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From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

Ross, Muriel D.↗

Climate Lecture 4: Atmospheric Radiation

The climate system is well known for its great complexity and complex interactions that involve dynamic, thermodynamic, radiative, chemical, biological and human-driven processes. This view of the climate system has emerged from detailed measurements, meticulous record keeping, and theoretical analyses arising from, and made possible by the science and technology revolution that greatly advanced our understanding the role of physical processes that operate in the global climate system. These measurements also show very clearly that the global surface temperature has been rising over the past century, and that this is a consequence of human industrial activity.

Oinas, Valdar↗

Complexity for Survival of Living Systems

A logical connection between the survivability of living systems and the complexity of their behavior (equivalently, mental complexity) has been established. This connection is an important intermediate result of continuing research on mathematical models that could constitute a unified representation of the evolution of both living and non-living systems. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the two most relevant being Characteristics of Dynamics of Intelligent Systems (NPO- 21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; and Self-Supervised Dynamical Systems (NPO- 30634) NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72. As used here, living systems is synonymous with active systems and intelligent systems. The quoted terms can signify artificial agents (e.g., suitably programmed computers) or natural biological systems ranging from single-cell organisms at one extreme to the whole of human society at the other extreme. One of the requirements that must be satisfied in mathematical modeling of living systems is reconciliation of evolution of life with the second law of thermodynamics. In the approach followed in this research, this reconciliation is effected by means of a model, inspired partly by quantum mechanics, in which the quantum potential is replaced with an information potential. The model captures the most fundamental property of life - the ability to evolve from disorder to order without any external interference. The model incorporates the equations of classical dynamics, including Newton s equations of motion and equations for random components caused by uncertainties in initial conditions and by Langevin forces. The equations of classical dynamics are coupled with corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces that are gradients of the information potential, which, in turn, is a function of the probability densities. The probability densities are associated with mental images both self-image and nonself images (images of external objects that can include other agents). The evolution of the probability densities represents mental dynamics. Then the interaction between the physical and metal aspects of behavior is implemented by feedback from mental to motor dynamics, as represented by the aforementioned fictitious forces. The interaction of a system with its self and nonself images affords unlimited capacity for increase of complexity. There is a biological basis for this model of mental dynamics in the discovery of mirror neurons that learn by imitation. The levels of complexity attained by use of this model match those observed in living systems. To establish a mechanism for increasing the complexity of dynamics of an active system, the model enables exploitation of a chain of reflections exemplified by questions of the form, "What do you think that I think that you think...?" Mathematically, each level of reflection is represented in the form of an attractor performing the corresponding level of abstraction with more details removed from higher levels. The model can be used to describe the behaviors, not only of biological systems, but also of ecological, social, and economics ones.

Zak, Michail↗

The adsorption and reaction of adenine nucleotides on montmorillonite

The binding of AMP to Zn(2+)-montmorillonite is investigated in the presence of salts and Good's zwitterion buffers, PIPES and MES. The initial concentrations of nucleotide and the percent adsorbtion are used to calculate the adsorption isotherms, and the Langmuir adsorption equation is used for the analysis of data. The adsorption coefficient was found to be three times greater in the presence of 0.2 M PIPES than in its absence. In addition, basal spacings measured by X-ray diffraction were increased by the buffer. These results are interpreted in terms of a model in which the adsorption of AMP is mediated by a Zn(2+) complex of PIPES in different orientations in the interlamellar region of the montmorillonite. Mixed ligand complexes of this type are reminiscent of the complexes observed between metal ions and biological molecules in living systems.

Ferris, James P.↗

Communal Sensor Network for Adaptive Noise Reduction in Aircraft Engine Nacelles

Emergent behavior, a subject of much research in biology, sociology, and economics, is a foundational element of Complex Systems Science and is apropos in the design of sensor network systems. To demonstrate engineering for emergent behavior, a novel approach in the design of a sensor/actuator network is presented maintaining optimal noise attenuation as an adaptation to changing acoustic conditions. Rather than use the conventional approach where sensors are managed by a central controller, this new paradigm uses a biomimetic model where sensor/actuators cooperate as a community of autonomous organisms, sharing with neighbors to control impedance based on local information. From the combination of all individual actions, an optimal attenuation emerges for the global system.

Jones, Kennie H.↗

Can the chirality of the ISM be measured

Many moderately complex carbon-based molecules of the type associated with biological systems can exist in one of two mirror-image forms (left-handed and right-handed), which can be distinguished on the basis of their influence on the state of polarization of a light beam. Both forms are possible in nature; yet in living organisms it is invariably the rule that one of these two species predominates. This gives rise to a net chirality. One possible explanation for the net chirality is that the early earth was somehow seeded from the ISM with an excess of chiral organic compounds which led to the development of life forms which are based on left-handed amino acids and right-handed sugars. Molecular spectroscopy of the interstellar medium (ISM) has revealed a complex variety of molecular species similar to those thought to have been available in the oceans and atmospheres of the earth at the time life formed. The detection of such molecules demonstrates the generality of the chemical processes occurring in both environments. If this generality extends to the processes which produce chirality, it may be possible to detect a net chirality in the ISM. This is of particular interest because determining whether or not net chirality exists elsewhere in the universe is an essential aspect of understanding how life developed on earth and how widely distributed it might be. Researchers report preliminary results of a feasibility study to determine whether or not a net chirality in the ISM can be measured. If laboratory results identify candidate chiral molecules that might exist in the ISM, the next step in this feasibility study will be to estimate the detectability of the chiral signature in astrophysical environments.

Pendleton, Y.↗

Is Water a Universal Solvent for Life?

There are strong reasons to believe that the laws, principles and constraints of physics and chemistry are universal. It is much less clear how this universality translates into our understanding of the origins of life. Conventionally, discussions of this topic focus on chemistry that must be sufficiently rich to seed life. Although this is clearly a prerequisite for the emergence of living systems, I propose to focus instead on self-organization of matter into functional structures capable of reproduction, evolution and responding to environmental changes. In biology, most essential functions are largely mediated by noncovalent interactions (interactions that do not involve making or breaking chemical bonds). Forming chemical bonds is only a small part of what living systems do. There are specific implications of this point of view for universality. I will concentrate on one of these implications. Strength of non-covalent interactions must be properly tuned. If they were too weak, the system would exhibit undesired, uncontrolled response to natural fluctuations of physical and chemical parameters. If they were too strong kinetics of biological processes would be slow and energetics costly. This balance, however, is not a natural property of complex chemical systems. Instead, it has to be achieved with the aid of an appropriate solvent for life. In particular, potential solvents for life must be characterized by a high dielectric constant to ensure solubility of polar species and sufficient flexibility of biological structures stabilized by electrostatic interactions. Among these solvents, water exhibits a remarkable trait that it also promotes solvophobic (hydrophobic) interactions between non-polar species, typically manifested by a tendency of these species to aggregate and minimize their contacts with the aqueous solvent. Hydrophobic interactions are responsible, at least in part, for many self-organization phenomena in biological systems, such as the formation of cellular boundary structures or protein folding. Strengths of electrostatic and hydrophobic interactions are similar and can be balanced over a wide range of temperatures, which considerably increases the repertoire of interactions that can be used to modulate biological functions. Some properties of water, e.g. its chemical activity against polymerization reactions, are considered as unfavorable to life. In actuality, this might be a favorable trait because life requires a balance between constructive and destructive processes. For example, molecules synthesized in response to specific conditions must be degraded once these conditions change. Otherwise regulation of biological processes would be virtually impossible. Water might not be the only liquid with favorable properties for supporting life. It has been proposed that formamide, which might be present elsewhere in the universe in sufficient quantities to warrant interest, could be a potential alternative to water for the origin of life. However, this will remain highly hypothetical until it is demonstrated in further studies on its physical, chemical and biological properties it is capable of mediating self-organization of matter and providing proper balance between different types of non-covalent interactions.

Pohorill, Andrew↗

Co-leveraging Scientific Advances in Space Biology and Astrobiology Towards Achieving NASA’s Life Science Objectives

Executive Summary: Distinct lines of scientific inquiry drives the separation of NASA’s fundamental life science research into Space Biology and Astrobiology. This division developed as a way to place life scientists alongside experts in the physical constraints that define the acclimation, adaptation and evolution of biology systems relevant to their respective subjects. For astrobiology, integration with disciplines such as geology, geochemistry, astronomy, planetary science, etc., enables a comprehensive assessment of the physical environment and its co-evolution with biological processes. Space Biology’s co-location with Physical Sciences places life science researchers adjacent to experts in the physical phenomena associated with microgravity and spaceflight, enabling an understanding of how the spaceflight environment affects biological systems. Despite this separation, aspects of both disciplines have converged on a similar, fundamental objective: to describe and understand the dynamics of complex living communities in the contexts of their physical environments. While the environmental systems and timescales are dramatically different, continuing to motivate the separation into distinct fields, similarities in the underlying objective present opportunities to find efficiencies, reduce overlap, and minimize duplication of effort. Space Biology and Astrobiology share a common need to understand microbial physiology in extreme environments – whether the ‘built’ spaceflight environment or the natural environments in which many astrobiology studies are conducted. In particular, open questions in each discipline require the development of quantitative frameworks, applicable at the ecosystem level, that support predictive capabilities for environments where observations are sparse. Additionally, both disciplines have a need to prepare, detect, and analyze the (potential) biological signal in complex samples-often in a completely autonomous fashion. The next decade will see NASA Space Biology moving to understand and describe the effects of the beyond low-earth orbit (BLEO) spaceflight environment on living systems. This new direction will dramatically reduce the opportunities for ground-based analysis of space-flown samples, driving space biology investigations towards fully autonomous experiments and missions. At the same time, astrobiology life detection missions aimed at detecting biosignatures on Mars and icy moons in the outer solar system could benefit from fully automated sample processing and analysis. There are opportunities to leverage instrument and method development between both disciplines within the context of these BLEO missions.

Astrobiology↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth independence and autonomy of mission operations. Here we present an overview of AI/ML architecture to support deep space mission goals, developed with leaders in the field. First, we focus on the fundamental biological research that supports our understanding of physiological responses to spaceflight, and we describe current efforts to support AI/ML research including data standardization and data engineering through maximally open and FAIR (findable, accessible, interoperable, reusable) databases and the generation of AI-ready datasets for reuse and analysis. We also discuss remote data management frameworks for research data as well as environmental and health data that are generated during deep space missions. We highlight several research projects that leverage data standardization and management for fundamental biological discovery to uncover the complex effects of space travel on living systems. Next, we provide an overview of cutting-edge AI/ML approaches that can be integrated to support remote monitoring and analysis during deep space missions, including generative models and large language models to learn the underlying biomedical patterns and predict outcomes or answer questions during off world medical scenarios. We also describe current AI/ML methods to support this research and monitoring through automated cloud-based labs which enable limited human intervention and closed-loop experimentation in remote settings. These labs could support mission autonomy by analyzing environmental data streams, and would be facilitated through in situ analytics capabilities to avoid sending large raw data files through low bandwidth communications. Finally, in the context of deep space missions with limited communications or access to medical advice from Earth, we describe a solution for integrated, real-time mission biomonitoring across hierarchical levels from continuous environmental monitoring, to wearables and point-of-care devices, to molecular and physiological monitoring. We introduce a precision space health system that will ensure that the future of space health is predictive, preventative, participatory and personalized.

artificial intelligence↗

BioWires: Conductive DNA Nanowires in a Computationally-Optimized, Synthetic Biological Platform for Nanoelectronic Fabrication

DNA is an ideal template for a biological nanowire-it has a linear structure several atoms thick; it possesses addressable nucleobase geometry that can be precisely defined; and it is massively scalable into branched networks. Until now, the drawback of DNA as a conducting nanowire been, simply put, its low conductance. To address this deficiency, we extensively characterize a chemical variant of canonical DNA that exploits the affinity of natural cytosine bases for silver ions. We successfully construct chains of single silver ions inside double-stranded DNA, confirm the basic dC-Ag+-dC bond geometry and kinetics, and show length-tunability dependent on mismatch distribution, ion availability and enzyme activity. An analysis of the absorbance spectra of natural DNA and silver-binding, poly-cytosine DNA demonstrates the heightened thermostability of the ion chain and its resistance to aqueous stresses such as precipitation, dialysis and forced reduction. These chemically critical traits lend themselves to an increase in electrical conductivity of over an order of magnitude for 11-base silver-paired duplexes over natural strands when assayed by STM break junction. We further construct and implement a genetic pathway in the E. coli bacterium for the biosynthesis of highly ionizable DNA sequences. Toward future circuits, we construct a model of transcription network architectures to determine the most efficient and robust connectivity for cell-based fabrication, and we perform sequence optimization with a genetic algorithm to identify oligonucleotides robust to changes in the base-pairing energy landscape. We propose that this system will serve as a synthetic biological fabrication platform for more complex DNA nanotechnology and nanoelectronics with applications to deep space and low resource environments.

DNA↗

Processes that Drove the Transition from Chemistry to Biology: Concepts and Evidence

Two properties are particularly germane to the transition from chemistry to biology. One is the emergence of complex molecules (polymers) capable of performing non-trivial functions, such as catalysis, energy transduction or transport across cell walls. The other is the ability of several functions to work in concert to provide reproductive advantage to systems hosting these functions. Biological systems exhibit these properties at remarkable levels of efficiency and accuracy in a way that appears effortless. However, dissection of these properties reveals great complexities that are involved. This opens a question: how a simple, ancestral system could have acquired the required properties? Other questions follow. What are the chances that a functional polymer emerges at random? What is the minimum structural complexity of a polymer to carry out a function at a reasonable level of efficiency? Can we identify concrete, protobiologically plausible mechanisms that yield advantageous coupling between different functions? These and similar questions are at the core of the main topic of this session: how soulless chemistry became life? Clearly, we do not have complete answers to any of these questions. However, in recent years a number of new and sometimes unexpected clues have been brought to light. Of particular interest are proteins because they are the main functional polymers in contemporary cells. The emergence of protein functions is a puzzle. It is widely accepted that a well ]defined, compact structure (fold) is a prerequisite for function. It is equally widely accepted that compact folds are rare among random amino acid polymers. Then, how did protein functionality start? According to one hypothesis well folded were preceded by their poorly folded, yet still functional ancestors. Only recently, however, experimental evidence supporting this hypothesis has been presented. In particular, a small enzyme capable of ligating two RNA fragments with the rate of 106 above background was evolved in vitro. This enzyme does not look like any contemporary protein. It is very flexible and its structure is kept together just by a single salt bridge between a charged residue and a coordinating zinc. A similar picture emerges from studies of simple transmembrane channels that mimic those in ancestral cells. Again, they are extremely flexible and do not form a conventional pore. Yet, they efficiently mediate ion transport. Studies on simple proteins that are on-going in several laboratories hold promise of revealing crucial links between chemical and biological catalysis and other ubiquitous cell functions. Interaction between composition, growth and division of protobiologically relevant vesicles and metabolic reactions that they encapsulate is an example of coupling between simple functions that promotes reproduction and evolution. Recent studies have demonstrated possible mechanisms by which vesicles might have evolved their composition from fatty acids to phospholipids, thus facilitating a number of new cellular functions. Conversely, it has been also demonstrated that an encapsulated metabolism might drive vesicle division. These are, again, examples of processes that might have driven the transition from chemistry to biology.

Pohorille, Andrew↗

Modular and Stochastic Approaches to Molecular Pathway Models of ATM, TGF beta, and WNT Signaling

Deterministic pathway models that describe the biochemical interactions of a group of related proteins, their complexes, activation through kinase, etc. are often the basis for many systems biology models. Low dose radiation effects present a unique set of challenges to these models including the importance of stochastic effects due to the nature of radiation tracks and small number of molecules activated, and the search for infrequent events that contribute to cancer risks. We have been studying models of the ATM, TGF -Smad and WNT signaling pathways with the goal of applying pathway models to the investigation of low dose radiation cancer risks. Modeling challenges include introduction of stochastic models of radiation tracks, their relationships to more than one substrate species that perturb pathways, and the identification of a representative set of enzymes that act on the dominant substrates. Because several pathways are activated concurrently by radiation the development of modular pathway approach is of interest.

Cucinotta, Francis A.↗

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

Dufrene, Warren R., Jr.↗

Fundamental Physics Program and the NASA Mission

The accomplishments of Physics, the increasing power of its instruments, and its expanding reach into other sciences have generated an unprecedented set of scientific opportunities. The committee has identified six such Grand Challenges listed below in no particular order: Developing quantum technologies. Creating new materials. Understanding complex systems. Unifying the forces of Nature. Exploring the universe Applying Physics to Biology.

Trinh, Eugene↗

Artificial Intelligence Based Control Power Optimization on Tailless Aircraft

Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process.

Gern, Frank↗

A Powerful Toolkit for Synthetic Biology: Over 3.8 Billion Years of Evolution

The combination of evolutionary with engineering principles will enhance synthetic biology. Conversely, synthetic biology has the potential to enrich evolutionary biology by explaining why some adaptive space is empty, on Earth or elsewhere. Synthetic biology, the design and construction of artificial biological systems, substitutes bio-engineering for evolution, which is seen as an obstacle. But because evolution has produced the complexity and diversity of life, it provides a proven toolkit of genetic materials and principles available to synthetic biology. Evolution operates on the population level, with the populations composed of unique individuals that are historical entities. The source of genetic novelty includes mutation, gene regulation, sex, symbiosis, and interspecies gene transfer. At a phenotypic level, variation derives from regulatory control, replication and diversification of components, compartmentalization, sexual selection and speciation, among others. Variation is limited by physical constraints such as diffusion, and chemical constraints such as reaction rates and membrane fluidity. While some of these tools of evolution are currently in use in synthetic biology, all ought to be examined for utility. A hybrid approach of synthetic biology coupled with fine-tuning through evolution is suggested

Rothschild, Lynn J.↗

Simple systems that exhibit self-directed replication

Biological experience and intuition suggest that self-replication is an inherently complex phenomenon, and early cellular automata models support that conception. More recently, simpler computational models of self-directed replication called sheathed loops have been developed. It is shown here that 'unsheathing' these structures and altering certain assumptions about the symmetry of their components leads to a family of nontrivial self-replicating structures some substantially smaller and simpler than those previously reported. The dependence of replication time and transition function complexity on initial structure size, cell state symmetry, and neighborhood are examined. These results support the view that self-replication is not an inherently complex phenomenon but rather an emergent property arising from local interactions in systems that can be much simpler than is generally believed.

Reggia, James A.↗

Biosynthetic Porphyrins and the Origin of Photosynthesis

Since the prebiotic atmosphere was anaerobic, if not reducing, a useful function of primordial photosynthesis would have been to photooxidize reduced substrates such as Fe(+2), S(-2) or reduced organic molecules and to emit hydrogen. Experiments have shown that the early biogenic pigments uroporphyrin and coproporphyrin do photooxidize organic compounds and emit hydrogen in the presence of a platinum catalyst. These experiments were carried out in dilute aqueous solution near neutral pH under anaerobic atmosphere, and quantum yields near 10-2 were obtained. Thus relevant prebiotic conditions were maintained. Rather then to further optimize conditions, attempts were made to replace the platinum catalyst by a more prebiotically suitable catalyst. Trials with an Fe4S4(SR)4 cluster, in analogy to the present hydrogenase and nitrogenase, were not successful. However, experiments using cobalt complexes to catalyze the formation of hydrogen are promising. In analogy with biological photosynthetic systems which group pigments, electron transfer molecules and enzymes in clusters for efficiency, it was found that binding the biogenic porphyrins to the polyvinyl alcohol used to support the platinum catalyst did increase the quantum yield of the reaction. It was also found that ultraviolet light can serve to photo-oxidize porphyrinogens to porphyrins under anaerobic conditions. Thus the formation of the colorless porphyriogens by the extraordinarily simple biosynthetic pathway would not be a problem because of the prevalence of UV light in the prebiotic, anoxic atmosphere.

David Mauzerall↗