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PubMed1987

Extending the quasi-steady state concept to analysis of metabolic networks.

A means is proposed for evaluating enzyme effectiveness in vivo via a simplified dynamic description of the metabolic reaction network within which the enzyme operates. The basis of the method is application of sensitivity analysis to a quasi-steady approximation of a complete dynamic model, and its implementation centers on interpreting the transient relations of selected intermediates following a perturbation to the system of interest: for many important situations such relations can be simply interpreted to give a useful global measure of enzyme effectiveness. This method is found to be successful for estimating phosphofructokinase and pyruvate kinase activity in the human red cell, and it appears promising as a basis for developing a means for detecting enzyme abnormalities caused by environmental or genetic factors. This method may also prove useful for comparative studies of glycolysis in different types of cells. The analysis presented is based on available models of red cell glycolysis, but the results are not highly sensitive to ambiguities in the system model. The approach suggested appears to provide an effective means for describing system dynamics and determining the behavior of an individual enzyme in an intact system by making a first-order allowance for interaction with the system as a whole. Requirements for success of this approach remain to be identified in detail, but effective time-scale separation is probably the key.

Erythrocytes↗
PubMed1992

Quasielastic light scattering study of thermal excitations of F-actin solutions and of growth kinetics of actin filaments.

In the first part of this work we report quasielastic light scattering (QELS) studies of the internal dynamics of transient actin networks over a time range of 10(-6)-10(-2) s, scattering angles between zeta = 20 degrees and 150 degrees, and a concentration range of 0.015 (0.3) to 0.7 mg/mL (15 microM). We confirm our previous result that (1) the dynamic structure factor g(q,t) is determined by the thermally excited undulations of the actin filaments and (2) that the initial decay of g(q, t) scales as g(q, t) varies; is directly proportional to exp(-q alpha t) while the long time decay scales as g(q, t) varies; is directly proportional to exp [-(Aq alpha t) 2/3] with alpha = 2.75. The deviation of alpha from the theoretical value of alpha = 3 predicted for Rouse-Zimm chains is similar to that found for high molecular weight macromolecular solutions by QELS. A refined analysis of the dynamic structure factor showed that it can be interpreted in terms of three relaxation processes (besides the contribution of the residual monomer diffusion): (1) the dominant Rouse-Zimm dynamics, which comprises between 65 (at high concentrations) and 85% of the signal; (2) a fast relaxation process with a decay constant of gamma = 9 x 10(3) s-1, which contributes at all concentrations with the same amplitude; and (3) a nonexponential ultraslow contribution of the form g(us) varies; is directly proportional to exp [(-gamma ust)]1/4. The third contribution appears only at high concentrations and increases strongly with decreasing scattering angles. It is thus attributed to fluctuations of the mesh size of the transient actin network. In the second part we show that high sensitivity QELS may be applied to follow the actin polymerization process at low temperatures (10 degrees C). The apparent diffusion coefficient and the static scattering intensity of the actin filaments were determined as functions of polymerization time tpol. We show that the process consists of the rapid growth of a few filaments that become very long (approximately 10 microns; even at actin concentrations of 0.04 micrograms/mL) near the critical growth concentration of 0.012 micrograms/mL, as is expected for a growth process determined by nucleation. Finally, we studied actin networks polymerized in the presence of complexes of gelsolin with actin. By application of the CONTIN program we could determine the length distribution of the filaments.(ABSTRACT TRUNCATED AT 400 WORDS)

Actins↗
PubMed1982

Dynamic aspects of the supramolecular organization of intermediate filament networks in cultured epidermal cells.

We have shown, by indirect immunofluorescence microscopy using an antiserum against the mouse keratin subunit K2 and by electron microscopy, that transformed (PAM) and primary (PME) mouse epidermal cells possess extensive networks of IF bundles. Following trypsinization and replating of PAM cells, IF bundles are seen to move as a continuous network from a perinuclear zone into the peripheral cytoplasmic regions. In PAM cells lysed in high-ionic-strength solutions containing Triton X-100 and DNAase-1, IF bundles appear to be closely associated with nuclear envelope remnants and, in some cases, appear to be attached to nuclear pore complexes. PME cells cultivated in low Ca2+-containing medium possess perinuclear birefringent arrays of IF bundles. Within 2 hours of switching the cells to normal Ca2+ levels, the PME IF bundle network moves towards and establishes contact with the cell surface as desmosomes form. Live cells observed by phase contrast and fixed cells observed by immunofluorescence microscopy demonstrate that desmosomes can be distinguished as dark bands separating neighboring cells. There is little difference between the major proteins seen in SDS-polyacrylamide gel profiles of isolated IF bundle networks from PME cells before and after the Ca2+ switch. Therefore, a reorganization of relatively insoluble membrane-associated protein following the Ca2+ switch may be involved in desmosome formation. The isolated IF networks from PAM cells differ in protein composition compared to the PME IF networks. This may be related to the greatly reduced number of desmosomes in PAM cells. The IF bundle system in epidermal cells appears to be involved in shape formation, shape maintenance, the establishment of desmosomes, nuclear centration, and cell-cell contact.

Animals↗
PubMedDate not supplied

[Dynamic processes during the organization of neurono-glial networks in nerve tissue culture].

Studies have been made on the pattern of cell behaviour and distribution of cellular projections during stabilization of neuroglial nets in the cortex of newborn rat puppies under the conditions of tissue culture. Observations were made on surviving cells at the 3rd day of cultivation. Projection growth and changes in cell location were registered microphotographically within a day with a 4-hour interval. It was found that together with relative stability of their location, cells exhibit translocations in various directions up to a distance of several cellular diameters. Projection growth in the vicinity of cells occurs mainly in a rhythmic pattern.

Animals↗
PubMed1989

Automata network theories in immunology: their utility and their underdetermination.

Small networks of threshold automata are used to model complex interactions between populations of regulatory cells (helpers and suppressors, antigen specific and anti-idiotypic) which participate in the immune response. The models, being discrete and semiquantitative, are well adapted to the situation of incomplete information often encountered in vivo. However, the dynamics of many different network structures usually end up in the same attractor set. Thus, many different theories are equivalent in their explicative power for the same facts. This property, known as underdetermination of the theories by the facts, is given a quantitative estimate. It appears that such an underdetermination, as a kind of irreducible complexity, can be expected in many in vivo biological processes, even when the number of interacting and functionally coupled elements is relatively small.

Animals↗
PubMed1986

Developing a social support network system to enhance mental and physical health.

A social network support system consists of a set of dynamic, ongoing relationships between the individual and significant others from one's immediate family, relatives, friends, work associates, or others. Through meaningful human interaction, these supportive individuals help meet a person's basic social needs by providing socioemotional aid (acceptance, affection, emotional understanding, empathy, and esteem), instrumental aid (advice, information, help with family or work responsibilities, financial aid), or both. This article provides an in-depth review of social support, explains the dynamics and importance of a viable social network system, and discusses its limitations. A number of selected topics receive special consideration: the social isolation of dentists, social support provided by one's spouse, some social aspects of female dentists, the individual's need for privacy, and personal space and loneliness.

Dentists↗
PubMed2025

Cross-feeding percolation phase transitions of intercellular metabolic networks.

Intercellular cross-talk is essential for the adaptation capabilities of populations of cells. While direct diffusion-driven cell-to-cell exchanges are difficult to map, current nanotechnology enables one to probe single-cell exchanges with the medium. We introduce a mathematical method to reconstruct the dynamic unfolding of intercellular exchange networks from these data, applying it to an experimental coculture system. The exchange network, initially dense, progressively fragments into small disconnected clusters. To explain these dynamics, we develop a maximum-entropy multicellular metabolic model with diffusion-driven exchanges. The model predicts a transition from a dense network to a sparse one as nutrient consumption shifts. We characterize this crossover both numerically, revealing a power-law decay in the cluster-size distribution, and analytically, by connecting to percolation theory. Comparison with data suggests that populations evolve toward the sparse phase by remaining near the crossover. These findings offer insights into the collective organization driving the adaptive dynamics of cell populations.

Metabolic Networks and Pathways↗
PubMed1990

Pattern-recognition by an artificial network derived from biologic neuronal systems.

A novel artificial neural network, derived from neurobiological observations, is described and examples of its performance are presented. This DYnamically STable Associative Learning (DYSTAL) network associatively learns both correlations and anticorrelations, and can be configured to classify or restore patterns with only a change in the number of output units. DYSTAL exhibits some particularly desirable properties: computational effort scales linearly with the number of connections, i.e., it is O(N) in complexity; performance of the network is stable with respect to network parameters over wide ranges of their values and over the size of the input field; storage of a very large number of patterns is possible; patterns need not be orthogonal; network connections are not restricted to multi-layer feed-forward or any other specific structure; and, for a known set of deterministic input patterns, the network weights can be computed, a priori, in closed form. The network has been associatively trained to perform the XOR function as well as other classification tasks. The network has also been trained to restore patterns obscured by binary or analog noise. Neither global nor local feedback connections are required during learning; hence the network is particularly suitable for hardware (VLSI) implementation.

Animals↗
PubMed1986

Habituation rules for a theory of the cerebellar cortex.

A quantitative model of cerebellar cortical function is described with a complete formalization based on (i) the topology of cerebellar cortical neuronal network, (ii) some particular synaptic properties of cell classes in cerebellum cortex, and (iii) the dynamics of excitation in this network. For (i), a construction of functional classes around one Purkinje cell is given and their existence is discussed. For (ii), as in Marr-Albus model, the modifiability of synapses between parallel fibres and Purkinje cell is assumed. But the formalization permits to consider the consequences of such a property at the level of glomerulus (with granule cells) which is known as a complex transformation system. For (iii) habituation rules are assumed. It is shown that this method leads to some interesting properties in the functioning of cerebellar cortex. Particularly, emitting frequency along a Purkinje cell axon results from a discrimination by the system between transformed input signals and an external "noise" due to all other "contexts," and learning could be considered as the result of a conflict between a set of patterns and the transformed input signals. This model could be a basis for future numerical simulations.

Animals↗
PubMed2026

Resolving cellular signaling in space and time: From organelle proteomics to spatial phosphoproteomics.

Cellular signaling is inherently organized in space and time, requiring coordinated control of protein localization, molecular interactions, and enzymatic activity across subcellular compartments. Recent advances in chemical biology, protein engineering, and quantitative proteomics have made it possible to interrogate these dimensions in an integrated manner. Here, we highlight emerging strategies to resolve signaling organization across three interconnected dimensions: organelle-resolved proteome mapping to define spatial context, proximity labeling to capture local protein interaction networks, and spatially resolved phosphoproteomics to quantify signaling outputs. Developments in proximity labeling, including split, conditionally activated and light-gated enzymes, enable temporally controlled, context-dependent profiling of transient protein assemblies in living cells. Advances in high-throughput and low-input phosphoproteomics, together with improved computational frameworks for kinase activity inference and subcellular enrichment strategies, are enabling spatially resolved measurement of signaling activity. Together, these approaches are shifting the field from static localization maps toward dynamic models of signaling networks.

Proteomics↗
PubMed1984

Recognition of self and regulation of specificity at the level of cell populations.

It is suggested that immunologic specificity and selective responsiveness, assayed by effector and memory cells, are, in part, determined by the existing repertoire of lymphocytes and, in part, by the dynamic nature of cellular growth. Clones within horizontal networks resemble competing species in a Darwinian world. Upon stimulation, the development of a clone is greatly affected, in a dynamic way, by factors that determine the balance between self-renewal and differentiation. Antigen is a major factor. The amount of antigen and the nature of encounter with the immune system (sudden, graded or continuous), through the selection of a particular subset of clones, can be correlated with a weak or a strong expression of effector function and with the generation of effective memory or of tolerance. The encounter with self antigens obeys the same rules. Thus, the distinction between self and non-self is a quantitative one, both at the single-cell level and at the systemic level. The encounter of developing lymphocytes with self antigens, and in particular with idiotypes and MHC-antigens, restricts the repertoire and imposes major constraints both on the mode of interaction with foreign antigens and on potential self-recognition networks. The proposed "dynamic scheme", differing from "structural schemes" in a number of fundamental aspects, calls for reevaluation of present concepts of immunoregulation and for reinterpretation of data.

Animals↗
PubMed1992

Information maintenance and statistical dependence reduction in simple neural networks.

This study compares the ability of excitatory, feed-forward neural networks to construct good transformations on their inputs. The quality of such a transformation is judged by the minimization of two information measures: the information loss of the transformation and the statistical dependency of the output. The networks that are compared differ from each other in the parametric properties of their neurons and in their connectivity. The particular network parameters studied are output firing threshold, synaptic connectivity, and associative modification of connection weights. The network parameters that most directly affect firing levels are threshold and connectivity. Networks incorporating neurons with dynamic threshold adjustment produce better transformations. When firing threshold is optimized, sparser synaptic connectivity produces a better transformation than denser connectivity. Associative modification of synaptic weights confers only a slight advantage in the construction of optimal transformations. Additionally, our research shows that some environments are better suited than others for recording. Specifically, input environments high in statistical dependence, i.e. those environments most in need of recoding, are more likely to undergo successful transformations.

Action Potentials↗
PubMedDate not supplied

Study of large DNA fragments in agarose gels by transient electric birefringence.

The pulsed-field gel electrophoresis (PFG) is a newly developing technique used in the fractionation of large DNA fragments. Advances in PFG demand a better understanding in the corresponding mechanisms of DNA dynamics in the gel network. Detailed experiments are needed to verify and to extend existing theoretical predictions as well as to find optimum conditions for efficient separation of large DNA fragments. In the present study, deformation of large DNA fragments (40-70 kilobase pairs) imbedded in agarose gels were investigated by using the transient electric birefringence (TEB) technique under both singular polarity and bipolarity electric pulses at low applied electric field strengths (E less than or equal to 5 V/cm). The steady-state optical retardation (delta s) of DNA molecules is linearly proportional to E2. At a given E, the amplitude of optical retardation [delta(t)] increases monotonically with the pulse width (PW) and then reaches a plateau value [delta(t = 0) = delta s] where t = 0 denotes the time when the applied field is turned off or reversed. The field-free decay time (tau-a few minutes) is several orders of magnitudes slower than that from previous TEB observations using high electric field strengths (E-kV/cm) and short pulse widths (PW-ms). The degree of deformation (stretching and orientation) and the time of restoration to the equilibrium conformation of overall DNA chains have been related to delta and tau. In field inversion measurements, exponentially rising and linearly falling of birefringence signals in the presence of forward/inverse applied fields were observed. The rising and falling of birefringence signals were reproducible under a sequence of alternating pulses. Comparison of our results with literature findings and discussions with theories are presented.

DNA↗
PubMed1991

Sequential configuration model for firing patterns in local neural networks.

This paper presents a sequential configuration model to represent the coordinated firing patterns of memory traces in groups of neurons in local networks. Computer simulations are used to study the dynamic properties of memory traces selectively retrieved from networks in which multiple memory traces have been embedded according to the sequential configuration model. Distinct memory traces which utilize the same neurons, but differ only in temporal sequencing are selectively retrievable. Firing patterns of constituent neurons of retrieved memory traces exhibit the main properties of neurons observed in multi microelectrode recordings. The paper shows how to adjust relative synaptic weightings so as to control the disruptive influences of cross-talk in multipy-embedded networks. The theoretical distinction between (primarily anatomical) beds and (primarily physiological) realizations underlines the fundamentally stochastic nature of network firing patterns, and allows the definition of 4 degrees of clarity of retrieved memory traces.

Animals↗
PubMed1985

Identification and estimation algorithm for stochastic neural system. II.

The algorithm for identifying the stochastic neural system and estimating the system process which reflects the dynamics of the neural network are presented in this paper. The analogous algorithm has been proposed in our preceding paper (Nakao et al., 1984), which was based on the randomly missed observations of a system process only. Since the previous algorithm mentioned above was subject to an unfavorable effect of consecutively missed observations, to reduce such an effect the algorithm proposed here is designed additionally to observe an intensity process in a neural spike train as the information for the estimation. The algorithm is constructed with the extended Kalman filters because it is naturally expected that a nonlinear and time variant structure is necessary for the filters to realize the observation of an intensity process by means of mapping from a system process to an intensity process. The performance of the algorithm is examined by applying it to some artificial neural systems and also to cat's visual nervous systems. The results in these applications are thought to prove the effectiveness of the algorithm proposed here and its superiority to the algorithm proposed previously.

Animals↗
PubMedDate not supplied

Immune networks: getting on to the real thing.

After some ten years of faltering development, the network approach in immunology is finally heading toward steady ground. At a recent international workshop (*), experimentalists and theoreticians discussed some of the latest developments, including an impressive array of novel results and applications to fundamental properties of biological immune networks: connectivity, patterns of dynamic activity, ontogenesis, and tolerance.

Animals↗
PubMed1991

Anomalous contours and illusion of angularity: phenomenal and theoretical comparisons.

Many experimental comparisons between real and anomalous contours have proven the functional equivalence of the two conditions; however, there are some contradictory findings. One of these is obtained by analyzing the anomalous contours in the light of a new illusion, called the 'illusion of angularity'. A circle becomes a polygon when it covers the centre of a radial arrangement of black stripes, and a polygon changes its perceptual shape depending on its orientation with respect to the same radial arrangement. Phenomenally, it appears like a very pointed polygon, in which every side is concave or, alternatively, a shape that looks like a circle with angles added in the spaces between the radial stripes, or a polygonal shape in which every side is convex. The reciprocal anomalous counterparts of these conditions, obtained by removing the geometrical/polygonal contours, reveal different results. In the first case, one sees a perfect circle; in the second case, a polygon with blunted vertices, or a circular shape with angular protrusions; in the third case, a deformed circle. These results are inconsistent with some theoretical models proposed to explain the emergence of anomalous contours, namely, all the top-down models expressed in terms of cognitive constructions and perceptual hypotheses, or in terms of global figural organizations. Rather, these comparisons suggest a different interpretation for the two phenomena (the illusion of angularity and anomalous contours). This interpretation is based on dynamic interactions or on network computations that synthesize both real and anomalous contours.

Adult↗