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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.

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., T cell activation triggers metabolic changes required to support the adaptive immune response (1-5). Indeed, the differentiation of cytotoxic and interleukin (IL)-17-producing effector T cells (T helper 17 cells; [T.sub.H]17 [...]

Dendritic spines (DS) are tiny protrusions implicated in excitatory postsynaptic responses in the CNS. To achieve their function, DS concentrate a high density of ion channels and dynamic actin networks in a tiny specialized compartment. However, to date there is no direct information on DS ionic conductances. Here, we used several experimental techniques to obtain direct electrical information from DS of the adult mouse hippocampus. First, we optimized a method to isolate DS from the dissected hippocampus. Second, we used the lipid bilayer membrane (BLM) reconstitution and patch clamping techniques and obtained heretofore unavailable electrical phenotypes on ion channels present in the DS membrane. Third, we also patch clamped DS directly in cultured adult mouse hippocampal neurons, to validate the electrical information observed with the isolated preparation. Electron microscopy and immunochemistry of PDS-95 and NMDA receptors and intrinsic actin networks confirmed the enrichment of the isolated DS preparation, showing open and closed DS, and multi-headed DS. The preparation was used to identify single channel activities and "whole-DS" electrical conductance. We identified NMDA and Ca2C-dependent intrinsic electrical activity in isolated DS and in situ DS of cultured adult mouse hippocampal neurons. In situ recordings in the presence of local NMDA, showed that individual DS intrinsic electrical activity often back-propagated to the dendrite from which it sprouted. The DS electrical oscillations were modulated by changes in actin cytoskeleton dynamics by addition of the F-actin disrupter agent, cytochalasin D, and exogenous actin-binding proteins. The data indicate that DS are elaborate excitable electrical devices, whose activity is a functional interplay between ion channels and the underlying actin networks. The data argue in favor of the active contribution of individual DS to the electrical activity of neurons at the level of both the membrane conductance and cytoskeletal signaling. [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]

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]

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]

An abstract of the article "Ionic Waves Propagation Along the Dendritic Cytoskeleton As a Signaling Mechanism," by Avner Priel and colleagues is presented.

The T cell repertoire potentially presents complexity compatible, or greater than, that of the human brain. T cell based immune response is involved with practically every part of human physiology, and high-throughput biology needed to follow the T-cell repertoire has made great leaps with the advent of massive parallel sequencing [1]. Nevertheless, tools to handle and observe the dynamics of this complexity have only recently started to emerge [e.g., 2, 3, 4] in parallel with sequencing technologies. Here, we present a network-based view of the dynamics of the T cell repertoire, during the course of mammary tumors development in a mouse model. The transition from the T cell receptor as a feature, to network-based clustering, followed by network-based temporal analyses, provides novel insights to the workings of the system and provides novel tools to observe cancer progression via the perspective of the immune system. The crux of the approach here is at the network-motivated clustering. The purpose of the clustering step is not merely data reduction and exposing structures, but rather to detect hubs, or attractors, within the T cell receptor repertoire that might shed light on the behavior of the immune system as a dynamic network. The Clone-Attractor is in fact an extension of the clone concept, i.e., instead of looking at particular clones we observe the extended clonal network by assigning clusters to graph nodes and edges to adjacent clusters (editing distance metric). Viewing the system as dynamical brings to the fore the notion of an attractors landscape, hence the possibility to chart this space and map the sample state at a given time to a vector in this large space. Based on this representation we applied two different methods to demonstrate its effectiveness in identifying changes in the repertoire that correlate with changes in the phenotype: (1) network analysis of the TCR repertoire in which two measures were calculated and demonstrated the ability to differentiate control from transgenic samples, and, (2) machine learning classifier capable of both stratifying control and trangenic samples, as well as to stratify pre-cancer and cancer samples.

It has been suggested that microtubules and other cytoskeletal filaments may act as electrical transmission lines. An electrical circuit model of the microtubule is constructed incorporating features of its cylindrical structure with nanopores in its walls. This model is used to study how ionic conductance along the lumen is affected by flux through the nanopores, both with and without an external potential applied across its two ends. Based on the results of Brownian dynamics simulations, the nanopores were found to have asymmetric inner and outer conductances, manifested as nonlinear IV curves. Our simulations indicate that a combination of this asymmetry and an internal voltage source arising from the motion of the C-terminal tails causes cations to be pumped across the microtubule wall and propagate in both directions down the microtubule through the lumen, returning to the bulk solution through its open ends. This effect is demonstrated to add directly to the longitudinal current through the lumen resulting from an external voltage source applied across the two ends of the microtubule. The predicted persistent currents directed through the microtubule wall and along the lumen could be significant in directing the dissipation of weak, endogenous potential gradients toward one end of the microtubule within the cellular environment.

Microtubules (MTs) are important cytoskeletal structures engaged in a number of specific cellular activities, including vesicular traffic, cell cyto-architecture and motility, cell division, and information processing within neuronal processes. MTs have also been implicated in higher neuronal functions, including memory and the emergence of "consciousness". How MTs handle and process electrical information, however, is heretofore unknown. Here we show new electrodynamic properties of MTs. Isolated, taxol-stabilized MTs behave as biomolecular transistors capable of amplifying electrical information. Electrical amplification by MTs can lead to the enhancement of dynamic information, and processivity in neurons can be conceptualized as an "ionic-based" transistor, which may affect, among other known functions, neuronal computational capabilities.