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At least 181 records · Page 10

Development of a Genetic Algorithm to Automate Clustering of a Dependency Structure Matrix

Much technology assessment and organization design data exists in Microsoft Excel spreadsheets. Tools are needed to put this data into a form that can be used by design managers to make design decisions. One need is to cluster data that is highly coupled. Tools such as the Dependency Structure Matrix (DSM) and a Genetic Algorithm (GA) can be of great benefit. However, no tool currently combines the DSM and a GA to solve the clustering problem. This paper describes a new software tool that interfaces a GA written as an Excel macro with a DSM in spreadsheet format. The results of several test cases are included to demonstrate how well this new tool works.

Rogers, James L.↗

Ground Vibration Test Planning and Pre-Test Analysis for the X-33 Vehicle

This paper describes the results of the modal test planning and the pre-test analysis for the X-33 vehicle. The pre-test analysis included the selection of the target modes, selection of the sensor and shaker locations and the development of an accurate Test Analysis Model (TAM). For target mode selection, four techniques were considered, one based on the Modal Cost technique, one based on Balanced Singular Value technique, a technique known as the Root Sum Squared (RSS) method, and a Modal Kinetic Energy (MKE) approach. For selecting sensor locations, four techniques were also considered; one based on the Weighted Average Kinetic Energy (WAKE), one based on Guyan Reduction (GR), one emphasizing engineering judgment, and one based on an optimum sensor selection technique using Genetic Algorithm (GA) search technique combined with a criteria based on Hankel Singular Values (HSV's). For selecting shaker locations, four techniques were also considered; one based on the Weighted Average Driving Point Residue (WADPR), one based on engineering judgment and accessibility considerations, a frequency response method, and an optimum shaker location selection based on a GA search technique combined with a criteria based on HSV's. To evaluate the effectiveness of the proposed sensor and shaker locations for exciting the target modes, extensive numerical simulations were performed. Multivariate Mode Indicator Function (MMIF) was used to evaluate the effectiveness of each sensor & shaker set with respect to modal parameter identification. Several TAM reduction techniques were considered including, Guyan, IRS, Modal, and Hybrid. Based on a pre-test cross-orthogonality checks using various reduction techniques, a Hybrid TAM reduction technique was selected and was used for all three vehicle fuel level configurations.

Bedrossian, Herand↗

Teleoperated Modular Robots for Lunar Operations

Solar system exploration is currently carried out by special purpose robots exquisitely designed for the anticipated tasks. However, all contingencies for in situ resource utilization (ISRU), human habitat preparation, and exploration will be difficult to anticipate. Furthermore, developing the necessary special purpose mechanisms for deployment and other capabilities is difficult and error prone. For example, the Galileo high gain antenna never opened, severely restricting the quantity of data returned by the spacecraft. Also, deployment hardware is used only once. To address these problems, we are developing teleoperated modular robots for lunar missions, including operations in transit from Earth. Teleoperation of lunar systems from Earth involves a three second speed-of-light delay, but experiment suggests that interactive operations are feasible.' Modular robots typically consist of many identical modules that pass power and data between them and can be reconfigured for different tasks providing great flexibility, inherent redundancy and graceful degradation as modules fail. Our design features a number of different hub, link, and joint modules to simplify the individual modules, lower structure cost, and provide specialized capabilities. Modular robots are well suited for space applications because of their extreme flexibility, inherent redundancy, high-density packing, and opportunities for mass production. Simple structural modules can be manufactured from lunar regolith in situ using molds or directed solar sintering. Software to direct and control modular robots is difficult to develop. We have used genetic algorithms to evolve both the morphology and control system for walking modular robots3 We are currently using evolvable system technology to evolve controllers for modular robots in the ISS glove box. Development of lunar modular robots will require software and physical simulators, including regolith simulation, to enable design and test of robot software and hardware, particularly automation software. Ready access to these simulators could provide opportunities for contest-driven development ala RoboCup (http://www.robocup.org/). Licensing of module designs could provide opportunities in the toy market and for spin-off applications.

Globus, Al↗

Genetic basis of clinical catecholamine disorders

Norepinephrine and epinephrine are critical determinants of minute-to-minute regulation of blood pressure. Here we review the characterization of two syndromes associated with a genetic abnormality in the noradrenergic pathway. In 1986, we reported a congenital syndrome of undetectable tissue and circulating levels of norepinephrine and epinephrine, elevated levels of dopamine, and absence of dopamine-beta-hydroxylase (DBH). These patients appeared with ptosis and severe orthostatic hypotension and lacked sympathetic noradrenergic function. In two persons with DBH deficiency, we identified seven novel polymorphisms. Both patients are compound heterozygotes for a variant that affects expression of DBH protein via impairment of splicing. Patient 1 also has a missense mutation in DBH exon 2, and patient 2 carries missense mutations in exons 1 and 6. Orthostatic intolerance is a common syndrome affecting young women, presenting with orthostatic tachycardia and symptoms of cerebral hypoperfusion on standing. We tested the hypothesis that abnormal norepinephrine transporter (NET) function might contribute to its etiology. In our proband, we found an elevated plasma norepinephrine with standing that was disproportionate to the increase in levels of dihydroxphenylglycol, as well as impaired norepinephrine clearance and tyramine resistance. Studies of NET gene structure revealed a coding mutation converting a conserved alanine residue in transmembrane domain 9 to proline. Analysis of the protein produced by the mutant cDNA demonstrated greater than 98% reduction in activity relative to normal. The finding of genetic mutations responsible for DBH deficiency and orthostatic intolerance leads us to believe that genetic causes of other autonomic disorders will be found, enabling us to design more effective therapeutic interventions.

Non-NASA Center↗

Systems report for payload G-652: Project origins

Experiments conducted to investigate possible hardware configurations and methodologies for a Get Away Special payload designated G-652 are discussed. Test data collected from the operation of a free electron laser wiggler using simulated ram glow phenomenon are described. Results of an experiment to synthesize organic compounds within a primordial atmosphere using a laser induced plasma are discussed. An experiment is described which utilized neutron bombardment to assess the risk of genetic alterations in embyros in space.

Bellina, J.↗

Evolutionary Design of a Robotic Material Defect Detection System

During the post-flight inspection of SSME engines, several inaccessible regions must be disassembled to inspect for defects such as cracks, scratches, gouges, etc. An improvement to the inspection process would be the design and development of very small robots capable of penetrating these inaccessible regions and detecting the defects. The goal of this research was to utilize an evolutionary design approach for the robotic detection of these types of defects. A simulation and visualization tool was developed prior to receiving the hardware as a development test bed. A small, commercial off-the-shelf (COTS) robot was selected from several candidates as the proof of concept robot. The basic approach to detect the defects was to utilize Cadmium Sulfide (CdS) sensors to detect changes in contrast of an illuminated surface. A neural network, optimally designed utilizing a genetic algorithm, was employed to detect the presence of the defects (cracks). By utilization of the COTS robot and US sensors, the research successfully demonstrated that an evolutionarily designed neural network can detect the presence of surface defects.

Ballard, Gary↗

Evaluation of nearest-neighbor methods for detection of chimeric small-subunit rRNA sequences

Detection of chimeric artifacts formed when PCR is used to retrieve naturally occurring small-subunit (SSU) rRNA sequences may rely on demonstrating that different sequence domains have different phylogenetic affiliations. We evaluated the CHECK_CHIMERA method of the Ribosomal Database Project and another method which we developed, both based on determining nearest neighbors of different sequence domains, for their ability to discern artificially generated SSU rRNA chimeras from authentic Ribosomal Database Project sequences. The reliability of both methods decreases when the parental sequences which contribute to chimera formation are more than 82 to 84% similar. Detection is also complicated by the occurrence of authentic SSU rRNA sequences that behave like chimeras. We developed a naive statistical test based on CHECK_CHIMERA output and used it to evaluate previously reported SSU rRNA chimeras. Application of this test also suggests that chimeras might be formed by retrieving SSU rRNAs as cDNA. The amount of uncertainty associated with nearest-neighbor analyses indicates that such tests alone are insufficient and that better methods are needed.

NASA Discipline Exobiology↗

Physiological Observations and Omics to Develop Personalized Sensormotor Adaptability Countermeasures Using Bed Rest and Space Flight Data

Astronauts experience sensorimotor disturbances during the initial exposure to microgravity and during the re-adapation phase following a return to an earth-gravitational environment. These alterations may disrupt the ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from space flight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual space flight, which crewmembers are likely to experience the greatest challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures that include: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; 3) genotype markers for genetic polymorphisms in Catechol-O-Methyl Transferase, Dopamine Receptor D2, Brain-derived neurotrophic factor and genetic polymorphism of alpha2-adrenergic receptor that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration space flight and an analog bed rest environment. We will be conducting a retrospective study leveraging data already collected from relevant ongoing/completed bed rest and space flight studies. These data will be combined with predictor metrics that will be collected prospectively - behavioral, brain imaging and genomic measures; from these returning subjects to build models for predicting post-mission (bed rest - non-astronauts or space flight - astronauts) adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures that are customized for each crewmember's sensory biases, adaptive capacity, brain structure and functional capacities, and genetic predispositions against decrements in post-mission adaptive capability. This ability will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Mulavara, A. P.↗

Multivariate Methods for Prediction of Geologic Sample Composition with Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) uses pulses of laser light to ablate a material from the surface of a sample and produce an expanding plasma. The optical emission from the plasma produces a spectrum which can be used to classify target materials and estimate their composition. The ChemCam instrument on the Mars Science Laboratory (MSL) mission will use LIBS to rapidly analyze targets remotely, allowing more resource- and time-intensive in-situ analyses to be reserved for targets of particular interest. ChemCam will also be used to analyze samples that are not reachable by the rover's in-situ instruments. Due to these tactical and scientific roles, it is important that ChemCam-derived sample compositions are as accurate as possible. We have compared the results of partial least squares (PLS), multilayer perceptron (MLP) artificial neural networks (ANNs), and cascade correlation (CC) ANNs to determine which technique yields better estimates of quantitative element abundances in rock and mineral samples. The number of hidden nodes in the MLP ANNs was optimized using a genetic algorithm. The influence of two data preprocessing techniques were also investigated: genetic algorithm feature selection and averaging the spectra for each training sample prior to training the PLS and ANN algorithms. We used a ChemCam-like laboratory stand-off LIBS system to collect spectra of 30 pressed powder geostandards and a diverse suite of 196 geologic slab samples of known bulk composition. We tested the performance of PLS and ANNs on a subset of these samples, choosing to focus on silicate rocks and minerals with a loss on ignition of less than 2 percent. This resulted in a set of 22 pressed powder geostandards and 80 geologic samples. Four of the geostandards were used as a validation set and 18 were used as the training set for the algorithms. We found that PLS typically resulted in the lowest average absolute error in its predictions, but that the optimized MLP ANN and the CC ANN often gave results comparable to PLS. Averaging the spectra for each training sample and/or using feature selection to choose a small subset of wavelengths to use for predictions gave mixed results, with degraded performance in some cases and similar or slightly improved performance in other cases. However, training time was significantly reduced for both PLS and ANN methods by implementing feature selection, making this a potentially appealing method for initial, rapid-turn-around analyses necessary for Chemcam's tactical role on MSL. Choice of training samples has a strong influence on the accuracy of predictions. We are currently investigating the use of clustering algorithms (e.g. k-means, neural gas, etc.) to identify training sets that are spectrally similar to the unknown samples that are being predicted, and therefore result in improved predictions

Morris, Richard↗

Tactical Maneuvering Using Immunized Sequence Selection

This paper describes a tactical maneuvering system that uses an artificial immune system based approach for selecting maneuver sequences. This approach combines the problem solving abilities of genetic algorithms with the memory retention characteristics of an immune system. Of significant importance here is the fact that the tactical maneuvering system can make time-critical decisions to accomplish near-term objectives within a dynamic environment. These objectives can be received from a human operator, autonomous executive, or various flight planning specialists. Simulation tests were performed using a high performance military aircraft model. Results demonstrate the potential of using immunized sequence selection in order to accomplish tactical maneuvering objectives ranging from flying to a location while avoiding unforeseen obstacles, to performing relative positioning in support of air combat maneuvering.

Kaneshige, John↗

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗

FOST 2 Upgrade with Hollow-Fiber CTA FO Module and Generation of Osmotic Agent for Microorganism Growth Studies

FOST 2 is an integrated membrane system that incorporates a forward osmosis subsystem and a reverse osmosis subsystem working in series. It has been designed as a post treatment system to process the effluent from the Membrane Aerated Biological Reactor developed at NASA Johnson Space Center and Texas Tech University. Its function is to remove dissolved solids residual such as ammonia and suspended solids, as well as to provide a physical barrier to microbial and viral contamination. A tubular CTA membrane module from HTI and a flat-sheet lipid-base membrane module from Porifera were integrated and tested on FOST 2 in the past, using both a bioreactor's effluent and greywater as the feed solution. This paper documents the performance of FOST 2 after its upgrade with a hollow-fiber CTA membrane module from Toyobo, treating real black-water to generate the osmotic agent solution necessary to conduct growth studies of genetically engineered microorganism for the Synthetic Biological Membrane project.

Water treatment↗

Development and Function of the Mouse Vestibular System in the Absence of Gravity Perception

The hypothesis that was tested in this research was that the absence of gravity perception, such as would occur in space, would affect the development and function of the vestibular and central nervous systems. Further, we postulated that these effects would be more significant at specific stages of post-natal development of the animal. We also proposed the use of molecular genetic approaches that would provide important information as to the hierarchy of gene function during the development and subsequent function of the vestibular system. The tilted (tlt) mutant mouse has been characterized as lacking the ability to provide sensory input to the gravity receptors. The tlt/tlt mutant mice were a particularly attractive model for the study of vestibular function since the primary defect was limited to the receptor part of the vestibular system, and there were no detectable abnormal phenotypes in other organ systems. The goal of the proposed studies was to assess immediate and delayed effects of the lack of gravity perception on the vestibular system. Particular attention was paid to characterizing primarily affected periods of vestibular morphogenesis, and to identifying downstream genetic pathways that are altered in the CNS of the tlt/tlt mutant mouse. The specific aims were: (1) to characterize the postnatal morphogenesis of the CNS in the tlt mutant mouse, using detailed morphometric analysis of isolated vestibular ganglia and brain tissue at different stages of postnatal development and assessment of apoptotic cell death; (2) to examine the expression of selected genes implicated by mutational analysis to be important in vestibular development or function by in situ hybridization or immunohistochemistry in the mutant mice; and (3) to identify other genes involved in vestibular development and function, using differential cloning strategies to isolate genes whose expression is changed in the mutant versus normal vestibular system.

Wolgemuth, Debra J.↗

Improving Efficacy and Safety of Pharmacological Treatment Through Precision Health and Pharmacogenomics

INTRODUCTION: Future spaceflight will require increased crew medical autonomy as exploration class missions expand in duration and distance from Earth, especially for Mars missions. As mission duration increases, it will be essential to have appropriate amounts of effective medication to ensure the maintenance of crew health and performance. Conversely, mass and volume constraints will become more severe as future spaceflight expands beyond low Earth orbit, where resupply is difficult or becomes impossible. These constraints thus convey an urgency to tailor medications for individual crewmembers and further examine appropriate dosing regimens. BACKGROUND: Precision Health is an exciting area of medicine focused on maintaining an individual’s health and performance through in-depth understanding of an individual’s unique clinical and environmental history, genetic makeup, and molecular profiles. This approach can be adapted to better predict, monitor, and address physiological responses to the spaceflight environment. A subset of this field is pharmacogenomics (PGX), the study of how the expressed genome impacts drug responses with the goal of prescribing the right dose of the right drug at the right time. Specifically, PGX testing provides valuable information on an individual’s precise allelic variations to guide physicians in making informed decisions on drug choice and dosing to avoid adverse events and maximize efficacy. The study goal was to identify which current space pharmacy drugs could be evaluated using PGX testing and to understand the potential impact on the health and wellness of the astronaut population. Additionally, we sought to evaluate clinically available FDA-approved PGX testing solutions to better understand its applicability. METHODS: A complete list of drugs on the ISS was analyzed for risk and likelihood of drug failure and PGX actionability. This analysis encompassed both astronauts’ personal medications, including supplements and over the counter drugs (n=151) contained in the ISS medical accessory kit (IMAK), and ISS MedKit formulary medications (n=95). Duplicate medications and different formulations were removed, which resulted in a total of 157 drugs used in the subsequent analysis. A 5x5 risk assessment table was produced by examining the likelihood of drug failure compared to the consequence of drug failure (LxC). Likelihood of individual drug failure was defined by whether existing processes are sufficient to prevent ineffective treatment or impactful side effect events, as ranked from 1 (very low, can easily be prevented) to 5 (very high, cannot be prevented) during a Mars mission. In contrast, the consequence of drug failure was defined by impact to safety, schedule, cost, or technical criteria and ranked from 1 (very low) to 5 (very high). An assessment of PGX reference laboratories is currently underway to evaluate sample requirements, benefit analysis (cost vs. utility of allele variant analysis), relevance to inflight medication usage, quality of reporting in enabling clinical application, and ease of integration into electronic medical records. RESULTS: Risk assessments (LxC 5x5 table) indicated 128 medications were in the green zone where risk is acceptable, with the remaining 29 of the medications in the yellow or red zone driven predominantly due to drug failure or safety concerns. We found that current PGX testing results could impact 21% of the total medications in the ISS MedKit and IMAK; of these, 9 medications currently have direct clinically actionable guidance available. Results of the clinical PGX solution evaluations as related to these medications will be presented. CONCLUSION: PGX testing has demonstrated clear benefits in terrestrial medicine and clinical environments for the selection of proper medications, avoiding adverse drug reactions, and maximizing drug efficacy. We propose that similar benefits would be bestowed on the astronaut and commercial spaceflight passenger population by performing preemptive preflight PGX testing to reduce risk of mission failure due to ineffective or toxic medications, improve drug efficacy, and further open the door to countermeasure research. For example, PGX results could allow tailoring of specific medications at optimal doses more precisely to each individual astronaut, particularly in areas of space motion sickness, sleep aids, and analgesics. An additional benefit is that PGX results could provide information for better planning of the components of a space pharmacy for deep space missions to be more effective and efficient in the utilization of limited pharmaceutical resources. Finally, while PGX testing of the astronaut corps is not currently conducted, this approach could provide immediate impact in support of mission success by reducing risks, optimizing astronaut performance, and providing valuable insights into long-term astronaut health. Such advancements in clinical decision making are important next steps in building dynamic individual risk profiles for astronauts, increasing selection of the best treatment choice, and providing tailored countermeasures for individual crewmembers.

Pharmacogenomics↗

Radiation effects in Caenorhabditis elegans - Mutagenesis by high and low LET ionizing radiation

The nematode C. elegans was used to measure the effectiveness of high-energy ionized particles in the induction of three types of genetic lesions. Recessive lethal mutations in a 40-map unit autosomal region, sterility, and X-chromosome nondisjunction or damage were investigated. Induction rates were measured as a function of linear energy transfer, LET(infinity), for nine ions of atomic nunmber 1-57 accelerated at the BEVALAC accelerator. Linear kinetics were observed for all three types of lesions within the dose/fluence ranges tested and were found to vary strongly as a function of particle LET(infinity). Relative biological effectiveness (RBE) values of up to 4.2 were measured, and action cross sections were calculated and compared to mutagenic responses in other systems.

Nelson, Gregory A.↗

EcAMSat: Effect of Space-Flight on Antibiotic Resistance of a Pathogenic Bacterium and its Genetic Basis

Human immune response is compromised in space and incidence of urinary tract infections (UTI) in astronauts has been reported. We have found that the causative agent of UTI, the uropathogenic Escherichia coli, becomes more resistant to gentamicin (Gm), which is commonly used to treat this disease, under modeled microgravity conditions (MMG), the increase being controlled by the stress response master regulator, σs. While the wild type bacterium becomes virtually invincible under MMG, the strain missing this sigma factor barely survives. We report here preparatory ground work for testing this finding in space flight on a nanosatellite. We have shown that the effect of Gm treatment on culture viability is directly correlated to increased Alamar Blue (AB) reduction; we have identified conditions to keep the experimental elements - the bacterial cultures, Gm, and AB - in a state of viability and potency to permit successful spaceflight experimentation given the necessary constraints. Spaceflight kinetics of AB reduction will be transmitted from the satellite via telemetry. The PharmaSat hardware previously used for space experimentation with yeast was modified to permit studies with bacteria by reducing the filter pore size and increasing fluidics volume to enable more fluid exchanges. Several verification tests have been run using the nanosatellite's flight software and prototype hardware. Cells were grown to stationary phase to induce the σs-controlled stress resistance and treated with Gm. Without Gm, the mutant took longer than the wild type to reduce the AB; this time difference increased almost 8 fold at 55 μg/mL Gm concentration. Thus, using flight hardware the mutant shows similarly increased sensitivity to Gm compared to the wild type to that found in our pilot microtiter plate experiments. Previous inflight experiments have given contradictory results concerning bacterial antibiotic resistance; none has yet explored the involvement of specific genes in this phenomenon. With our system ready to fly in late 2015/early 2016, these questions can be approached

uropathogenic E. coli↗

Cell biology experiments conducted in space

A review of cell biology experiments conducted during the first two decades of space flight is provided. References are tabulated for work done with six types of living test system: isolated viruses, bacteriophage-host, bacteria, yeasts and filamentous fungi, protozoans, and small groups of cells (such as hamster cell tissue and fertilized frog eggs). The general results of studies involving the survival of cells in space, the effect of space flight on growing cultures, the biological effects of multicharged high-energy particles, and the effects of space flight on the genetic apparatus of microorganisms are summarized. It is concluded that cell systems remain sufficiently stable during space flight to permit experimentation with models requiring a fixed cell line during the space shuttle era.

Taylor, G. R.↗

Ultrastructure of meristem and root cap of pea seedlings under spaceflight conditions

Data of electron microscopic analysis of meristem and root cap of pea seedlings grown aboard the Salyut-6 orbital research station in the Oazis apparatus and in the laboratory are presented. The main morphological and anatomical characteristics of the test and control plants are shown to be similar. At the same time, some differences are found in the structural and functional organization of the experimental cells as compared to the controls. They concern first of all the plastic apparatus, mitochondria and Golgi apparatus. It is assumed that cell function for certain periods of weightlessness on the whole ensures execution of the cytodifferentiation programs genetically determined on the Earth. Biochemical and physiological processes vary rather markedly due to lack of initially rigorous determination.

Sytnyk, K. M.↗