On the possible role of protein vibrations in information processing in the brain: three Russian dolls

The Computational Boundary of a "Self": Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

All epistemic agents physically consist of parts that must somehow comprise an integrated cognitive self. Biological individuals consist of subunits (organs, cells, and molecular networks) that are themselves complex and competent in their own native contexts. How do coherent biological Individuals result from the activity of smaller sub-agents? To understand the evolution and function of metazoan creatures' bodies and minds, it is essential to conceptually explore the origin of multicellularity and the scaling of the basal cognition of individual cells into a coherent larger organism. In this article, I synthesize ideas in cognitive science, evolutionary biology, and developmental physiology toward a hypothesis about the origin of Individuality: "Scale-Free Cognition." I propose a fundamental definition of an Individual based on the ability to pursue goals at an appropriate level of scale and organization and suggest a formalism for defining and comparing the cognitive capacities of highly diverse types of agents. Any Self is demarcated by a computational surface - the spatio-temporal boundary of events that it can measure, model, and try to affect. This surface sets a functional boundary - a cognitive "light cone" which defines the scale and limits of its cognition. I hypothesize that higher level goal-directed activity and agency, resulting in larger cognitive boundaries, evolve from the primal homeostatic drive of living things to reduce stress - the difference between current conditions and life-optimal conditions. The mechanisms of developmental bioelectricity - the ability of all cells to form electrical networks that process information - suggest a plausible set of gradual evolutionary steps that naturally lead from physiological homeostasis in single cells to memory, prediction, and ultimately complex cognitive agents, via scale-up of the basic drive of infotaxis. Recent data on the molecular mechanisms of pre-neural bioelectricity suggest a model of how increasingly sophisticated cognitive functions emerge smoothly from cell-cell communication used to guide embryogenesis and regeneration. This set of hypotheses provides a novel perspective on numerous phenomena, such as cancer, and makes several unique, testable predictions for interdisciplinary research that have implications not only for evolutionary developmental biology but also for biomedicine and perhaps artificial intelligence and exobiology.

A Self-Consistent Sonification Method to Translate Amino Acid Sequences into Musical Compositions and Application in Protein Design Using Artificial Intelligence

We report a self-consistent method to translate amino acid sequences into audible sound, use the representation in the musical space to train a neural network, and then apply it to generate protein designs using artificial intelligence (AI). The sonification method proposed here uses the normal mode vibrations of the amino acid building blocks of proteins to compute an audible representation of each of the 20 natural amino acids, which is fully defined by the overlay of its respective natural vibrations. The vibrational frequencies are transposed to the audible spectrum following the musical concept of transpositional equivalence, playing or writing music in a way that makes it sound higher or lower in pitch while retaining the relationships between tones or chords played. This transposition method ensures that the relative values of the vibrational frequencies within each amino acid and among different amino acids are retained. The characteristic frequency spectrum and sound associated with each of the amino acids represents a type of musical scale that consists of 20 tones, the "amino acid scale". To create a playable instrument, each tone associated with the amino acids is assigned to a specific key on a piano roll, which allows us to map the sequence of amino acids in proteins into a musical score. To reflect higher-order structural details of proteins, the volume and duration of the notes associated with each amino acid are defined by the secondary structure of proteins, computed using DSSP and thereby introducing musical rhythm. We then train a recurrent neural network based on a large set of musical scores generated by this sonification method and use AI to generate musical compositions, capturing the innate relationships between amino acid sequence and protein structure. We then translate the de novo musical data generated by AI into protein sequences, thereby obtaining de novo protein designs that feature specific design characteristics. We illustrate the approach in several examples that reflect the sonification of protein sequences, including multihour audible representations of natural proteins and protein-based musical compositions solely generated by AI. The approach proposed here may provide an avenue for understanding sequence patterns, variations, and mutations and offers an outreach mechanism to explain the significance of protein sequences. The method may also offer insight into protein folding and understanding the context of the amino acid sequence in defining the secondary and higher-order folded structure of proteins and could hence be used to detect the effects of mutations through sound.

How water mediates the long-range interactions between remote protein molecules

A mechanism of the influence of the presence of one protein molecule on the internal dynamics of another is proposed.

On Having No Head: Cognition throughout Biological Systems

The central nervous system (CNS) underlies memory, perception, decision-making, and behavior in numerous organisms. However, neural networks have no monopoly on the signaling functions that implement these remarkable algorithms. It is often forgotten that neurons optimized cellular signaling modes that existed long before the CNS appeared during evolution, and were used by somatic cellular networks to orchestrate physiology, embryonic development, and behavior. Many of the key dynamics that enable information processing can, in fact, be implemented by different biological hardware. This is widely exploited by organisms throughout the tree of life. Here, we review data on memory, learning, and other aspects of cognition in a range of models, including single celled organisms, plants, and tissues in animal bodies. We discuss current knowledge of the molecular mechanisms at work in these systems, and suggest several hypotheses for future investigation. The study of cognitive processes implemented in aneural contexts is a fascinating, highly interdisciplinary topic that has many implications for evolution, cell biology, regenerative medicine, computer science, and synthetic bioengineering.

Dehydration and Cognition in Geriatrics: A Hydromolecular Hypothesis

Dehydration is one of the ten most frequent diagnoses responsible for the hospital admission of elderly in the United States. It is associated with increased mortality, morbidity and an estimated cost of 1.14 billion per year (Xiao et al., 2004; Schlanger et al., 2010; Pretorius et al., 2013; Frangeskou et al., 2015). Older individuals are predisposed to dehydration encephalopathy as a result of decreased total body water (TBW) and diminished sensation of thirst. We hypothesize that thirst blunting in older individuals is the result of a defective microRNA-6842-3p failing to silence the expression of the vesicular GABA transporters (VGAT) and alpha 7 cholinergic nicotinic receptors in the subfornical organ (SFO) of the hypothalamus. We hypothesize further that resultant dehydration facilitates protein misfolding and aggregation, predisposing to neurocognitive disorders. We completed a search of predicted microRNA targets, utilizing the public domain tool miRDB and found that microRNA-6842-3p modulates the SLC6A1 and CHRNA7 genes both of which were previously hypothesized to inhibit the thirst sensation by their action on SFO. The primary aim of this article is to answer two questions: Can prevention and correction of dehydration in elderly lower age-related cognitive deterioration? Can exosomal miR-6842 in the peripheral blood predict dehydration encephalopathy in elderly?

Intercellular Signaling in Cancer-the SMT and TOFT Hypotheses, Exosomes, Telocytes and Metastases: Is the Messenger in the Message?

This review examines the current two leading hypotheses relating to cancer neogenesis—the somatic mutation theory (SMT) and the tissue organization field theory (TOFT)—and focuses on four specific issues.

What are the details of the process that changes the epigenetic cargo of the exosomes a cell produces when it becomes malignant?

Can exosomes produced by a malignant cell induce on their own a metastatic cancer in the target tissue?

What is the functional significance of the fact that exosomes from cancer cells carry in their loads segments of genomic DNA bearing cancer-related mutations across the entire spectrum?

What is the evolutionary advantage for the organism of the production by its cancer cells of exosomes that carry epigenetic instructions for the building of elaborate molecular mechanisms that promote the growth of metastatic cancers?

These issues are examined with a view of determining the support they give to one or other of the two hypotheses. The conclusion is that they support a specific form of TOFT in which exosomes play a key role.