Water Recovery System Design to Accommodate Dormant Periods for Manned Missions

Future manned missions beyond lower Earth orbit may include intermittent periods of extended dormancy. Under the NASA Advanced Exploration System (AES) project, NASA personnel evaluated the viability of the ISS Water Recovery System (WRS) to support such a mission. The mission requirement includes the capability for life support systems to support crew activity, followed by a dormant period of up to one year, and subsequently for the life support systems to come back online for additional crewed missions. Dormancy could be a critical issue due to concerns with microbial growth or chemical degradation that might prevent water systems from operating properly when the crewed mission began. As such, it is critical that the water systems be designed to accommodate this dormant period. This paper details the results of this evaluation, which include identification of dormancy issues, results of testing performed to assess microbial stability of pretreated urine during dormancy periods, and concepts for updating to the WRS architecture and operational concepts that will enable the ISS WRS to support the dormancy requirement

Performance Qualification Test of the ISS Water Processor Assembly (WPA) Expendables

The Water Processor Assembly (WPA) for use on the International Space Station (ISS) includes various technologies for the treatment of waste water. These technologies include filtration, ion exchange, adsorption, catalytic oxidation, and iodination. The WPA hardware implementing portions of these technologies, including the Particulate Filter, Multifiltration Bed, Ion Exchange Bed, and Microbial Check Valve, was recently qualified for chemical performance at the Marshall Space Flight Center. Waste water representing the quality of that produced on the ISS was generated by test subjects and processed by the WPA. Water quality analysis and instrumentation data was acquired throughout the test to monitor hardware performance. This paper documents operation of the test and the assessment of the hardware performance

MODIFYING METADATA BASED ON A RECEIVED GESTURE

A metadata modification system can be used to modify metadata associated with one or more products displayed at a display screen. The system presents the metadata associated with one or more products at the display screen of the electronic device. The system receives a gesture from a user at the display screen. The system modifies the metadata associated with one or more products based on the received gesture from the user

Water Recovery System Architecture and Operational Concepts to Accommodate Dormancy

Future manned missions beyond low Earth orbit will include intermittent periods of extended dormancy. The mission requirement includes the capability for life support systems to support crew activity, followed by a dormant period of up to one year, and subsequently for the life support systems to come back online for additional crewed missions. NASA personnel are evaluating the architecture and operational concepts that will allow the Water Recovery System (WRS) to support such a mission. Dormancy could be a critical issue due to concerns with microbial growth or chemical degradation that might prevent water systems from operating properly when the crewed mission began. As such, it is critical that the water systems be designed to accommodate this dormant period. This paper identifies dormancy issues, concepts for updating the WRS architecture and operational concepts that will enable the WRS to support the dormancy requirement

Determination of Peptide and Protein Ion Charge States by Fourier Transformation of Isotope-Resolved Mass Spectra

We report an automated method for determining charge states from high-resolution mass spectra. Fourier transforms of isotope packets from high-resolution mass spectra are compared to Fourier transforms of modeled isotopic peak packets for a range of charge states. The charge state for the experimental ion packet is determined by the model isotope packet that yields the best match in the comparison of the Fourier transforms. This strategy is demonstrated for determining peptide ion charge states from “zoom scan” data from a linear quadrupole ion trap mass spectrometer, enabling the subsequent automated identification of singly- through quadruply-charged peptide ions, while reducing the numbers of conflicting identifications from ambiguous charge state assignments. We also apply this technique to determine the charges of intact protein ions from LC-FTICR data, demonstrating that it is more sensitive under these experimental conditions than two existing algorithms. The strategy outlined in this paper should be generally applicable to mass spectra obtained from any instrument capable of isotopic resolution

Comparative proteomics analysis between maize and sorghum uncovers important proteins and metabolic pathways mediating drought tolerance

Drought severely affects crop yield and yield stability. Maize and sorghum are major crops in Africa and globally, and both are negatively impacted by drought. However, sorghum has a better ability to withstand drought than maize. Consequently, this study identifies differences between maize and sorghum grown in water deficit conditions, and identifies proteins associated with drought tolerance in these plant species. Leaf relative water content and proline content were measured, and label-free proteomics analysis was carried out to identify differences in protein expression in the two species in response to water deficit. Water deficit enhanced the proline accumulation in sorghum roots to a higher degree than in maize, and this higher accumulation was associated with enhanced water retention in sorghum. Proteomic analyses identified proteins with differing expression patterns between the two species, revealing key metabolic pathways that explain the better drought tolerance of sorghum than maize

A Label-Free Proteomic and Complementary Metabolomic Analysis of Leaves of the Resurrection Plant Xerophyta schlechteri during Dehydration

Vegetative desiccation tolerance, or the ability to survive the loss of ~95% relative water content (RWC), is rare in angiosperms, with these being commonly called resurrection plants. It is a complex multigenic and multi-factorial trait, with its understanding requiring a comprehensive systems biology approach. The aim of the current study was to conduct a label-free proteomic analysis of leaves of the resurrection plant Xerophyta schlechteri in response to desiccation. A targeted metabolomics approach was validated and correlated to the proteomics, contributing the missing link in studies on this species. Three physiological stages were identified: an early response to drying, during which the leaf tissues declined from full turgor to a RWC of ~80–70%, a mid-response in which the RWC declined to 40% and a late response where the tissues declined to 10% RWC. We identified 517 distinct proteins that were differentially expressed, of which 253 proteins were upregulated and 264 were downregulated in response to the three drying stages. Metabolomics analyses, which included monitoring the levels of a selection of phytohormones, amino acids, sugars, sugar alcohols, fatty acids and organic acids in response to dehydration, correlated with some of the proteomic differences, giving insight into the biological processes apparently involved in desiccation tolerance in this species

Network-assisted protein identification and data interpretation in shotgun proteomics

Protein assembly and biological interpretation of the assembled protein lists are critical steps in shotgun proteomics data analysis. Although most biological functions arise from interactions among proteins, current protein assembly pipelines treat proteins as independent entities. Usually, only individual proteins with strong experimental evidence, that is, confident proteins, are reported, whereas many possible proteins of biological interest are eliminated. We have developed a clique-enrichment approach (CEA) to rescue eliminated proteins by incorporating the relationship among proteins as embedded in a protein interaction network. In several data sets tested, CEA increased protein identification by 8–23% with an estimated accuracy of 85%. Rescued proteins were supported by existing literature or transcriptome profiling studies at similar levels as confident proteins and at a significantly higher level than abandoned ones. Applying CEA on a breast cancer data set, rescued proteins coded by well-known breast cancer genes. In addition, CEA generated a network view of the proteins and helped show the modular organization of proteins that may underpin the molecular mechanisms of the disease