Some mechanisms for a theory of the reticular formation Final report, 15 Nov. 1965 - 14 Nov. 1966
Nonlinear, probabilistic hybrid computer concepts for specifying operational schemata of central nervous system models
PROBABILITY THEORY↗
SEARCH · Engineering Papers
Results for “biological system modeling”
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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Isotopically nonstationary metabolic flux analysis of plants: recent progress and future opportunities
Metabolic flux analysis (MFA) is a valuable tool for quantifying cellular phenotypes and to guide plant metabolic engineering. By introducing stable isotopic tracers and employing mathematical models, MFA can quantify the rates of metabolic reactions through biochemical pathways. Recent applications of isotopically nonstationary MFA (INST–MFA) to plants have elucidated nonintuitive metabolism in leaves under optimal and stress conditions, described coupled fluxes for fast–growing algae, and produced a synergistic multi–organ flux map that is a first in MFA for any biological system. Finally, these insights could not be elucidated through other approaches and show the potential of INST–MFA to correct an oversimplified understanding of plant metabolism.
59 BASIC BIOLOGICAL SCIENCES↗
Automating Genetic Algorithm Mutations for Molecules Using a Masked Language Model
Inspired by the evolution of biological systems, genetic algorithms have been applied to generate solutions for optimization problems in a variety of scientific and engineering disciplines. For a given problem, a suitable genome representation must be defined along with a mutation operator to generate subsequent generations. Unlike natural systems which display a variety of complex rearrangements (e.g. mobile genetic elements), mutation for genetic algorithms commonly utilizes only random point-wise changes. Furthermore, generalizing beyond point-wise mutations poses a key difficulty as useful genome rearrangements depend on the representation and problem domain. To move beyond the limitations of manually defined point-wise changes, here we propose the use of techniques from masked language models to automatically generate mutations. As a first step, common subsequences within a given population are used to generate a vocabulary. The vocabulary is then used to tokenize each genome. A masked language model is trained on the tokenized data in order to generate possible rearrangements (i.e. mutations). In order to illustrate the proposed strategy, we use string representations of molecules and use a genetic algorithm to optimize for drug-likeness and synthesizability. Finally, our results show that moving beyond random point-wise mutations accelerates genetic algorithm optimization.
59 BASIC BIOLOGICAL SCIENCES↗
A standardized workflow for kinetic metabolic model curation and dissemination
Kinetic metabolic models provide invaluable insights into cellular metabolism, supporting applications in synthetic biology, metabolic engineering, and systems biology. However, reproducibility and utility of these models hinge on clear and rigorous documentation, standardized annotation, and accessible visualization. This paper presents a workflow for building, annotating, visualizing, and sharing kinetic metabolic models. Our method integrates community standards and open-source tools to ensure reproducibility, interoperability, and user accessibility. This procedure enables researchers to produce reusable and well-documented kinetic models, advancing their role as powerful tools in metabolic research.
Cook, Margaret [Univ. of Washington, Seattle, WA (↗
Autonomous adaptive data acquisition for scanning hyperspectral imaging
Non-invasive and label-free spectral microscopy (spectromicroscopy) techniques can provide quantitative biochemical information complementary to genomic sequencing, transcriptomic profiling, and proteomic analyses. However, spectromicroscopy techniques generate high-dimensional data; acquisition of a single spectral image can range from tens of minutes to hours, depending on the desired spatial resolution and the image size. This substantially limits the timescales of observable transient biological processes. To address this challenge and move spectromicroscopy towards efficient real-time spatiochemical imaging, we developed a grid-less autonomous adaptive sampling method. Our method substantially decreases image acquisition time while increasing sampling density in regions of steeper physico-chemical gradients. When implemented with scanning Fourier Transform infrared spectromicroscopy experiments, this grid-less adaptive sampling approach outperformed standard uniform grid sampling in a two-component chemical model system and in a complex biological sample, Caenorhabditis elegans. We quantitatively and qualitatively assess the efficiency of data acquisition using performance metrics and multivariate infrared spectral analysis, respectively.
47 OTHER INSTRUMENTATION↗
Increasing accessibility to deep learning-based analytics for space biology: pretrained models, transfer learning, and analytics platform development
Biological systems react in complex ways to the stressors of spaceflight, and the data capturing these relationships is concomitantly high-dimensional and complex. Deep learning and machine learning approaches are increasingly popular as an analytical approach for space biosciences, due to their ability to model complex relationships in complex data. However, such approaches often require large datasets and extensive computational resources. New approaches that minimize data sizes and computational power needed to leverage machine learning, and resources that make these approaches accessible, are needed to increase accessibility and adoption of machine learning in the space biosciences. Transfer learning, in which a pretrained model of broad utility is trained on a large dataset, and subsequently reused on downstream applications for which data is more limited, is one approach to minimizing data and computational intensity of deep learning applications. This transfer learning approach results in more performant models in high-dimensional, low-sample-size settings such as space biology, as compared to training models on limited data from scratch. This presentation will outline efforts to generate pretrained models for the space biology community, and highlight transfer learning applications modeling microbial antibiotic resistance during spaceflight. Finally, in order to increase accessibility of these models and tools, as well as others, for the broader space biology community, we present a modeling and analysis platform facilitating machine learning applications in space biology. This platform streamlines machine learning training and analysis in a notebook format, facilitates download and use of space biology data from the NASA GeneLab database, and can be utilized on NASA-hosted servers or downloaded and hosted locally. This effort, as part of the AI4LS (Artificial Intelligence for Life in Space) working group, will increase accessibility, feasibility, and performance of machine learning approaches for the space biology community.
Adrienne Hoarfrost↗
The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions
The purple non-sulfur bacterium Rhodopseudomonas palustris is recognized as a critical microorganism in the nitrogen and carbon cycle and one of the most common members in wastewater treatment communities. This bacterium is metabolically extremely versatile. It is capable of heterotrophic growth under aerobic and anaerobic conditions, but also able to grow photoautotrophically as well as mixotrophically. Therefore R . palustris can adapt to multiple environments and establish commensal relationships with other organisms, expressing various enzymes supporting degradation of amino acids, carbohydrates, nucleotides, and complex polymers. Moreover, R . palustris can degrade a wide range of pollutants under anaerobic conditions, e.g., aromatic compounds such as benzoate and caffeate, enabling it to thrive in chemically contaminated environments. However, many metabolic mechanisms employed by R . palustris to breakdown and assimilate different carbon and nitrogen sources under chemoheterotrophic or photoheterotrophic conditions remain unknown. Systems biology approaches, such as metabolic modeling, have been employed extensively to unravel complex mechanisms of metabolism. Previously, metabolic models have been reconstructed to study selected capabilities of R . palustris under limited experimental conditions. Here, we developed a comprehensive metabolic model (M-model) for R . palustris Bis A53 ( i DT1294) consisting of 2,721 reactions, 2,123 metabolites, and comprising 1,294 genes. We validated the model using high-throughput phenotypic, physiological, and kinetic data, testing over 350 growth conditions. i DT1294 achieved a prediction accuracy of 90% for growth with various carbon and nitrogen sources and close to 80% for assimilation of aromatic compounds. Moreover, the M-model accurately predicts dynamic changes of growth and substrate consumption rates over time under nine chemoheterotrophic conditions and demonstrated high precision in predicting metabolic changes between photoheterotrophic and photoautotrophic conditions. This comprehensive M-model will help to elucidate metabolic processes associated with the assimilation of multiple carbon and nitrogen sources, anoxygenic photosynthesis, aromatic compound degradation, as well as production of molecular hydrogen and polyhydroxybutyrate.
59 BASIC BIOLOGICAL SCIENCES↗
A model for plant lighting system selection
A decision model is presented that compares lighting systems for a plant growth scenario and chooses the most appropriate system from a given set of possible choices. The model utilizes a Multiple Attribute Utility Theory approach, and incorporates expert input and performance simulations to calculate a utility value for each lighting system being considered. The system with the highest utility is deemed the most appropriate system. The model was applied to a greenhouse scenario, and analyses were conducted to test the model's output for validity. Parameter variation indicates that the model performed as expected. Analysis of model output indicates that differences in utility among the candidate lighting systems were sufficiently large to give confidence that the model's order of selection was valid.
NASA Center KSC↗
The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior
Lipid membranes are central to cellular life. Complementing experiments, computational modeling has been essential in unraveling complex lipid-biomolecule interactions, crucial in both academia and industry. The Martini model, a coarse-grained force field for efficient molecular dynamics simulations, is widely used to study membrane phenomena but has faced limitations, particularly in capturing realistic lipid phase behavior. Here, we present refined Martini 3 lipid models with a mapping scheme that distinguishes lipid tails that differ by just two carbon atoms, enhancing the structural resolution and thermodynamic accuracy of model membrane systems including ternary mixtures. The expanded Martini lipid library includes thousands of models, enabling simulations of complex and biologically relevant systems. These advancements establish Martini as a robust platform for lipid-based simulations across diverse fields.
Lipids↗
Radial Distribution of Electron Spectra from High-Energy Ions
The average track model describes the response of physical and biological systems using radial dose distribution as the key physical descriptor. We report on an extension of this model to describe the average distribution of electron spectra as a function of radial distance from an ion. We present calculations of these spectra for ions of identical linear energy transfer (LET), but dissimilar charge and velocity to evaluate the differences in electron spectra from these ions. To illustrate the usefulness of the radial electron spectra for describing effects that are not described by electron dose, we consider the evaluation of the indirect events in microdosimetric distributions for ions. We show that folding our average electron spectra model with experimentally determined frequency distributions for photons or electrons provides a good representation of radial event spectra from high-energy ions in 0.5-2 micrometer sites.
Cucinotta, Francis A.↗
BRN 3.1 Knockouts Affect the Vestibular, Autonomic, and Circadian Rhythm Responses to 2G Exposure
Our previous studies have demonstrated that 2G exposure via centrifugation significantly attenuated the daily mean and circadian rhythm amplitude of rat body temperature (Tb), heart rate, and activity (Act). In addition, 2G exposure activates neural responses in several vestibular, autonomic, and circadian nuclei. Although we have characterized the effect of 2G on an animal's physiological, neuronal, and behavioral responses, it will be important to understand the underlying neural and physiological mechanisms that mediate those responses. For example, the vestibular responses, proprioceptive feedback, or fluid shifts may be the critical factors that mediate the responses to 2G. As a first step to understand the relative importance of these different response pathways to altered gravitational fields, this study examined the contribution of the vestibular system by utilizing an animal model from molecular biology. Brain 3.1 (Bm 3.1) is a POU domain homeobox gene involved in the normal development of the vestibular and auditory system. Brn 3.1 deletion results in a loss of hair cells in the otoliths, semicircular canals, and cochlea. As a result mice with a Brn 3.1 deletion do not have a functioning vestibular or auditory system. The BRN 3.1 knockout mouse could be a very useful animal model for isolating the role of the vestibular system in mediating the physiological responses to 2G exposure. Therefore, this study compared the effect of 2G exposure via centrifugation between Brn 3.1 knockout (KO) versus Wildtype (W) mice.
Murakami, D. M.↗
Ultrastructure of the green alga Dunaliella salina strain CCAP19/18 (Chlorophyta) as investigated by quick-freeze deep-etch electron microscopy
The single-celled green alga Dunaliella salina is a model system for studies on stress biology, in particular regarding secondary carotenoid accumulation. Under non-stress conditions the cells are green, but under abiotic stress the cells turn orange, because they switch their metabolism and accumulate β-Carotene in globules in the chloroplast. For the first time, Quick-freeze deep-etch electron microscopy was used to visualize cellular structures in green and orange cells of D. salina strain CCAP19/18. This allowed us to present an in-depth analysis of the cellular ultrastructure describing and comparing the features of the two cell types. Our images illustrate the presence of a pericellular matrix for this strain of D. salina. The pericellular matrix was spongy and strands of unknown material anchored it into the plasma membrane. The cytoplasm contained a variety of vesicles, vacuoles, and acidocalcisomes. We could show for strain CCAP19/18 that cytoplasmic lipid bodies were often in close proximity to and sometimes in contact with the outer chloroplast envelope membrane and with the endoplasmic reticulum. Major visible differences between green and orange cells were in the chloroplast: the orange cells have greatly reduced amounts of thylakoid membranes and greatly increased numbers of β-Carotene globules. We showed that the β-Carotene globules often made point contacts with thylakoid membranes, and frequently laid side-by-side along the thylakoid membrane surface, providing support to studies that indicated exchange of molecules between β-Carotene globules and thylakoid membranes. A unique finding was the β-Carotene globule duplets, suggesting intermediate stages in β-Carotene globule morphogenesis. Overall, the β-Carotene globules appear to be similar to plant plastoglobuli. We provide this description of the cellular ultrastructure features as a resource in the context of the recent publication of the genome of D. salina strain CCAP19/18 to expand on the knowledge regarding this novel reference strain.
59 BASIC BIOLOGICAL SCIENCES↗
Systems dynamics and the uncertainties of diagnostics, testing and contact tracing for COVID-19
Not Available
59 BASIC BIOLOGICAL SCIENCES↗
Biological carbon pump estimate based on multidecadal hydrographic data
The transfer of photosynthetically produced organic carbon from surface to mesopelagic waters draws carbon dioxide from the atmosphere. However, current observation-based estimates disagree on the strength of this biological carbon pump (BCP). Earth system models (ESMs) also exhibit a large spread of BCP estimates, indicating limited representations of the known carbon export pathways. Here we use several decades of hydrographic observations to produce a top-down estimate of the strength of the BCP with an inverse biogeochemical model that implicitly accounts for all known export pathways. Our estimate of total organic carbon (TOC) export at 73.4 m (model euphotic zone depth) is 15.00 ± 1.12 Pg C year –1 , with only two-thirds reaching 100 m depth owing to rapid remineralization of organic matter in the upper water column. Partitioned by sequestration time below the euphotic zone, τ, the globally integrated organic carbon production rate with τ > 3 months is 11.09 ± 1.02 Pg C year –1 , dropping to 8.25 ± 0.30 Pg C year –1 for τ > 1 year, with 81% contributed by the non-advective-diffusive vertical flux owing to sinking particles and vertically migrating zooplankton. Nevertheless, export of organic carbon by mixing and other fluid transport of dissolved matter and suspended particles remains regionally important for meeting the respiratory carbon demand. Here, the temperature dependence of the sequestration efficiency inferred from our inversion suggests that future global warming may intensify the recycling of organic matter in the upper ocean, potentially weakening the BCP.
58 GEOSCIENCES↗
Gene regulatory networks controlling carbohydrate selective deconstruction pathways in fungi
The work performed at Clark University (PI, David Hibbett) was a subcomponent of the research lead by Jonathan Schilling at University of Minnesota (award number DE-SC0019427). The overall goal of this project was to address how fungi metabolize lignocellulose. Specifically, we targeted a carbohydrate-selective group of fungi known as 'brown rot' fungi that are well-aligned to be harness for bioconversion to biofuels and other products. These organisms orchestrate a two-step mechanism that initiates decomposition using oxidative radical-based chemistry and follows with enzymatic attack. We have helped characterize that this mechanism occurs in this sequence, but currently lack the fundamental regulatory information needed to harness these fungi for application. Thus, the major goal of this project was to use systems biology to create an integrated model of brown rot wood decay that couples fungal gene regulation with the metabolite feedbacks used to coordinate a two-step oxidative-hydrolytic mechanism. The research at Clark University focused on phylogenomic analyses of data produced by other project partners. Hence, the Clark component of the research was staged to initiate somewhat after that in other partner laboratories. The major Clark-based accomplishment was to advise on selection of fungal species for analyses of brown rot decay chemistry, and to interpret results in a phylogenetic context. The Clark University group also performed complementary analyses of gene families encoding plant cell wall-degrading enzymes in the the basidiomycete genus Lentinula, as well as analyses of substrate-specific gene expression and RNA editing in brown rot fungi.
59 BASIC BIOLOGICAL SCIENCES↗
Neural nets with terminal chaos for simulation of non-deterministic patterns
Models for simulating some aspects of neural intelligence are presented and discussed. Special attention is given to terminal neurodynamics as a particular architecture of terminal dynamics suitable for modeling information flows. Applications of terminal chaos to information fusion as well as to planning and modeling coordination among neurons in biological systems are disussed.
Zak, Michail↗
2015 Space Radiation Standing Review Panel
The 2015 Space Radiation Standing Review Panel (from here on referred to as the SRP) met for a site visit in Houston, TX on December 8 - 9, 2015. The SRP met with representatives from the Space Radiation Element and members of the Human Research Program (HRP) to review the updated research plan for the Risk of Radiation Carcinogenesis Cancer Risk. The SRP also reviewed the newly revised Evidence Reports for the Risk of Acute Radiation Syndromes Due to Solar Particle Events (SPEs) (Acute Risk), the Risk of Acute (In-flight) and Late Central Nervous System Effects from Radiation Exposure (CNS Risk), and the Risk of Cardiovascular Disease and Other Degenerative Tissue Effects from Radiation (Degen Risk), as well as a status update on these Risks. The SRP would like to commend Dr. Simonsen, Dr. Huff, Dr. Nelson, and Dr. Patel for their detailed presentations. The Space Radiation Element did a great job presenting a very large volume of material. The SRP considers it to be a strong program that is well-organized, well-coordinated and generates valuable data. The SRP commended the tissue sharing protocols, working groups, systems biology analysis, and standardization of models. In several of the discussed areas the SRP suggested improvements of the research plans in the future. These include the following: It is important that the team has expanded efforts examining immunology and inflammation as important components of the space radiation biological response. This is an overarching and important focus that is likely to apply to all aspects of the program including acute, CVD, CNS, cancer and others. Given that the area of immunology/inflammation is highly complex (and especially so as it relates to radiation), it warrants the expansion of investigators expertise in immunology and inflammation to work with the individual research projects and also the NASA Specialized Center of Research (NSCORs). Historical data on radiation injury to be entered into the Watson “big data” study must be used with caution. The general scientific issues of reproducibility, details of experimental methods and data analysis from preclinical and basic research laboratories have been raised broadly over the last few years (not specific to this work) and indicate that caution must be applied in the ways these data are used. This pertains to preclinical data and also to phase 3 clinical trials in radiation oncology and medical oncology. Of course, appropriate use and analysis of these “big-data” sets also offer the potential of pinpointing limitations and extracting remaining useful information. Emphasis should be placed on the latter possibility. A key target is risk reduction from radiation exposure. Progress of the entire space program, now moving towards the Mars mission, requires timely answers to key components of human risk, which are known to be complex. Periodic review of progress should be conducted with additional resources directed into achieving critical milestones. Turning the long red bars to yellow and green (or for some risks such as CNS possibly to grey) must be high priority. That such progress will require new science and not engineering means that it should be viewed in a knowledge-based light. The technology-based aspects of engineering issues are certainly as important, however, science and knowledge-based problems are solved in a different way than engineering. Timelines for engineering are more predictable, while for science, progress can be methodical with occasional major incremental findings that can rapidly change the rate of progress. As opportunities for rapid incremental changes arise, periodic enhancement of investment is strongly recommended to enable such new knowledge to be quickly and efficiently exploited. Collaborations and linkages with National Institute of Allergy and Infectious Diseases (NIAID), the Biomedical Advanced Research and Development Authority (BARDA) and the Department of Defense (DoD) are in place and more are encouraged, where possible, with the radiation injury and medical countermeasure studies. This could include utilizing some of their animal model testing contracts to facilitate obtaining results using common platforms. Such approach will facilitate the comparison of results among laboratories, and will facilitate and accelerate the development of medical countermeasures. It is particularly noteworthy that the NASA Space Radiation Element is reaching out to the Multidisciplinary European Low Dose Initiative (MELODI) platform coordinating low dose radiation risk research, and to other international agencies that are studying low dose radiation effects in an effort to fill the void generated by the cancelation of the Department of Energy (DOE) low dose radiation program. While NASA is working actively with NIAID and BARDA to integrate their relevant findings of radiation mitigator investigations to NASA programs, the committee notes its disappointment that the United States currently lacks a dedicated low dose radiation program with clear mechanistic orientation and aimed at the quantification and mitigation of human radiation risk on Earth. This void gives to the NASA Space Radiation Program Element special societal value, but also makes its overall design more challenging.
Steinberg, Susan↗
A Review and Comparison of Mouse and Rat Responses to Micro Gravity, Hyper Gravity and Simulated Models of Partial Gravity; Species Differences, Gaps in the Available Data, and Consideration of the Advantages and Caveats of Each Model for Spaceflight
Laboratory strains of mice and rat are widely used to study mammalian responses to stimulus, and both have been studied under a variety of gravity conditions, including space flight. We compared results obtained from exposure to spaceflight and microgravity, hyper gravity via centrifugation, earth gravity, and models of simulated partial gravity (hind-limb unloading and partial weight bearing treatments). We examined the reported changes in survival, body mass, circadian rhythm (body temperature and activity levels), behavior, bone, muscle, immune, cardio-vasculature, vestibular, reproduction and neonate survival, microbiome, and the visual system. Not all categories have published data for both species, some have limited data, and there are variations in experiment design that allow for only relative comparisons to be considered. The data reveal species differences in both the level of gravity required to obtain a response, degree of response, and in temporal expression of responses. Examination of the data across the gravity levels allows consideration of the hypothesis that gravitational responses follow a continuum, and organ specific differences are noted. In summary, we present advantages and caveats of each model system as pertains to gravitational biology research and identify gaps in our knowledge of how these mammals respond to gravity.
mouse rat gravity↗