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Microtubules (MTs) are essential cytoskeletal polymers of eukaryote cells implicated in various cell functions, including cell division, cargo transfer, and cell signaling. MTs also are highly charged polymers that generate electrical oscillations that may underlie their ability to act as nonlinear transmission lines. However, the oscillatory composition and time–frequency differences of the MT electrical oscillations have not been identified. Here, we applied the Empirical Mode Decomposition (EMD) to bovine brain MT sheet recordings to determine the number and fundamental frequencies of the Intrinsic Modes Functions (IMF) and evaluate their energetic contribution to the electrical signal. As previously reported, raw signals were obtained from cow brain MTs (Cantero et al. Sci Rep 6:27143, 2016), sampled, filtered, and subjected to signal decomposition from representative experiments. Filtered signals (200 Hz) allowed us to identify either six or seven IMFs. The reconstructed tracings faithfully resembled the original signals, with identifiable frequency peaks. To extend the analysis to obtain time–frequency information and the energy implicated in each IMF, we applied the Hilbert–Huang Transform (HHT) and the Continuous Wavelet Transform (CWT) to the same samples. The analyses disclosed the presence of more fundamental frequency peaks than initially reported and evidenced the advantages and disadvantages of each transform. The study indicates that the EMD is a robust approach to quantifying signal decomposition of brain MT oscillations and suggests novel similarities with human brain wave electroencephalogram (EEG) recordings. The evidence points to the potentially fundamental role of MT oscillations in brain electrical activity. [ABSTRACT FROM AUTHOR]

A vectorial distance measure for trees is presented. Given two trees, we define a Tree-Alignment (T-Alignment). We T-align the trees from their centers outwards, starting from the root-branches, to make the next level as similar as possible. The algorithm is recursive; condition on the T-alignment of the root-branches we T-align the sub-branches, thereafter each T-alignment is conditioned on the previous one. We define a minimal T-alignment under a lexicographic order which follows the intuition that the differences between the two trees constitutes a vector. Given such a minimal T-alignment, the difference in the number of branches calculated at any level defines the entry of the distance vector at that level. We compare our algorithm to other well-known tree distance measures in the task of clustering sets of phylogenetic trees. We use the TreeSimGM simulator for generating stochastic phylogenetic trees. The vectorial tree distance (VTD) can successfully separate symmetric from asymmetric trees, and hierarchical from non-hierarchical trees. We also test the algorithm as a classifier of phylogenetic trees extracted from two members of the fungi kingdom, mushrooms and mildews, thus showimg that the algorithm can separate real world phylogenetic trees. The Matlab code can be accessed via: https://gitlab.com/avner.priel/vectorial-tree-distance. [ABSTRACT FROM AUTHOR]

We present a two sided resource allocation problem, between demands and supplies, where both parties are ranked. For example, in Big Data problems where a set of different computational tasks is divided between a set of computers each with its own resources, or between employees and employers where both parties are ranked, the employees by their fitness and the employers by their package benefits. The allocation process can be viewed as a repeated game where in each iteration the strategy is decided by a meta-rule, based on the ranks of both parties and the results of the previous games. We show the existence of a phase transition between an absorbing state, where all demands are satisfied, and an active one where part of the demands are always left unsatisfied. The phase transition is governed by the ratio between supplies and demand. In a job allocation problem we find positive correlation between the rank of the workers and the rank of the factories; higher rank workers are usually allocated to higher ranked factories. These all suggest global emergent properties stemming from local variables. To demonstrate the global versus local relations, we introduce a local inertial force that increases the rank of employees in proportion to their persistence time in the same factory. We show that such a local force induces non trivial global effects, mostly to benefit the lower ranked employees. [ABSTRACT FROM AUTHOR]

This paper discusses the possibility of quantum coherent oscillations playing a role in neuronal signaling. Consciousness correlates strongly with coherent neural oscillations, however the mechanisms by which neurons synchronize are not fully elucidated. Recent experimental evidence of quantum beats in light-harvesting complexes of plants (LHCII) and bacteria provided a stimulus for seeking similar effects in important structures found in animal cells, especially in neurons. We argue that microtubules (MTs), which play critical roles in all eukaryotic cells, possess structural and functional characteristics that are consistent with quantum coherent excitations in the aromatic groups of their tryptophan residues. Furthermore we outline the consequences of these findings on neuronal processes including the emergence of consciousness. [ABSTRACT FROM AUTHOR]

This paper discusses the possibility of quantum coherent oscillations playing a role in neuronal signaling. Consciousness correlates strongly with coherent neural oscillations, however the mechanisms by which neurons synchronize are not fully elucidated. Recent experimental evidence of quantum beats in light-harvesting complexes of plants (LHCII) and bacteria provided a stimulus for seeking similar effects in important structures found in animal cells, especially in neurons. We argue that microtubules (MTs), which play critical roles in all eukaryotic cells, possess structural and functional characteristics that are consistent with quantum coherent excitations in the aromatic groups of their tryptophan residues. Furthermore we outline the consequences of these findings on neuronal processes including the emergence of consciousness. [ABSTRACT FROM AUTHOR]

Abstract: Why the genetic code has a fixed length? Protein information is transferred by coding each amino acid using codons whose length equals 3 for all amino acids. Hence the most probable and the least probable amino acid get a codeword with an equal length. Moreover, the distributions of amino acids found in nature are not uniform and therefore the efficiency of such codes is sub-optimal. The origins of these apparently non-efficient codes are yet unclear. In this paper we propose an a priori argument for the energy efficiency of such codes resulting from their reversibility, in contrast to their time inefficiency. Such codes are reversible in the sense that a primitive processor, reading three letters in each step, can always reverse its operation, undoing its process. We examine the codes for the distributions of amino acids that exist in nature and show that they could not be both time efficient and reversible. We investigate a family of Zipf-type distributions and present their efficient (non-fixed length) prefix code, their graphs, and the condition for their reversibility. We prove that for a large family of such distributions, if the code is time efficient, it could not be reversible. In other words, if pre-biotic processes demand reversibility, the protein code could not be time efficient. The benefits of reversibility are clear: reversible processes are adiabatic, namely, they dissipate a very small amount of energy. Such processes must be done slowly enough; therefore time efficiency is non-important. It is reasonable to assume that early biochemical complexes were more prone towards energy efficiency, where forward and backward processes were almost symmetrical. [Copyright &y& Elsevier]

This paper proposes a physical model involving the key structures within the neural cytoskeleton as major players in molecular-level processing of information required for learning and memory storage. In particular, actin filaments and microtubules are macromolecules having highly charged surfaces that enable them to conduct electric signals. The biophysical properties of these filaments relevant to the conduction of ionic current include a condensation of counterions on the filament surface and a nonlinear complex physical structure conducive to the generation of modulated waves. Cytoskeletal filaments are often directly connected with both ionotropic and metabotropic types of membrane-embedded receptors, thereby linking synaptic inputs to intracellular functions. Possible roles for cable-like, conductive filaments in neurons include intracellular information processing, regulating developmental plasticity, and mediating transport. The cytoskeletal proteins form a complex network capable of emergent information processing, and they stand to intervene between inputs to and outputs from neurons. In this manner, the cytoskeletal matrix is proposed to work with neuronal membrane and its intrinsic components (e.g., ion channels, scaffolding proteins, and adaptor proteins), especially at sites of synaptic contacts and spines. An information processing model based on cytoskeletal networks is proposed that may underlie certain types of learning and memory. [ABSTRACT FROM AUTHOR]

Microtubules (MTs) are important cytoskeletal superstructures implicated in neuronal morphology and function, which are involved in vesicle trafficking, neurite formation and differentiation and other morphological changes. The structural and functional properties of MTs depend on their high intrinsic charge density and functional regulation by the MT depolymerising properties of changes in Ca2 + concentration. Recently, we reported on remarkable properties of isolated MTs, which behave as biomolecular transistors capable of amplifying electrical signals (Priel et al., Biophys J 90:4639–4643, ). Here, we demonstrate that MT-bathing (cytoplasmic) Ca2 + concentrations modulate the electrodynamic properties of MTs. Electrical amplification by MTs was exponentially dependent on the Ca2 + concentration between 10 − 7 and 10 − 2 M. However, the electrical connectivity (coupling) of MTs was optimal at a narrower window of Ca2 + concentrations. We observed that while raising bathing Ca2 + concentration increased electrical amplification by MTs, energy transfer was highest in the presence of ethylene glycol tetraacetic acid (lowest Ca2 + concentration). Our data indicate that Ca2 + is an important modulator of electrical amplification by MTs, supporting the hypothesis that this divalent cation, which adsorbs onto the polymer’s surface, plays an important role as a regulator of the electrical properties of MTs. The Ca2 + -dependent ability of MTs to modulate and amplify electrical signals may provide a novel means of cell signaling, likely contributing to neuronal function. [ABSTRACT FROM AUTHOR]

We model the dynamical states of the C-termini of tubulin dimers that comprise neuronal microtubules. We use molecular dynamics and other computational tools to explore the time-dependent behavior of conformational states of a C-terminus of tubulin within a microtubule and assume that each C-terminus interacts via screened Coulomb forces with the surface of a tubulin dimer, with neighboring C-termini and also with any adjacent microtubule-associated protein 2 (MAP2). Each C-terminus can either bind to the tubulin surface via one of the several positively charged regions or can be allowed to explore the space available in the solution surrounding the dimer. We find that the preferential orientation of each C-terminus is away from the tubulin surface but binding to the surface may also take place, albeit at a lower probability. The results of our model suggest that perturbations generated by the C-termini interactions with counterions surrounding a MAP2 may propagate over distances greater than those between adjacent microtubules. Thus, the MAP2 structure is able to act as a kind of biological wire (or a cable) transmitting local electrostatic perturbations resulting in ionic concentration gradients from one microtubule to another. We briefly discuss the implications the current dynamic modeling may have on synaptic activation and potentiation. [ABSTRACT FROM AUTHOR]

A novel model for information processing in dendrites is proposed based on electrodynamic signaling mediated by the cytoskeleton. Our working hypothesis is that the dendritic cytoskeleton, including both microtubules (MTs) and actin filaments plays an active role in computations affecting neuronal function. These cytoskeletal elements are affected by, and in turn regulate, a key element of neuronal information processing, namely, dendritic ion channel activity. We present a molecular dynamics description of the C-termini protruding from the surface of an MT that reveals the existence of several conformational states, which lead to collective dynamical properties of the neuronal cytoskeleton. Furthermore, these collective states of the C-termini on MTs have a significant effect on ionic condensation and ion cloud propagation with physical similarities to those recently found in actin filaments. Our objective is to provide an integrated view of these phenomena in a bottom-up scheme, demonstrating that ionic wave interactions and propagation along cytoskeletal structures impacts channel functions and, thus, neuronal computational capabilities. [ABSTRACT FROM AUTHOR]

The neuronal cytoskeleton has been hypothesized to play a role in higher cognitive functions including learning, memory and consciousness. Experimental evidence suggests that both microtubules and actin filaments act as biological electrical wires that can transmit and amplify electric signals via the flow of condensed ion clouds. The potential transmission of electrical signals via the cytoskeleton is of extreme importance to the electrical activity of neurons in general. In this regard, the unique structure, geometry and electrostatics of microtubules are discussed with the expected impact on their specific functions within the neuron. Electric circuit models of ionic flow along microtubules are discussed in the context of experimental data, and the specific importance of both the tubulin C-terminal tail regions, and the nano-pore openings lining the microtubule wall is elucidated. Overall, these recent results suggest that ions, condensed around the surface of the major filaments of the cytoskeleton, flow along and through microtubules in the presence of potential differences, thus acting as transmission lines propagating intracellular signals in a given cell. The significance of this conductance to the functioning of the electrically active neuron, and to higher cognitive function is also discussed. [ABSTRACT FROM AUTHOR]

Our understanding of the pathways that regulate lymphocyte metabolism, as well as the effects of metabolism and its products on the immune response, is still limited. We report that a metabolic program controlled by the transcription factors hypoxia inducible factor-1α (HIF1-α) and aryl hydrocarbon receptor (AHR) supports the differentiation of type 1 regulatory T cell (Tr1) cells. HIF1-α controls the early metabolic reprograming of Tr1 cells. At later time points, AHR promotes HIF1-α degradation and takes control of Tr1 cell metabolism. Extracellular ATP (eATP) and hypoxia, linked to inflammation, trigger AHR inactivation by HIF1-α and inhibit Tr1 cell differentiation. Conversely, CD39 promotes Tr1 cell differentiation by depleting eATP. CD39 also contributes to Tr1 suppressive activity by generating adenosine in cooperation with CD73 expressed by responder T cells and antigen-presenting cells. These results suggest that HIF1-α and AHR integrate immunological, metabolic and environmental signals to regulate the immune response. [ABSTRACT FROM AUTHOR]