using a simple extension of the two-state model, yields an improved agreement of the predicted variation with R of frequency isotope effects. The role of bending modes is also considered: their quantum effects compete with those of the stretching mode for weak to moderate H-bond strengths. In spite of the economy in the parametrization of the model used, it offers key insights into the defining features of H-bonds, and semi-quantitatively captures several trends.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Patterns of gene expression associated with recovery and injury in heat-stressed rats

Background: The in vivo gene response associated with hyperthermia is poorly understood. Here, we perform a global, multiorgan characterization of the gene response to heat stress using an in vivo conscious rat model. Results: We heated rats until implanted thermal probes indicated a maximal core temperature of 41.8°C (T c,Max ). We then compared transcriptomic profiles of liver, lung, kidney, and heart tissues harvested from groups of experimental animals at T c,Max , 24 hours, and 48 hours after heat stress to time-matched controls kept at an ambient temperature. Cardiac histopathology at 48 hours supported persistent cardiac injury in three out of six animals. Microarray analysis identified 78 differentially expressed genes common to all four organs at T c,Max . Self-organizing maps identified gene-specific signatures corresponding to protein-folding disorders in heat-stressed rats with histopathological evidence of cardiac injury at 48 hours. Quantitative proteomics analysis by iTRAQ (isobaric tag for relative and absolute quantitation) demonstrated that differential protein expression most closely matched the transcriptomic profile in heat-injured animals at 48 hours. Calculation of protein supersaturation scores supported an increased propensity of proteins to aggregate for proteins that were found to be changing in abundance at 24 hours and in animals with cardiac injury at 48 hours, suggesting a mechanistic association between protein misfolding and the heat-stress response. Conclusions: Pathway analyses at both the transcript and protein levels supported catastrophic deficits in energetics and cellular metabolism and activation of the unfolded protein response in heat-stressed rats with histopathological evidence of persistent heat injury, providing the basis for a systems-level physiological model of heat illness and recovery.

59 BASIC BIOLOGICAL SCIENCES↗

Tumor associated osteoclast-like giant cells promote tumor growth and lymphangiogenesis by secreting vascular endothelial growth factor-C

Highlights: • M-CSF and RANKL expressing HeLa cells induced osteoclastogenesis in vitro. • We established OGC-containing tumor model in vivo. • OGC-containing tumor became larger independent of M-CSF or RANKL effect. • VEGF-C secreted from OGCs was a one of candidates for OGC-containing tumor growth. - Abstract: Tumors with osteoclast-like giant cells (OGCs) have been reported in a variety of organs and exert an invasive and prometastatic phenotype, but the functional role of OGCs in the tumor environment has not been fully clarified. We established tumors containing OGCs to clarify the role of OGCs in tumor phenotype. A mixture of HeLa cells expressing macrophage colony-stimulating factor (M-CSF, HeLa-M) and receptor activator of nuclear factor-κB ligand (RANKL, HeLa-R) effectively supported the differentiation of osteoclast-like cells from bone marrow macrophages in vitro. Moreover, a xenograft study showed OGC formation in a tumor composed of HeLa-M and HeLa-R. Surprisingly, the tumors containing OGCs were significantly larger than the tumors without OGCs, although the growth rates were not different in vitro. Histological analysis showed that lymphangiogenesis and macrophage infiltration in the tumor containing OGCs, but not in other tumors were accelerated. According to quantitative PCR analysis, vascular endothelial growth factor (VEGF)-C mRNA expression increased with differentiation of osteoclast-like cells. To investigate whether VEGF-C expression is responsible for tumor growth and macrophage infiltration, HeLa cells overexpressing VEGF-C (HeLa-VC) were established and transplanted into mice. Tumors composed of HeLa-VC mimicked the phenotype of the tumors containing OGCs. Furthermore, the vascular permeability of tumor microvessels also increased in tumors containing OGCs and to some extent in VEGF-C-expressing tumors. These results suggest that macrophage infiltration and vascular permeability are possible mediators in these tumors. These findings revealed that OGCs in the tumor environment promoted tumor growth and lymphangiogenesis, at least in part, by secreting VEGF-C.

60 APPLIED LIFE SCIENCES↗

Automated defect analysis in electron microscopic images

Electron microscopy and defect analysis are a cornerstone of materials science, as they offer detailed insights on the microstructure and performance of a wide range of materials and material systems. Building a robust and flexible platform for automated defect recognition and classification in electron microscopy will result in the completion of analysis orders of magnitude faster after images are recorded, or even online during image acquisition. Automated analysis has the potential to be significantly more efficient, accurate, and repeatable than human analysis, and it can scale with the increasingly important methods of automated data generation. Herein, an automated recognition tool is developed based on a computer vison–based approach; it sequentially applies a cascade object detector, convolutional neural network, and local image analysis methods. We demonstrate that the automated tool performs as well as or better than manual human detection in terms of recall and precision and achieves quantitative image/defect analysis metrics close to the human average. The proposed approach works for images of varying contrast, brightness, and magnification. Furthermore, these promising results suggest that this and similar approaches are worth exploring for detecting multiple defect types and have the potential to locate, classify, and measure quantitative features for a range of defect types, materials, and electron microscopic techniques.

47 OTHER INSTRUMENTATION↗

A simple novel device for air sampling by electrokinetic capture

A variety of different sampling devices are currently available to acquire air samples for the study of the microbiome of the air. All have a degree of technical complexity that limits deployment. Here, we evaluate the use of a novel device, which has no technical complexity and is easily deployable. An air-cleaning device powered by electrokinetic propulsion has been adapted to provide a universal method for collecting samples of the aerobiome. Plasma-induced charge in aerosol particles causes propulsion to and capture on a counter-electrode. The flow of ions creates net bulk airflow, with no moving parts. A device and electrode assembly have been re-designed from air-cleaning technology to provide an average air flow of 120 lpm. This compares favorably with current air sampling devices based on physical air pumping. Capture efficiency was determined by comparison with a 0.4 μm polycarbonate reference filter, using fluorescent latex particles in a controlled environment chamber. Performance was compared with the same reference filter method in field studies in three different environments. For 23 common fungal species by quantitative polymerase chain reaction (qPCR), there was 100 % sensitivity and apparent specificity of 87%, with the reference filter taken as “gold standard.” Further, bacterial analysis of 16S RNA by amplicon sequencing showed equivalent community structure captured by the electrokinetic device and the reference filter. Unlike other current air sampling methods, capture of particles is determined by charge and so is not controlled by particle mass. We analyzed particle sizes captured from air, without regard to specific analyte by atomic force microscopy: particles at least as low as 100 nM could be captured from ambient air. This work introduces a very simple plug-and-play device that can sample air at a high-volume flow rate with no moving parts and collect particles down to the sub-micron range. In conclusion, the performance of the device is substantially equivalent to capture by pumping through a filter for microbiome analysis by quantitative PCR and amplicon sequencing.

47 OTHER INSTRUMENTATION↗

Bio-project “derisking” through development of systematic methodologies and frameworks for risk assessment

One of the primary hindrances to producing a viable, sustainable domestic biomass industry for renewable biofuels, bio-products and bio-power is the lack of understanding and quantification of the risks associated with both the biomass supply chain and preprocessing and conversion technologies. Currently a consistent method for assessing, comparing, and quantifying risks in biomass supply chains does not exist, creating a major investment barrier to bioenergy projects in the U.S. The lack of a standardized approach has resulted in bioenergy stakeholders independently using inconsistent approaches and evaluation criteria, leading to unreliable and incomparable assessments of risks and financing barriers to bio-project development. Along with the challenges of inconsistent risk assessment for supply chain risk, technology specific risks based on variability in biomass properties are not fully understood and can pose significant unforeseen challenges for bioenergy projects. In many cases these properties have not yet been identified and the impacts on the proposed technology and products unquantified. This is particularly challenging for emerging preprocessing and conversion technologies. Without a firm understanding of the preprocessing/conversion technology-specific critical properties, the risk of a proposed bio-project cannot be fully evaluated. To address inconsistent risk evaluation in the biomass supply chain supporting project financing, a Biomass Supply Chain Risk Standards (BSCRS) framework was developed. The BSCRS framework includes a comprehensive list of known and perceived risks (Risk Indicators) to the supply chain developed through 100’s of interviews with bioenergy industry experts spanning from feedstock growers and suppliers to representatives from the financial sector. These risks have been organized into a manageable hierarchy of Risk Categories and Risk Factors that can be practically assessed. This BSCRS framework also provides mitigation strategies for multiple Risk Indicators from best available industry practices and research findings. Additionally, a risk quantification methodology for each Risk Factor, Risk Category, and the bio-project as a whole was developed to enable capital markets to assess feedstock risk more efficiently and more accurately. Multiple case studies representing existing bio-projects have been used to evaluate and verify the BSCRS framework and scoring methodology. To address technological risk along with the supply chain risk captured in the developed BSCRS framework, this work also focuses on development of a systematic criticality assessment tool using well-accepted, quantitative risk analysis methods to evaluate bioenergy feedstock critical properties impacting system unit operations. The proposed Failure Mode and Effect Analysis (FMEA) approach uses a team of subject area experts (SAEs) for each targeted unit operation within a system. Collectively, the team will develop and use a quantitative scoring system to assess the material attributes, process parameters, and quality attributes for key unit operations that have already been identified. The FMEA process generates Risk Priority Numbers (RPNs) for the various failures and predominant causes for each material/process unit/product combination resulting in a semi-quantitative, standardized methodology for assessing technological risk and biomass properties contributing to that risk.

09 BIOMASS FUELS↗

Stream network analysis from orbital and suborbital imagery, Colorado River Basin, Texas

The author has identified the following significant results. Orbital SL-2 imagery (earth terrain camera S-190B), received September 5, 1973, was subjected to quantitative network analysis and compared to 7.5 minute topographic mapping (scale: 1/24,000) and U.S.D.A. conventional black and white aerial photography (scale: 1/22,200). Results can only be considered suggestive because detail on the SL-2 imagery was badly obscured by heavy cloud cover. The upper Bee Creek basin was chosen for analysis because it appeared in a relatively cloud-free portion of the orbital imagery. Drainage maps were drawn from the three sources digitized into a computer-compatible format, and analyzed by the WATER system computer program. Even at its small scale (1/172,000) and with bad haze the orbital photo showed much drainage detail. The contour-like character of the Glen Rose Formation's resistant limestone units allowed channel definition. The errors in pattern recognition can be attributed to local areas of dense vegetation and to other areas of very high albedo caused by surficial exposure of caliche. The latter effect caused particular difficulty in the determination of drainage divides.

Baker, V. R.↗

Landsat analysis of tropical forest succession employing a terrain model

Landsat multispectral scanner (MSS) data have yielded a dual classification of rain forest and shadow in an analysis of a semi-deciduous forest on Mindonoro Island, Philippines. Both a spatial terrain model, using a fifth side polynomial trend surface analysis for quantitatively estimating the general spatial variation in the data set, and a spectral terrain model, based on the MSS data, have been set up. A discriminant analysis, using both sets of data, has suggested that shadowing effects may be due primarily to local variations in the spectral regions and can therefore be compensated for through the decomposition of the spatial variation in both elevation and MSS data.

Barringer, T. H.↗

Diel metabolomics analysis of a hot spring chlorophototrophic microbial mat leads to new hypotheses of community member metabolisms

Dynamic environmental factors such as light, nutrients, salt, and temperature continuously affect chlorophototrophic microbial mats, requiring adaptative and acclimative responses to stabilize composition and function. Quantitative metabolomics analysis can provide insights into metabolite dynamics for understanding community response to such changing environmental conditions. In this study, we quantified volatile organic acids, polar metabolites (amino acids, glycolytic and citric acid cycle intermediates, nucleobases, nucleosides, and sugars), wax esters, and polyhydroxyalkanoates, resulting in the identification of 104 metabolites and related molecules in thermal chlorophototrophic microbial mat cores collected over a diel cycle in Mushroom Spring, Yellowstone National Park. A limited number of predominant taxa inhabiting this community and their functional potentials have been previously identified through metagenomic and metatranscriptomic analyses and in situ metabolisms and metabolic interactions among these taxa have been hypothesized. Our metabolomics results confirmed the diel cycling of photorespiration (e.g. glycolate) and fermentation (e.g. acetate, propionate, and lactate) products, the carbon storage polymers polyhydroxyalkanoates, and dissolved gases (e.g. H2 and CO2) in the waters overlying the mat, which were hypothesized to occur in major mat chlorophototrophic community members. In addition, we have formulated the following new hypotheses: 1) the morning hours are a time of biosynthesis of amino acids, DNA, and RNA; 2) Synechococcus spp. produce CH4 via metabolism of phosphonates, and photo-inhibited cells may also produce lactate via fermentation as an alternate metabolism; 3) glycolate and lactate are exchanged among Synechococcus and Roseiflexus spp.; and 4) fluctuations in many metabolite pools (e.g. wax esters) at different times of day result from species found at different depths within the mat responding to temporal differences in their niches.

54 ENVIRONMENTAL SCIENCES↗

On-Orbit Quantitative Real-Time Gene Expression Analysis Using the Wetlab-2 System

NASA Ames Research Center's WetLab-2 Project enables on-orbit quantitative Reverse Transcriptase PCR (qRT-PCR) analysis without the need for sample return. The WetLab-2 system is capable of processing sample types ranging from microbial cultures to animal tissues dissected on-orbit. The project developed a RNA preparation module that can lyse cells and extract RNA of sufficient quality and quantity for use as templates in qRT-PCR reactions. Our protocol has the advantage of using non-toxic chemicals and does not require alcohols or other organics. The resulting RNA is dispensed into reaction tubes that contain all lyophilized reagents needed to perform qRT-PCR reactions. System operations require simple and limited crew actions including syringe pushes, valve turns and pipette dispenses. The project selected the Cepheid SmartCycler (TradeMark), a Commercial-Off-The-Shelf (COTS) qRT-PCR unit, because of its advantages including rugged modular design, low power consumption, rapid thermal ramp times and four-color multiplex detection. Single tube multiplex assays can be used to normalize for RNA concentration and integrity, and to study multiple genes of interest in each module. The WetLab-2 system can downlink data from the ISS to the ground after a completed run and uplink new thermal cycling programs. The ability to conduct qRT-PCR and generate results on-orbit is an important step towards utilizing the ISS as a National Laboratory facility. Specifically, the ability to get on-orbit data will provide investigators with the opportunity to adjust experimental parameters in real time without the need for sample return and re-flight. On orbit gene expression analysis can also eliminate the confounding effects on gene expression of reentry stresses and shock acting on live cells and organisms or the concern of RNA degradation of fixed samples and provide on-orbit gene expression benchmarking prior to sample return. Finally, the system can also be used for analysis of air, surface, water, and clinical samples to monitor environmental pathogens and crew health. The validation flight of the WetLab-2 system using E. coli bacteria and mouse liver launched on SpaceX-7 in June 2015 and will remain on the ISS National Laboratory.

ISS tools↗

Design improvement of the three-beam detector towards a precise long-range 6-degree of freedom motion sensor system

This paper presents performance enhancement of the three beam detector through design improvement based on the error analysis. The three-beam detector is a novel sensor system that measures six motions (i.e., 3 translations and 3 rotations) of a remote object with high accuracy by implementing three laser distance sensors and a vision sensor. In this paper, finite element analysis and parameter analysis are applied to the three-beam detector to analyze its structural frames and sensor configuration, respectively, in terms of sensing error. By virtue of such a systematic, quantitative error analysis, this research has successfully improved the performance of the three-beam detector and thoroughly validated through field tests that it can detect the 6-degree of freedom motions of a remote target at 30 m with an accuracy of 1.51 mm and 0.18° and precision of 0.38 mm and 0.13°.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Potable water taste enhancement

An analysis was conducted to determine the causes of and remedies for the unpalatability of potable water in manned spacecraft. Criteria and specifications for palatable water were established and a quantitative laboratory analysis technique was developed for determinig the amounts of volatile organics in good tasting water. Prototype spacecraft water reclamation systems are evaluated in terms of the essential palatability factors.

Source record↗