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

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Pattern formation in a coupled membrane-bulk reaction-diffusion model for intracellular polarization and oscillations

Reaction-diffusion systems have been widely used to study spatio-temporal phenomena in cell biology, such as cell polarization. Coupled bulk-surface models naturally include compartmentalization of cytosolic and membrane-bound polarity molecules. Here we study the distribution of the polarity protein Cdc42 in a mass-conserved membrane-bulk model, and explore the effects of diffusion and spatial dimensionality on spatio-temporal pattern formation. We first analyze a one-dimensional (1-D) model for Cdc42 oscillations in fission yeast, consisting of two diffusion equations in the bulk domain coupled to nonlinear ODEs for binding kinetics at each end of the cell. In 1-D, our analysis reveals the existence of symmetric and asymmetric steady states, as well as anti-phase relaxation oscillations typical of slow-fast systems. We then extend our analysis to a two-dimensional (2-D) model with circular bulk geometry, for which species can either diffuse inside the cell or become bound to the membrane and undergo a nonlinear reaction-diffusion process. We also consider a nonlocal system of PDEs approximating the dynamics of the 2-D membrane-bulk model in the limit of fast bulk diffusion. In all three model variants we find that mass conservation selects perturbations of spatial modes that simply redistribute mass. In 1-D, only anti-phase oscillations between the two ends of the cell can occur, and in-phase oscillations are excluded. In higher dimensions, no radially symmetric oscillations are observed. Instead, the only instabilities are symmetry-breaking, either corresponding to stationary Turing instabilities, leading to the formation of stationary patterns, or to oscillatory Turing instabilities, leading to traveling and standing waves. Codimension-two Bogdanov—Takens bifurcations occur when the two distinct instabilities coincide, causing traveling waves to slow down and to eventually become stationary patterns. Our work clarifies the effect of geometry and dimensionality on behaviors observed in ma.ss-conserved cell polarity models.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Benchmark Models for Classification of Radiation Type Induced in Immune Cells

NASA Biological and Physical Sciences and the Science Mission Directorate have published a benchmark dataset of mouse immune cells subjected to radiation-induced DNA damage. The dataset comprises ML-ready microscopic imagery of said cells, including labels indicating radiation type and dose. The machine learning team at NASA Interagency Implementation and Advanced Concept Team (IMPACT) created multiple benchmark models. Initially, we conducted a preliminary analysis using thresholding. The algorithm used thresholds on average brightness of the available images to classify them into their respective radiation type. We also tested machine learning approaches. Convolutional Neural Networks (CNN) emerged as the best-performing model. This poster presents the benchmark scores obtained by the models.

Vishal Perekadan↗
NASA NTRS1996

Two-stage model of radon-induced malignant lung tumors in rats: effects of cell killing

A two-stage stochastic model of carcinogenesis is used to analyze lung tumor incidence in 3750 rats exposed to varying regimens of radon carried on a constant-concentration uranium ore dust aerosol. New to this analysis is the parameterization of the model such that cell killing by the alpha particles could be included. The model contains parameters characterizing the rate of the first mutation, the net proliferation rate of initiated cells, the ratio of the rates of cell loss (cell killing plus differentiation) and cell division, and the lag time between the appearance of the first malignant cell and the tumor. Data analysis was by standard maximum likelihood estimation techniques. Results indicate that the rate of the first mutation is dependent on radon and consistent with in vitro rates measured experimentally, and that the rate of the second mutation is not dependent on radon. An initial sharp rise in the net proliferation rate of initiated cell was found with increasing exposure rate (denoted model I), which leads to an unrealistically high cell-killing coefficient. A second model (model II) was studied, in which the initial rise was attributed to promotion via a step function, implying that it is due not to radon but to the uranium ore dust. This model resulted in values for the cell-killing coefficient consistent with those found for in vitro cells. An "inverse dose-rate" effect is seen, i.e. an increase in the lifetime probability of tumor with a decrease in exposure rate. This is attributed in large part to promotion of intermediate lesions. Since model II is preferable on biological grounds (it yields a plausible cell-killing coefficient), such as uranium ore dust. This analysis presents evidence that a two-stage model describes the data adequately and generates hypotheses regarding the mechanism of radon-induced carcinogenesis.

NASA Program Radiation Health↗
DOE OSTI2023

Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms

The probability that an observed cancer was caused by radiation exposure is usually estimated using cancer rates and risk models from radioepidemiological cohorts and is called assigned share (AS). This definition implicitly assumes that an ongoing carcinogenic process is unaffected by the studied radiation exposure. However, there is strong evidence that radiation can also accelerate an existing clonal development towards cancer. In this work, we define different association measures that an observed cancer was newly induced, accelerated, or retarded. The measures were quantified exemplarily by Monte Carlo simulations that track the development of individual cells. Three biologically based two-stage clonal expansion (TSCE) models were applied. In the first model, radiation initiates cancer development, while in the other two, radiation has a promoting effect, i.e. radiation accelerates the clonal expansion of pre-cancerous cells. The parameters of the TSCE models were derived from breast cancer data from the atomic bomb survivors of Hiroshima and Nagasaki. For exposure at age 30, all three models resulted in similar estimates of AS at age 60. For the initiation model, estimates of association were nearly identical to AS. However, for the promotion models, the cancerous clonal development was frequently accelerated towards younger ages, resulting in associations substantially higher than AS. This work shows that the association between a given cancer and exposure in an affected person depends on the underlying biological mechanism and can be substantially larger than the AS derived from classic radioepidemiology.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
NASA NTRS2004

Computation Molecular Kinetics Model of HZE Induced Cell Cycle Arrest

Cell culture models play an important role in understanding the biological effectiveness of space radiation. High energy and charge (HZE) ions produce prolonged cell cycle arrests at the G1/S and G2/M transition points in the cell cycle. A detailed description of these phenomena is needed to integrate knowledge of the expression of DNA damage in surviving cells, including the determination of relative effectiveness factors between different types of radiation that produce differential types of DNA damage and arrest durations. We have developed a hierarchical kinetics model that tracks the distribution of cells in various cell phase compartments (early G1, late G1, S, G2, and M), however with transition rates that are controlled by rate-limiting steps in the kinetics of cyclin-cdk's interactions with their families of transcription factors and inhibitor molecules. The coupling of damaged DNA molecules to the downstream cyclin-cdk inhibitors is achieved through a description of the DNA-PK and ATM signaling pathways. For HZE irradiations we describe preliminary results, which introduce simulation of the stochastic nature of the number of direct particle traversals per cell in the modulation of cyclin-cdk and cell cycle population kinetics. Comparison of the model to data for fibroblast cells irradiated photons or HZE ions are described.

Cucinotta, Francis A.↗
NASA NTRS1994

Charged-particle mutagenesis II. Mutagenic effects of high energy charged particles in normal human fibroblasts

The biological effects of high LET charged particles are a subject of great concern with regard to the prediction of radiation risk in space. In this report, mutagenic effects of high LET charged particles are quantitatively measured using primary cultures of human skin fibroblasts, and the spectrum of induced mutations are analyzed. The LET of the charged particles ranged from 25 KeV/micrometer to 975 KeV/micrometer with particle energy (on the cells) between 94-603 MeV/u. The X-chromosome linked hypoxanthine guanine phosphoribosyl transferase (hprt) locus was used as the target gene. Exposure to these high LET charged particles resulted in exponential survival curves; whereas, mutation induction was fitted by a linear model. The Relative Biological Effect (RBE) for cell-killing ranged from 3.73 to 1.25, while that for mutant induction ranged from 5.74 to 0.48. Maximum RBE values were obtained at the LET of 150 keV/micrometer. The inactivation cross-section (alpha i) and the action cross-section for mutant induction (alpha m) ranged from 2.2 to 92.0 micrometer2 and 0.09 to 5.56 x 10(-3) micrometer2, respectively. The maximum values were obtained by 56Fe with an LET of 200 keV/micrometer. The mutagenicity (alpha m/alpha i) ranged from 2.05 to 7.99 x 10(-5) with the maximum value at 150 keV/micrometer. Furthermore, molecular analysis of mutants induced by charged particles indicates that higher LET beams are more likely to cause larger deletions in the hprt locus.

NASA Center JSC↗
NASA NTRS1994

Charged-particle mutagenesis 2. Mutagenic effects of high energy charged particles in normal human fibroblasts

The biological effects of high Linear Energy Transfer (LET) charged particles are a subject of great concern with regard to the prediction of radiation risk in space. In this report, mutagenic effects of high LET charged particles are quantitatively measured using primary cultures of human skin fibroblasts, and the spectrum of induced mutations are analyzed. The LET of the charged particles ranged from 25 KeV/micrometer to 975 KeV/micrometer with particle energy (on the cells) between 94-603 MeV/u. The X-chromosome linked hypoxanthine guanine phosphoribosyl transferase (hprt) locus was used as the target gene. Exposure to these high LET charged particles resulted in exponential survival curves; whereas, mutation induction was fitted by a linear model. The Relative Biological Effect (RBE) for cell-killing ranged from 3.73 to 1.25, while that for mutant induction ranged from 5.74 to 0.48. Maximum RBE values were obtained at the LET of 150 keV/micrometer. The inactivation cross-section (alpha i) and the action cross-section for mutant induction (alpha m) ranged from 2.2 to 92.0 sq micrometer and 0.09 to 5.56 x 10(exp -3) sq micrometer respectively. The maximum values were obtained by Fe-56 with an LET of 200 keV/micrometer. The mutagenicity (alpha m/alpha i) ranged from 2.05 to 7.99 x 10(exp -5) with the maximum value at 150 keV/micrometer. Furthermore, molecular analysis of mutants induced by charged particles indicates that higher LET beams are more likely to cause larger deletions in the hprt locus.

Chen, D. J.↗
NASA NTRS2004

Bioavailability of iron from spinach using an in vitro/human Caco-2 cell bioassay model

Spinach (Spinacia oleracea) cv Whitney was tested for iron bioavailabilty using an in vitro human intestinal cell culture ferritin bioassay technique previously developed. Spinach was cultured in a growth chamber for 33 days, harvested, and freeze-dried. Total iron in the samples was an average of 71 micrograms/g dry weight. Spinach was digested in vitro (pepsin and 0.1 M HCl followed by pancreatin and 0.1 M NaHCO3) with and without the addition of supplemental ascorbic acid. Caco-2 cell cultures were used to determine iron bioavailability from the spinach mixtures. Production of the iron-binding protein ferritin in the Caco-2 cells showed the supplemental ascorbic acid doubled bioavailability of iron from spinach. The data show fresh spinach is a poor source of iron, and emphasize the importance of evaluation of whole meals rather than single food items. The data support the usefulness of the in vitro/Caco-2 cell ferritin bioassay model for prescreening of space flight diets for bioavailable iron.

NASA Discipline Life Support Systems↗
DOE OSTI2024

A hierarchal model for bacterial cell inactivation in solution by direct and indirect treatment using cold atmospheric plasmas

Cold atmospheric plasma devices have shown promise for a variety of plasma medical applications, including wound healing and bacterial inactivation often performed in liquids. In the latter application, plasma-produced reactive oxygen and nitrogen species (RONS) interact with and damage bacterial cells, though the exact mechanism by which cell damage occurs is unclear. Computational models can help elucidate relationships between plasma-produced RONS and cell killing by enabling direct comparison between dissimilar plasma devices and by examining the effects of changing operating parameters in these devices. In biological applications, computational models of plasma-liquid interactions would be most effective in design and optimization of plasma devices if there is a corresponding prediction of the biological outcome. In this work, we propose a hierarchal model for planktonic bacterial cell inactivation by plasma produced RONS in liquid. A previously developed reaction mechanism for plasma induced modification of cysteine was extended to provide a basis for cell killing by plasma-produced RONS. Results from the model are compared to literature values to provide proof of concept. Differences in time to bacterial inactivation as a function of plasma operating parameters including gas composition and plasma source configuration are discussed. Results indicate that optimizing gas-phase reactive nitrogen species production may be key in the design of plasma devices for disinfection.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

Ceratopteris richardii: a productive model for revealing secrets of signaling and development

Ceratopteris richardii is an aquatic fern grown in tropical and subtropical regions of the world. It is proven to be a productive model system for studies in the genetics, biochemistry, and cell biology of basic biologic processes that occur in early gametophytic development. It provides several advantages to biologists, especially those interested in gravitational biology, polarity development, and in the genetics of sexual development. It is easy to culture, has a relatively short life cycle, and offers an array of attractive features that facilitate genetic studies. The germination and early development of large populations of genetically identical spores are easy to synchronize, and both the direction of polarity development and cell-level gravity responses can be measured and readily manipulated within the first 24 h of spore development. Although there is no reliable transformation system available yet in Ceratopteris, recent studies suggest that the technique of RNA interference can be used to block translation of specific genes in a related fern, Marsilea, and current studies will soon reveal the applicability of this approach, as well as of other transformation approaches, in Ceratopteris. A recently completed expressed sequence tag (EST) sequencing project makes available the partial sequence of more than 2000 cDNAs, representing a significant percentage of the genes being expressed during the first 24 h of spore germination, when many developmentally interesting processes are occurring. A microarray of these ESTs is being constructed, so especially for those scientists interested in basic cellular phenomena that occur early in spore germination, the availability of the ESTs and of the microarray will make Ceratopteris an even more attractive model system.

NASA Discipline Plant Biology↗
NASA NTRS2003

Mathematical model of diffusion-limited evolution of multiple gas bubbles in tissue

Models of gas bubble dynamics employed in probabilistic analyses of decompression sickness incidence in man must be theoretically consistent and simple, if they are to yield useful results without requiring excessive computations. They are generally formulated in terms of ordinary differential equations that describe diffusion-limited gas exchange between a gas bubble and the extravascular tissue surrounding it. In our previous model (Ann. Biomed. Eng. 30: 232-246, 2002), we showed that with appropriate representation of sink pressures to account for gas loss or gain due to heterogeneous blood perfusion in the unstirred diffusion region around the bubble, diffusion-limited bubble growth in a tissue of finite volume can be simulated without postulating a boundary layer across which gas flux is discontinuous. However, interactions between two or more bubbles caused by competition for available gas cannot be considered in this model, because the diffusion region has a fixed volume with zero gas flux at its outer boundary. The present work extends the previous model to accommodate interactions among multiple bubbles by allowing the diffusion region volume of each bubble to vary during bubble evolution. For given decompression and tissue volume, bubble growth is sustained only if the bubble number density is below a certain maximum.

Evaluation Studies↗
NASA NTRS1997

Correspondence between discrete and continuous models of excitable media: trigger waves

We present a theoretical framework for relating continuous partial differential equation (PDE) models of excitable media to discrete cellular automata (CA) models on a randomized lattice. These relations establish a quantitative link between the CA model and the specific physical system under study. We derive expressions for the CA model's plane wave speed, critical curvature, and effective diffusion constant in terms of the model's internal parameters (the interaction radius, excitation threshold, and time step). We then equate these expressions to the corresponding quantities obtained from solution of the PDEs (for a fixed excitability). This yields a set of coupled equations with a unique solution for the required CA parameter values. Here we restrict our analysis to "trigger" wave solutions obtained in the limiting case of a two-dimensional excitable medium with no recovery processes. We tested the correspondence between our CA model and two PDE models (the FitzHugh-Nagumo medium and a medium with a "sawtooth" nonlinear reaction source) and found good agreement with the numerical solutions of the PDEs. Our results suggest that the behavior of trigger waves is actually controlled by a small number of parameters.

Non-NASA Center↗
DOE OSTI2022

Cell wall biology of the moss Physcomitrium patens

Abstract The moss Physcomitrium (previously Physcomitrella) patens is a non-vascular plant belonging to the bryophytes that has been used as a model species to study the evolution of plant cell wall structure and biosynthesis. Here, we present an updated review of the cell wall biology of P. patens. Immunocytochemical and structural studies have shown that the cell walls of P. patens mainly contain cellulose, hemicelluloses (xyloglucan, xylan, glucomannan, and arabinoglucan), pectin, and glycoproteins, and their abundance varies among different cell types and at different plant developmental stages. Genetic and biochemical analyses have revealed that a number of genes involved in cell wall biosynthesis are functionally conserved between P. patens and vascular plants, indicating that the common ancestor of mosses and vascular plants had already acquired most of the biosynthetic machinery to make various cell wall polymers. Although P. patens does not synthesize lignin, homologs of the phenylpropanoid biosynthetic pathway genes exist in P. patens and they play an essential role in the production of caffeate derivatives for cuticle formation. Further genetic and biochemical dissection of cell wall biosynthetic genes in P. patens promises to provide additional insights into the evolutionary history of plant cell wall structure and biosynthesis.

Plant Sciences↗
DOE OSTI2021

Designing efficient genetic code expansion in Bacillus subtilis to gain biological insights

Abstract Bacillus subtilis is a model gram-positive bacterium, commonly used to explore questions across bacterial cell biology and for industrial uses. To enable greater understanding and control of proteins in B. subtilis , here we report broad and efficient genetic code expansion in B. subtilis by incorporating 20 distinct non-standard amino acids within proteins using 3 different families of genetic code expansion systems and two choices of codons. We use these systems to achieve click-labelling, photo-crosslinking, and translational titration. These tools allow us to demonstrate differences between E. coli and B. subtilis stop codon suppression, validate a predicted protein-protein binding interface, and begin to interrogate properties underlying bacterial cytokinesis by precisely modulating cell division dynamics in vivo. We expect that the establishment of this simple and easily accessible chemical biology system in B. subtilis will help uncover an abundance of biological insights and aid genetic code expansion in other organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Chromatin structures from integrated AI and polymer physics model

The physical organization of the genome in three-dimensional space regulates many biological processes, including gene expression and cell differentiation. Three-dimensional characterization of genome structure is critical to understanding these biological processes. Direct experimental measurements of genome structure are challenging; computational models of chromatin structure are therefore necessary. We develop an approach that combines a particle-based chromatin polymer model, molecular simulation, and machine learning to efficiently and accurately estimate chromatin structure fromindirectmeasures of genome structure. More specifically, we introduce a new approach where the interaction parameters of the polymer model are extracted from experimental Hi-C data using a graph neural network (GNN). We train the GNN on simulated data from the underlying polymer model, avoiding the need for large quantities of experimental data. The resulting approach accurately estimates chromatin structures across all chromosomes and across several experimental cell lines despite being trained almost exclusively on simulated data. The proposed approach can be viewed as a general framework for combining physical modeling with machine learning, and it could be extended to integrate additional biological data modalities. Ultimately, we achieve accurate and high-throughput estimations of chromatin structure from Hi-C data, which will be necessary as experimental methodologies, such as single-cell Hi-C, improve.

Biochemistry & Molecular Biology↗