1,075 research outputs found
Antinociceptive and anti-Inflammatory effects of the standardized oil of Indian Callistemon lanceolatus leaves in experimental animals
The effect of Callistemon lanceolatus (Syn. C. citrinus curtis; Family: Myrtaceae) leaf oil was studied for the antinociceptive and anti-inflammatory activity in experimental animals. C. lanceolatus, 25 – 100 mg/kg administered orally for 3 days exhibited graded dose response equivalent to 21.95% - 89.90% protection in the tail flick latent test in rat. The C. lanceolatus oil (50 and 100 mg/kg, given orally for 3 days) was effective in hot plate reaction time (64.05% and 112.97%,
Markov chain aggregation and its application to rule-based modelling
Rule-based modelling allows to represent molecular interactions in a compact
and natural way. The underlying molecular dynamics, by the laws of stochastic
chemical kinetics, behaves as a continuous-time Markov chain. However, this
Markov chain enumerates all possible reaction mixtures, rendering the analysis
of the chain computationally demanding and often prohibitive in practice. We
here describe how it is possible to efficiently find a smaller, aggregate
chain, which preserves certain properties of the original one. Formal methods
and lumpability notions are used to define algorithms for automated and
efficient construction of such smaller chains (without ever constructing the
original ones). We here illustrate the method on an example and we discuss the
applicability of the method in the context of modelling large signalling
pathways
Fluctuation induces evolutionary branching in a modeled microbial ecosystem
The impact of environmental fluctuation on species diversity is studied with
a model of the evolutionary ecology of microorganisms. We show that
environmental fluctuation induces evolutionary branching and assures the
consequential coexistence of multiple species. Pairwise invasibility analysis
is applied to illustrate the speciation process. We also discuss how
fluctuation affects species diversity.Comment: 4 pages, 4 figures. Submitted to Physical Review Letter
Nuclear localization and function of polypeptide ligands and their receptors: a new paradigm for hormone specificity within the mammary gland?
The specific effects triggered by polypeptide hormone/growth factor stimulation of mammary cells were considered mediated solely by receptor-associated signaling networks. A compelling body of new data, however, clearly indicates that polypeptide ligands and/or their receptors are transported into the nucleus, where they function directly to regulate the expression of specific transcription factors and gene loci. The intranuclear function of these complexes may contribute to the explicit functions associated with a given ligand, and may serve as new targets for pharmacologic intervention
Feedback control architecture and the bacterial chemotaxis network.
PMCID: PMC3088647This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Bacteria move towards favourable and away from toxic environments by changing their swimming pattern. This response is regulated by the chemotaxis signalling pathway, which has an important feature: it uses feedback to 'reset' (adapt) the bacterial sensing ability, which allows the bacteria to sense a range of background environmental changes. The role of this feedback has been studied extensively in the simple chemotaxis pathway of Escherichia coli. However it has been recently found that the majority of bacteria have multiple chemotaxis homologues of the E. coli proteins, resulting in more complex pathways. In this paper we investigate the configuration and role of feedback in Rhodobacter sphaeroides, a bacterium containing multiple homologues of the chemotaxis proteins found in E. coli. Multiple proteins could produce different possible feedback configurations, each having different chemotactic performance qualities and levels of robustness to variations and uncertainties in biological parameters and to intracellular noise. We develop four models corresponding to different feedback configurations. Using a series of carefully designed experiments we discriminate between these models and invalidate three of them. When these models are examined in terms of robustness to noise and parametric uncertainties, we find that the non-invalidated model is superior to the others. Moreover, it has a 'cascade control' feedback architecture which is used extensively in engineering to improve system performance, including robustness. Given that the majority of bacteria are known to have multiple chemotaxis pathways, in this paper we show that some feedback architectures allow them to have better performance than others. In particular, cascade control may be an important feature in achieving robust functionality in more complex signalling pathways and in improving their performance
Bridging Time Scales in Cellular Decision Making with a Stochastic Bistable Switch
Cellular transformations which involve a significant phenotypical change of
the cell's state use bistable biochemical switches as underlying decision
systems. In this work, we aim at linking cellular decisions taking place on a
time scale of years to decades with the biochemical dynamics in signal
transduction and gene regulation, occuring on a time scale of minutes to hours.
We show that a stochastic bistable switch forms a viable biochemical mechanism
to implement decision processes on long time scales. As a case study, the
mechanism is applied to model the initiation of follicle growth in mammalian
ovaries, where the physiological time scale of follicle pool depletion is on
the order of the organism's lifespan. We construct a simple mathematical model
for this process based on experimental evidence for the involved genetic
mechanisms. Despite the underlying stochasticity, the proposed mechanism turns
out to yield reliable behavior in large populations of cells subject to the
considered decision process. Our model explains how the physiological time
constant may emerge from the intrinsic stochasticity of the underlying gene
regulatory network. Apart from ovarian follicles, the proposed mechanism may
also be of relevance for other physiological systems where cells take binary
decisions over a long time scale.Comment: 14 pages, 4 figure
Linear mapping approximation of gene regulatory networks with stochastic dynamics
The intractability of most stochastic models of gene regulatory networks (GRNs) limits their utility. Here, the authors present a linear-mapping approximation mapping models onto simpler ones, giving approximate but accurate analytic or semi- analytic solutions for a wide range of model GRNs
The Goldbeter-Koshland switch in the first-order region and its response to dynamic disorder
In their classical work (Proc. Natl. Acad. Sci. USA, 1981, 78:6840-6844),
Goldbeter and Koshland mathematically analyzed a reversible covalent
modification system which is highly sensitive to the concentration of
effectors. Its signal-response curve appears sigmoidal, constituting a
biochemical switch. However, the switch behavior only emerges in the
"zero-order region", i.e. when the signal molecule concentration is much lower
than that of the substrate it modifies. In this work we showed that the
switching behavior can also occur under comparable concentrations of signals
and substrates, provided that the signal molecules catalyze the modification
reaction in cooperation. We also studied the effect of dynamic disorders on the
proposed biochemical switch, in which the enzymatic reaction rates, instead of
constant, appear as stochastic functions of time. We showed that the system is
robust to dynamic disorder at bulk concentration. But if the dynamic disorder
is quasi-static, large fluctuations of the switch response behavior may be
observed at low concentrations. Such fluctuation is relevant to many biological
functions. It can be reduced by either increasing the conformation
interconversion rate of the protein, or correlating the enzymatic reaction
rates in the network.Comment: 23 pages, 4 figures, accepted by PLOS ON
The interplay of intrinsic and extrinsic bounded noises in genetic networks
After being considered as a nuisance to be filtered out, it became recently
clear that biochemical noise plays a complex role, often fully functional, for
a genetic network. The influence of intrinsic and extrinsic noises on genetic
networks has intensively been investigated in last ten years, though
contributions on the co-presence of both are sparse. Extrinsic noise is usually
modeled as an unbounded white or colored gaussian stochastic process, even
though realistic stochastic perturbations are clearly bounded. In this paper we
consider Gillespie-like stochastic models of nonlinear networks, i.e. the
intrinsic noise, where the model jump rates are affected by colored bounded
extrinsic noises synthesized by a suitable biochemical state-dependent Langevin
system. These systems are described by a master equation, and a simulation
algorithm to analyze them is derived. This new modeling paradigm should enlarge
the class of systems amenable at modeling.
We investigated the influence of both amplitude and autocorrelation time of a
extrinsic Sine-Wiener noise on: the Michaelis-Menten approximation of
noisy enzymatic reactions, which we show to be applicable also in co-presence
of both intrinsic and extrinsic noise, a model of enzymatic futile cycle
and a genetic toggle switch. In and we show that the
presence of a bounded extrinsic noise induces qualitative modifications in the
probability densities of the involved chemicals, where new modes emerge, thus
suggesting the possibile functional role of bounded noises
A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli
Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon
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