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NASA NTRS2019

MODIS Aqua Reflective Solar Bands Calibration for NASA's R2018 Ocean Color Products

Remote sensing ocean color products have stringent requirements on radiometric calibration stability. To address a calibration deficiency in MODIS Aqua in recent years, the NASA Ocean Biological Processing Group (OBPG) developed a new calibration for the reflective solar bands. Prior to the reprocessing of NASA's ocean color products for 2018 (R2018), the OBPG MODIS products had been based on calibration provided by the MODIS Calibration Support Team (MCST). Several modifications were made to the MCST calibration approach to improve the calibration accuracy for ocean color products. These include: 1) apply 936nm detector normalization to solar diffuser stability monitor (SDSM) data to reduce coherent noise; 2) modeling solar diffuser (SD) degradation wavelength dependency to determine SD degradation in near-infrared and shortwave infrared wavelength; 3) detector gains are computed using SD screen-closed data to better match ocean radiance levels in all bands; 4) a simple atmospheric correction is performed to reduce bidirectional reflectance distribution function (BRDF) effects in desert trends; 5) modulated relative spectral response (RSR) impact on ocean data is estimated and used to adjust the calibration coefficients. 6) smoothing is used to characterize the temporal change in calibration, and response versus scan angle (RVS) changes are characterized using 2nd order polynomials to improve spatial/temporal calibration stability. Relative to the previous R2014 ocean color products, the R2018 calibration removed the suspect late-mission global trends in blue-band water-leaving reflectance, and some anomalously large short-term variability (spikes) in the temporal trend of chlorophyll concentration. This paper will describe the OBPG calibration with a focus on the differences between the MCST and OBPG approaches.

calibration↗

NASA NTRSDate not supplied

TPSAS-NF1676L-11084-DND

The solar radiation must be considered as the primary factor when we study the climatic system because it provides almost all energy that drives the climatic system and most atmospheric phenomena. The solar radiation at the TOA is partially transferred, transformed into other forms of energy that are eventually dissipated by the general circulation of the atmosphere and oceans, and partially used in chemical and biological processes. The absorption of solar energy in the atmosphere (Acol) plays a key role in the climate system, not only because it affects the amount of solar energy absorbed by the Earth system, but also because it changes the vertical distribution of absorbed energy, which in turn impacts surface evaporation, atmospheric convection and precipitation. To investigate Acol, we have collected the collocated satellite-surface observations over the 35 selected BSRN surface sites during the period 2000-2004. The surface radiation budgets are averaged from the BSRN Shortwave (SW) observations over a 1-hour interval centered at the time of the NASA Terra and Aqua satellites overpass, and the TOA radiation budgets are averaged from the closest FOV satellite data to the BSRN stations. Then the atmospheric column SW absorption will be inferred from the satellite TOA albedo and BSRN surface absorption (through the estimated surface albedo). Monthly means of Acol, TOA albedo, and surface absorption have been calculated under both clear- and all-sky conditions over the 35 selected BSRN sites which represent different climate regimes. To evaluate the GCM simulations, we have collected the ECHAM5-HAM simulated surface, TOA and atmospheric radiation budgets by researchers at ETH Zurich and compared those simulations with observations. The preliminary comparisons have shown that the ECHAM5 simulated clear-sky surface absorption, TOA albedo, and ACOL agree very well (1-3%) with observations. Under all-sky conditions, they have strong correlations with CERES-derived cloud fraction. The simulated surface absorption is lower and TOA albedo is higher than those under clear skies, but ACOL does not increase too much. However, there are relatively large differences over some regions and months. A further study is needed.

X. Dong↗

NASA NTRS2019

Improvements in the on-orbit response versus scan-angle characterization for the MODIS ocean color bands

On-orbit characterization of the response versus scan-angle (RVS) is one of the most challenging aspects of the reflective solar band (RSB) calibration for the MODIS instruments onboard the Terra and Aqua spacecraft. The degradation of the solar diffuser, together with the lack of onboard calibrators (OBCs) to cover additional scan angles, other than the one for the lunar observations, has resulted in the use of Earth view responses from the pseudo-invariant desert sites to track the on-orbit RVS changes. This approach has been implemented in Collection 6 (C6) and C6.1 for bands 1-4, 8 and 9 of both instruments and also band 10 of Terra MODIS. As the missions continue to operate over a decade beyond their designed life and the instrument optics continue to degrade, it is expected that the OBC based RVS currently applied to other bands, specifically the high-gain ocean bands, will be inadequate to maintain the long-term calibration stability. An interband calibration approach is formulated and implemented in this paper. The proposed approach relies on the use of a spectrally matching stable reference band to evaluate the long-term calibration stability of the high-gain ocean bands that typically saturate while viewing the selected calibration deserts. Results from this approach indicate a noticeable drift for Terra MODIS bands 11 and 12 whereas the Aqua bands continue to show excellent temporal stability. These results are consistent with the corrections derived by the NASA Ocean Biology Processing Group (OBPG) and are expected to have minimum impacts on the downstream science products.

MODIS↗

NASA NTRS2019

The NASA OBPG 2020 On-Orbit Calibration of SNPP VIIRS for Ocean Color Applications

The NASA Ocean Biology Processing Group (OBPG) has continued monitoring the SNPP VIIRS on-orbit calibration for bands M1-M11 over its mission to optimize the calibration for ocean color applications. The OBPG has recently implemented several changes to the calibration scheme: using solar-derived f-factors to detrend the lunar observations; using long-term exponentials of time as basis vectors (along with libration angles) for radiometric fits to any resulting lunar temporal drifts; deriving gain adjustments to the solar f-factors from these exponentials; and deriving gain adjustments due to modulated RSRs outside of the solar/lunar calibration using TOA reference spectra. These calibration changes minimize the impact of uncertainties in any one component of the calibration on the derived f-factors. The final f-factors incorporate VIIRS solar diffuser measurements, h-factor BRDF corrections, lunar-derived gains, and modulated RSR gains. The combined BRDF corrections, lunar gain adjustments, and mRSR gain adjustments define effective h-factors for each band. The improvements in the on-orbit calibration are validated by evaluation of globally-derived anomaly plots of remote sensing reflectance for the ocean color bands. The ultimate goal of the OBPG calibration effort is incorporation of a consistent SNPP VIIRS ocean color data set into the NASA multi-mission ocean color climate data record.

VIIRS↗

NASA NTRS2021

Identifying Molecules as Biosignatures with Assembly Theory and Mass Spectrometry

The search for evidence of life elsewhere in the universe is hard because it is not obvious what signatures are unique to life. Here we postulate that complex molecules found in high abundance are universal biosignatures as they cannot form by chance. To explore this, we developed the first intrinsic measure of molecular complexity that can be experimentally determined, and this is based upon a new approach called assembly theory which gives the molecular assembly number (MA) of a given molecule. MA allows us to compare the intrinsic complexity of molecules using the minimum number of steps required to construct the molecular graph starting from basic objects, and a probabilistic model shows how the probability of any given molecule forming randomly drops dramatically as its MA increases. To map chemical space, we calculated the MA of ca. 2.5 million compounds, and collected data which showed the complexity of a molecule can be experimentally determined by using three independent techniques including infra-red spectroscopy, nuclear magnetic resonance, and by fragmentation in a mass spectrometer, and this data has an excellent corelation with the values predicted from our assembly theory. We then set out to see if this approach could allow us to identify molecular biosignatures with a set of diverse samples from around the world, outer space, and the laboratory including prebiotic soups. The results show that there is a non-living to living threshold in MA complexity and the higher the MA for a given molecule, the more likely that it had to be produced by a biological process. This work demonstrates it is possible to use this approach to build a life detection instrument that could be deployed on missions to extra-terrestrial locations to detect biosignatures, map the extent of life on Earth, and be used as a molecular complexity scale to quantify the constraints needed to direct prebiotically plausible processes in the laboratory. Such an approach is vital if we are going to find new life elsewhere in the universe or create de-novo life in the lab.

Stuart M Marshall↗

NASA NTRS2021

Integrating continuous atmospheric boundary layer and tower-based flux measurements to advance understanding of land-atmosphere interactions

The atmospheric boundary layer mediates the exchange of energy, matter, and momentum between the land surface and the free troposphere, integrating a range of physical, chemical, and biological processes and is defined as the lowest layer of the atmosphere (ranging from a few meters to 3 km). In this review, we investigate how continuous, automated observations of the atmospheric boundary layer can enhance the scientific value of co-located eddy covariance measurements of land-atmosphere fluxes of carbon, water, and energy, as are being made at FLUXNET sites worldwide. We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics and feedbacks at flux tower sites, (2) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous and mountainous terrain, and quality control of eddy covariance flux measurements, (3) to support regional-scale modeling and upscaling of surface fluxes to continental scales, and (4) to quantify land-atmosphere coupling and validate its representation in Earth system models. Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites, and supporting the sharing of these data to tower networks, would allow the Earth science community to address new emerging research questions, better interpret ongoing flux tower measurements, and would present novel opportunities for collaborations between FLUXNET scientists and atmospheric and remote sensing scientists.

Manuel Helbig↗

NASA NTRS2021

Interrelationships of Sea Surface Salinity, Chlorophyll-α Concentration, and Sea Surface Temperature near the Antarctic Ice Edge

Satellite data can now provide a coherent picture of sea surface salinity (SSS), chlorophyll-α concentration (Chlα), sea surface temperature (SST), and sea ice cover across the Southern Ocean. The availability of these data at the basin scale enables novel insight into the physical and biological processes in an area that has historically been difficult to gather in situ data from. The analysis shows large regional and interannual variability of these parameters but also strong coherence across the Southern Ocean. The covariability of the parameters near the marginal ice zone shows a generally negative relationship between SSS and Chlα (r = −0.87). This may in part be attributed to the large seasonality of the variables, but analysis of data within the spring period (from November to December) shows similarly high correlation (r = −0.81). This is the first time that a large-scale robust connection between low salinity and high phytoplankton concentration during ice melt period has been quantified. Chlorophyll-α concentration is also well correlated with SST (r = 0.79) providing a potential indicator of the strength of the temperature limitation on primary productivity in the region. The observed correlation also varied regionally due to differences in ice melt patterns during spring and summer. Overall, this study provides new insights into the physical characteristics of the Southern Ocean as observed from space. In a continually warming and freshening Southern Ocean, the relationships observed here provide a key data source for testing ocean biogeochemical models and assessing the effect of sea ice–ocean processes on primary production.

Cynthia Garcia-Eidell↗

NASA NTRSDate not supplied

Effects of Simulated Microgravity and LINC-Complex on Chromosome 8 of Human Mammary Cells

Previously, human breast epithelial cells were studied under simulated microgravity to determine the role of the LINC-complex in maintaining nuclear morphology and gene expression. Data from that study was used in this project to understand how the LINC-complex influences gene expression at chromosome 8 under simulated microgravity. Differentially expressed genes found in clusters typically indicate a molecular relationship amongst them. Visual and data analyses (GO, pathways) identified 51 genes within clusters on chromosome 8 across various simulated microgravity conditions that did not share any molecular relationship. Additional results also determined that cells with a disrupted LINC-complex experienced more differential gene expression than the control, and that extended periods of simulated microgravity exacerbated differential gene expression in chromosome 8 of LINC-disrupted cells. These results suggest that the stressful simulated microgravity environment coupled with disrupted biological processes, such as in the case of the LINC-complex, can increase differential gene expression in chromosomes. Future studies where additional analyses are performed to further analyze gene expression of clusters under simulated microgravity could potentially elucidate the molecular relationship amongst affected genes.

Simulated microgravity↗

NASA NTRS2021

Customized Science Carrier Modules and Accessories Developed for Microgravity Simulation Devices

Because the access to the true weightless environment of the ISS and other Low Earth Orbit (LEO) vehicles is limited and cost prohibitive, the need for ground-based microgravity simulation analogs to bridge the gravity continuum gap between 1g gravity and costly space flight studies with true weightlessness was realized. As such, the Microgravity Simulation Support Facility (MSSF) was established at NASA John F. Kennedy Space Center (KSC) to fulfill the need of the scientific community. Our facility provides the US science community with a focal point in the field of gravitational research by granting access to an array of two-dimensional(2D) and three-dimensional (3D)clinostats, and Random Positioning Machine (RPM) platforms developed by teams throughout the world. The availability of these capabilities will allow further understanding the role of altered gravity vectors from “functional weightlessness”, partial gravity conditions (1 x 10-3to 0.9g, and Moon and Mars ‘g vectors), to hypergravity (up to3g) on biological processes. We have designed and 3D printed a variety of specialized attachments(and associated “static control” hardware)to allow researchers to mount their samples onto these microgravity simulation devices to meet their unique science requirements. A summary of each attachment module will be presented below. Note: All software or code information should be requested to the author Ye Zhang, Kennedy Space Center ye.zhang-1@nasa.gov

Ye Zhang↗

NASA NTRSDate not supplied

The Sufficient Component Cause Model Explaining Low-Dose Radiobiology through an Epidemiologic Lens

One of the major challenges in understanding space radiation-induced carcinogenesis is the uncertainty from translating radiobiological research in cellular and animal models to humans, especially at doses below 100 mSv. Biological studies have shown a host of potential outcomes at low doses in animal and cellular models. The existence of non-targeted effects as bystander and abscopal effects is well-documented from clinical research and basic science1,2,3. While some studies have shown increased effects at low doses, others have shown evidence of hormetic bystander effects, where radiation exposure may be beneficial4,5,6. Despite these varied and diverse findings, epidemiologic studies largely support the linear-no threshold (LNT) assumption used by radiation protection guidance7,8. Translational animal-to-human models have predominantly considered ratio values such as the relative biological effectiveness (RBE) and dose and dose-rate effectiveness factor (DDREF) that rely on the assumption of LNT rather than implementing specific dose-response shapes in the low-dose region, and translational cell-to-human models are uncommon. The sufficient component cause model presents an opportunity to examine biological findings at low doses from an epidemiological lens9. In this model, exposures “sufficient” to cause an outcome of interest are presented in pie charts, such that when all slices of a pie chart are fulfilled, the outcome will occur. Multiple pie charts may exist for a single outcome, illustrating individual differences9. In 1988,Greenland and Poole adapted the sufficient component cause model to incorporate interaction with other exposures (such as genetics or lifestyle factors)10. They show that a range of biological processes are possible in a population, but that an epidemiologic study will only reveal the mean outcome from the population at large10,11. Using this construct, the multiple outcomes presented in radiobiological models to date can be explained in the context of epidemiologic studies. This presentation aims to demonstrate a causal framework that can integrate radiobiological and epidemiological models to date. It is intended as a conversation starter to spur future research.

C M Milder↗

NASA NTRSDate not supplied

How Discipline-Oriented DAACs Collaborate to Support Interdisciplinary Earth Science

The Earth system is made of multiple complex subsystems. While scientists tend to specialize in single subsystems or even portions of a subsystem, to fully understand the physical, chemical and biological processes occurring on the Earth, we must understand how these systems interact. Thus, scientists need to be able to expand beyond their chosen field and collaborate across disciplines. The NASA Earth Observing System Data and Information System (EOSDIS) is focusing on new capabilities to make interdisciplinary science easier. The EOSDIS DAACS are responsible for archiving and distributing NASA’s rapidly growing collection of satellite, airborne and field data. Like the scientists they serve, the DAACs are discipline oriented. This has many advantages. Scientists are able to interact with experts on data in their domain and receive data appropriate for their research. However, discipline-oriented services may be confusing to cross-disciplinary users who may not know how to get started. Fortunately, collaboration across scientific communities is a specialty of the DAACs who support interdisciplinary users with a collaborative culture and technology that empowers the open sharing of data, information, and knowledge within the scientific community and the wider public to accelerate scientific research and understanding. This presentation will discuss the capabilities of a discipline-oriented approach to support future Earth science goals including those of Open Science and cross-disciplinary collaboration.

Sara Lubkin↗

NASA NTRSDate not supplied

LOW-COST MARS IN-SITU ASTROBIOLOGY MEASUREMENTS AND STRATEGY.

Identifying evidence of Martian life would revolutionize our understanding of biological processes and predictions about the likelihood of life elsewhere. Of all Solar System bodies, Mars remains a primary life-detection target because conditions during its first 500 million years resembled those on Earth when early life emerged [1]. The search for life on Mars should include identifying preserved remains of ancient life from this more habitable epoch in Martian history relative to today, as well as searching for evidence of potential modern survivors that could have found refuge in locations with available liquid water and protection from the harsh surface environment [2]

M B Wilhelm↗

NASA NTRSDate not supplied

The Potential Outcome Model: Explaining Low-Dose Radiobiology through an Epidemiologic Lens

One of the major challenges in understanding space radiation-induced carcinogenesis is the uncertainty from translating radiobiological research in cellular and animal models to humans, especially at doses below 100 mSv. Biological studies have shown a host of potential outcomes at lowdoses in animal and cellular models. The existence of non-targeted effects as bystander and abscopal effects is well-documented from clinical research and basic science1,2,3. While some studies have shown increased effects at low doses, others have shown evidence of hormetic bystander effects, where radiation exposure may be beneficial4,5,6. Despite these varied and diverse findings, epidemiologic studies largely support the linear-no threshold (LNT) assumption used by radiation protection guidance7,8. Translational animal-to-human models have predominantly considered ratio values such as the relative biological effectiveness (RBE) and dose and dose-rate effectiveness factor (DDREF) that rely on the assumption of LNT rather than implementing specific dose-response shapes in the low-dose region, and translational cell-to-human models are uncommon. The sufficient component cause model presents an opportunity to examine biological findings at low doses from an epidemiological lens9. In this model, exposures “sufficient” to cause an outcome of interest are presented in pie charts, such that when all slices of a pie chart are fulfilled, the outcome will occur. Multiple pie charts may exist for a single outcome, illustrating individual differences9. In 1988,Greenland and Poole adapted the sufficient component cause model to incorporate interaction with other exposures (such as genetics or lifestyle factors)10. They show that a range of biological processes are possible in a population, but that an epidemiologic study will only reveal the mean outcome from the population at large10,11. Using this construct, the multiple outcomes presented in radiobiological models to date can be explained in the context of epidemiologic studies. This presentation aims to demonstrate a causal framework that can integrate radiobiological and epidemiological models to date. It is intended as a conversation starter to spur future research.

C M Milder↗

NASA NTRSDate not supplied

Investigation into Space Effects on Biofilm Growth Using Simulated Microgravity

Bacterial growth in liquid media while under microgravity conditions is not well understood. Trends such as a shortened lag phase, longer log phase, slower growth rate, and a higher final population concentration have been noted but the underlying cause remains unclear. Ground-based spaceflight analogs, or simulated microgravity devices, are often employed to achieve different attributes of weightlessness to study effects on bacterial growth. Though these technologies could isolate gravity’s role in various biological processes, they cannot replicate all its effects and underlying mechanisms. Hence, results could be misleading even if they are similar to spaceflight. At the single cell level, it is predicted that bacteria are less gravity-sensitive than larger species. The effects on their immediate environment, including the cell settlement and slower mass transfer of nutrients, might help explain the trends seen in liquid media microgravity studies. Therefore, experimental design factors must be carefully considered when selecting a simulated microgravity device for proper underlying mechanisms and interpretation of results. To verify if the simulated microgravity devices simulate the relevant microgravity conditions for bacterial growth, including the changes in cell settlement and mass transfer of nutrients, a high aspect ratio vessel (HARV) was used with dyes of different density in various simulated microgravity setups. The results will help inform the selection of the proper simulated microgravity device as well as interpretation of subsequent biofilm growth results.

Angie M. Diaz↗

NASA NTRS2021

Impact of Recent Climate Extremes on Mosquito-borne Disease Transmission in Kenya

Climate change and variability influence temperature and rainfall, which impact vector abundance and the dynamics of vector-borne disease transmission. Climate change is projected to increase the frequency and intensity of extreme climate events. Mosquito-borne diseases, such as dengue fever, are primarily transmitted by Aedes aegypti mosquitoes. Freshwater availability and temperature affect dengue vector populations via a variety of biological processes and thus influence the ability of mosquitoes to effectively transmit disease. However, the effect of droughts, floods, heat waves, and cold waves is not well understood. Using vector, climate, and dengue disease data collected between 2013 and 2019 in Kenya, this retrospective cohort study aims to elucidate the impact of extreme rainfall and temperature on mosquito abundance and the risk of arboviral infections. To define extreme periods of rainfall and land surface temperature (LST), we calculated monthly anomalies as deviations from long-term means (1983–2019 for rainfall, 2000–2019 for LST) across four study locations in Kenya. We classified extreme climate events as the upper and lower 10% of these calculated LST or rainfall deviations. Monthly Ae. aegypti abundance was recorded in Kenya using four trapping methods. Blood samples were also collected from children with febrile illness presenting to four field sites and tested for dengue virus using an IgG enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR). We found that mosquito eggs and adults were significantly more abundant one month following an abnormally wet month. The relationship between mosquito abundance and dengue risk follows a non-linear association. Our findings suggest that early warnings and targeted interventions during periods of abnormal rainfall and temperature, especially flooding, can potentially contribute to reductions in risk of viral transmission

Aedes aegypti mosquitoes↗

NASA NTRSDate not supplied

Translational Line of Sight: a multi-omics longitudinal study of the murine retinal response to spaceflight hazard analogs

The space environment includes unique hazards like radiation and microgravity which adversely affect physiology and behavior of humans and rodent models. To better characterize the retinal response to spaceflight, we assessed a multi-omics NASA GeneLab dataset where 6-month-old female mice were gamma irradiated and/or hindlimb unloaded for 21 days followed by whole transcriptome shotgun sequencing (RNA-Seq) and reduced representation bisulfite sequencing (RRBS) of retina samples collected at 7 days, 1 month or 4 months post-exposure. We compared time-matched epigenomic and transcriptomic retinal profiles revealing a total of 4,178 differentially methylated loci or regions, and 457 differentially expressed genes. Highest correlation in methylation differences was seen across different conditions at the same time point (e.g., between radiation exposure and hindlimb unloaded at 7 days). Biological processes related to nucleotide metabolism were enriched in all groups with activation at 1 month and suppression at 7 days and 4 months. Genes and processes related to Notch and Wnt signaling showed alterations 4 months post-exposure. Interestingly, Notch3 and Lrg1 showed differential patterns in the NASA Twins Study in-flight samples and in response to stressors in the murine retina in the current study. A total of 23 genes were both differentially methylated and expressed, including genes involved in retinal disease or cataract development (Crybb3, Fgfr1, Pitpnm3, Sipa1l3, Sox9) and inflammatory response (B4galt6, Ppm1a, Sphk1). To our knowledge, the current multi-omics analysis is the first multi-omics study to interrogate the epigenomic and transcriptomic impacts of radiation and hindlimb unloading on the retina in isolation and in combination. The results provide an insight into the retinal response to individual spaceflight hazard analogs and their interplay at different post-exposure stages and contributes towards a mechanistic understanding of spaceflight-induced vision impairment using ground-based models.

Prachi Kothiyal↗

NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), has typically limited machine learning (ML) in space studies and further study of radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNAseq) data from 6 mouse liver GeneLab datasets (GLDS) with a total of 113 spaceflight and ground-control samples to determine top features relevant to spaceflight including the effect of radiation exposure. Data was normalized within each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. The top MRMR features were used to predict spaceflight vs. ground-control samples using a Random Forest (RF) classifier with 5-fold cross validation (CV). The ML-based gene sets were further compared against differential gene expression results from individual GLDS. CV training using the top 100 MRMR genes show averages of 86% accuracy and 0.95 AUC value on the validation set over 5 folds (Figure 1A). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 811 or 68 DEGs overlapping between at least 2 or 3 studies, respectively (Figure 1B). Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism. Set analysis between the MRMR features and the DEGs showed 60 or 8 genes overlapping with at least 1 or 2 studies, respectively. MRMR feature selection and ensemble ML methods (e.g. RF) improve performance relative to a Naïve Bayes classifier when NGS data sets are analyzed. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise ratio. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from RNASeq analysis. Non-intersecting sets introduce opportunity to explore spaceflight relevant genes and implementing ML methods across existing NGS datasets may overcome sample size limitations. ML coupled with existing analytical methods enhances understanding of disease by revealing common underlying pathways across datasets.

Machine Learning↗

NASA NTRSDate not supplied

Investigation into Stimulated Microgravity Techniques used to Study Biofilm Growth

Bacterial growth in liquid media in microgravity conditions is not well understood. Trends such as a shortened lag phase, longer log phase, slower growth rate, and a higher final population concentration have been noted but the underlying cause remains unclear. At the single cell level, it is predicted that bacteria are less gravity-sensitive than larger species. The effects on their immediate environment, including the lack of cell settlement and slower mass transfer of nutrients due to lack of density driven convection, could help explain the trends. Ground-based spaceflight analogs, or simulated microgravity devices, are often employed to achieve different attributes of weightlessness to study effects on bacterial growth. Though these technologies could isolate gravity’s role in various biological processes, they cannot replicate all its effects and underlying mechanisms. Hence, interpretation of results could be misleading, even if similar to spaceflight. In this study two common simulated microgravity devices were investigated to determine whether they could simulate relevant microgravity conditions for bacterial growth. A bioreactor, the high aspect ratio vessel (HARV), was used with dyes of different density mounted on a random positioning machine (RP machine) or a rotating wall vessel (RWV). The RP machine displayed higher mixing rates than the RWV. The RWV was further tested at different rotations per minute (RPM). The range to minimize effects of density driven convection (low speeds) or centrifugal forces (high speeds) was between a range of 15-20 RPM. These results will help inform the selection of simulated microgravity device as well as interpretation of subsequent biofilm growth results.

Angie M. Diaz↗