A New Cost-Profit Model for Measuring the Optimal Scale of China’s Foreign Exchange Reserve

The fast increase of foreign exchange reserve in developing countries has raised a number of important financial questions in recent years. The analysis of the optimal scale of the foreign exchange reserve can provide important indicator to measure the strength and stability of country’s financial standing. In this work we propose a cost-profit model and use the financial data during 2000 to 2008 to analyze the optimal scale of China’s foreign exchange reserve. We identify a number of financial factors to measure the cost and profit of holding the reserves. Our prediction suggested that China’s foreign exchange reserves were still within the moderate range in 1999–2001. However, during 2002–2008 the foreign exchange reserve began to exceed the appropriate scale, and this upward trend was accelerated each year

Oscillatory regulation of Hes1: discrete stochastic delay modelling and simulation

Discrete stochastic simulations are a powerful tool for understanding the dynamics of chemical kinetics when there are small-to-moderate numbers of certain molecular species. In this paper we introduce delays into the stochastic simulation algorithm, thus mimicking delays associated with transcription and translation. We then show that this process may well explain more faithfully than continuous deterministic models the observed sustained oscillations in expression levels of hes1 mRNA and Hes1 protein

A robust method for designing multistable systems by embedding bistable subsystems

Although multistability is an important dynamic property of a wide range of complex systems, it is still a challenge to develop mathematical models for realising high order multistability using realistic regulatory mechanisms. To address this issue, we propose a robust method to develop multistable mathematical models by embedding bistable models together. Using the GATA1-GATA2-PU.1 module in hematopoiesis as the test system, we first develop a tristable model based on two bistable models without any high cooperative coefficients, and then modify the tristable model based on experimentally determined mechanisms. The modified model successfully realises four stable steady states and accurately reflects a recent experimental observation showing four transcriptional states. In addition, we develop a stochastic model, and stochastic simulations successfully realise the experimental observations in single cells. These results suggest that the proposed method is a general approach to develop mathematical models for realising multistability and heterogeneity in complex systems

Stochastic Simulation of Process Calculi for Biology

Biological systems typically involve large numbers of components with complex, highly parallel interactions and intrinsic stochasticity. To model this complexity, numerous programming languages based on process calculi have been developed, many of which are expressive enough to generate unbounded numbers of molecular species and reactions. As a result of this expressiveness, such calculi cannot rely on standard reaction-based simulation methods, which require fixed numbers of species and reactions. Rather than implementing custom stochastic simulation algorithms for each process calculus, we propose to use a generic abstract machine that can be instantiated to a range of process calculi and a range of reaction-based simulation algorithms. The abstract machine functions as a just-in-time compiler, which dynamically updates the set of possible reactions and chooses the next reaction in an iterative cycle. In this short paper we give a brief summary of the generic abstract machine, and show how it can be instantiated with the stochastic simulation algorithm known as Gillespie's Direct Method. We also discuss the wider implications of such an abstract machine, and outline how it can be used to simulate multiple calculi simultaneously within a common framework.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

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

Effects of the particle of ground alfalfa hay on the growth performance, methane production and archaeal populations of rabbits

Publication history: Accepted - 20 August 2018; Published online - 17 September 2018.The world's annual output of rabbits is over 1.2 billion, therefore this sector is also one of the sources of greenhouse gases in livestock production. One hundred-twenty New Zealand rabbits were allocated into four treatments, five replicates in each treatment and six rabbits in each replicate to examine the effect of grinding alfalfa hay to different sizes on growth performance, methane production and cecal archaeal populations. The particle sizes of the alfalfa meal in the four treatment diets were 2500, 1000, 100 and 10 μm, while the other ingredients were ground through a 2.5 mm sieve. The average daily gain (ADG) and average daily feed intake (ADFI) increased (P<0.001) as the particle size decreased, but the feed conversion ratio (FCR) was not affected (P = 0.305). The digestibility of neutral detergent fiber (NDF) (P = 0.006) and acid detergent fiber (ADF) (P<0.006) increased while the greatest digestibility of crude protein (CP) was obtained in 1000 um group (P = 0.015). The rabbits produced more methane (CH4, L/kgBM0.75/d) with decreasing alfalfa particle size (P<0.001). The molar proportion of acetic acid and propionic acid decreased (P<0.001) at the cost of butyric acid (P<0.001). The greatest villus height:crypt depth ratio were obtained in 1000 μm group, and the decrease in the alfalfa hay particle size decreased the jejunum and ilem villus height:crypt depth ratio (P<0.05). The gastric muscular and mucosal thickness decreased with decreasing alfalfa particle size (P<0.05). Archaea diversity decreased with decreasing alfalfa particle size, and the relative abundance of genus Methanobrevibacter increased (P<0.001) while the genus Methanosphaera decreased (P<0.001). It is concluded that a finer particle size favors the growth of genus Methanobrevibacter, which produces more methane but promotes the growth performance of rabbits.The financial support was provided by the International Cooperation Project of Ministry of Science and Technology of China (2014DFA32860), http://www.most.gov.cn/eng/. LZ Wang received the funding. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

The underlying microbial mechanism of epizootic rabbit enteropathy triggered by a low fiber diet

Publication history: Accepted - 24 July 2018; Published online - 21 August 2018.Epizootic rabbit enteropathy (ERE) is reproduced successfully in the present study by feeding rabbits a low-fibre diet, and high-throughput sequencing and quantitative real-time PCR (qPCR) analysis were applied to examine the microbial variations in the stomach, small intestine and caecum. The evenness was disturbed and the richness was decreased in the ERE groups. When the rabbits were suffering from ERE, the abundance of the Firmicutes was decreased in three parts of the digestive tract, whereas the Proteobacteria was increased in the stomach and caecum, the Bacteroidetes and Verrucomicrobia were increased in the small intestine. Correlation analysis showed that the reduced concentrations of TVFA and butyrate in the caeca of the ERE group were attributed to the decreased abundances of genera such as Lactobacillus, Alistipes and other fibrolytic bacteria and butyrate- producing bacteria such as Eubacterium and Faecalibacterium. It is concluded that, in terms of microorganisms, the overgrowth of Bacteroides fragilis, Clostridium perfringen, Enterobacter sakazakii and Akkermansia muciniphila and inhibition of Bifidobacterium spp. and Butyrivibrio fibrisolvens in the stomach, small intestine and caecum resulted in a decrease in butyrate yield, leading to the incidence of ERE, and the probability of developing ERE could be manipulated by adjusting the dietary fibre level.The financial support was provided by the International Cooperation Project of Ministry of Science and Technology of China (2014DFA32860)