1,606 research outputs found
The Mechanical Behavior of a 25Cr Super Duplex Stainless Steel at Elevated Temperature
Peer reviewedPostprin
Evolution of opinions on social networks in the presence of competing committed groups
Public opinion is often affected by the presence of committed groups of
individuals dedicated to competing points of view. Using a model of pairwise
social influence, we study how the presence of such groups within social
networks affects the outcome and the speed of evolution of the overall opinion
on the network. Earlier work indicated that a single committed group within a
dense social network can cause the entire network to quickly adopt the group's
opinion (in times scaling logarithmically with the network size), so long as
the committed group constitutes more than about 10% of the population (with the
findings being qualitatively similar for sparse networks as well). Here we
study the more general case of opinion evolution when two groups committed to
distinct, competing opinions and , and constituting fractions and
of the total population respectively, are present in the network. We show
for stylized social networks (including Erd\H{o}s-R\'enyi random graphs and
Barab\'asi-Albert scale-free networks) that the phase diagram of this system in
parameter space consists of two regions, one where two stable
steady-states coexist, and the remaining where only a single stable
steady-state exists. These two regions are separated by two fold-bifurcation
(spinodal) lines which meet tangentially and terminate at a cusp (critical
point). We provide further insights to the phase diagram and to the nature of
the underlying phase transitions by investigating the model on infinite
(mean-field limit), finite complete graphs and finite sparse networks. For the
latter case, we also derive the scaling exponent associated with the
exponential growth of switching times as a function of the distance from the
critical point.Comment: 23 pages: 15 pages + 7 figures (main text), 8 pages + 1 figure + 1
table (supplementary info
Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53
Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets.
Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region.
Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes
Cisplatin-induced emesis: systematic review and meta-analysis of the ferret model and the effects of 5-HT3 receptor antagonists
PURPOSE: The ferret cisplatin emesis model has been used for ~30 years and enabled identification of clinically used anti-emetics. We provide an objective assessment of this model including efficacy of 5-HT(3) receptor antagonists to assess its translational validity. METHODS: A systematic review identified available evidence and was used to perform meta-analyses. RESULTS: Of 182 potentially relevant publications, 115 reported cisplatin-induced emesis in ferrets and 68 were included in the analysis. The majority (n = 53) used a 10 mg kg(−1) dose to induce acute emesis, which peaked after 2 h. More recent studies (n = 11) also used 5 mg kg(−1), which induced a biphasic response peaking at 12 h and 48 h. Overall, 5-HT(3) receptor antagonists reduced cisplatin (5 mg kg(−1)) emesis by 68% (45–91%) during the acute phase (day 1) and by 67% (48–86%) and 53% (38–68%, all P < 0.001), during the delayed phase (days 2, 3). In an analysis focused on the acute phase, the efficacy of ondansetron was dependent on the dosage and observation period but not on the dose of cisplatin. CONCLUSION: Our analysis enabled novel findings to be extracted from the literature including factors which may impact on the applicability of preclinical results to humans. It reveals that the efficacy of ondansetron is similar against low and high doses of cisplatin. Additionally, we showed that 5-HT(3) receptor antagonists have a similar efficacy during acute and delayed emesis, which provides a novel insight into the pharmacology of delayed emesis in the ferret
Robustness of circadian clocks to daylight fluctuations: hints from the picoeucaryote Ostreococcus tauri
The development of systemic approaches in biology has put emphasis on
identifying genetic modules whose behavior can be modeled accurately so as to
gain insight into their structure and function. However most gene circuits in a
cell are under control of external signals and thus quantitative agreement
between experimental data and a mathematical model is difficult. Circadian
biology has been one notable exception: quantitative models of the internal
clock that orchestrates biological processes over the 24-hour diurnal cycle
have been constructed for a few organisms, from cyanobacteria to plants and
mammals. In most cases, a complex architecture with interlocked feedback loops
has been evidenced. Here we present first modeling results for the circadian
clock of the green unicellular alga Ostreococcus tauri. Two plant-like clock
genes have been shown to play a central role in Ostreococcus clock. We find
that their expression time profiles can be accurately reproduced by a minimal
model of a two-gene transcriptional feedback loop. Remarkably, best adjustment
of data recorded under light/dark alternation is obtained when assuming that
the oscillator is not coupled to the diurnal cycle. This suggests that coupling
to light is confined to specific time intervals and has no dynamical effect
when the oscillator is entrained by the diurnal cycle. This intringuing
property may reflect a strategy to minimize the impact of fluctuations in
daylight intensity on the core circadian oscillator, a type of perturbation
that has been rarely considered when assessing the robustness of circadian
clocks
Robust Detection of Hierarchical Communities from Escherichia coli Gene Expression Data
Determining the functional structure of biological networks is a central goal
of systems biology. One approach is to analyze gene expression data to infer a
network of gene interactions on the basis of their correlated responses to
environmental and genetic perturbations. The inferred network can then be
analyzed to identify functional communities. However, commonly used algorithms
can yield unreliable results due to experimental noise, algorithmic
stochasticity, and the influence of arbitrarily chosen parameter values.
Furthermore, the results obtained typically provide only a simplistic view of
the network partitioned into disjoint communities and provide no information of
the relationship between communities. Here, we present methods to robustly
detect coregulated and functionally enriched gene communities and demonstrate
their application and validity for Escherichia coli gene expression data.
Applying a recently developed community detection algorithm to the network of
interactions identified with the context likelihood of relatedness (CLR)
method, we show that a hierarchy of network communities can be identified.
These communities significantly enrich for gene ontology (GO) terms, consistent
with them representing biologically meaningful groups. Further, analysis of the
most significantly enriched communities identified several candidate new
regulatory interactions. The robustness of our methods is demonstrated by
showing that a core set of functional communities is reliably found when
artificial noise, modeling experimental noise, is added to the data. We find
that noise mainly acts conservatively, increasing the relatedness required for
a network link to be reliably assigned and decreasing the size of the core
communities, rather than causing association of genes into new communities.Comment: Due to appear in PLoS Computational Biology. Supplementary Figure S1
was not uploaded but is available by contacting the author. 27 pages, 5
figures, 15 supplementary file
Dynamic modeling of gene expression in prokaryotes: application to glucose-lactose diauxie in Escherichia coli
Coexpression of genes or, more generally, similarity in the expression
profiles poses an unsurmountable obstacle to inferring the gene regulatory
network (GRN) based solely on data from DNA microarray time series. Clustering
of genes with similar expression profiles allows for a course-grained view of
the GRN and a probabilistic determination of the connectivity among the
clusters. We present a model for the temporal evolution of a gene cluster
network which takes into account interactions of gene products with genes and,
through a non-constant degradation rate, with other gene products. The number
of model parameters is reduced by using polynomial functions to interpolate
temporal data points. In this manner, the task of parameter estimation is
reduced to a system of linear algebraic equations, thus making the computation
time shorter by orders of magnitude. To eliminate irrelevant networks, we test
each GRN for stability with respect to parameter variations, and impose
restrictions on its behavior near the steady state. We apply our model and
methods to DNA microarray time series' data collected on Escherichia coli
during glucose-lactose diauxie and infer the most probable cluster network for
different phases of the experiment.Comment: 20 pages, 4 figures; Systems and Synthetic Biology 5 (2011
Femoral revision knee Arthroplasty with Metaphyseal sleeves: the use of a stem is not mandatory of a structural point of view
Purpose
Metaphyseal sleeves are an option for patients with severe metaphyseal bony defects requiring TKA revision. Although sleeves are usually used with stems, little is known about the exact contribution/need of the stem for the initial sleeve-bone interface stability, particularly in the femur, if the intramedullary canal is deformed or bowed. It is hypothesised that diaphyseal-stem addition increases the sleeve-femur interface stability and the strain-shielding effect on the metaphyseal femur relatively to the stemless condition.
Material and methods
Synthetic-femur was used to measure cortex strain behaviour and implant cortex micromotions for three techniques: only femoral-component, stemless-sleeve and stemmed-sleeve. Paired t-tests were performed to evaluate the statistical significance of the difference between mean principal strains and implant-cortex micromotions. Finite-element models were developed to assess the cancellous-bone strain behaviour and sleeve-bone interface micromotions; these models were validated against the measurements.
Results
Cortex strains are reduced significantly (p<0.05) in 83% of strain gauges on stemmed-sleeve, which compares with 33% in stemless condition. Both techniques presented a cancellous bone strain reduction of 50% at the distal region and an increase of nearly four times at the sleeve proximal region relative to the model only with the femoral component. Both techniques presented sleeve-bone micromotions amplitude below 50-150μm, suitable for bone ingrowth.
Conclusions
The use of a supplemental diaphyseal-stem potentiates the risk of cortex bone resorption compared with the stemless-sleeve condition; however, the stem is not vital for increasing the initial sleeve-bone stability and has a minor effect on the cancellous-bone strain behaviour. Of a purely structural point view, appears that the use of a diaphyseal-femoral-stem with the metaphyseal sleeve is not mandatory in the revision TKA which is particularly relevant in cases where the use of stems is impracticable.publishe
An Electronic Analog of Synthetic Genetic Networks
An electronic analog of a synthetic genetic network known as the repressilator is proposed. The repressilator is a synthetic biological clock consisting of a cyclic inhibitory network of three negative regulatory genes which produces oscillations in the expressed protein concentrations. Compared to previous circuit analogs of the repressilator, the circuit here takes into account more accurately the kinetics of gene expression, inhibition, and protein degradation. A good agreement between circuit measurements and numerical prediction is observed. The circuit allows for easy control of the kinetic parameters thereby aiding investigations of large varieties of potential dynamics
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