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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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149 records · Page 9

Avian dark cells

Dark cells (DCs) of mammalian and non-mammalian species help to maintain the homeostasis of the inner ear fluids in vivo. Although the avian cochlea is straight and the mammalian cochlea is coiled, no significant difference in the morphology and/or function of mammalian and avian DCs has been reported. The mammalian equivalent of avian DCs are marginal cells and are located in the stria vascularis along a bony sheet. Avian DCs hang free from the tegmentum vasculosum (TV) of the avian lagena between the perilymph and endolymph. Frame averaging was used to image the fluorescence emitted by several fluorochromes applied to freshly isolated dark cells (iDCs) from chickens (Gallus domesticus) inner ears. The viability of iDCs was monitored via trypan blue exclusion at each isolation step. Sodium Green, BCECF-AM, Rhodamine 123 and 9-anthroyl ouabain molecules were used to test iDC function. These fluorochromes label iDCs ionic transmembrane trafficking function, membrane electrogenic potentials and Na+/K+ ATPase pump's activity. Na+/K+ ATPase pump sites, were also evaluated by the p-nitrophenyl phosphatase reaction. These results suggest that iDCs remain viable for several hours after isolation without special culturing requirements and that the number and functional activity of Na+/K+ ATPase pumps in the iDCs were indistinguishable from in vivo DCs. Primary cultures of freshly iDCs were successfully maintained for 28 days in plastic dishes with RPMI 1640 culture medium. The preparation of iDCs overcomes the difficulty of DCs accessability in vivo and the unavoidable contamination that rupturing the inner ear microenvironments induces.

NASA Discipline Neuroscience↗

Sympathetic activation in exercise is not dependent on muscle acidosis. Direct evidence from studies in metabolic myopathies

Muscle acidosis has been implicated as a major determinant of reflex sympathetic activation during exercise. To test this hypothesis we studied sympathetic exercise responses in metabolic myopathies in which muscle acidosis is impaired or augmented during exercise. As an index of reflex sympathetic activation to muscle, microneurographic measurements of muscle sympathetic nerve activity (MSNA) were obtained from the peroneal nerve. MSNA was measured during static handgrip exercise at 30% of maximal voluntary contraction force to exhaustion in patients in whom exercise-induced muscle acidosis is absent (seven myophosphorylase deficient patients; MD [McArdle's disease], and one patient with muscle phosphofructokinase deficiency [PFKD]), augmented (one patient with mitochondrial myopathy [MM]), or normal (five healthy controls). Muscle pH was monitored by 31P-magnetic resonance spectroscopy during handgrip exercise in the five control subjects, four MD patients, and the MM and PFKD patients. With handgrip to exhaustion, the increase in MSNA over baseline (bursts per minute [bpm] and total activity [%]) was not impaired in patients with MD (17+/-2 bpm, 124+/-42%) or PFKD (65 bpm, 307%), and was not enhanced in the MM patient (24 bpm, 131%) compared with controls (17+/-4 bpm, 115+/-17%). Post-handgrip ischemia studied in one McArdle patient, caused sustained elevation of MSNA above basal suggesting a chemoreflex activation of MSNA. Handgrip exercise elicited an enhanced drop in muscle pH of 0.51 U in the MM patient compared with the decrease in controls of 0.13+/-0.02 U. In contrast, muscle pH increased with exercise in MD by 0.12+/-0.05 U and in PFKD by 0.01 U. In conclusion, patients with glycogenolytic, glycolytic, and oxidative phosphorylation defects show normal muscle sympathetic nerve responses to static exercise. These findings indicate that muscle acidosis is not a prerequisite for sympathetic activation in exercise.

NASA Discipline Cardiopulmonary↗

Ionic signaling in plant gravity and touch responses

Plant roots are optimized to exploit resources from the soil and as each root explores this environment it will encounter a range of biotic and abiotic stimuli to which it must respond. Therefore, each root must possess a sensory array capable of monitoring and integrating these diverse stimuli to direct the appropriate growth response. Touch and gravity represent two of the biophysical stimuli that plants must integrate. As sensing both of these signals requires mechano-transduction of biophysical forces to biochemical signaling events, it is likely that they share signal transduction elements. These common signaling components may allow for cross-talk and so integration of thigmotropic and gravitropic responses. Indeed, signal transduction events in both plant touch and gravity sensing are thought to include Ca(2+)- and pH-dependent events. Additionally, it seems clear that the systems responsible for root touch and gravity response interact to generate an integrated growth response. Thus, primary and lateral roots of Arabidopsis respond to mechanical stimuli by eliciting tropic growth that is likely part of a growth strategy employed by the root to circumvent obstacles in the soil. Also, the mechano-signaling induced by encountering an obstacle apparently down-regulates the graviperception machinery to allow this kind of avoidance response. The challenge for future research will be to define how the cellular signaling events in the root cap facilitate this signal integration and growth regulation. In addition, whether other stimuli are likewise integrated with the graviresponse via signal transduction system cross-talk is an important question that remains to be answered.

Review↗

Aqueous nitrite ion determination by selective reduction and gas phase nitric oxide chemiluminescence

An improved method of flow injection analysis for aqueous nitrite ion exploits the sensitivity and selectivity of the nitric oxide (NO) chemilluminescence detector. Trace analysis of nitrite ion in a small sample (5-160 microL) is accomplished by conversion of nitrite ion to NO by aqueous iodide in acid. The resulting NO is transported to the gas phase through a semipermeable membrane and subsequently detected by monitoring the photoemission of the reaction between NO and ozone (O3). Chemiluminescence detection is selective for measurement of NO, and, since the detection occurs in the gas-phase, neither sample coloration nor turbidity interfere. The detection limit for a 100-microL sample is 0.04 ppb of nitrite ion. The precision at the 10 ppb level is 2% relative standard deviation, and 60-180 samples can be analyzed per hour. Samples of human saliva and food extracts were analyzed; the results from a standard colorimetric measurement are compared with those from the new chemiluminescence method in order to further validate the latter method. A high degree of selectivity is obtained due to the three discriminating steps in the process: (1) the nitrite ion to NO conversion conditions are virtually specific for nitrite ion, (2) only volatile products of the conversion will be swept to the gas phase (avoiding turbidity or color in spectrophotometric methods), and (3) the NO chemiluminescence detector selectively detects the emission from the NO + O3 reaction. The method is free of interferences, offers detection limits of low parts per billion of nitrite ion, and allows the analysis of up to 180 microL-sized samples per hour, with little sample preparation and no chromatographic separation. Much smaller samples can be analyzed by this method than in previously reported batch analysis methods, which typically require 5 mL or more of sample and often need chromatographic separations as well.

NASA Discipline Environmental Health↗

Integrated Bosch Process System Models for In-Situ Oxygen and Carbon Production

In-Situ Resource Utilization (ISRU) technology is a vital component to NASA’s mission of a sustainable presence on the Moon and Mars. Local resources can be leveraged to reduce resupply frequency and mass. Elements of the Bosch process, combined with the carbothermal reduction process, can produce oxygen on the lunar surface with minimal consumables. The Bosch process can also produce oxygen on the Martian surface by using the CO 2 -rich environment. Between both systems, adsorption pump, solar thermal energy, carbon formation reactor, and water recovery subsystems are modeled and integrated to create a functional model in MATLAB software. The model is used to simulate performance of the system and reduce mass, power, and volume requirements. This integrated system model provides a tool to scale ISRU technologies for oxygen and carbon production. The MATLAB model is created by developing a system of independent subsystem models that are solved for their quasi-steady state values which can be integrated with respect to time to determine the change in current states. A flexible time stepping method is used to ensure a high level of accuracy during periods of rapid change while still making use of a simple explicit integration method. The flexible time step is calculated for each independent subsystem and the minimum value from those is used as the overall time step. A flexible time step is calculated by dividing a resolution value, or the maximum change per time step, by the variables current rate of change. The maximum value from all points in space is used for subsystem models that contain multiple values. The process is done for every variable that is being monitored in each subsystem and the global minimum is used as that iteration’s timestep. Several assumptions used in the MATLAB model for fluid flow dynamics, such as 1-D gas flow through the sorption pump, are supported by modeling in Ansys Fluent software. The Lunar oxygen production system is outlined in Fig. 1. The carbothermal reduction subsystem uses solar energy to heat a mixture of lunar regolith and carbon powder to produce carbon monoxide. To begin, the carbon monoxide feeds to the modified Bosch subsystem along with hydrogen gas. The reactants then enter the carbon formation reactor where water and carbon powder are produced. Solar thermal energy is used to add energy to the reactor, but waste heat from the carbothermal process is another potential heat source. The water is collected and electrolyzed to produce hydrogen which reenters the Bosch subsystem, and the oxygen is stored for downstream use. The carbon powder is collected and feeds back into the carbothermal subsystem. The Martian oxygen production system uses the full Bosch process and is outlined in Fig 2. A CO 2 adsorption pump thermally cycles to scrub and pressurize CO 2 from the environment. Along with an initial supply of hydrogen, the reactants enter the Reverse Water Gas Shift Reactor (RWGSR) which produces carbon monoxide and water. Carbon monoxide and unreacted hydrogen enter the carbon formation reactor to produce water and carbon powder. The water is collected from both reactors and electrolyzed to reintroduce hydrogen and store oxygen for propellant production or life support. Carbon is removed from the carbon formation reactor and stored. The adsorption pump utilizes rapid cycle temperature swings within a stack of zeolite coated surfaces. The subsystem model solves 1-D quasi-steady conservation laws of the quasi-steady form, shown in Eq. 1, for the gas stream and heat exchange liquid to predict performance parameters such as breakthrough capacity and optimum cycle time. The source term S is used to capture interactions between the fluid flows and the sorbent. A quasi-steady-state scheme is used where no time derivatives appear in the governing equations, except for those in the source terms. This results in an autonomous system, where ∂F/∂x = ƒ(F). The fluxes F are provided at the inlet, and an explicit method is used to solve for the spatial distribution of F. The heat and mass flows to the sorbent are then extracted from the source terms. These flows are numerically integrated to produce a 1-D solution for the system’s state as a function of both time and space. The body of the adsorption pump is separated into two semi-independent models: the heat exchanger fluid flow and gas flow through the zeolite coated surfaces. Both models are solved using the above-described method to find a 1-D solution as a function of space and interact only once a timestep is taken. The interaction point is the sorbent through which all heat transfer between the two models must occur. Sorbent mass adsorption is calculated using the Lagergren model, shown in Eq. 2, where the transfer coefficient, λ D , is found by solving a system of nondimensionalized equations derived by using the heat and mass transfer analogy for transport phenomena. Using Grade 544 Type 13X zeolite as the sorbent material, the equilibrium concentration, θ eq , is calculated using the k-site Langmuir isotherm and fit parameters. Additionally, the enthalpy of adsorption used in the model is computed by interpolation of available data [1]. The subsystem model was validated using the Rapid Cycle Temperature Swing Adsorption (RC-TSA) pump. The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC). The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC).

In situ Resource Utilization↗