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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Surface, Water, and Air Biocharacterization (SWAB) Flight Experiment

The determination of risk from infectious disease during spaceflight missions is composed of several factors including both the concentration and characteristics of the microorganisms to which the crew are exposed. Thus, having a good understanding of the microbial ecology aboard spacecraft provides the necessary information to mitigate health risks to the crew. While preventive measures are taken to minimize the presence of pathogens on spacecraft, medically significant organisms have been isolated from both the Mir and International Space Station (ISS). Historically, the method for isolation and identification of microorganisms from spacecraft environmental samples depended upon their growth on culture media. Unfortunately, only a fraction of the organisms may grow on a specific culture medium, potentially omitting those microorganisms whose nutritional and physical requirements for growth are not met. To address this bias in our understanding of the ISS environment, the Surface, Water, and Air Biocharacterization (SWAB) Flight Experiment was designed to investigate and develop monitoring technology to provide better microbial characterization. For the SWAB flight experiment, we hypothesized that environmental analysis using non-culture-based technologies would reveal microorganisms, allergens, and microbial toxins not previously reported in spacecraft, allowing for a more complete health assessment. Key findings during this experiment included: a) Generally, advanced molecular techniques were able to reveal a few organisms not recovered using culture-based methods; however, there is no indication that current monitoring is "missing" any medically significant bacteria or fungi. b) Molecular techniques have tremendous potential for microbial monitoring, however, sample preparation and data analysis present challenges for spaceflight hardware. c) Analytical results indicate that some molecular techniques, such as denaturing gradient gel electrophoresis (DGGE), can be much less sensitive than culture-based methods. d) More sensitive molecular techniques, such as quantitative polymerase chain reaction (QPCR), were able to identify viral DNA from ISS environments, suggesting potential transfer of the organism between crewmembers. In addition, the hardware selected for this experiment represented advances for next-generation sample collection. The advanced nature of this collection hardware was noted, when the Sartorius MD8 Air Port air sampler from the SWAB experiment remained on board ISS at the request of JAXA investigators, who intend to use it in completion of their microbial ecology experiment.

Castro, V. A.↗
DOE OSTI2019

Show me your secret(ed) weapons: a multifaceted approach reveals a wide arsenal of type III‐secreted effectors in the cucurbit pathogenic bacterium Acidovorax citrulli and novel effectors in the Acidovorax genus

Summary The cucurbit pathogenic bacterium Acidovorax citrulli requires a functional type III secretion system (T3SS) for pathogenicity. In this bacterium, as with Xanthomonas and Ralstonia spp . , an AraC‐type transcriptional regulator, HrpX, regulates expression of genes encoding T3SS components and type III‐secreted effectors (T3Es) . The annotation of a sequenced A. citrulli strain revealed 11 T3E genes. Assuming that this could be an underestimation, we aimed to uncover the T3E arsenal of the A. citrulli model strain, M6. Thorough sequence analysis revealed 51 M6 genes whose products are similar to known T3Es. Furthermore, we combined machine learning and transcriptomics to identify novel T3Es. The machine‐learning approach ranked all A. citrulli M6 genes according to their propensity to encode T3Es. RNA‐Seq revealed differential gene expression between wild‐type M6 and a mutant defective in HrpX: 159 and 28 genes showed significantly reduced and increased expression in the mutant relative to wild‐type M6, respectively. Data combined from these approaches led to the identification of seven novel T3E candidates that were further validated using a T3SS‐dependent translocation assay. These T3E genes encode hypothetical proteins that seem to be restricted to plant pathogenic Acidovorax species. Transient expression in Nicotiana benthamiana revealed that two of these T3Es localize to the cell nucleus and one interacts with the endoplasmic reticulum. This study places A. citrulli among the ‘richest’ bacterial pathogens in terms of T3E cargo. It also revealed novel T3Es that appear to be involved in the pathoadaptive evolution of plant pathogenic Acidovorax species.

Jiménez‐Guerrero, Irene↗
DOE OSTI2017

Hyperspectral fluorescence microscopy detects autofluorescent factors that can be exploited as a diagnostic method for Candida species differentiation

Fungi in the Candida genus are the most common fungal pathogens. They not only cause high morbidity and mortality but can also cost billions of dollars in healthcare. To alleviate this burden, early and accurate identification of Candida species is necessary. However, standard identification procedures can take days and have a large false negative error. The method described in this study takes advantage of hyperspectral confocal fluorescence microscopy, which enables the capability to quickly and accurately identify and characterize the unique autofluorescence spectra from different Candida species with up to 84% accuracy when grown in conditions that closely mimic physiological conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Pressured cytotoxic T cell epitope strength among SARS-CoV-2 variants correlates with COVID-19 severity

Heterogeneity in susceptibility among individuals to COVID-19 has been evident through the pandemic worldwide. Cytotoxic T lymphocyte (CTL) responses generated against pathogens in certain individuals are known to impose selection pressure on the pathogen, thus driving emergence of new variants. In this study, we probe the role played by host genetic heterogeneity in terms of HLA-genotypes in determining differential COVID-19 severity in patients. We use bioinformatic tools for CTL epitope prediction to identify epitopes under immune pressure. Using HLA-genotype data of COVID-19 patients from a local cohort, we observe that the recognition of pressured epitopes from the parent strain Wuhan-Hu-1 correlates with COVID-19 severity. We also identify and rank list HLA-alleles and epitopes that offer protectivity against severe disease in infected individuals. Finally, we shortlist a set of 6 pressured and protective epitopes that represent regions in the viral proteome that are under high immune pressure across SARS-CoV-2 variants. In conclusion, identification of such epitopes, defined by the distribution of HLA-genotypes among members of a population, could potentially aid in prediction of indigenous variants of SARS-CoV-2 and other pathogens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

How lipidomics can transform our understanding of virus infections

Traditionally, lipids have been thought of as molecules that provide structure and energy, but their functional relevance in disease mechanisms is increasingly clear, and with advancements in mass spectrometry technologies, lipidomics analyses is a tool gaining recognition. Beyond the utility of lipoprotein and fatty acid profiles in clinical diagnosis and chemotaxonomic identifications, respectively, lipidomics analysis that combines knowledge across disciplines and can resolve exact lipid structures has the potential to advance clinical diagnoses and associated treatment, differentiate pathogen types (e.g., virus vs. bacterial vs. fungal), detect natural vs lab-grown viruses, and perhaps distinguish a pathogen from a benign biological agent (i.e., threat potential). As new viruses emerge and localized outbreaks expand, lipidomics will accelerate our understanding of viral infections and aid in maximizing the discovery of novel biomarkers of pathogenicity and host response.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods

Early and accurate diagnosis of respiratory pathogens and associated outbreaks can allow for the control of spread, epidemiological modeling, targeted treatment, and decision making–as is evident with the current COVID-19 pandemic. Many respiratory infections share common symptoms, making them difficult to diagnose using only syndromic presentation. Yet, with delays in getting reference laboratory tests and limited availability and poor sensitivity of point-of-care tests, syndromic diagnosis is the most-relied upon method in clinical practice today. Here, we examine the variability in diagnostic identification of respiratory infections during the annual infection cycle in northern New Mexico, by comparing syndromic diagnostics with polymerase chain reaction (PCR) and sequencing-based methods, with the goal of assessing gaps in our current ability to identify respiratory pathogens. Of 97 individuals that presented with symptoms of respiratory infection, only 23 were positive for at least one RNA virus, as confirmed by sequencing. Whereas influenza virus (n = 7) was expected during this infection cycle, we also observed coronavirus (n = 7), respiratory syncytial virus (n = 8), parainfluenza virus (n = 4), and human metapneumovirus (n = 1) in individuals with respiratory infection symptoms. Four patients were coinfected with two viruses. In 21 individuals that tested positive using PCR, RNA sequencing completely matched in only 12 (57%) of these individuals. Few individuals (37.1%) were diagnosed to have an upper respiratory tract infection or viral syndrome by syndromic diagnostics, and the type of virus could only be distinguished in one patient. Thus, current syndromic diagnostic approaches fail to accurately identify respiratory pathogens associated with infection and are not suited to capture emerging threats in an accurate fashion. We conclude there is a critical and urgent need for layered agnostic diagnostics to track known and unknown pathogens at the point of care to control future outbreaks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Quantitative Dissection of Agrobacterium Virulence to Generate a Synthetic Ti Plasmid

Agrobacterium is not only a costly plant pathogen but is also an essential tool for plant transformation. Though Agrobacterium-mediated transformation (AMT) has been heavily studied, its polygenic nature and complex transcriptional regulation make identification of the genetic basis of transformational efficiency difficult through traditional genetic and bioinformatic approaches. Here, we use a bottom-up synthetic approach to systematically engineer the tumor-inducing plasmid (pTi), wherein the majority of virulence machinery is encoded. Using a validated toolkit to control Agrobacterium gene expression in planta, we perform a quantitative dissection of AMT to investigate the contributions of critical vir-genes at different expression levels. We construct a synthetic pTi capable of transient plant and stable fungal transformation and characterize bottlenecks and solutions for complex polygenic synthetic pTi designs. Our reductionist approach demonstrates how bottom-up engineering can be used to dissect and elucidate the genetic underpinnings of complex biological traits, laying the foundation for future engineering to establish full synthetic control over the critical process of AMT.

Agrobacterium-mediated transformation↗
DOE OSTI2024

Quantifying leaf symptoms of sorghum charcoal rot in images of field‐grown plants using deep neural networks

Abstract Charcoal rot of sorghum (CRS) is a significant disease affecting sorghum crops, with limited genetic resistance available. The causative agent, Macrophomina phaseolina (Tassi) Goid, is a highly destructive fungal pathogen that targets over 500 plant species globally, including essential staple crops. Utilizing field image data for precise detection and quantification of CRS could greatly assist in the prompt identification and management of affected fields and thereby reduce yield losses. The objective of this work was to implement various machine learning algorithms to evaluate their ability to accurately detect and quantify CRS in red‐green‐blue images of sorghum plants exhibiting symptoms of infection. EfficientNet‐B3 and a fully convolutional network emerged as the top‐performing models for image classification and segmentation tasks, respectively. Among the classification models evaluated, EfficientNet‐B3 demonstrated superior performance, achieving an accuracy of 86.97%, a recall rate of 0.71, and an F1 score of 0.73. Of the segmentation models tested, FCN proved to be the most effective, exhibiting a validation accuracy of 97.76%, a recall rate of 0.68, and an F1 score of 0.66. As the size of the image patches increased, both models’ validation scores increased linearly, and their inference time decreased exponentially. This trend could be attributed to larger patches containing more information, improving model performance, and fewer patches reducing the computational load, thus decreasing inference time. The models, in addition to being immediately useful for breeders and growers of sorghum, advance the domain of automated plant phenotyping and may serve as a foundation for drone‐based or other automated field phenotyping efforts. Additionally, the models presented herein can be accessed through a web‐based application where users can easily analyze their own images.

Gonzalez, Emmanuel M.↗
DOE OSTI2026

Discovering novel therapeutic V H Hs for emerging viruses: perspectives from VEEV selection strategies

Introduction: Evolution or emergence of a new viral variant is a significant public health concern. Alphaviruses, such as Venezuelan equine encephalitis virus (VEEV), are mosquito-borne viruses which are becoming more prevalent due to expansion of vector habitats. Despite this, there are currently no antiviral therapies or FDA-approved vaccines available to treat or prevent VEEV infection. The increased prevalence of such viruses provides opportunities for novel variants to evolve. Key therapeutic molecules that could be developed against viral pathogens are recombinant antibodies or antibody fragments, such as the variable heavy domain of heavy chain antibodies (V H Hs). Methods: In vitro selections offer a promising pathway for identification of therapeutic antibodies, here we explored isolation of V H Hs using phage and yeast display methodology with three antigen formats 1) recombinant E2, 2) linear peptides of E2, selected based on molecular dynamics analysis, and 3) UV inactivated virus. Results: Here we report four novel “human” V H Hs which bind to the VEEV E2 protein selected using different strategies that include both computational and biochemical design of suitable antigens and whole virus selections. These V H Hs have distinct complementarity-determining regions (CDRs). Multiple VHHs bind to the VEEV viral particles in ELISAs, and we report the peptide epitope recognized by these V H Hs. Discussion: Though non-neutralizing, these V H Hs bind to and sequester VEEV viral particles preventing infection, demonstrating the potential of these V H Hs to perform viral “sponging” which represents a novel therapeutic approach. The selection strategies we report may have applications to further antibody developments against other viruses.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1977

Microbe Detector

The AutoMicrobic System (AMS) represents years of intensive research and development by McDonnell Douglas Corp. that originated with a NASA study aimed at development of a fully automated microbial detection and identification system for spacecraft use. A urine specimen is placed into the system, where it is subjected to different freeze-dried microbe nutrients for the nine most common pathogens. An electro-optical scanner studies each specimen once an hour through a 4-to-13 hour cycle, operating automatically. Changes in cell growths on each culture are monitored by computer. The presence of pathogens is indicated when growth reaches a predetermined level. The system also enumerates the pathogens and specifies the type. Developed initially to handle urine testing, AMS soon is expected to allow analyses of blood, spinal fluid, and other body fluids. An additional capability under development is "susceptibility testing," or the determination of which microbe-killing agents-such as penicillin or other antibiotics-would be most effective in eliminating the pathogens. The whole process of detecting, identifying, and enumerating the pathogens and determining susceptibility is accomplished in less half the time required for the manual procedure. The AMS minimizes human error, reduces technician time , and increases laboratory output.

Source record↗
DOE OSTI2016

Pond Crash Forensics: Presumptive identification of pond crash agents by next generation sequencing in replicate raceway mass cultures of Nannochloropsis salina

Productivity of algal mass culture can be severely reduced by contaminating organisms. It is, therefore, important to identify contaminants, determine their effect on productivity and, ultimately, develop countermeasures against such contamination. In this paper, we utilized microbiome analysis by second-generation sequencing of small subunit rRNA genes to characterize the predator and pathogen burden of open raceway cultures of Nannochloropsis salina. Samples were analyzed from replicate raceways before and after crashes. In one culture cycle, we identified two algivorous species, the rotifer Brachionus and gastrotrich Chaetonotus, the presence of which may have contributed to the loss of algal biomass. In the second culture cycle, the raceways were treated with hypochlorite in an unsuccessful attempt to interdict the crash. Finally, our analyses were shown to be an effective strategy for the identification of the biological contaminants and the characterization of intervention strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

PKC-η-MARCKS Signaling Promotes Intracellular Survival of Unopsonized Burkholderia thailandensis

Pathogenic Burkholderia rely on host factors for efficient intracellular replication and are highly refractory to antibiotic treatment. To identify host genes that are required by Burkholderia spp. during infection, we performed a RNA interference (RNAi) screen of the human kinome and identified 35 host kinases that facilitated Burkholderia thailandensis intracellular survival in human monocytic THP-1 cells. We validated a selection of host kinases using imaging flow cytometry to assess efficiency of B. thailandensis survival in the host upon siRNA-mediated knockdown. We focused on the role of the novel protein kinase C isoform, PKC-η, in Burkholderia infection and characterized PKC-η/MARCKS signaling as a key event that promotes the survival of unopsonized B. thailandensis CDC2721121 within host cells. While infection of lung epithelial cells with unopsonized Gram-negative bacteria stimulated phosphorylation of Ser175/160 in the MARCKS effector domain, siRNA-mediated knockdown of PKC-η expression reduced the levels of phosphorylated MARCKS by >3-fold in response to infection with Bt CDC2721121. We compared the effect of the conventional PKC-α and novel PKC-η isoforms on the growth of B. thailandensis CDC2721121 within monocytic THP-1 cells and found that ≥75% knock-down of PRKCH transcript levels reduced intracellular bacterial load 100% more efficiently when compared to growth in cells siRNA-depleted of the classical PKC-α, suggesting that the PKC-η isoform can specifically mediate Burkholderia intracellular survival. Based on imaging studies of intracellular B. thailandensis , we found that PKC-η function stimulates phagocytic pathways that promote B. thailandensis escape into the cytoplasm leading to activation of autophagosome flux. As a result, identification of host kinases that are targeted by Burkholderia during infection provides valuable molecular insights in understanding Burkholderia pathogenesis, and ultimately, in designing effective host-targeted therapies against infectious disease caused by intracellular pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Identification and Classification of Fungal GPCR Gene Families

G protein-coupled receptors (GPCRs) are transmembrane proteins crucial for signal transduction in eukaryotes, responding to diverse extracellular signals. Researchers have found and systematically summarized 14 distinct types of GPCRs in fungi but their distribution among numerous fungal species remained largely unexamined. Additionally, three families of mammalian homologs (Rhodopsin, Glutamate, and Frizzled) have been found in previous studies, but they are not included in the systematic classification of fungal GPCRs. Our study establishes a unified classification of 17 GPCR classes in fungi, combining 14 fungal and 3 mammalian previously recognized groups, and classifies 28,294 GPCRs across 1357 fungal species, significantly expanding the scale of GPCRs in fungi and demonstrating their broader distribution. We found that mammalian homologs are notably more prevalent in Early Diverging Fungi (EDF), whereas the previous 14 classes are predominantly found in Ascomycota and Basidiomycota. The most abundant class detected in fungi was Pth11-like GPCRs, exclusively found in Pezizomycotina and involved in fungal pathogenicity. Our analysis suggested that Pezizomycotina ancestor possessed an extensive array of Pth11-like GPCRs, but over time, some species underwent considerable reductions in these GPCRs in conjunction with genome contractions. Utilizing a custom-built convolutional neural network (CNN) for the identification of fungal GPCRs, we identified several putative novel fungal GPCRs. Predicted interactions between these prospective new GPCRs and G-alpha proteins, as simulated by AlphaFold Multimer, provided additional support for their functional relevance. In conclusion, our work defines the first large-scale, unified classification of fungal GPCRs, reveals lineage-specific expansions and contractions, and uncovers previously unrecognized GPCR candidates with potential functional roles in fungal signaling.

G protein-coupled receptors↗
DOE OSTI2021

A k-mer based approach for classifying viruses without taxonomy identifies viral associations in human autism and plant microbiomes

Viruses are an underrepresented taxa in the study and identification of microbiome constituents; however, they play an essential role in health, microbiome regulation, and transfer of genetic material. Only a few thousand viruses have been isolated, sequenced, and assigned a taxonomy, which limits the ability to identify and quantify viruses in the microbiome. Additionally, the vast diversity of viruses represents a challenge for classification, not only in constructing a viral taxonomy, but also in identifying similarities between a virus’ genotype and its phenotype. However, the diversity of viral sequences can be leveraged to classify their sequences in metagenomic and metatranscriptomic samples, even if they do not have a taxonomy. To identify and quantify viruses in transcriptomic and genomic samples, we developed a dynamic programming algorithm for creating a classification tree out of 715,672 metagenome viruses. To create the classification tree, we clustered proportional similarity scores generated from the k-mer profiles of each of the metagenome viruses to create a database of metagenomic viruses. The resulting Kraken2 database of the metagenomic viruses can be found here: https://www.osti.gov/biblio/1615774 and is compatible with Kraken2. We then integrated the viral classification database with databases created with genomes from NCBI for use with ParaKraken (a parallelized version of Kraken provided in Supplemental Zip 1), a metagenomic/transcriptomic classifier. To illustrate the breadth of our utility for classifying metagenome viruses, we analyzed data from a plant metagenome study identifying genotypic and compartment specific differences between two Populus genotypes in three different compartments. We also identified a significant increase in abundance of eight viral sequences in post mortem brains in a human metatranscriptome study comparing Autism Spectrum Disorder patients and controls. We also show the potential accuracy for classifying viruses by utilizing both the JGI and NCBI viral databases to identify the uniqueness of viral sequences. Finally, we validate the accuracy of viral classification with NCBI databases containing viruses with taxonomy to identify pathogenic viruses in known COVID-19 and cassava brown streak virus infection samples. Our method represents the compulsory first step in better understanding the role of viruses in the microbiome by allowing for a more complete identification of sequences without taxonomy. Better classification of viruses will improve identifying associations between viruses and their hosts as well as viruses and other microbiome members. Despite the lack of taxonomy, this database of metagenomic viruses can be used with any tool that utilizes a taxonomy, such as Kraken, for accurate classification of viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Stenotrophomonas maltophilia differential gene expression in synthetic cystic fibrosis sputum reveals shared and cystic fibrosis strain-specific responses to the sputum environment.

Stenotrophomonas maltophilia is a Gram-negative opportunistic pathogen that can infect the lungs of people with cystic fibrosis (CF). The highly viscous mucus in the CF lung, expectorated as sputum, serves as the primary nutrient source for microbes colonizing this site and induces virulence-associated phenotypes and gene expression in several CF pathogens. Here, we characterized the transcriptional responses of three S. maltophilia strains during exposure to synthetic CF sputum media (SCFM2) to gain insight into how this organism interacts with the host in the CF lung. These efforts led to the identification of 881 transcripts differentially expressed by all three strains, many of which reflect the metabolic pathways used by S. maltophilia in sputum, as well as altered stress responses. The latter correlated with increased resistance to peroxide exposure after pre-growth in SCFM2 for two of the strains. We also compared the SCFM2 transcriptomes of two S. maltophilia CF isolates to that of the acute infection strain, S. maltophilia K279a, allowing us to identify CF isolate-specific signatures in differential gene expression. Expression of genes from the accessory genomes was also differentially altered in response to SCFM2. Finally, a number of biofilm-associated genes were differentially induced in SCFM2, particularly in K279a, which corresponded to increased aggregation and biofilm formation in this strain relative to both CF strains. Collectively, this work details the response of S. maltophilia to an environment that mimics important aspects of the CF lung, identifying potential survival strategies and metabolic pathways used by S. maltophilia during infections. Importance Stenotrophomonas maltophilia is an important infecting bacterium in the airways of people with cystic fibrosis (CF). However, compared to the other CF pathogens, S. maltophilia has been relatively understudied. The significance of our research is to provide insight into the global transcriptomic changes of S. maltophilia in response to a medium that was designed to mimic important aspects of the CF lung. This work allows us to understand the overall metabolic changes that occur when S. maltophilia encounters the CF lung, and generates a roadmap of candidate genes to test using in vitro and in vivo models of CF.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The essential effector SCRE1 in Ustilaginoidea virens suppresses rice immunity via a small peptide region

Summary The biotrophic fungal pathogen Ustilaginoidea virens causes rice false smut, a newly emerging plant disease that has become epidemic worldwide in recent years. The U. virens genome encodes many putative effector proteins that, based on the study of other pathosystems, could play an essential role in fungal virulence. However, few studies have been reported on virulence functions of individual U. virens effectors. Here, we report our identification and characterization of the secreted cysteine‐rich protein SCRE1, which is an essential virulence effector in U. virens . When SCRE1 was heterologously expressed in Magnaporthe oryzae , the protein was secreted and translocated into plant cells during infection. SCRE1 suppresses the immunity‐associated hypersensitive response in the nonhost plant Nicotiana benthamiana . Induced expression of SCRE1 in rice also inhibits pattern‐triggered immunity and enhances disease susceptibility to rice bacterial and fungal pathogens. The immunosuppressive activity is localized to a small peptide region that contains an important ‘cysteine‐proline‐alanine‐arginine‐serine’ motif. Furthermore, the scre1 knockout mutant generated using the CRISPR/Cas9 system is attenuated in U. virens virulence to rice, which is greatly complemented by the full‐length SCRE1 gene. Collectively, this study indicates that the effector SCRE1 is able to inhibit host immunity and is required for full virulence of U. virens .

Zhang, Nan↗
DOE OSTI2018

Impacts of environmental exposure on thermal and mycological characteristics of insulation wools

Highlights: • Insulation materials (IM) suffer expositions to weather on energy efficient buildings. • Induced exposure to weather of IM reveals differences in ATR-FTIR spectra. • Mycological analysis shows a significant effect of exposure condition on IM. • Mold species detected may induce human health risk and degradation of IM. • Thermal conductivity of IM according humidity of air may impact energy performance. - Abstract: Fieldwork was conducted on 138 energy efficient buildings, to check if building site practices induced exposure to weather of thermal insulation. In nearly 80% of cases, insulation was exposed to weather due to insufficient protection. Therefore insulating wools were exposed, divided into three parts (control, exposure under shelter, exposure to weather). After the exposure period these samples were submitted to thermal conductivity measurements and infrared spectroscopy. A numerical study was carried out to evaluate the influence of weather conditions on thermal performance. Identifications of molds were realized by direct cultures of each sample. Mycological analyses provided the most significant results, showing a significant effect of exposure condition, with possible consequences in human health (toxinogenic, allergenic or pathogenic species) and material properties (cellulolytic species). Infrared spectrometry also showed some changes in sensitivity to water. These results show the interest to study in more detail the variations in the sensitivity, to moisture and mold, of insulation material throughout its ageing on site, and the interactions with the practices of the building process.

36 MATERIALS SCIENCE↗
NASA NTRS2009

Human System Risk Management - Tools of our Trade

The risk of infectious disease to select individuals has historically been difficult to predict in either spaceflight or on Earth with health care efforts relying on broad-based prevention and post-infection treatment. Over the past 10 years, quantitative microbial risk assessment evaluations have evolved to formalize the assessment process and quantify the risk. This process of hazard identification, exposure assessment, dose-response assessment, and risk characterization has been applied by the water and food safety industries to address the public health impacts associated with the occurrence of and human exposure to pathogens in water and food for the development of preventive strategies for microbial disease. NASA is currently investigating the feasibility of using these techniques to better understand the risks to astronauts and refine their microbiological requirements. To assess these techniques, NASA began an evaluation of the potable water system on the International Space Station to determine how the microbial risk from water consumption during flight differed from terrestrial sources, such as municipal water systems. The ultimate goal of this work is to optimize microbial requirements which would minimize unnecessary cargo and use of crew time, while still protecting the health of the crew. Successful demonstration of this risk assessment framework with the water system holds the potential to maximize the use of available resources during spaceflight missions and facilitate investigations into the evaluation of other routes of infection, such as through the spaceflight foods system.

Ott, C. Mark↗