Intracellular sensing of viral DNA by the innate immune system

Recent years have seen a great advance in knowledge of how a host senses infection. Nucleic acids, as a common denominator to all pathogens, are at the centre of several of the sensing pathways, especially those involved with the recognition of viruses. In this review we discuss the current knowledge on how intracellular DNA is sensed by the mammalian host.     

A simple model of pathogen–immune dynamics including specific and non-specific immunity

We present and analyze a model for the dynamics of the interactions between a pathogen and its host’s immune response. The model consists of two differential equations, one for pathogen load, the other one for an index of specific immunity. Differently from other simple models in the literature, this model exhibits, according to the hosts’ or pathogen’s parameter values, or to the initial infection size, a rich repertoire of behaviours: immediate clearing of the pathogen through aspecific immune response; or acute infection followed by clearing of the pathogen through specific immune response; or uncontrolled infections; or acute infection followed by convergence to a stable state of chronic infection; or periodic solutions with intermittent acute infections. The model can also mimic some features of immune response after vaccination. This model could be a basis on which to build epidemic models including immunological features.     

Isolation and Purification of Carp Mitochondrial DNA and Structural Analysis of Its tRNA~(Cys) Gene and the Light Strand Origin

A new method is presented with which we isolated milochondrial DNA from fresh carp liver usingdifferential centrifugation and DNase treatment that gave high yield of purified product with an easyand economical procedure. Highly distinct bands were displayed in agarose gel electrophoresls ofthe product digested with restrictlon enzymes, which were successfully used in constructingrestriction map and molecular clone of mitochondrial genes. With DNAs thus obtained, we havecloned cysteine tRNA gene (tRNA~(Cys) gene) of carp mitochondria, determined the nucleotide sequenceof it and the light strand origin, and depicted the cloverleaf secondary structure of tDNA~(Cya) and thelight strand origin. Analysis of nucleotide sequences of tRNA~(Cy) genes of 5 vertebrates has revealedunusual features of carp mitochondrial tRNA~(Cy) gene as compared with their cytoplasmic counter-parts, Altogether 36 bases were found in the light strand origin of carp mitochondriaf: 11 pairs in thestem; and 14 bases in the loop. As compared with those of other 11 vertebrate species, the sequenceof the stem is very conservative while both sequence and length of the loop are quite variable. Thestructure of the stem-loop may play an important role in light strand replication.     

Diffusion versus network models as descriptions for the spread of prion diseases in the brain

In this paper we will discuss different modeling approaches for the spread of prion diseases in the brain. Firstly, we will compare reaction-diffusion models with models of epidemic diseases on networks. The solutions of the resulting reaction-diffusion equations exhibit traveling wave behavior on a one-dimensional domain, and the wave speed can be estimated. The models can be tested for diffusion-driven (Turing) instability, which could present a possible mechanism for the formation of plaques. We also show that the reaction-diffusion systems are capable of reproducing experimental data on prion spread in the mouse visual system. Secondly, we study classical epidemic models on networks, and use these models to study the influence of the network topology on the disease progression.     

Autoimmunity as an immune defense against degenerative processes: a primary mathematical model illustrating the bright side of autoimmunity

Self-tolerance, or the ability of the immune system to refrain from destroying the organism's own tissues, is a prerequisite for proper immune system operation. How such self-tolerance is achieved is still a subject of debate. The belief that autoimmunity poses a continuous threat to the organism was challenged by data demonstrating that autoimmunity has a protective function after traumatic injury to the central nervous system. This finding led us to suggest the 'comprehensive immunity' approach by which autoimmunity is viewed as a special case of immunity, namely as a defense mechanism that operates by fighting against the threat of potential destructive activity originated or mediated within the organism, similarly to the immune defense that operates against the threat from exogenous pathogens. We present a primary mathematical spatio-temporal model that supports this concept. The numerical solutions of this model illustrate the beneficial operation of a well-controlled immune response specific to self-antigens residing in the site of lesion. The model also explains how the response to self might be tolerated on a day-to-day basis. In addition, we demonstrate that the same autoimmune response, operating at different levels of regulation, can lead to either an autoimmune disease or a degenerative disorder. This preliminary qualitative model supports our contention that the way autoimmunity is perceived should be revised.     

A quasi-static three-dimensional, mathematical, three-body segment model of the canine knee

A mathematical, three-dimensional, anatomically accurate model of the canine knee was created to determine the forces in the knee ligaments and the knee joint reaction forces during the stance phase of a slow walk. This quasi-static model considered both the tibio-femoral and patello-femoral articulations. The geometric and morphometric data of the hind limb were obtained from cadaver data. Muscle forces acting on the femur and the hip joint reaction force were determined by numerical optimization. Ligaments were modeled as non-linear-springs. Ligament material properties were obtained from the literature pertaining to the human knee. The model consists of-28 non-linear algebraic equations describing equilibrium of the femur and the patella, and geometric constraints. This system of equations was solved by a non-linear least-squares method. Results are presented for a knee with an intact cranial cruciate ligament (CCL) and for a knee with a ruptured CCL. Forces predicted to occur in the CCL by analysis of the model were found to be very similar to reported results of CCL forces measured in vivo in goats.     

数学判别模型在预测害虫种群动态上的应用

根据两个总体的Fisher判别准则,建立了预测害虫种群动态的数学判别模型,对山东省惠民县1967～1977年共11年二代棉铃虫发生程度的两类资料进行了数量分析,建立了数学模型：y＝0．0127x1－0．023X2,对历史资料的回代验证与独立样本的预测,符合率在90％以上。     

Sleep deprivation in a quantitative physiologically based model of the ascending arousal system

A physiologically based quantitative model of the human ascending arousal system is used to study sleep deprivation after being calibrated on a small set of experimentally based criteria. The model includes the sleep-wake switch of mutual inhibition between nuclei which use monoaminergic neuromodulators, and the ventrolateral preoptic area. The system is driven by the circadian rhythm and sleep homeostasis. We use a small number of experimentally derived criteria to calibrate the model for sleep deprivation, then investigate model predictions for other experiments, demonstrating the scope of application. Calibration gives an improved parameter set, in which the form of the homeostatic drive is better constrained, and its weighting relative to the circadian drive is increased. Within the newly constrained parameter ranges, the model predicts repayment of sleep debt consistent with experiment in both quantity and distribution, asymptoting to a maximum repayment for very long deprivations. Recovery is found to depend on circadian phase, and the model predicts that it is most efficient to recover during normal sleeping phases of the circadian cycle, in terms of the amount of recovery sleep required. The form of the homeostatic drive suggests that periods of wake during recovery from sleep deprivation are phases of relative recovery, in the sense that the homeostatic drive continues to converge toward baseline levels. This undermines the concept of sleep debt, and is in agreement with experimentally restricted recovery protocols. Finally, we compare our model to the two-process model, and demonstrate the power of physiologically based modeling by correctly predicting sleep latency times following deprivation from experimental data.     

A mathematical model of the methionine cycle

Building on the work of Martinov et al. (2000), a mathematical model is developed for the methionine cycle. A large amount of information is available about the enzymes that catalyse individual reaction steps in the cycle, from methionine to S-adenosylmethionine to S-adenosylhomocysteine to homocysteine, and the removal of mass from the cycle by the conversion of homocysteine to cystathionine. Nevertheless, the behavior of the cycle is very complicated since many substrates alter the activities of the enzymes in the reactions that produce them, and some can also alter the activities of other enzymes in the cycle. The model consists of four differential equations, based on known reaction kinetics, that can be solved to give the time course of the concentrations of the four main substrates in the cycle under various circumstances. We show that the behavior of the model in response to genetic abnormalities and dietary deficiencies is similar to the changes seen in a wide variety of experimental studies. We conduct computational "experiments" that give understanding of the regulatory behavior of the methionine cycle under normal conditions and the behavior in the presence of genetic variation and dietary deficiencies.     

An evolutionary model for maximum likelihood alignment of DNA sequences

Summary Most algorithms for the alignment of biological sequences are not derived from an evolutionary model. Consequently, these alignment algorithms lack a strong statistical basis. A maximum likelihood method for the alignment of two DNA sequences is presented. This method is based upon a statistical model of DNA sequence evolution for which we have obtained explicit transition probabilities. The evolutionary model can also be used as the basis of procedures that estimate the evolutionary parameters relevant to a pair of unaligned DNA sequences. A parameter-estimation approach which takes into account all possible alignments between two sequences is introduced; the danger of estimating evolutionary parameters from a single alignment is discussed.     

A mathematical model on the optimal timing of offspring desertion

We consider the offspring desertion as the optimal strategy for the deserter parent, analyzing a mathematical model for its expected reproductive success. It is shown that the optimality of the offspring desertion significantly depends on the offsprings' birth timing in the mating season, and on the other ecological parameters characterizing the innate nature of considered animals. Especially, the desertion is less likely to occur for the offsprings born in the later period of mating season. It is also implied that the offspring desertion after a partially biparental care would be observable only with a specific condition.     

Novel mathematical method for quantitative expression of deviation from the Higuchi model

A simple mathematical method to express the deviation in release profile of a test product following Higuchi's kinetics from an ideal Higuchi release profile was developed. The method is based on calculation of area under the curve (AUC) by using the trapezoidal rule. The precision of prediction depends on the number of data points. The method is exemplified for 2 dosage forms (tablets of diltiazem HCl and microspheres of diclofenac sodium) that are designed to release the drug over a 12-hour period. The method can be adopted for the formulations where drug release is incomplete (<100%) or complete (100%) at last sampling time. To describe the kinetics of drug release from the test formulation, zero-order, first-order, Higuchi's. Hixson-Crowell's, and Weibull's models were used. The criterion for selecting the most appropriate model was based on the goodness-of-fit test. The release kinetics of the tablets and microspheres were explained by the Higuchi model. The release profiles of the test batches were slightly below the ideal Higuchi release profile. For the test products, observed percentage deviation from an ideal Higuchi profile is less than 16% for tablets and less than 11% for microspheres. The proposed method can be extended to the modified release formulations that are designed to release a drug over 6, 18, or 24 hours. If the data points are not evenly separated, the ideal drug release profile and AUC are calculated according to the specific sampling time. The proposed method may be used for comparing formulated products during the research and development stage, for quality control of the products, or for promoting products by comparing performance of the test product with that of the innovator's product.     

Visualization of DNA replication in the vertebrate model system DT40 using the DNA fiber technique

Maintenance of replication fork stability is of utmost importance for dividing cells to preserve viability and prevent disease. The processes involved not only ensure faithful genome duplication in the face of endogenous and exogenous DNA damage but also prevent genomic instability, a recognized causative factor in tumor development. Here, we describe a simple and cost-effective fluorescence microscopy-based method to visualize DNA replication in the avian B-cell line DT40. This cell line provides a powerful tool to investigate protein function in vivo by reverse genetics in vertebrate cells(1). DNA fiber fluorography in DT40 cells lacking a specific gene allows one to elucidate the function of this gene product in DNA replication and genome stability. Traditional methods to analyze replication fork dynamics in vertebrate cells rely on measuring the overall rate of DNA synthesis in a population of pulse-labeled cells. This is a quantitative approach and does not allow for qualitative analysis of parameters that influence DNA synthesis. In contrast, the rate of movement of active forks can be followed directly when using the DNA fiber technique(2-4). In this approach, nascent DNA is labeled in vivo by incorporation of halogenated nucleotides (Fig 1A). Subsequently, individual fibers are stretched onto a microscope slide, and the labeled DNA replication tracts are stained with specific antibodies and visualized by fluorescence microscopy (Fig 1B). Initiation of replication as well as fork directionality is determined by the consecutive use of two differently modified analogues. Furthermore, the dual-labeling approach allows for quantitative analysis of parameters that influence DNA synthesis during the S-phase, i.e. replication structures such as ongoing and stalled forks, replication origin density as well as fork terminations. Finally, the experimental procedure can be accomplished within a day, and requires only general laboratory equipment and a fluorescence microscope.     

A theory of drug tolerance and dependence II: the mathematical model

The preceding paper presented a model of drug tolerance and dependence. The model assumes the development of tolerance to a repeatedly administered drug to be the result of a regulated adaptive process. The oral detection and analysis of exogenous substances is proposed to be the primary stimulus for the mechanism of drug tolerance. Anticipation and environmental cues are in the model considered secondary stimuli, becoming primary in dependence and addiction or when the drug administration bypasses the natural-oral-route, as is the case when drugs are administered intravenously. The model considers adaptation to the effect of a drug and adaptation to the interval between drug taking autonomous tolerance processes. Simulations with the mathematical model demonstrate the model's behaviour to be consistent with important characteristics of the development of tolerance to repeatedly administered drugs: the gradual decrease in drug effect when tolerance develops, the high sensitivity to small changes in drug dose, the rebound phenomenon and the large reactions following withdrawal in dependence. The present paper discusses the mathematical model in terms of its design. The model is a nonlinear, learning feedback system, fully satisfying control theoretical principles. It accepts any form of the stimulus-the drug intake-and describes how the physiological processes involved affect the distribution of the drug through the body and the stability of the regulation loop. The mathematical model verifies the proposed theory and provides a basis for the implementation of mathematical models of specific physiological processes.     

Addition of a non-photic component to a light-based mathematical model of the human circadian pacemaker

Mathematical models have become vital to the study of many biological processes in humans due to the complexity of the physiological mechanisms underlying these processes and systems. While our current mathematical representation of the human circadian pacemaker has proven useful in many experimental situations, it uses as input only a direct effect of light on the circadian pacemaker. Although light (a photic stimulus) has been shown to be the primary synchronizer of the circadian pacemaker across a number of species, studies in both animals and humans have confirmed the existence of non-photic effects that also contribute to phase shifting and entrainment. We modified our light-based circadian mathematical model to reflect evidence from these studies that the sleep-wake cycle and/or associated behaviors have a non-photic effect on the circadian pacemaker. In our representation, the sleep-wake cycle and its associated behaviors provides a non-photic drive on the circadian pacemaker that acts both independently and concomitantly with light stimuli. Further experiments are required to validate fully our model and to understand the exact effect of the sleep-wake cycle as a non-photic stimulus for the human circadian pacemaker.     

Development of a mathematical model that predicts the outcome of hormone therapy for prostate cancer

We propose a mathematical model that quantitatively reproduces the dynamics of the serum prostate-specific antigen (PSA) level under intermittent androgen suppression (IAS) for prostate cancer. Taking into account the biological knowledge that there are reversible and irreversible changes in a malignant cell, we constructed a piecewise-linear dynamical model where the testosterone dynamics are modelled with rapid shifts between two levels, namely the normal and castrate concentrations of the male hormone. The validity of the model was supported by patient data obtained from a clinical trial of IAS. It accurately reproduced the kinetics of the therapeutic reduction of PSA and predicted the future nadir level correctly. The coexistence of reversible and irreversible changes within the malignant cell provided the best explanation of early progression to androgen independence. Finally, since the model identified patients for whom IAS was effective, it potentially offers a novel approach to individualized therapy requiring the input of time sequence values of PSA only.     

DNA methyltransferase inhibitor assay system based on the HBx-induced DNA methylation of E-cadherin

We here report a simple assay system for DNA methyltransferase (DNMT) inhibitors based on the HBx-induced DNA methylation of E-cadherin. A stable cell line named G1 was generated by co-transfecting E-cadherin luciferase reporter and HBx-expression plasmid into HepG2 cells. Treatment of G1 cells with DNMT inhibitors, 5-azacytidine, 5-aza-2′-deoxycytidine, and procainamaid, dose-dependently inhibited DNA methylation of E-cadherin promoter in the reporter, resulting in up-regulation of luciferase levels and its enzyme activity. Treatment with all-trans retinoic acid that is known to inhibit DNMT expression, also induced similar effects. Our system can be useful for development of epi-drugs targeting DNA methylation in malignancies.     

Comparison of immune responses against FMD by a DNA vaccine encoding the FMDV/O/IRN/2007 VP1 gene and the conventional inactivated vaccine in an animal model

Foot-and-mouth disease virus (FMDV) is highly contagious and responsible for huge outbreaks among cloven hoofed animals. The aim of the present study is to evaluate a plasmid DNA immunization system that expresses the FMDV/O/IRN/2007 VP1 gene and compare it with the conventional inactivated vaccine in an animal model. The VP1 gene was sub-cloned into the unique Kpn I and BamH I cloning sites of the pcDNA3.1+ and pEGFP-N1 vectors to construct the VP₁ gene cassettes. The transfected BHKT7 cells with sub-cloned pEGFP-N1-VP1 vector expressed GFP-VP1 fusion protein and displayed more green fluorescence spots than the transfected BHKT7 cells with pEGFP-N1 vector, which solely expressed the GFP protein. Six mice groups were respectively immunized by the sub-cloned pcDNA3.1⁺-VP1 gene cassette as the DNA vaccine, DNA vaccine and PCMV-SPORT-GMCSF vector (as molecular adjuvant) together, conventional vaccine, PBS (as negative control), pcDNA3.1⁺ vector (as control group) and PCMV-SPORT vector that contained the GMCSF gene (as control group). Significant neutralizing antibody responses were induced in the mice which were immunized using plasmid vectors expressing the VP1 and GMCSF genes together, the DNA vaccine alone and the conventional inactivated vaccine (P<0.05). Co-administration of DNA vaccine and GMCSF gene improved neutralizing antibody response in comparison with administration of the DNA vaccine alone, but this response was the most for the conventional vaccine group. However, induction of humeral immunity response in the conventional vaccine group was more protective than for the DNA vaccine, but T-cell proliferation and IFN-γ concentration were the most in DNA vaccine with the GMCSF gene. Therefore the group that was vaccinated by DNA vaccine with the GMCSF gene, showed protective neutralizing antibody response and the most Th1 cellular immunity.     

A mathematical model of the food-consumer system I. A case without food replenishment

A simple mathematical model was proposed to describe the dynamics of a food-consumer system. The model was based on the Logistic Theory and consisted of Eqs. (4), (5) and (6). The model was divided into the following three cases for further analyss; i) without food supply except at the initial time, ii) with continuous food supply at a constant rate, and iii) with food supply at varying rates. Only the first model was dealth with in this paper. The assumptions of the model 1 are that a definite amount of food is given only once at the initial time and only the feeding by animals is responsible for the decrease of food, and that the rate of decrease is proportional to the amount of animals. It is also assumed that the growth of animal population is represented by the logistic curve, and that the upper limit of the population is proportional to the amount of food at that time. For simplicity the parameters of basic differential equations are assumed to be constant throughout the time course. Analytical solutions of this non-linear model were given by Eqs. (8), (9), (10) and (11). The properties of time course of the food amount and consumer population were discussed from the mathematical and biological points of view. The method of the estimation of the three constants λ,b, and c from the experimental data was also suggested. Since we had no available data for animal populations, we applied the model, regarding reserve substance as x and new plant body as y, to the data of the initial growth of Azuki bean plant in the dark. This model is very simple, but it may be useful for analyzing the behavior of food-consumer system. And it may give some clue to the analysis of the more complex systems.