A neuronal network switch for approach/avoidance toggled by appetitive state

Concrete examples of computation and implementation of cost/benefit decisions at the level of neuronal circuits are largely lacking. Such decisions are based on appetitive state, which is the integration of sensation, internal state, and memory. Value-based decisions are accessible in neuronal circuitry of simple systems. In one such system, the predatory sea slug Pleurobranchaea, appetite is readily quantified in behavior and related to approach/avoidance decision. Moreover, motor aspects of feeding and turning can be observed as fictive motor output in the isolated central nervous system (CNS). Here we found that the excitation state of the feeding motor network both manifested appetitive state and controlled expression of orienting versus avoidance. In isolated CNSs, spontaneous feeding network activity varied proportionally to donor feeding thresholds. CNSs from low- and high-feeding-threshold donors expressed fictive orienting or avoidance, respectively, in response to brief stimulation of sensory nerves. Artificially exciting the feeding network converted fictive avoidance to orienting. Thus, the feeding network embodied appetitive state and toggled approach/avoidance decision by configuring response symmetry of the premotor turn network. A resulting model suggests a basic cost/benefit decision module from which to consider evolutionary elaboration of the circuitry to serve more intricate valuation processes in complex animals.     

Membrane adsorption characteristics determine the kinetics of flow-through transductions

Retrovirus-mediated gene transfer is currently limited by random Brownian motion of the retrovirus. This limitation can be overcome by flowing the retrovirus solution through a porous membrane that supports the target cells, leading to a significant increase in the transduction efficiency. This procedure is termed "flow-through transduction." In this study, we characterized the effects of the fluid flowrate and the influence that membrane characteristics have on the flow-through transduction procedure. The transduction efficiencies increased with flowrate until a plateau was reached at average flow velocities exceeding 0.3 cm/h for flow times of 3 to 4 h, using a collagen-coated depth (COL) membrane. A correlation between the optimal time for maximal gene transfer using flow-through transductions and the optimal time for maximal virus activity on the membrane was found, suggesting that the membrane adsorption capacity for virus determined the amount of gene transfer that could occur.Membrane adsorption characteristics were further investigated using two different membrane types: a tracketched polyester screen (PE) membrane and the COL membrane. Flow-through transductions using the PE and COL membranes showed that a high level of gene transfer could be attained using the COL membrane while the PE membrane gave much lower transduction efficiencies. The addition of the polycation polybrene (PB) changed these results markedly, making transductions achieved on the PE membrane similar in number to those obtained on the COL membrane. Since PB is believed to influence the virus adsorption to PE membrane, these results further support the conclusion that the increase in gene transfer achieved by the flow-through transduction procedure is due to virus adsorption to the membrane. The flow-through transduction procedure thus leads to co-localization of the viral vector and the target cell that in turn leads to a high transduction efficiency. (c) 1996 John Wiley & Sons, Inc.     

Myosin dynamics on the millisecond time scale

Myosin is a motor protein associating with actin and ATP. It translates along actin filaments against a force by transduction of free energy liberated with ATP hydrolysis. Various myosin crystal structures define time points during ATPase showing the protein undergoes large conformation change during transduction over a cycle with approximately 10 ms periodicity. The protein conformation trajectory between two intermediates in the cycle is surmised by non-equilibrium Monte Carlo simulation utilizing free-energy minimization. The trajectory shows myosin transduction of free energy to mechanical work giving evidence for: (i) a causal relationship between product release and work production in the native isoform that is correctly disrupted in a chemically modified protein, (ii) the molecular basis of ATP-sensitive tryptophan fluorescence enhancement and acrylamide quenching, (iii) an actin-binding site peptide containing the free-energy barrier to ATPase product release defining the rate limiting step and, (iv) a scenario for actin-activation of myosin ATPase.     

Conformational propagation with prion-like characteristics in a simple model of protein folding

Protein refolding/misfolding to an alternative form plays an aetiologic role in many diseases in humans, including Alzheimer's disease, the systemic amyloidoses, and the prion diseases. Here we have discovered that such refolding can occur readily for a simple lattice model of proteins in a propagatable manner without designing for any particular alternative native state. The model uses a simple contact energy function for interactions between residues and does not consider the peculiarities of polypeptide geometry. In this model, under conditions where the normal (N) native state is marginally stable or unstable, two chains refold from the N native state to an alternative multimeric energetic minimum comprising a single refolded conformation that can then propagate itself to other protein chains. The only requirement for efficient propagation is that a two-faced mode of packing must be in the ground state as a dimer (a higher-energy state for this packing leads to less efficient propagation). For random sequences, these ground-state dimeric configurations tend to have more beta-sheet-like extended structure than almost any other sort of dimeric ground-state assembly. This implies that propagating states (such as for prions) are beta-sheet rich because the only likely propagating forms are beta-sheet rich. We examine the details of our simulations to see to what extent the observed properties of prion propagation can be predicted by a simple protein folding model. The formation of the alternative state in the present model shows several distinct features of amyloidogenesis and of prion propagation. For example, an analog of the phenomenon of conformationally distinct strains in prions is observed. We find a parallel between 'glassy' behavior in liquids and the formation of a propagatable state in proteins. This is the first report of simulation of conformational propagation using any heteropolymer model. The results imply that some (but not most) small protein sequences must maintain a sequence signal that resists refolding to propagatable alternative native states and that the ability to form such states is not limited to polypeptides (or reliant on regular hydrogen bonding per se) but can occur for other protein-like heteropolymers.     

14-3-3 proteins: regulation of signal-induced events

The field of signal transduction has experienced a significant paradigm shift as a result of an increased understanding of the roles of 14-3-3 proteins. There are many cases where signal-induced phosphorylation itself may cause a change in protein function. This simple modification is, in fact, the primary basis of signal transduction events in many systems. There are a large and growing number of cases, however, where simple phosphorylation is not enough to effect a change in protein function. In these cases, the 14-3-3 proteins can be required to complete the change in function. Therefore signal transduction can be either the relatively simple process where phosphorylation alters target activity, or it can be a more complex, multistep process with the 14-3-3 proteins playing the major role of bringing the signal transduction event to completion. This makes 14-3-3-modulated signal transduction a more complicated process with additional avenues for regulation and variety. Adding further complexity to the process is the fact that 14-3-3 proteins are present as multigene families in most organisms (Aitken et al. Trends Biochem Sci 17: 498–501, 1992; Ferl Annu Rev Plant Physiol Plant Molecular Biology 47: 49–73, 1996), with each member of the family being differentially expressed in various tissues and with potentially differential affinity for various target proteins. This review focuses on the 14-3-3 family of Arabidopsis as a model for further developing understanding of the roles of the 14-3-3 proteins as modulators of signal transduction events in plants. The primary approaches to these questions are not unlike the approaches that would be used in the functional dissection of any multigene family, but the interpretation of these data will have wide implications since the 14-3-3 s physically interact with other protein families.     

Principles of entrainment: diagnostic utility for supraventricular tachycardia

Entrainment is an important pacing maneuver that can be used to identify reentry as a tachycardia mechanism and define components of the circuit. This review examines how principles of entrainment can be used to arrive at a firm supraventricular tachycardia diagnosis using a simple algorithm and builds a foundation for the application of entrainment to more complex or unknown circuits.     

Approximations and their consequences for dynamic modelling of signal transduction pathways

Signal transduction is the process by which the cell converts one kind of signal or stimulus into another. This involves a sequence of biochemical reactions, carried out by proteins. The dynamic response of complex cell signalling networks can be modelled and simulated in the framework of chemical kinetics. The mathematical formulation of chemical kinetics results in a system of coupled differential equations. Simplifications can arise through assumptions and approximations. The paper provides a critical discussion of frequently employed approximations in dynamic modelling of signal transduction pathways. We discuss the requirements for conservation laws, steady state approximations, and the neglect of components. We show how these approximations simplify the mathematical treatment of biochemical networks but we also demonstrate differences between the complete system and its approximations with respect to the transient and steady state behavior.     

Sectoral Aggregation Error in the Accounting of Energy and Emissions Embodied in Trade and Consumption

Correctly accounting for the energy and emissions embodied in consumption and trade is essential to effective climate policy design. Robust methods are needed for both policy making and research—for example, the assignment of border carbon adjustments (BCAs) and greenhouse gas emission reduction responsibilities rely on the consistency and accuracy of such estimates. This analysis investigates the potential magnitude and consequences of the error present in estimates of energy and emissions embodied in trade and consumption. To quantify the error of embodied emissions accounting, we compare the results from the disaggregated Global Trade Analysis Project (GTAP 8) data set, which contains 57 sectors to results from different levels of aggregation of this data set (3, 7, 16, and 26 sectors), using 5,000 randomly generated sectoral aggregation schemes as well as aggregations generated using several commonly applied decisions rules. We find that some commonly applied decision rules for sectoral aggregation can produce a large error. We further show that an aggregation scheme that clusters sectors according to their energy, emissions, and trade intensities (net exports over output) can minimize error in embodied energy and emissions accounting at different levels of aggregation. This sectoral aggregation scheme can be readily used in any input‐output analysis and provide useful information for computable general equilibrium modeling exercises in which sector aggregation is necessary, although our findings suggest that, when possible, the most disaggregated data available should be used.     

Knowledge representation of signal transduction pathways

MOTIVATIONS: Signal transduction is the common term used to define a diverse topic that encompasses a large body of knowledge about the biochemical mechanisms. Since most of the knowledge of signal transduction resides in scientific articles and is represented by texts in natural language or by diagrams, there is the need of a knowledge representation model for signal transduction pathways that can be as readily processed by a computer as it is easily understood by humans. RESULTS: A signal transduction pathway representation model is presented. It is based on a compound graph structure and is designed to handle the diversity and hierarchical structure of pathways. A prototype knowledge base was implemented on a deductive database and a number of biological queries are demonstrated on it.     

Physiological basis of differences in the body tolerance to submaximal physical load to capacity in healthy young individuals

A complex approach to studying the physiological basis of the individual and typological features of functional states and tolerance of physical load in healthy young individuals using superslow physiological processes (SSPP) was elaborated. Statistically significant differences were found in the values of central hemodynamics, physicochemical homeostasis, the level of oxygen consumption by the tissues and general nonspecific adaptation reactions of the body. These reactions correlated with differences in the integral values of the wakefulness level, as judged by the SSPP data, in healthy individuals tolerant of physical fatigue and quickly fatigued individuals at rest and after a two-step individually submaximal physical stress to capacity. The possibilities of the use of this approach to substantiate the physiological significance of SSPP in the differential diagnosis of the optimal level of wakefulness, the state of physical tension, the state of fatigue, and asthenic states of a different degree of severity in healthy individuals with regulatory and homeostatic control inherent in these states were revealed.     

A laser flash photolysis study of the reactivities of the triplet states of 8-methoxypsoralen and 4,5',8-trimethylpsoralen with nucleic acid bases in solution.

The extinction coefficients, quantum yields and reactivities of the triplet states of 8-methoxypsoralen and 4,5',8-trimethylpsoralen in methanolic solution have been determined using laser flash photolysis techniques. The second-order rate constants for the quenching of these triplet states by pyrimidine and purine bases were found to be several orders of magnitude lower than those found for other furocoumarin derivatives. This may suggest, therefore, that the skin photosensitising ability of such compounds does not necessarily correlate with in vitro triplet state reactivity. Preliminary experiments on the reactivity of the psoralen triplet state with DNA itself indicate that no transient absorptions due to psoralen excited states can be observed when a photon is absorbed by the psoralen-DNA complex.     

The retinal phototransduction process: enzymatic cascade and regulation

Among cellular systems performing the transduction of an external stimulus, phototransduction in vertebrate rod cells is a unique case which allows convergent approaches to electrophysiological, biophysical and biochemical analyses. The framework of the molecular processes involved in the corresponding enzymatic cascade is now elucidated and can be considered as a model for G protein mediated transductions. We present here the main features of this cascade, its amplification and regulation properties. The mode of stimulation by the aluminofluoride ion is particularly addressed.     

A General Channel Model Accounts for Channel,Carrier, Countertransport and Cotransport Kinetics

In this work we propose a unifying model of mediated membrane transport, based upon the idea that the integral membrane proteins involved in these processes operate via complex channel mechanisms. In the first part, we briefly review literature about the structural aspects of membrane transporters. We conclude that there is a substantial amount of evidence suggesting that most membrane proteins performing transport are embodied with channel-like structures that may constitute the translocation paths. This includes cases where the phenomenological transport kinetics do not correspond to the classical channel behavior. In the second part of this article we introduce the general channel model of mediated transport and employ it to derive specific examples, like simple one- or two-ligand channels, water-ligand channels, simple carriers, co- and counter-transport systems and more complex water-ligand carriers. We show that, for the most part, these particular cases can be obtained by the application of the techniques of diagram reduction to the full model. The necessary conditions for diagram reduction reflect physical properties of the protein and its surroundings.     

Self-sustained asynchronous irregular states and Up–Down states in thalamic,cortical and thalamocortical networks of nonlinear integrate-and-fire neurons

Randomly-connected networks of integrate-and-fire (IF) neurons are known to display asynchronous irregular (AI) activity states, which resemble the discharge activity recorded in the cerebral cortex of awake animals. However, it is not clear whether such activity states are specific to simple IF models, or if they also exist in networks where neurons are endowed with complex intrinsic properties similar to electrophysiological measurements. Here, we investigate the occurrence of AI states in networks of nonlinear IF neurons, such as the adaptive exponential IF (Brette-Gerstner-Izhikevich) model. This model can display intrinsic properties such as low-threshold spike (LTS), regular spiking (RS) or fast-spiking (FS). We successively investigate the oscillatory and AI dynamics of thalamic, cortical and thalamocortical networks using such models. AI states can be found in each case, sometimes with surprisingly small network size of the order of a few tens of neurons. We show that the presence of LTS neurons in cortex or in thalamus, explains the robust emergence of AI states for relatively small network sizes. Finally, we investigate the role of spike-frequency adaptation (SFA). In cortical networks with strong SFA in RS cells, the AI state is transient, but when SFA is reduced, AI states can be self-sustained for long times. In thalamocortical networks, AI states are found when the cortex is itself in an AI state, but with strong SFA, the thalamocortical network displays Up and Down state transitions, similar to intracellular recordings during slow-wave sleep or anesthesia. Self-sustained Up and Down states could also be generated by two-layer cortical networks with LTS cells. These models suggest that intrinsic properties such as adaptation and low-threshold bursting activity are crucial for the genesis and control of AI states in thalamocortical networks.     

Oncogenic Dbl, Cdc42, and p21-activated kinase form a ternary signaling intermediate through the minimum interactive domains

Activation of many Rho family GTPase pathways involves the signaling module consisting of the Dbl-like guanine nucleotide exchange factors (GEFs), the Rho GTPases, and the Rho GTPase specific effectors. The current biochemical model postulates that the GEF-stimulated GDP/GTP exchange of Rho GTPases leads to the active Rho-GTP species, and subsequently the active Rho GTPases interact with and activate the effectors. Here we report an unexpected finding that the Dbl oncoprotein, Cdc42 GTPase, and PAK1 can form a complex through their minimum functional motifs, i.e., the Dbl-homolgy (DH) and Pleckstrin-homology domains of Dbl, Cdc42, and the PBD domain of PAK1. The Dbl-Cdc42-PAK1 complex is sensitive to the nucleotide-binding state of Cdc42 since either dominant negative or constitutively active Cdc42 readily disrupts the ternary binding interaction. The complex formation depends on the interactions between the DH domain of Dbl and Cdc42 and between Cdc42 and the PBD domain of PAK1 and can be reconstituted in vitro by using the purified components. Furthermore, the Dbl-Cdc42-PAK1 ternary complex is active in generating signaling output through the activated PAK1 kinase in the complex. The GEF-Rho-effector ternary intermediate is also found in other Dbl-like GEF, Rho GTPase, and effector interactions. Finally, PAK1, through the PDB domain, is able to accelerate the GEF-induced GTP loading onto Cdc42. These results suggest that signal transduction through Cdc42 and possibly other Rho family GTPases could involve tightly coupled guanine nucleotide exchange and effector activation mechanisms and that Rho GTPase effector may have a feedback regulatory role in the Rho GTPase activation.     

Memory is a property of an ion channels pool: ion channels formed by Staphylococcus aureus alpha-toxin.

The short-time depolarization effects on the integral conductance induced by S. aureus alpha-toxin (ST) in planar lipid bilayer membranes has been studied. Ion channels formed by ST were found to have several potential-induced nonconductance (closed) states. The transitions of ion channels between the states are only through one conductance state. The transition of ST-channels from closed to open state is induced by membrane depolarization. The amplitude current after a series of voltage pulses is a function of pulse number, and is effectively independent of the time interval between the neighbouring pulses. Therefore, a membrane which contains a pool of ion channels "remembers" its previous existence. A simple model can be used to explain this phenomenon.     

Dynamical estimation of neuron and network properties II: path integral Monte Carlo methods

Hodgkin–Huxley (HH) models of neuronal membrane dynamics consist of a set of nonlinear differential equations that describe the time-varying conductance of various ion channels. Using observations of voltage alone we show how to estimate the unknown parameters and unobserved state variables of an HH model in the expected circumstance that the measurements are noisy, the model has errors, and the state of the neuron is not known when observations commence. The joint probability distribution of the observed membrane voltage and the unobserved state variables and parameters of these models is a path integral through the model state space. The solution to this integral allows estimation of the parameters and thus a characterization of many biological properties of interest, including channel complement and density, that give rise to a neuron’s electrophysiological behavior. This paper describes a method for directly evaluating the path integral using a Monte Carlo numerical approach. This provides estimates not only of the expected values of model parameters but also of their posterior uncertainty. Using test data simulated from neuronal models comprising several common channels, we show that short (<50 ms) intracellular recordings from neurons stimulated with a complex time-varying current yield accurate and precise estimates of the model parameters as well as accurate predictions of the future behavior of the neuron. We also show that this method is robust to errors in model specification, supporting model development for biological preparations in which the channel expression and other biophysical properties of the neurons are not fully known.     

Dynamic polymorphism of Ras observed by single molecule FRET is the basis for molecular recognition

Ras regulates signal transduction pathway function by dynamically interacting with various effectors. To understand the basis for Ras function, its conformational dynamics were measured in the absence and presence of effectors using single molecule fluorescence resonance energy transfer (FRET) between probes located on the Switch II region and GTP. The time trajectories of FRET efficiency from GTP-bound Ras showed that this conformation spontaneously varies among multiple states. Among them, a low FRET state was identified as an inactive state. The transition involving the inactive conformational state occurred in the time range of seconds. In contrast, fluctuation occurring most probably between multiple active high FRET conformational states lasted approximately 30 ms but converged to a specific conformational state upon binding to an effector. Thus, Ras conformation spontaneously fluctuates to readily interact with various effectors.