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At least 415 records · Page 23Linked to original sources
PubMed2005

Modeling Lactococcus lactis using a genome-scale flux model.

BACKGROUND: Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA) and minimization of metabolic adjustment (MOMA) were used as modeling frameworks. RESULTS: The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. CONCLUSION: The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.

Bacteria, Anaerobic↗
PubMedDate not supplied

Prediction of plasma levels of aminoglycoside antibiotic in patients with severe illness by means of an artificial neural network simulator.

PURPOSE: The purpose of this work was to predict plasma peak and trough levels of an aminoglycoside antibiotic in patients with severe illness in an intensive care unit by a novel approach. Plasma levels were predicted based on the values of 15 physiological measurements using an artificial neural network (ANN) simulator. METHOD: A data set of 15 physiological measurements for 30 patients was used to develop the model. The ANN structure consisted of three layers: an input layer comprised of 15 processing elements, a hidden layer comprised of 10 processing elements with a sigmoid function as an activation function, and an output layer of two processing elements (peak and trough levels). The weight between neurons was trained according to the delta rule back-propagation of errors algorithm. Predicted values were obtained by "leave-one-out" experiments by both ANN and multiple linear regression analysis (MLRA). RESULTS: The correlation coefficients between observed and predicted values obtained by ANN prediction using standardized data sets were r=0.825 and r=0.854 for peak and trough levels, respectively. The correlation coefficients obtained by MLRA were r=0. 037 and r=0.276 for peak and trough levels, respectively. These results indicate that ANN shows better performance in prediction of aminoglycoside plasma levels from patients' physiological measurements than MLRA. CONCLUSIONS: Prediction of plasma levels of antibiotic in patients with severe illness by ANN was superior to the standard statistical method. Standardization of input data was found to be important for better prediction. ANN has some advantages over standard statistical methods, as it can recognize complex relationships in the data.

Aminoglycosides↗
PubMed1986

Effect of temperature, pH and ionic strength and composition on fibrin network structure and its development.

Networks were developed in fibrinogen solution under pathophysiological conditions of clotting. Mass-length ratio (a measure of fibre thickness) was derived independently from the turbidity (microT) and from the permeability (microP) of the network. Kinetics of network growth were investigated turbidimetrically. Physiological concentrations of Ca++and Mg++increased microT while those of K+, Na+, Cl-, HCO-3, H2PO-4 and SO--4 had no effect. As pH and ionic strength were increased stepwise within the pathophysiological range, network development was delayed. Under these conditions the turbidity curves did not cross and both microT and microP were progressively decreased. When temperature was lowered, although network growth was delayed, the turbidy curves crossed: the equilibrium turbidity was higher at lower temperatures. It appears that while pH and ionic strength affect network structure by influencing fibrin assembly, lowering the temperature influences both the rate of fibrin monomer generation and fibrin assembly.

Fibrin↗
PubMed2003

Reconstruction of the central carbon metabolism of Aspergillus niger.

The topology of central carbon metabolism of Aspergillus niger was identified and the metabolic network reconstructed, by integrating genomic, biochemical and physiological information available for this microorganism and other related fungi. The reconstructed network may serve as a valuable database for annotation of genes identified in future genome sequencing projects on aspergilli. Based on the metabolic reconstruction, a stoichiometric model was set up that includes 284 metabolites and 335 reactions, of which 268 represent biochemical conversions and 67 represent transport processes between the different intracellular compartments and between the cell and the extracellular medium. The stoichiometry of the metabolic reactions was used in combination with biosynthetic requirements for growth and pseudo-steady state mass balances over intracellular metabolites for the quantification of metabolic fluxes using metabolite balancing. This framework was employed to perform an in silico characterisation of the phenotypic behaviour of A. niger grown on different carbon sources. The effects on growth of single reaction deletions were assessed and essential biochemical reactions were identified for different carbon sources. Furthermore, application of the stoichiometric model for assessing the metabolic capabilities of A. niger to produce metabolites was evaluated by using succinate production as a case study.

Aspergillus niger↗
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↗
PubMed1996

Synchronization without oscillatory neurons.

Experimental results suggest that neurons in the cortex synchronize their action potentials on the millisecond time scale. More importantly this binding expresses functional relationships between the neurons. A model of neuronal interactions is proposed in which simultaneous discharges of neurons develop through specialized synaptic circuits. As an important prerequisite for this synchronization it is demonstrated that SynFire chains, generating different levels of excitation, propagate their activity waves at distinct velocities. Two chains were coupled by excitatory synapses and their activity was initiated at different times. Due to synaptic interactions, activity in the earlier-initiated chain accelerates propagation in the other chain until the two activity waves are synchronized. Compared with several neural network models with oscillatory units, physiologically more plausible neurons are simulated. It is still under debate whether neurons in the cortex show oscillatory discharges per se. In particular, a high rate of noise relative to very weak synaptic gains cannot impair our results in the neural network simulations.

Action Potentials↗
PubMed2001

Comparison of artificial intelligence techniques with UKTRISS for estimating probability of survival after trauma. UK Trauma and Injury Severity Score.

BACKGROUND: The development of TRISS was principally a search for variables that correlated with outcome. It is not known, however, if linear statistical models provide optimal results. Artificial intelligence techniques can answer this question and also determine the most important predictor variables. METHODS: An artificial neural network, using 16 anatomic and physiologic predictor variables, was compared with the latest United Kingdom version of TRISS model. RESULTS: Both methods were 89.6% correct, but TRISS was significantly better by the area under the receiver operating characteristic curve (0.941 vs. 0.921, p < 0.001). The artificial neural network, however, was better calibrated to the test data (Hosmer-Lemeshow statistic, 58.3 vs. 105.4). Head injury, age, and chest injury were the most important predictors by linear or nonlinear methods, whereas respiration rate, heart rate, and systolic blood pressure were underused. CONCLUSION: Prediction using linear statistics is adequate but not optimal. Only half the predictors have important predictive value, fewer still when using linear classification. The strongest predictors swamp any nonlinearity observed in other variables.

Artificial Intelligence↗
PubMed1999

Metabolic engineering from a cybernetic perspective. 1. Theoretical preliminaries

The theoretical basis of a cybernetic metabolic network design and analysis framework, which has been subsequently successfully applied to predict system response to genetic alteration, is presented. This conceptual methodology consists of three main branches, namely, a model realization framework, a representation of genetic alteration, and lastly, a metabolic design component. These concepts are introduced as a series of postulates that describe the basic tenets of the approach. Each branch is discussed in turn, starting with the cybernetic representation of arbitrarily complex metabolic networks. A set of postulates is put forth that affords the modular construction of cybernetic models of metabolic networks using as a base a library of elementary pathways. This is followed by a discussion of the representation of genetic alterations within the cybernetic framework. It is postulated that the objective of the base network and the altered system are identical (at least on the time scale required for the organism to "learn" new objectives). This implies, with respect to resource allocation, that the base network and its genetically altered counterpart may still be treated as optimal systems; however, the set of competing physiological choices open to the altered network expands or contracts depending upon the nature of the genetic perturbation. Lastly, to add a predictive design aspect to the methodology, we present a set of postulates that outline the application of metabolic control analysis to cybernetic model systems. We postulate that sensitivity coefficients computed from a cybernetic model, although still local in scope, have the added benefit of a systematic representation of regulatory function as described by the cybernetic variables. Thus, information gained from sensitivity measurements stemming from a cybernetic model include the explicit input of metabolic regulation, a component that is lacking in a purely kinetic representation of metabolic function. The sensitivity results can then be employed to develop qualitative strategies for the rational alteration of metabolic function, which can be evaluated by simulation of an appropriately modified cybernetic model of the base network.

Journal Article↗
PubMed2006

Application of an ecological framework linking scales based on self-thinning.

Barnes and Roderick developed a generic, theoretical framework for vegetation modeling across scales. Inclusion of a self-thinning mechanism connects the individual to the larger-scale population and, being based on the conservation of mass, all mass flux processes are integral to the formulation. Significantly, disturbance (both regular and stochastic) and its impact at larger scales are included in the formulation. The purpose of this paper is to illustrate how this model can be used to predict patch and ecosystem dry mass, and consequently system carbon. Examples from pine plantations and mixed forests are considered, with these applications requiring estimates of system carrying capacity and the growth rates of individual plants. The results indicate that the model is relatively simple and straightforward to apply, and its predictions compare well with the data. A significant feature of this approach is that the impact of local scale data on the dynamics of larger patch and ecosystem scales can be determined explicitly, as we show by example. Further, the general formulation has an analytic solution based on characteristics of the individual, facilitating practical and predictive application.

Adaptation, Physiological↗
PubMed1995

Injury severity and probability of survival assessment in trauma patients using a predictive hierarchical network model derived from ICD-9 codes.

UNLABELLED: Accurate assessment of injury severity is critical for decision making related to the prevention, triage, and treatment of injured patients. Presently, the standard method of controlling for variations of injury severity between groups has been based upon the Injury Severity Score (ISS) and the Trauma Score and the Trauma and Injury Severity Score (TRISS) methodology. The purpose of this study was to attempt to build upon previous work using International Classification of Diseases, ninth revision (ICD-9) coded diagnosis, and procedure information available from standard hospital discharge abstracts (UB-82 Billing format) to create a hierarchical network to provide a tool for predicting injury severity and probability of survival. METHODS: Data were obtained for this analysis from the North Carolina Medical Database. Data were available on all trauma patients admitted to hospitals in North Carolina from January 1, 1988 until June 30, 1992. The dependent variable of interest was the patient's survival after injury, coded as live or die. The independent variables used in the study included the ISS derived using the technique described by MacKenzie Abbreviated Injury Score (AIS) and body system maximum AIS scores, mortality risk ratios derived from the ICD-9-DM primary, secondary, and tertiary diagnoses, primary and secondary procedures as described in previous work, age and gender. Network generation used a commercial software package, AIM (Abtech Corp., Charlottesville, Va.), which is a numeric modeling tool that automatically "learns" knowledge from a data base of examples. RESULTS: In the test data set an ISS and a prediction of survival based upon the derived network were calculated for each and every patient. The relative predictive power of these two scores were compared by calculating the overall accuracy, sensitivity, and specificity and the false positive and false negative rates. The receiver operator characteristic curves demonstrate that the network is a more effective tool in predicting the outcome of trauma patients. All the measures of predictive power show that the network was the better predictor of outcome than the ISS. CONCLUSIONS: Given the recognized limitations of the ISS, the widespread availability of the ICD-9 coded diagnoses and procedures, and the availability of many state and regional data bases that have no ISS or Trauma Score, the purpose of this study was to assess the ability of a network derived from limited but widely available hospital discharge data to predict the outcome of injured patients. The study confirms previous work showing that the ICD-9 codes were strongly associated with outcome. The study demonstrated that the network created from these data was a better predictor of outcome than the derived ISS. When the results of the network were compared with other published series, the network, created without access to physiologic information, was almost as accurate, sensitive, and specific as reported values for TRISS and A Severity Characterization of Trauma (ASCOT). Because the present study is the first of its type, further investigations are needed to validate these findings. If other studies corroborate this study, a network model based upon ICD-9 codes could become the principal method for grading injury severity. This would provide superior predictive power of injury severity with important cost savings and universal application.

Adult↗
PubMed1996

Pathogenesis of scleroderma. Collagen.

It is now evident that persistent overproduction of collagen and other connective tissue macromolecules results in excessive tissue deposition, and is responsible for the progressive nature of fibrosis in SSc. Up-regulation of collagen gene expression in SSc fibroblasts appears to be a critical event in the development of tissue fibrosis. The coordinate transcriptional activation of a number of extracellular matrix genes suggests a fundamental alteration in the regulatory control of gene expression in SSc fibroblasts. Trans-acting nuclear factors that bind to cis-acting elements in enhancer and promoter regions of the genes modulate the basal and inducible transcriptional activity of the collagen genes. The identity of the nuclear transcriptional factors that regulate normal collagen gene expression remains to be firmly established, and to date, no alterations in the level or in the activity of such DNA binding factors has been demonstrated in SSc fibroblasts. In addition to important interactions between fibroblasts and the extracellular matrix, cytokines and other cellular mediators can positively and negatively influence fibroblast collagen synthesis. Some of these signaling molecules may have physiologic roles, and their aberrant expression, or altered responsiveness of SSc fibroblasts to them, may result in the acquisition of the activated phenotype. The rapid expansion of knowledge regarding the effects of cytokines on extracellular matrix synthesis has led to an appreciation of the enormous complexity of regulatory networks that operate in the physiologic maintenance of connective tissue and which may be responsible for the occurrence of pathologic fibrosis. The ubiquitous growth factor TGF beta is the most potent inducer of collagen gene expression and connective tissue accumulation yet discovered. The expression of TGF beta in activated infiltrating mononuclear cells suggests a role for this cytokine as a mediator of fibroblast activation in SSc. Furthermore, the recognition that TGF beta is capable of inducing its own expression in a variety of cell types, coupled with the demonstration that a subpopulation of SSc dermal fibroblasts produces TGF beta, indicates the existence of a possible autocrine loop whereby lymphocyte-derived TGF beta in early SSc not only signals biosynthetic activation of fibroblasts in a paracrine manner, but autoinduces endogenous TGF beta production by the target fibroblasts themselves. Such an autocrine loop involving TGF beta may explain the persistent activation of collagen gene expression in SSc fibroblasts, and could be responsible for the progressive nature of fibrosis in SSc. Numerous other cytokines, as well as cell-matrix interactions, also modify collagen gene expression and can significantly influence the effects of TGF beta. Although their physiologic function in tissue remodeling or their involvement in abnormal fibrogenesis has not yet been conclusively demonstrated, the study of the biologic effects of these cytokines may provide important clues to understanding the pathogenesis of SSc, and to the development of rational drug therapy aimed at interrupting the abnormal fibrogenic process in this disease.

Animals↗
PubMed2002

Learning the invariance properties of complex cells from their responses to natural stimuli.

Neurons in primary visual cortex are typically classified as either simple or complex. Whereas simple cells respond strongly to grating and bar stimuli displayed at a certain phase and visual field location, complex cell responses are insensitive to small translations of the stimulus within the receptive field [Hubel & Wiesel (1962) J. Physiol. (Lond.), 160, 106-154; Kjaer et al. (1997) J. Neurophysiol., 78, 3187-3197]. This constancy in the response to variations of the stimuli is commonly called invariance. Hubel and Wiesel's classical model of the primary visual cortex proposes a connectivity scheme which successfully describes simple and complex cell response properties. However, the question as to how this connectivity arises during normal development is left open. Based on their work and inspired by recent physiological findings we suggest a network model capable of learning from natural stimuli and developing receptive field properties which match those of cortical simple and complex cells. Stimuli are drawn from videos obtained by a camera mounted to a cat's head, so they should approximate the natural input to the cat's visual system. The network uses a competitive scheme to learn simple and complex cell response properties. Employing delayed signals to learn connections between simple and complex cells enables the model to utilize temporal properties of the input. We show that the temporal structure of the input gives rise to the emergence and refinement of complex cell receptive fields, whereas removing temporal continuity prevents this processes. This model lends a physiologically based explanation of the development of complex cell invariance response properties.

Animals↗
PubMed2005

Compensatory physiological responses to chronic blockade of amino acid receptors during early development in spontaneously active organotypic cerebral cortex explants cultured in vitro.

Paired organotypic explants from rat occipital cortex were cultured for up to three weeks in the presence of selective blockers of amino acid receptor blockers, during which period spontaneous action potential generation was monitored electrophysiologically. In contrast to isolated explants (Corner, M.A., van Pelt, J., Wolters, P.S., Baker, R.E.and Nuytinck, R.H. (2002) Physiological e.ects of sustained blockade of excitatory synaptic transmission on spontaneously active developing neuronal networks--an inquiry into the reciprocal linkage between intrinsic biorhythms and neuroplasticity in early ontogeny. Neurosci. Biobehav. Rev., 26: 127-185), which upregulated their initially depressed spontaneous bursting activity only under conditions of N-methyl D-aspartate (NMDA) receptor blockade, cross-innervated co-cultures showed a large degree of functional recovery even when combined NMDA and AMPA receptor blockade was carried out. This compensatory activity could be eliminated by acute addition of a selective kainate receptor blocker to the medium. When kainate along with AMPA and NMDA receptor mediated activity was chronically suppressed, however, considerable functional recovery--in the form of recurrent burst discharges--took place gradually over a period of three weeks in vitro. These spontaneous bursts disappeared rapidly upon treatment with the muscarinic receptor blocker, atropine, but continuous low-level firing emerged at the same time. Similar "tonic" background activity was induced in control cultures as well, but without any noticeable reduction in burst discharges. Co-cultured neocortex explants, in which cyto-morphological maturation proceeds to a far greater degree than in isolated explants (Baker, R.E.and van Pelt, J. (1997) Co-cultured but not isolated cortical explants display normal dendritic development: a longterm quantitative study. Dev. Brain Res., 98: 21-27) are evidently capable of an astonishing degree of functional compensation for loss of excitatory synaptic drive during development. It could be shown, furthermore, that such homeostatic responses are not mediated largely by a weakening of inhibitory mechanisms in the absence of spontaneous firing. Chronic inhibitory synaptic blockade, on the other hand, led to intensified bursting activity which gradually normalized over a 3-week culture period. The cellular basis for this reversal of the disinhibited state, as well as for the residual neuronal firing even after cholinergic mechanisms have been largely eliminated, is at present unknown. The degree to which immature cortical networks attempt to compensate for altered levels of physiological activity, as documented in the present report, is another indication of how important such activity can be for normal development (see Corner, M.A., van Pelt, J., Wolters, P.S., Baker, R.E. and Nuytinck, R.H. (2002) Physiological e.ects of sustained blockade of excitatory synaptic transmission on spontaneously active developing neuronal networks-an inquiry into the reciprocal linkage between intrinsic biorhythms and neuroplasticity in early ontogeny. Neurosci. Biobehav. Rev., 26: 127-185).. At the same time, the large variations in overall firing levels and "macro-scale" temporal patterns from culture to culture within a given series, despite all attempts at identical preparation of the explants, can only mean that the "set-points" for such regulation are themselves subject to unknown ontogenetic factors which, apparently, are nonuniformly distributed even within a restricted region of the neocortex. On the other hand, it was striking to note that, regardless of age or treatment, an unexpected degree of consistency in temporal patterning existed at "mini-" and "micro-" time-scales (viz., EEG delta and beta frequency ranges, respectively) even when network bursting tendencies became greatly reduced in favor of tonic firing.

Adaptation, Physiological↗
PubMed2004

Quantal transmission at mossy fibre targets in the CA3 region of the rat hippocampus.

Recent anatomical evidence that inhibitory interneurones receive approximately 10 times more synapses from mossy fibres than do principal neurones (Acsády et al. 1998) has led to the re-examination of the extent to which interneurones are involved in CA3 network excitability. Although many of the anatomical and physiological properties of mossy fibre-CA3 interneurone synapses have been previously described (Acsády et al. 1998; Tóth et al. 2000), an investigation into the quantal nature of transmission at this synapse has not yet been conducted. Here, we employed variance-mean (VM) analysis to compare the release probability, quantal size (q) and number of release sites (n) at mossy fibre target neurones in CA3. At six of seven interneurone synapses in which a high concentration of Ca2+ was experimentally imposed, the variance-mean relationship could be approximated by a parabola. Estimates of n were 1-2, and the weighted release probability in normal Ca2+ conditions ranged from 0.34 to 0.51. At pyramidal cell synapses, the variance-mean relationship approximated a linear relationship, suggesting that release probability was significantly lower. The weighted quantal amplitude was similar at interneurone synapses and pyramidal cell synapses, although the variability in quantal amplitude was larger at interneurone synapses. Mossy fibre transmission at CA3 interneurone synapses can be explained by a lower number of release sites, a broader range of release probabilities, and larger range of quantal amplitudes than at CA3 pyramidal synapses. Finally, quantal events on to interneurones elicited spike transmission, owing in part to the more depolarized membrane potential than pyramidal cells. These results suggest that although mossy fibre synapses on to pyramidal cells are associated with a larger number of release sites per synapse, the higher connectivity, higher initial release probability, and larger relative impact per quantum on to CA3 interneurones generate strong feedforward inhibition at physiological firing frequencies of dentate granule cells. Given the central role of CA3 interneurones in mossy fibre synaptic transmission, these details of mossy fibre synaptic transmission should provide insight into CA3 network dynamics under both physiological and pathophysiological circumstances.

Action Potentials↗
PubMed1995

The network theory: 21 years later.

The network theory was proposed 21 years ago, attracting then much interest as applied to the regulation of (clonal) immune responses. The first 10 years of 'idiotypic network' research have thus addressed questions that were already appropriately solved by the clonal selection theory, leading to a justifiable loss of its impact. In contrast, 'second generation networks', concentrate on systemic properties that emerge from a network organization, thus providing a framework for several major questions that seem to supersede clonal solutions: the developmental 'learning' of self antigenic composition and the maintenance of the respective 'memory' (self-tolerance), repertoire selection and the homeostatic regulation of lymphocyte numbers, natural immune activities that are independent of external antigens, the physiology of autoreactivity. The immune network may well contribute solutions to autoimmune diseases, where clonal approaches, classical and modern alike, have failed.

Allergy and Immunology↗
PubMed1988

'Photo-degeneration' of neurones after extracellular dye application.

Irradiation in the presence of a dye applied to the extracellular space was found to trigger neuronal degeneration in fly photoreceptor neurones. This phenomenon endowed the selected cells with a dark and fine-grained label such that they could be traced and scrutinized for synaptic specializations. It also initiated their phagocytotic removal from the neural network. Various states of degeneration fitting classical descriptions could be achieved by acting upon the light dose. The phenomenon seems to rely on photosensitization of the cell by the dye. The simplicity and precision with which this phenomenon can be induced makes 'photo-degeneration' an exciting prospective tool for combined anatomical and physiological studies on (natural) neural networks and may provide a new line of medical applications.

Animals↗
PubMed2005

[Emphasize the role of bioactive small molecules in the homeostasis regulation of cardiovascular system].

Bioactive small molecules play a crucial role in maintaining structural and functional homeostasis of cardiovascular system. However, systemic research pattern is rare because of the multiple forms, diverse effects and complicated interaction of these molecules. Therefore firstly, they can be classified into different single 'families' according to their internal relationships. Secondly, studies may be focused on the network of members within each 'family' as well as network among different 'families', especially the physiological and pathological significance of each member in the cardiovascular diseases. Lastly, efforts should be made to establish a primary and simple regulation network as the strategy of researches on biology of cardiovascular systems, and to promote the transition to a network covering more complicated multiplex 'families', even the whole body.

Biological Products↗