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NASA NTRS1976

Behavior of queues at signalized intersections in heavy traffic

This paper derives the asymptotic behavior of traffic queues at signalized intersections when the excess of departure capacity over arrivals approaches zero from above. The most interesting result is that the distribution of queue length approaches a negative exponential, with fewer restrictive assumptions than hitherto known. The main improvement results from more precise use of a combinatorial lemma of Spitzer, giving the maximum of the partial sums of a sequence of independent identically distributed random variables, plus some specific constructive probability calculations, many of them involving the Fourier transform. New results are presented on the probability that the queue be below a fixed bound and/or on the probability that the queue be empty. Applications to on-line estimators for real-time traffic control are suggested.

Posner, E. C.↗
NASA NTRS2001

Evidence for a role in growth and salt resistance of a plasma membrane H+-ATPase in the root endodermis

The plasma membrane of plant cells is energized by an electrochemical gradient produced by P-type H+-ATPases (proton pumps). These pumps are encoded by at least 12 genes in Arabidopsis. Here we provide evidence that isoform AHA4 contributes to solute transport through the root endodermis. AHA4 is expressed most strongly in the root endodermis and flowers, as suggested by promoter-GUS reporter assays. A disruption of this pump (aha4-1) was identified as a T-DNA insertion in the middle of the gene (after VFP(574)). Truncated aha4-1 transcripts accumulate to approximately 50% of the level observed for AHA4 mRNA in wild-type plants. Plants homozygous for aha4-1 (-/-) show a subtle reduction in root and shoot growth compared with wild-type plants when grown under normal conditions. However, a mutant phenotype is very clear in plants grown under salt stress (e.g., 75 or 110 mM NaCl). In leaves of mutant plants subjected to Na stress, the ratio of Na to K increased 4-5-fold. Interestingly, the aha4-1 mutation appears to be semidominant and was only partially complemented by the introduction of additional wild-type copies of AHA4. These results are consistent with the hypothesis that aha4-1 may produce a dominant negative protein or RNA that partially disrupts the activity of other pumps or functions in the root endodermal tissue, thereby compromising the function of this cell layer in controlling ion homeostasis and nutrient transport.

NASA Discipline Plant Biology↗
NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the respective standard approach. Of the methods tested, standard ComBat and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

GeneLab↗
NASA NTRSDate not supplied

Combining RNA-SEQ Datasets from NASA GENELAB: An Evaluation of Correction Methods

Background: Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. Methods: In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, the median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. Results: The results showed that the reference-based approach introduced several additional (and likely artificial) differentially expressed genes when compared with the respective standard approach. Conclusions: Of the methods tested, standard ComBat_seq and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

Finsam Samson↗
NASA NTRSDate not supplied

Does Collection Time Bias the Ecology of Cleanroom Air Samples?

Microbial monitoring of astromaterials collections has taken on increased importance with the return of biologically sensitive samples from the asteroids Ryugu and Bennu and the initiation of the Mars Sample Return Program. Terrestrial bacteria and fungi can alter the mineralogy and organic composition of our collections causing irreversible contamination of pristine samples and increasing the risk of false positives for life detection measurements. NASA has conducted routine microbial monitoring of its existing collections since 20181. Initial monitoring focused on surface samples collected with foam swabs. Although, airborne microbiology is often decoupled from surface microbiology in the built environment2 culture-based air sampling techniques like impactors were not compliant with existing contamination control requirements. Bringing organic rich media, gelatin or liquids into curation cleanrooms presents an unacceptable risk to pristine samples. In 2022 NASA purchased a materials complaint air sampler and began collecting air samples from the cleanrooms in addition to surface samples3. The new instrument uses an electret filter to collect samples that are suitable for cultivating organisms or for direct DNA sequencing. Preliminary DNA sequencing results appeared to indicate that longer sampling times biased the microbial community in favor of hearty, spore-forming bacteria3. We present the results of a study comparing overnight sampling (17 hours) to short (1 hour) sampling of unoccupied curation cleanrooms. The results will help us optimize our monitoring protocols and develop a more detailed inventory of the ecology of astromaterials curation cleanrooms. Methods: We analyzed 72 paired air samples from six different cleanrooms including the meteorite processing lab (ISO 7 equivalent, 16 samples), the lunar lab (ISO 6 equivalent, 10 samples), the stardust lab (ISO 5 equivalent 14 samples), the OSIRIS-REx lab (ISO 5 equivalent, 12 samples), the Hayabusa2 lab (ISO 5 equivalent, 14 samples), and the Genesis lab (ISO 4 equivalent, 6 samples). All the samples were collected with an InnovaPrep Bobcat air sampler operating at a sampling rate of 200 L/min. The sampler operates for 5 minutes out of every 20 minute period. Half of the samples were collected by filtering 3,000L (15 min. of active sampling) of air across an electret filter for one hour. The rest of the samples were collected by filtering approximately 51,000 L air across the filter overnight (~17 hours, 255 min. of active sampling). Cells were eluted from the filter using 6-7 ml of pressurized 0.15% tween 20 in PBS (phosphate buffered saline). This liquid was used to cultivate bacteria according to previously published methods1,4,5 and for DNA extraction and next generation sequencing. DNA was extracted with a Qiagen MagAttract PowerMicrobiome kit6. To identify bacteria and archaea, the 16S rRNA gene was amplified using Earth Microbiome primers for the V4 region 7. The amplified DNA was sequenced on an Illumina MiSeq using a V3 reagent kit. The resulting sequences were processed using DADA2 and QIIME2 as implemented on the EDGE bioinformatics platform8–10. Results: Only two of the 72 samples had no amplifiable DNA. Amplified DNA concentrations ranged from 2.67 – 0.272 ng/µl. The median concentration of amplified DNA for the 1 hour samples was 0.770 ± 0.368 ng/µl. The median concentration of amplified DNA for the overnight samples was 0.877 ± 0.434 ng/µl. On average the overnight samples had slightly more sequences (58,960 vs. 59,456) and ASV’s (amplicon sequence variants) (60 vs 64.5) than the one hour samples, but these differences are not statistically significant. The most abundant ASV in every sample mapped to the genus Cupravidus. ASV’s mapping to the genuses Bacillus, Schlegelella, Thermus, and Staphylococcus were also common. Discussion and Future Work: Alpha diversity statistics like Shannon Entropy and Faith Phylogenetic Diversity are used to describe the diversity of organisms in a single sample. If a longer sampling time was biasing the data, we would expect to see a change in these diversity statistics vs. sample time. However, we did not observe this in our data. The median Shannon entropy was slightly higher for the overnight samples (3.773 vs 3.611) as was the Faith Phylogenetic Diversity (4.042 vs 3.596), but both values were within a standard deviation of each other for the two sampling times (Fig. 1). It is unlikely, that the longer sampling time is introducing bias into our data. We do observe a significant decrease in diversity when comparing the air samples by lab. The Genesis lab (ISO 4 equivalent) has a lower median number of ASV’s (45.5) than the other labs (62). Median values for Shannon Entropy (3.717 vs. 3.430) and Faith Phylogenetic Diversity (3.796 vs. 3.548) are also lower for Genesis, but those values are with one standard deviation of each other for the different sampling times. This is consistent with previous culture-based results suggesting that the environment in cleanrooms tends to select for a core group of organisms capable of surviving under dry, low nutrient, conditions. The presence of the ASV’s mapping to Cupravidus and Thermus in our sequencing blanks and controls suggests that several of the most common organisms in our samples represent contaminants from the reagents used to perform the DNA extractions and sequencing. Further work is needed to identify these contaminants, remove them from our data and recalculate the diversity statistics. This is a systematic error. Therefore, we do not expect removing the sequencing contaminants to change our conclusions. Longer air sample collection times appear to result in slightly higher diversity and do not bias the results towards “hardy” bacteria like spore-formers. Based on these preliminary results we conclude that sampling at least 3,000 liters of air is sufficient to capture the microbial diversity of cleanrooms, and that air samples can also be collected overnight without negatively impacting diversity. These results allow us to be flexible when designing microbial monitoring plans so that they do not interfere with routine lab activity. References: 1. Regberg, A. B. et al. 49th Lunar and Planetary Science Conference (2018). 2. The United States Pharmacopeial Convention. USP General Chapter <1116> (2013). 3. Regberg, A. B., et al. 54th Lunar and Planetary Science Conference (2023). 4. Regberg, A. B. et al. 53rd Lunar and Planetary Science Conference ( 2022). 5. Davis, R. E.,et al. 50th Lunar and Planetary Science Conference (2019). 6. Qiagen. MagAttract® PowerMicrobiome® DNA/RNA EP Kit Handbook. (2018). 7. Walters, W. et al. mSystems 1, (2015). 8. Callahan, B. J. et al. Nat. Methods 13, 581–583 (2016). 9. Hall, M. & Beiko, R. G. Microbiome Analysis: Methods and Protocols113–129 (Springer, 2018). 10. Philipson, C. et al. Bio-Protoc. 7, e2622 (2017).

A. B. Regberg↗
NASA NTRS2004

Microbial monitoring of spacecraft and associated environments

Rapid microbial monitoring technologies are invaluable in assessing contamination of spacecraft and associated environments. Universal and widespread elements of microbial structure and chemistry are logical targets for assessing microbial burden. Several biomarkers such as ATP, LPS, and DNA (ribosomal or spore-specific), were targeted to quantify either total bioburden or specific types of microbial contamination. The findings of these assays were compared with conventional, culture-dependent methods. This review evaluates the applicability and efficacy of some of these methods in monitoring the microbial burden of spacecraft and associated environments. Samples were collected from the surfaces of spacecraft, from surfaces of assembly facilities, and from drinking water reservoirs aboard the International Space Station (ISS). Culture-dependent techniques found species of Bacillus to be dominant on these surfaces. In contrast, rapid, culture-independent techniques revealed the presence of many Gram-positive and Gram-negative microorganisms, as well as actinomycetes and fungi. These included both cultivable and noncultivable microbes, findings further confirmed by DNA-based microbial detection techniques. Although the ISS drinking water was devoid of cultivable microbes, molecular-based techniques retrieved DNA sequences of numerous opportunistic pathogens. Each of the methods tested in this study has its advantages, and by coupling two or more of these techniques even more reliable information as to microbial burden is rapidly obtained. Copyright 2004 Springer-Verlag.

Environmental Monitoring/methods↗
NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets such as sex or age of the model organism used. In the present study, NASA GeneLab-hosted RNAseq datasets from rodent liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC, to determine statistical differences between datasets before and after correction, Principal Component Analysis, to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the standard approach. Thus, the most robust standard correction will be implemented in the GeneLab Visualization 2.0 platform when datasets are combined.

GeneLab, RNA-seq, Batch Correction↗
NASA NTRS2003

Polyomavirus JCV excretion and genotype analysis in HIV-infected patients receiving highly active antiretroviral therapy

OBJECTIVE: To assess the frequency of shedding of polyomavirus JC virus (JCV) genotypes in urine of HIV-infected patients receiving highly active antiretroviral therapy (HAART). METHODS: Single samples of urine and blood were collected prospectively from 70 adult HIV-infected patients and 68 uninfected volunteers. Inclusion criteria for HIV-infected patients included an HIV RNA viral load < 1000 copies, CD4 cell count of 200-700 x 106 cells/l, and stable HAART regimen. PCR assays and sequence analysis were carried out using JCV-specific primers against different regions of the virus genome. RESULTS: JCV excretion in urine was more common in HIV-positive patients but not significantly different from that of the HIV-negative group [22/70 (31%) versus 13/68 (19%); P = 0.09]. HIV-positive patients lost the age-related pattern of JCV shedding (P = 0.13) displayed by uninfected subjects (P = 0.01). Among HIV-infected patients significant differences in JCV shedding were related to CD4 cell counts (P = 0.03). Sequence analysis of the JCV regulatory region from both HIV-infected patients and uninfected volunteers revealed all to be JCV archetypal strains. JCV genotypes 1 (36%) and 4 (36%) were the most common among HIV-infected patients, whereas type 2 (77%) was the most frequently detected among HIV-uninfected volunteers. CONCLUSION: These results suggest that JCV shedding is enhanced by modest depressions in immune function during HIV infection. JCV shedding occurred in younger HIV-positive persons than in the healthy controls. As the common types of JCV excreted varied among ethnic groups, JCV genotypes associated with progressive multifocal leukoencephalopathy may reflect demographics of those infected patient populations.

Non-NASA Center↗
NASA NTRS2014

Thrust Measurement of Dielectric Barrier Discharge (DBD) Plasma Actuators: New Anti-Thrust Hypothesis, Frequency Sweeps Methodology, Humidity and Enclosure Effects

We discuss thrust measurements of Dielectric Barrier Discharge (DBD) plasma actuators devices used for aerodynamic active flow control. After a review of our experience with conventional thrust measurement and significant non-repeatability of the results, we devised a suspended actuator test setup, and now present a methodology of thrust measurements with decreased uncertainty. The methodology consists of frequency scans at constant voltages. The procedure consists of increasing the frequency in a step-wise fashion from several Hz to the maximum frequency of several kHz, followed by frequency decrease back down to the start frequency of several Hz. This sequence is performed first at the highest voltage of interest, then repeated at lower voltages. The data in the descending frequency direction is more consistent and selected for reporting. Sample results show strong dependence of thrust on humidity which also affects the consistency and fluctuations of the measurements. We also observed negative values of thrust, or "anti-thrust", at low frequencies between 4 Hz and up to 64 Hz. The anti-thrust is proportional to the mean-squared voltage and is frequency independent. Departures from the parabolic anti-thrust curve are correlated with appearance of visible plasma discharges. We propose the anti-thrust hypothesis. It states that the measured thrust is a sum of plasma thrust and anti-thrust, and assumes that the anti-thrust exists at all frequencies and voltages. The anti-thrust depends on actuator geometry and materials and on the test installation. It enables the separation of the plasma thrust from the measured total thrust. This approach enables more meaningful comparisons between actuators at different installations and laboratories. The dependence on test installation was validated by surrounding the actuator with a grounded large-diameter metal sleeve. Strong dependence on humidity is also shown; the thrust significantly increased with decreasing humidity, e.g., 44 percent increase as relative humidity changed from 18 percent and dew point 33 degF to 50 percent and dew point of 57 degF.

Ashpis, David E.↗
NASA NTRS2014

Dielectric Barrier Discharge (DBD) Plasma Actuators Thrust-Measurement Methodology Incorporating New Anti-Thrust Hypothesis

We discuss thrust measurements of Dielectric Barrier Discharge (DBD) plasma actuators devices used for aerodynamic active flow control. After a review of our experience with conventional thrust measurement and significant non-repeatability of the results, we devised a suspended actuator test setup, and now present a methodology of thrust measurements with decreased uncertainty. The methodology consists of frequency scans at constant voltages. The procedure consists of increasing the frequency in a step-wise fashion from several Hz to the maximum frequency of several kHz, followed by frequency decrease back down to the start frequency of several Hz. This sequence is performed first at the highest voltage of interest, then repeated at lower voltages. The data in the descending frequency direction is more consistent and selected for reporting. Sample results show strong dependence of thrust on humidity which also affects the consistency and fluctuations of the measurements. We also observed negative values of thrust or "anti-thrust", at low frequencies between 4 Hz and up to 64 Hz. The anti-thrust is proportional to the mean-squared voltage and is frequency independent. Departures from the parabolic anti-thrust curve are correlated with appearance of visible plasma discharges. We propose the anti-thrust hypothesis. It states that the measured thrust is a sum of plasma thrust and anti-thrust, and assumes that the anti-thrust exists at all frequencies and voltages. The anti-thrust depends on actuator geometry and materials and on the test installation. It enables the separation of the plasma thrust from the measured total thrust. This approach enables more meaningful comparisons between actuators at different installations and laboratories. The dependence on test installation was validated by surrounding the actuator with a large diameter, grounded, metal sleeve.

Ashpis, David E.↗
NASA NTRS1974

Vectorcardiographic results from Skylab medical experiment M092: Lower body negative pressure

Vectorcardiograms were recorded via a modified Frank lead system from all crewmen of the three Skylab missions in conjuction with the Lower Body Negative Pressure - M092 Experiment. Data were analyzed by a specially developed computer program (VECTAN). Design of the test sequences allowed direct comparisons of supine resting, Earth based (reference) vectorcardiograms with those taken during lower body negative pressure stress and those obtained at rest in orbit, as well as combinations of these conditions. Results revealed several statistically significant space flight related changes; namely, increased testing and lower body negative pressure stressed heart rates, modestly increased PR interval and corrected QTC interval, and greatly increased P and QPS loop maximal amplitudes. In addition, orientation changes in the QRS maximum vector and the J-vector at rest in space seem quite consistent among crewmen and different from those caused by the application of lower body negative pressure. No clinical abnormalities were observed. Etiology of these findings is conjectured to be, at least in part, related to fluid mass shifts occurring in weightlessness and attendant alterations in cardiovascular dynamics and myocardial autonomic control mechanisms.

Hoffler, G. W.↗
NASA NTRSDate not supplied

Microbial Monitoring of New Cleanrooms Used to Curate Astrobiologically Relevant Asteroid Samples from Bennu and Ryugu

Introduction: NASA has constructed two new cleanrooms to house materials from the OSRIS-REx and Hayabusa2 missions to the asteroids Ryugu (162173) and Bennu (101955), respectively. In accordance with standard astromaterials curation practices, these cleanrooms will be monitored for particulate contamination and maintained to ISO 5 equivalent standards1. Since the samples in these collections are expected to contain prebiotic organic compounds that may help explain the origin of life on Earth, these labs will also be monitored for organic and biological contamination2. Samples from Ryugu arrived on Earth in December, 2020. After basic characterization in Japan, NASA received a subset of these samples at the astromaterials curation facility in Houston in December of 2021. OSIRIS-REx is expected to return samples in September, 2023. Here we present preliminary microbial monitoring results from monthly monitoring of these new labs and the connected microtomy and staging areas that support them, as they are being commissioned. We also compare these results to baseline values for other astromaterials curation labs. We will also briefly describe additional cleaning efforts employed to reduce the bioburden in these new cleanrooms. Methods: Microbial samples were collected from surfaces using a dry macrofoam swab (Puritan Brand 2518051PFRNDFD). Swabs were also opened in the lab but not touched to any surfaces to function as negative controls. Samples and controls were processed inside a class II biosafety cabinet to avoid inadvertent cross contamination. The swabs were suspended in 15 ml of PBS (Phosphate Buffered Saline) and vortexed for 20 seconds to remove cells from the swab surface. The PBS was used to inoculate Petri dishes filled with TSA (Tryptic Soy Agar), Blood Agar, or Reasoners 2 agar to check for microbial growth. Each plate was inoculated with 0.1 ml of PBS. The TSA and blood agar plates were incubated at 35˚C and the Reasoners 2 agar plates were incubated at 25˚C for seven days. Petri dishes filled with Potato dextrose agar, Saboraud dextrose agar, or Saboraud dextrose agar with 0.1 mg/ml of chloramphenicol, an antibiotic, were used to check for fungal growth. These plates were inoculated with 0.3 ml of PBS and incubated at 30˚C. The remaining PBS was frozen at -80 ˚C for DNA sequencing. After incubation, isolates were counted and reisolated for identification. Isolates were identified using the VITEK23 system or by sequencing a portion of the 16S rRNA gene for bacteria or the ribosomal internal transcribed spacer (ITS) for fungi. Sequencing was performed with an ABI 3500 Sanger sequencer. Results: During our initial sampling, six of the seven sites sampled (86%) displayed bacterial or fungal growth. Samples collected from the staging areas and microtomy labs are not included in this calculation since those areas are maintained at a lower ISO 7 equivalent cleanliness standard. A month later, only three of the seven sites (43%) displayed bacterial growth. No fungal growth was detected in the second sampling. Since new equipment had been introduced to the Hayabusa2 lab since the first round of sampling, an additional three sampling sites were included in the second round of sampling. None of these sites displayed microbial growth. These sites will be included in all future sampling efforts. Bacterial isolates have been identified from the following genera at multiple time points: Micrococcus, Staphylococcus, and Bacillus. Isolates from the genera: Microbacterium, Nocardioides, Methylocystis, and Microvirga were identified in the initial sampling, but were not present at later time points. Identification of fungal isolates is in progress. Results are summarized in Table 1. Discussion: The recovery rate or percentage of positive samples4 was initially 86%, which is higher than the median recovery rate for comparable ISO 5 equivalent curation labs like Stardust (33%), Hayabusa (33%), and Cosmic Dust (50%). However, after a month of operation, the recovery rate for these same sites decreased to 43%, which is similar to what we observe in comparable curation cleanrooms with no microbial control requirements. Adding in the new sampling sites further decreases the recovery rate to 30%. With the reduction in recovery rate, we also observed a decrease in microbial diversity. At the first time point, we observed at least 10 different bacterial species and at least two different fungi. This is a higher diversity than the median values for comparable ISO 5 equivalent labs (2-4 isolates per sampling event). After the second sampling, we observed at least 4 bacterial species and no fungi, which is more consistent with comparable labs. We expect the recovery rate and diversity in both labs to continue to decrease as routine operation continues. We will use ultrapure hydrogen peroxide to disinfect equipment and work areas prior to opening any sample containers. Most of the bacterial and fungal isolates were detected on samples from the cleanroom floors. This is consistent with baseline results from other curation labs. Organisms from the genera Bacillus, Staphylococcus, and Micrococcus that were repeatedly detected are common in cleanrooms and on human skin5,6. These organisms are generally thought to be introduced when people enter the cleanroom. Microbacterium, Nocardioides, and Microvirga have also previously been identified in astromaterials cleanrooms, but not as frequently as Bacillus, Staphylococcus, and Micrococcus. Methylocystis is a novel genus in the astromaterials cleanrooms, but it was identified with low accuracy (93% match in the sequenced region of the 16S rRNA gene) and further work is needed to confirm this identification. Microbacterium is a diverse genus with isolates identified from terrestrial and aquatic sediments. Some species of Microbacterium are capable of degrading complex organic compounds found in crude oil. The presence of these bacteria in the OSIRIS REx and Hayabusa2 cleanrooms should be closely monitored. Methylocystis is a genus of methanotrophic bacteria capable of oxidizing methane. If this identification proves to be correct and it is detected again, it should be closely monitored as well. Under nominal operating conditions, samples should not ever encounter the cleanroom floor or other high traffic areas. If we observe an increase in the bioburden in sensitive work areas that appears to be influenced by organism transfer from high traffic areas like the floors, we can employ additional hydrogen peroxide treatments to disinfect high traffic areas. Routine microbial monitoring of these labs will ensure that NASA’s astromaterials collections remain pristine and useful for scientific study. Table 1. Sampling Locations and Colony Counts Bacterial CFUa Fungal CFU Bacterial CFU Fungal CFU Lab - Location 11/2/2021 11/2/2021 12/13/2021 12/13/2021 H2b-Floor 4 8 1 0 H2-staging pass through 3 0 0 0 H2-microtomy pass through TNTCc 0 0 0 H2 Microscope 1 NA NA 0 0 H2 Microscope 2 NA NA 0 0 H2-Table NA NA 0 0 OREXd- microtomy pass through 0 0 6 0 OREX – Anteroom pass through 0 0 0 0 OREX – Floor 1 2 0 0 OREX Witness Foil Table 3 0 1 0 Staging-Floor 16 0 15 0 Microtomy-Floor 3 0 2 0 a: CFU = Colony Forming Unit b: H2 = Hayabusa2 Lab c: TNTC = too numerous to count d: OREX = OSIRIS-REx Lab References: 1. ISO 14644-1:2015 - Cleanrooms and associated controlled environments -- Part 1: Classification of air cleanliness by particle concentration. 37 (2015). 2. McCubbin, F. M. et al. Space Sci Rev 215, (2019). 3. Pincus, D. H. Encyclopedia of Rapid Microbiological Methods (2005). 4. The United States Pharmacopeial Convention. USP General Chapter <1116> 17, 784–794 (2013). 5. Sheraba, N. S., Yassin, A. S. & Amin, M. BMC Research Notes 3, 278 (2010). 6. Utescher, C. L. de A., Franzolin, M. R., Trabulsi, L. R. & Gambale, V. Brazilian Journal of Microbiology 38, 710–716 (2007).

A B Regberg↗
NASA NTRS2011

Verification of the Solar Dynamics Observatory High Gain Antenna Pointing Algorithm Using Flight Data

The Solar Dynamics Observatory (SDO) is a NASA spacecraft designed to study the Sun. It was launched on February 11, 2010 into a geosynchronous orbit, and uses a suite of attitude sensors and actuators to finely point the spacecraft at the Sun. SDO has three science instruments: the Atmospheric Imaging Assembly (AIA), the Helioseismic and Magnetic Imager (HMI), and the Extreme Ultraviolet Variability Experiment (EVE). SDO uses two High Gain Antennas (HGAs) to send science data to a dedicated ground station in White Sands, New Mexico. In order to meet the science data capture budget, the HGAs must be able to transmit data to the ground for a very large percentage of the time. Each HGA is a dual-axis antenna driven by stepper motors. Both antennas transmit data at all times, but only a single antenna is required in order to meet the transmission rate requirement. For portions of the year, one antenna or the other has an unobstructed view of the White Sands ground station. During other periods, however, the view from both antennas to the Earth is blocked for different portions of the day. During these times of blockage, the two HGAs take turns pointing to White Sands, with the other antenna pointing out to space. The HGAs handover White Sands transmission responsibilities to the unblocked antenna. There are two handover seasons per year, each lasting about 72 days, where the antennas hand off control every twelve hours. The non-tracking antenna slews back to the ground station by following a ground commanded trajectory and arrives approximately 5 minutes before the formerly tracking antenna slews away to point out into space. The SDO Attitude Control System (ACS) runs at 5 Hz, and the HGA Gimbal Control Electronics (GCE) run at 200 Hz. There are 40 opportunities for the gimbals to step each ACS cycle, with a hardware limitation of no more than one step every three GCE cycles. The ACS calculates the desired gimbal motion for tracking the ground station or for slewing, and sends the command to the GCE at 5 Hz. This command contains the number of gimbals steps for that ACS cycle, the direction of motion, the spacing of the steps, and the delay before taking the first step. The AIA and HMI instruments are sensitive to spacecraft jitter. Pre-flight analysis showed that jitter from the motion of the HGAs was a cause of concern. Three jitter mitigation techniques were developed to overcome the effects of jitter from different sources. The first method is the random step delay, which avoids gimbal steps hitting a cadence on a jitter-critical mode by pseudo-randomly delaying the first gimbal step in an ACS cycle. The second method of jitter mitigation is stagger stepping, which forbids the two antennas from taking steps during the same ACS cycle in order to avoid constructively adding jitter from two antennas. The third method is the inclusion of an instrument No Step Request (NSR), which allows the instruments to request a stoppage in gimbal stepping during the times when they are taking images. During the commissioning phase of the mission, a jitter test was performed onboard the spacecraft. Various sources of jitter, such as the reaction wheels, the High Gain Antenna motors, and the motion of the instrument filter wheels, were examined to determine the level of their effect on the instruments. During the HGA portion of the test, the jitter amplitudes from the single step of a gimbal were examined, as well as the amplitudes due to the execution of various gimbal rates. These jitter levels are compared with the gimbal jitter allocations for each instrument. Additionally, the jitter test provided insight into a readback delay that exists with the GCE. Pre-flight analysis suggested that gimbal steps scheduled to occur during the later portion of an ACS cycle would not be read during that cycle, resulting in a delay in the telemetered current gimbal position. Flight data from the jitter test confirmed this expectation. Analysis is presentehat shows the readback delay does not have a negative impact on gimbal control. The decision was made to consider implementing two of the jitter mitigation techniques on board the spacecraft: stagger stepping and the NSR. Flight data from two sets of handovers, one set without jitter mitigation and the other with mitigation enabled, were examined. The trajectory of the predicted handover was compared with the measured trajectory for the two cases, showing that tracking was not negatively impacted with the addition of the jitter mitigation techniques. Additionally, the individual gimbal steps were examined, and it was confirmed that the stagger stepping and NSRs worked as designed. An Image Quality Test was performed to determine the amount of cumulative jitter from the reaction wheels, HGAs, and instruments during various combinations of typical operations. In this paper, the flight results are examined from a test where the HGAs are following the path of a nominal handover with stagger stepping on and HMI NSRs enabled. In this case, the reaction wheels are moving at low speed and the instruments are taking pictures in their standard sequence. The flight data shows the level of jitter that the instruments see when their shutters are open. The HGA-induced jitter is well within the jitter requirement when the stagger step and NSR mitigation options are enabled. The SDO HGA pointing algorithm was designed to achieve nominal antenna pointing at the ground station, perform slews during handover season, and provide three HGA-induced jitter mitigation options without compromising pointing objectives. During the commissioning phase, flight data sets were collected to verify the HGA pointing algorithm and demonstrate its jitter mitigation capabilities.

Bourkland, Kristin L.↗
NASA NTRS2022

Final Report - Hypergravity Effects on Chromatin Conformation and Nuclear Structure in Cultured Cells using High-throughput Sequencing

The conformation of the human genome is known to play an important role in transcriptional control of gene expression. Our aim is to assess whether exposure of cultured human cardiomyocytes to hypergravity can induce changes in chromatin organization as assayed by Hi-C proximity ligation technique. Hi-C is used to analyze chromatin interactions by using formaldehyde to crosslink regions of chromatin that are in close proximity. The DNA is then fragmented using a restriction enzyme and ligated under dilute conditions to favor intramolecular ligation of cross-linked fragments. Finally, the DNA is sequenced, allowing reconstruction of genomic structure. iCell cardiomyocyte cultures will be exposed to 40 g via an engineered device (incu-fuge) that allows for the chemical fixation of cells on a spinning centrifuge. Additionally, we plan on using fluorescence microscopy to analyze the nuclear and actin cytoskeletal conformation of cardiomyocytes post hypergravity exposure. We hypothesize that chromatin will rearrange in hypergravity conditions, both rapidly due to direct mechanical forces, as well as over longer time frames due to changes to structures necessary for transcriptional responses such as the de novo formation of promoter-enhancer loops. A negative result–no change between 1 g and hypergravity conditions–would nevertheless be an important data point in our understanding of the rheology of the nucleus, and how cells and cellular structures respond to different gravity fields. The cellular physiology of hypergravity has clinical relevance for spaceflight, and can further inform our understanding of microgravity physiology.

chromatin↗
NASA NTRS1991

Some practical universal noiseless coding techniques, part 3, module PSl14,K+

The algorithmic definitions, performance characterizations, and application notes for a high-performance adaptive noiseless coding module are provided. Subsets of these algorithms are currently under development in custom very large scale integration (VLSI) at three NASA centers. The generality of coding algorithms recently reported is extended. The module incorporates a powerful adaptive noiseless coder for Standard Data Sources (i.e., sources whose symbols can be represented by uncorrelated non-negative integers, where smaller integers are more likely than the larger ones). Coders can be specified to provide performance close to the data entropy over any desired dynamic range (of entropy) above 0.75 bit/sample. This is accomplished by adaptively choosing the best of many efficient variable-length coding options to use on each short block of data (e.g., 16 samples) All code options used for entropies above 1.5 bits/sample are 'Huffman Equivalent', but they require no table lookups to implement. The coding can be performed directly on data that have been preprocessed to exhibit the characteristics of a standard source. Alternatively, a built-in predictive preprocessor can be used where applicable. This built-in preprocessor includes the familiar 1-D predictor followed by a function that maps the prediction error sequences into the desired standard form. Additionally, an external prediction can be substituted if desired. A broad range of issues dealing with the interface between the coding module and the data systems it might serve are further addressed. These issues include: multidimensional prediction, archival access, sensor noise, rate control, code rate improvements outside the module, and the optimality of certain internal code options.

Rice, Robert F.↗
NASA NTRS2006

NASA Tech Briefs, November 2006

Topics include: Simulator for Testing Spacecraft Separation Devices; Apparatus for Hot Impact Testing of Material Specimens; Instrument for Aircraft-Icing and Cloud-Physics Measurements; Advances in Measurement of Skin Friction in Airflow; Improved Apparatus for Testing Monoball Bearings; High-Speed Laser Scanner Maps a Surface in Three Dimensions; Electro-Optical Imaging Fourier-Transform Spectrometer; Infrared Instrument for Detecting Hydrogen Fires; Modified Coaxial Probe Feeds for Layered Antennas; Detecting Negative Obstacles by Use of Radar; Cryogenic Pound Circuits for Cryogenic Sapphire Oscillators; PixelLearn; New Software for Predicting Charging of Spacecraft; Conversion Between Osculating and Mean Orbital Elements; Generating a 2D Representation of a Complex Data Structure; Making Activated Carbon by Wet Pressurized Pyrolysis; Composite Solid Electrolyte Containing Li+- Conducting Fibers; Electrically Conductive Anodized Aluminum Surfaces; Rapid-Chill Cryogenic Coaxial Direct-Acting Solenoid Valve; Variable-Tension-Cord Suspension/Vibration- Isolation System; Techniques for Connecting Superconducting Thin Films; Versatile Friction Stir Welding/Friction Plug Welding System; Thermal Spore Exposure Vessels; Enumerating Spore-Forming Bacteria Airborne with Particles; Miniature Oxidizer Ionizer for a Fuel Cell; Miniature Ion-Array Spectrometer; Promoted-Combustion Chamber with Induction Heating Coil; Miniature Ion-Mobility Spectrometer; Mixed-Salt/Ester Electrolytes for Low-Temperature Li+ Cells; Miniature Free-Space Electrostatic Ion Thrusters; Miniature Bipolar Electrostatic Ion Thruster; Holographic Plossl Retroreflectors; Miniature Electrostatic Ion Thruster With Magnet; Using Apex To Construct CPM-GOMS Models; Sequence Detection for PPM Optical Communication With ISI; Algorithm for Rapid Searching Among Star-Catalog Entries; Expectation-Based Control of Noise and Chaos; Radio Heating of Lunar Soil to Release Gases; Using Electrostriction to Manipulate Ullage in Microgravity; Equations for Scoring Rules When Data Are Missing; Insulating Material for Next-Generation Spacecraft; and Pseudorandom Switching for Adding Radar to the AFF Sensor.

Source record↗
NASA NTRS2001

Ecological physiology of Synechococcus sp. strain SH-94-5, a naturally occurring cyanobacterium deficient in nitrate assimilation

Synechococcus sp. strain SH-94-5 is a nitrate assimilation-deficient cyanobacterium which was isolated from an ammonium-replete hot spring in central Oregon. While this clone could grow on ammonium and some forms of organic nitrogen as sole nitrogen sources, it could not grow on either nitrate or nitrite, even under conditions favoring passive diffusion. It was determined that this clone does not express functional nitrate reductase or nitrite reductase and that the lack of activity of either enzyme is not due to inactivation of the cyanobacterial nitrogen control protein NtcA. A few other naturally occurring cyanobacterial strains are also nitrate assimilation deficient, and phylogenetic analyses indicated that the ability to utilize nitrate has been independently lost at least four times during the evolutionary history of the cyanobacteria. This phenotype is associated with the presence of environmental ammonium, a negative regulator of nitrate assimilation gene expression, which may indicate that natural selection to maintain functional copies of nitrate assimilation genes has been relaxed in these habitats. These results suggest how the evolutionary fates of conditionally expressed genes might differ between environments and thereby effect ecological divergence and biogeographical structure in the microbial world.

Nitrates/metabolism↗
NASA NTRSDate not supplied

Transcriptomic Changes in Peripheral Blood Mononuclear Cells of International Space Station Crewmembers

In space, living organisms are exposed to numerous stress factors including microgravity and space radiation. For humans, these harmful environmental factors have been known to cause negative health impacts such as immune dysfunction. Understanding the mechanisms by which spaceflight impacts human health at the molecular level is critical not only for accurately assessing the risks associated with spaceflight, but also for developing effective countermeasures. This study is part of the Functional Immune Project, intended to determine alterations in crewmembers` immunobiology before, during, and after spaceflight. For this project, blood samples were collected from International Space Station (ISS) crewmembers at the following time points: i) at two pre-flight time points of 180 days (L180) and 45 days (L45) before launch. ii) During flight, blood was drawn at approximately the midpoint (mid-flight, MF) of the mission, and shortly before egress from the ISS (late-flight, LF). iii) Post-flight blood samples were collected within 24 hrs (R0), 30 days (R30) and 90 days (R90) after landing. For each crewmember, blood was also drawn from a matching test subject on the ground at the corresponding time point. For both the ISS crewmembers and the ground control subjects, total RNA was isolated from peripheral blood mononuclear cells (PBMC) and mRNA was analysed using next generation RNA-sequencing (NGS). Differentially expressed genes were determined by performing contrast analysis. Using the ground control subjects of all of the time points combined as a control, a number of dysregulated genes were identified in astronauts at MF, LF and R0, including downregulations of SMAD7 and CDKN1A at MF and LF. Some of the genes such as SERPINE1 and VEGFA were downregulated at MF and LF, but upregulated at R0, while others such as NKG7 were down regulated at all of the 3 time points. Pathway analysis of these differentially expressed genes indicated that the NF-κB pathway was chronically activated in space. Analysis of the consequent diseases suggested potential associations with not only immune dysfunction, but also other health risks including osteoarthritis, cardiac hypertrophy and neuroinflammation.

Maria Moreno-Villanueva↗