Modeling and simulation of pathways in menopause

Analyzing the Behavior of Neuronal Pathways in Alzheimer's Disease Using Petri Net Modeling Approach

Alzheimer's Disease (AD) is the most common neuro-degenerative disorder in the elderly that leads to dementia. The hallmark of AD is senile lesions made by abnormal aggregation of amyloid beta in extracellular space of brain. One of the challenges in AD treatment is to better understand the mechanism of action of key proteins and their related pathways involved in neuronal cell death in order to identify adequate therapeutic targets. This study focuses on the phenomenon of aggregation of amyloid beta into plaques by considering the signal transduction pathways of Calpain-Calpastatin (CAST) regulation system and Amyloid Precursor Protein (APP) processing pathways along with Ca2+ channels. These pathways are modeled and analyzed individually as well as collectively through Stochastic Petri Nets for comprehensive analysis and thorough understating of AD. The model predicts that the deregulation of Calpain activity, disruption of Calcium homeostasis, inhibition of CAST and elevation of abnormal APP processing are key cytotoxic events resulting in an early AD onset and progression. Interestingly, the model also reveals that plaques accumulation start early (at the age of 40) in life but symptoms appear late. These results suggest that the process of neuro-degeneration can be slowed down or paused by slowing down the degradation rate of Calpain-CAST Complex. In the light of this study, the suggestive therapeutic strategy might be the prevention of the degradation of Calpain-CAST complexes and the inhibition of Calpain for the treatment of neurodegenerative diseases such as AD.

The Availability of Beneficial Insects-originated Materials on Women's Health following Menopause

Human health problems due to long life are becoming major issues in society, and in particular greater interest collected on women's health after menopause. Many substances can be introduced to women's health, however, materials from the substances have not shown all of the safety and efficacy properties that are not easily found. Currently, it is known about the effects of the disease on the female insect-derived material that is capable of overcoming this problem significantly. When using the insect-derived material through the results of several studies suggest that it is possible to solve a hormonal imbalance and nutritional imbalance in the elderly. Here, we'd like to try to dissertate about the new trends for women's health improvement using novel materials-derived from insects.

Modeling innate immune response to early Mycobacterium infection

In the study of complex patterns in biology, mathematical and computational models are emerging as important tools. In addition to experimental approaches, these modeling tools have recently been applied to address open questions regarding host-pathogen interaction dynamics, including the immune response to mycobacterial infection and tuberculous granuloma formation. We present an approach in which a computational model represents the interaction of the Mycobacterium infection with the innate immune system in zebrafish at a high level of abstraction. We use the Petri Net formalism to model the interaction between the key host elements involved in granuloma formation and infection dissemination. We define a qualitative model for the understanding and description of causal relations in this dynamic process. Complex processes involving cell-cell or cell-bacteria communication can be modeled at smaller scales and incorporated hierarchically into this main model; these are to be included in later elaborations. With the infection mechanism being defined on a higher level, lower-level processes influencing the host-pathogen interaction can be identified, modeled, and tested both quantitatively and qualitatively. This systems biology framework incorporates modeling to generate and test hypotheses, to perform virtual experiments, and to make experimentally verifiable predictions. Thereby it supports the unraveling of the mechanisms of tuberculosis infection.

Regulation of the estrous cycle by neutrophil infiltration into the vagina

During metestrus of the estrous cycle, a number of neutrophils infiltrate into the vaginal vault, presumably due to a neutrophil-specific chemokine, MIP-2, in mice. The physiological role of the infiltrating neutrophils, however, remains largely obscure. In this study we examined the effects of neutrophil depletion on the estrous cycle and steroid hormone levels. When mice were treated with an anti-Gr-1 mAb, they became neutropenic, as assessed as to the number of neutrophils in the peripheral blood. The estrous cycle of such mice was specifically blocked at diestrus irrespective of the phase at which the anti-Gr-1 mAb was administered. The blockade was reversible, because restoration of neutrophils to a normal level caused a restart of the cycle. Immunohistochemical analyses revealed that neutrophils were present mainly on the luminal surface and in the lumen at metestrus and to a lesser extent at diestrus but scarcely in the uterine cervix at any phase, and that the anti-Gr-1 mAb depleted neutrophils but not eosinophils in the vagina. The treatment with the anti-Gr-1 mAb significantly affected the serum 17beta-estradiol and progesterone levels at diestrus after the estrous cycle was blocked. Together, these results suggest that neutrophil infiltration into the vagina is critical in maintaining the estrous cycle through control of steroid hormone levels.

Stochastic Petri Net extension of a yeast cell cycle model

This paper presents the definition, solution and validation of a stochastic model of the budding yeast cell cycle, based on Stochastic Petri Nets (SPN). A specific family of SPNs is selected for building a stochastic version of a well-established deterministic model. We describe the procedure followed in defining the SPN model from the deterministic ODE model, a procedure that can be largely automated. The validation of the SPN model is conducted with respect to both the results provided by the deterministic one and the experimental results available from literature. The SPN model catches the behavior of the wild type budding yeast cells and a variety of mutants. We show that the stochastic model matches some characteristics of budding yeast cells that cannot be found with the deterministic model. The SPN model fine-tunes the simulation results, enriching the breadth and the quality of its outcome.

Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach

MOTIVATION

New developments in post-genomic technology now provide researchers with the data necessary to study regulatory processes in a holistic fashion at multiple levels of biological organization. One of the major challenges for the biologist is to integrate and interpret these vast data resources to gain a greater understanding of the structure and function of the molecular processes that mediate adaptive and cell cycle driven changes in gene expression. In order to achieve this biologists require new tools and techniques to allow pathway related data to be modelled and analysed as network structures, providing valuable insights which can then be validated and investigated in the laboratory.

RESULTS

We propose a new technique for constructing and analysing qualitative models of genetic regulatory networks based on the Petri net formalism. We take as our starting point the Boolean network approach of treating genes as binary switches and develop a new Petri net model which uses logic minimization to automate the construction of compact qualitative models. Our approach addresses the shortcomings of Boolean networks by providing access to the wide range of existing Petri net analysis techniques and by using non-determinism to cope with incomplete and inconsistent data. The ideas we present are illustrated by a case study in which the genetic regulatory network controlling sporulation in the bacterium Bacillus subtilis is modelled and analysed.

AVAILABILITY

The Petri net model construction tool and the data files for the B. subtilis sporulation case study are available at http://bioinf.ncl.ac.uk/gnapn.

Hypothesis Generation in Signaling Networks

Biological signaling networks comprise the chemical processes by which cells detect and respond to changes in their environment. Such networks have been implicated in the regulation of important cellular activities, including cellular reproduction, mobility, and death. Though technological and scientific advances have facilitated the rapid accumulation of information about signaling networks, utilizing these massive information resources has become infeasible except through computational methods and computer-based tools. To date, visualization and simulation tools have received significant emphasis. In this paper, we present a graph-theoretic formalization of biological signaling network models that are in wide but informal use, and formulate two problems on the graph: the Constrained Downstream and Minimum Knockout Problems. Solutions to these problems yield qualitative tools for generating hypotheses about the networks, which can then be experimentally tested in a laboratory setting. Using established graph algorithms, we provide a solution to the Constrained Downstream Problem. We also show that the Minimum Knockout Problem is NP-Hard, propose a heuristic, and assess its performance. In tests on the Epidermal Growth Factor Receptor (EGFR) network, we find that our heuristic reports the correct solution to the problem in seconds. Source code for the implementations of both solutions is available from the authors upon request.

Pharmacological study on Samia cynthia ricini in old female mice

The effect of the extraction from female moths Samia cynthia ricini (family Saturniidae) on menopausal syndrome was studied in order to search for an effective traditional Chinese medicine to menopausal syndrome and offer a theoretical support for the further research on Samia cynthia ricini. Aged, nonreproductive female mice was used as the model and randomly divided into three groups: control, ethanol extraction group and diethylstilbestrol (DES) group according to the medicine applied. After 4 weeks of treatment, keratinization rates of vagina epithelia, indexes of organs, serum concentrations of estradiol (E2) and progesterone (P), the bone mineral contents (BMC) and the morphological changes of ovary and uterus were measured. And the fingerprint of the extracts was obtained by gas chromatography-mass spectrometry (GC-MS). The results showed that the moth extraction could obviously accelerate the keratinization of aged mice's vagina epithelia, increase the weight of the ovary and ameliorate its degenerative process. It could also, to some extent, increase the serum concentrations of estradiol, progesterone concentrations as well as the bone mineral contents. Furthermore, there is no obvious side effect detected on immune system in our research. The extraction from female moths Samia cynthia ricini could ameliorate the menopause symptom of aged female mice and thus be a potential remedy for it.

Using Petri Net tools to study properties and dynamics of biological systems

Petri Nets (PNs) and their extensions are promising methods for modeling and simulating biological systems. We surveyed PN formalisms and tools and compared them based on their mathematical capabilities as well as by their appropriateness to represent typical biological processes. We measured the ability of these tools to model specific features of biological systems and answer a set of biological questions that we defined. We found that different tools are required to provide all capabilities that we assessed. We created software to translate a generic PN model into most of the formalisms and tools discussed. We have also made available three models and suggest that a library of such models would catalyze progress in qualitative modeling via PNs. Development and wide adoption of common formats would enable researchers to share models and use different tools to analyze them without the need to convert to proprietary formats.

Application of Petri net theory for modelling and validation of the sucrose breakdown pathway in the potato tuber

MOTIVATION

Because of the complexity of metabolic networks and their regulation, formal modelling is a useful method to improve the understanding of these systems. An essential step in network modelling is to validate the network model. Petri net theory provides algorithms and methods, which can be applied directly to metabolic network modelling and analysis in order to validate the model. The metabolism between sucrose and starch in the potato tuber is of great research interest. Even if the metabolism is one of the best studied in sink organs, it is not yet fully understood.

RESULTS

We provide an approach for model validation of metabolic networks using Petri net theory, which we demonstrate for the sucrose breakdown pathway in the potato tuber. We start with hierarchical modelling of the metabolic network as a Petri net and continue with the analysis of qualitative properties of the network. The results characterize the net structure and give insights into the complex net behaviour.

Biomedical informatics: the future for drug development

The problems that exist in drug development are well documented: the limited number of new chemical entities, increased cost of drug development, problems in clinical trials (Phase III), product launches that result in withdrawal, and pressure to reduce the cost of pharmaceuticals from the government. It appears that the promise of genomics has not yet reached its full potential to impact the process. This review identifies the need to develop and implement the area of biomedical informatics for increased success in drug development and healthcare in general.