A mathematical model of the sterol regulatory element binding protein 2 cholesterol biosynthesis pathway

Cholesterol is one of the key constituents for maintaining the cellular membrane and thus the integrity of the cell itself. In contrast high levels of cholesterol in the blood are known to be a major risk factor in the development of cardiovascular disease. We formulate a deterministic nonlinear ordinary differential equation model of the sterol regulatory element binding protein 2 (SREBP-2) cholesterol genetic regulatory pathway in an hepatocyte. The mathematical model includes a description of genetic transcription by SREBP-2 which is subsequently translated to mRNA leading to the formation of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR), a main precursor of cholesterol synthesis. Cholesterol synthesis subsequently leads to the regulation of SREBP-2 via a negative feedback formulation. Parameterised with data from the literature, the model is used to understand how SREBP-2 transcription and regulation affects cellular cholesterol concentration. Model stability analysis shows that the only positive steady-state of the system exhibits purely oscillatory, damped oscillatory or monotic behaviour under certain parameter conditions. In light of our findings we postulate how cholesterol homestasis is maintained within the cell and the advantages of our model formulation are discussed with respect to other models of genetic regulation within the literature.

Managing governance, risk and compliance for post-crisis regulatory change: a model of IS capabilities for financial organizations

The 2008-2009 financial crisis and related organizational and economic failures have meant that financial organizations are faced with a ‘tsunami’ of new regulatory obligations. This environment provides new managerial challenges as organizations are forced to engage in complex and costly remediation projects with short deadlines. Drawing from a longitudinal study conducted with nine financial institutions over twelve years, this paper identifies nine IS capabilities which underpin activities for managing regulatory themed governance, risk and compliance efforts. The research shows that many firms are now focused on meeting the Regulators’ deadlines at the expense of developing a strategic, enterprise-wide connected approach to compliance. Consequently, executives are in danger of implementing siloed compliance solutions within business functions. By evaluating the maturity of their IS capabilities which underpin regulatory adherence, managers have an opportunity to develop robust operational architectures and so are better positioned to face the challenges derived from shifting regulatory landscapes.

Modeling gene expression regulatory networks with the sparse vector autoregressive model

Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

The Choice of Expedient Regulatory Controls on Housing Market Using Short-Term Equilibria Model

Khutoretsky dealt with the problem of maximising a linear utility function (MUF) over the set of short-term equilibria in a housing market by reducing it to a linear programming problem, and suggested a combinatorial algorithm for this problem. Two approaches to the market adjustment were considered: the funding of housing construction and the granting of housing allowances. In both cases, locally optimal regulatory measures can be developed using the corresponding dual prices. The optimal effects (with the regulation expenditures restricted by an amount K) can be found using specialised models based on MUF: a model M1 for choice of the optimum structure of investment in housing construction, and a model M2 for optimum distribution of housing allowances. The linear integer optimisation problems corresponding to these models are initially difficult but can be solved after slight modifications of the parameters. In particular, the necessary modification of K does not exceed the maximum construction cost of one dwelling (for M1) or the maximum size of one housing allowance (for M2). The result is particularly useful since slight modification of K is not essential in practice.

Final regulatory analysis of the model year 1982 light truck fuel economy standards.

Mode of access: Internet.

A model burglar and hold-up alarm business licensing and regulatory statute : a report.

"April 1975."

Network topology and the evolution of dynamics in an artificial genetic regulatory network model created by whole genome duplication and divergence

Topological measures of large-scale complex networks are applied to a specific artificial regulatory network model created through a whole genome duplication and divergence mechanism. This class of networks share topological features with natural transcriptional regulatory networks. Specifically, these networks display scale-free and small-world topology and possess subgraph distributions similar to those of natural networks. Thus, the topologies inherent in natural networks may be in part due to their method of creation rather than being exclusively shaped by subsequent evolution under selection. The evolvability of the dynamics of these networks is also examined by evolving networks in simulation to obtain three simple types of output dynamics. The networks obtained from this process show a wide variety of topologies and numbers of genes indicating that it is relatively easy to evolve these classes of dynamics in this model. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

The role of local and systemic renin angiotensin system activation in a genetic model of sympathetic hyperactivity-induced heart failure in mice

Sympathetic hyperactivity (SH) and renin angiotensin system (RAS) activation are commonly associated with heart failure (HF), even though the relative contribution of these factors to the cardiac derangement is less understood. The role of SH on RAS components and its consequences for the HF were investigated in mice lacking alpha(2A) and alpha(2C) adrenoceptor knockout (alpha(2A)/alpha(2C) ARKO) that present SH with evidence of HF by 7 mo of age. Cardiac and systemic RAS components and plasma norepinephrine (PN) levels were evaluated in male adult mice at 3 and 7 mo of age. In addition, cardiac morphometric analysis, collagen content, exercise tolerance, and hemodynamic assessments were made. At 3 mo, alpha(2A)/alpha(2C)ARKO mice showed no signs of HF, while displaying elevated PN, activation of local and systemic RAS components, and increased cardiomyocyte width (16%) compared with wild-type mice (WT). In contrast, at 7 mo, alpha(2A)/alpha(2C)ARKO mice presented clear signs of HF accompanied only by cardiac activation of angiotensinogen and ANG II levels and increased collagen content (twofold). Consistent with this local activation of RAS, 8 wk of ANG II AT(1) receptor blocker treatment restored cardiac structure and function comparable to the WT. Collectively, these data provide direct evidence that cardiac RAS activation plays a major role underlying the structural and functional abnormalities associated with a genetic SH-induced HF in mice.

Capacity of the extracellular matrix of the bone marrow to induce proliferation of myeloid cells in vitro in model of protein malnutrition in mice

The aim of this study was to verify the capacity of the extracellular matrix (ECM) obtained from bone marrow of malnourished mice to sustain survival and to induce the proliferation of myeloid cells. We also verified the capacity of the tests to interact with in vitro hematopoietic cytokines. Male ""Swiss"" mice were submitted to protein malnutrition with a diet contents of 4% casein until they lost 20% of the original weight, while the group-control was kept with a diet content of 14% of casein. The bone marrow was extracted with 1.0 mg of aprotinin/mL in PBS. The proliferation tests were carried out with myeloid cell line FDCP-1, by the colorimetric method of reduction of the MTT. The obtained ECM from nourished and undernourished mice induced cellular proliferation in vitro. Tests performed with Il-3 and GM-CSF cytokines in a concentration of 10 and 500 rho g/mL displayed synergic and regulatory effects respectively. The ECM obtained from the malnourished group submitted to the binding to GM-CSF demonstrated higher cellular proliferation than the ECM obtained from the control group (p<0.05). The results suggest that the alterations in the composition of ECM of bone marrow caused by malnutrition might lead to modification of the GM-CSF activity modulation.

Histamine Plays an Essential Regulatory Role in Lung Inflammation and Protective Immunity in the Acute Phase of Mycobacterium tuberculosis Infection

The course and outcome of infection with mycobacteria are determined by a complex interplay between the immune system of the host and the survival mechanisms developed by the bacilli. Recent data suggest a regulatory role of histamine not only in the innate but also in the adaptive immune response. We used a model of pulmonary Mycobacterium tuberculosis infection in histamine-deficient mice lacking histidine decarboxylase (HDC(-/-)), the histamine-synthesizing enzyme. To confirm that mycobacterial infection induced histamine production, we exposed mice to M. tuberculosis and compared responses in C57BL/6 (wild-type) and HDC(-/-) mice. Histamine levels increased around fivefold above baseline in infected C57BL/6 mice at day 28 of infection, whereas only small amounts were detected in the lungs of infected HDC(-/-) mice. Blocking histamine production decreased both neutrophil influx into lung tissue and the release of proinflammatory mediators, such as interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-alpha), in the acute phase of infection. However, the accumulation and activation of CD4(+) T cells were augmented in the lungs of infected HDC(-/-) mice and correlated with a distinct granuloma formation that contained abundant lymphocytic infiltration and reduced numbers of mycobacteria 28 days after infection. Furthermore, the production of IL-12, gamma interferon, and nitric oxide, as well as CD11c(+) cell influx into the lungs of infected HDC(-/-) mice, was increased. These findings indicate that histamine produced after M. tuberculosis infection may play a regulatory role not only by enhancing the pulmonary neutrophilia and production of IL-6 and TNF-alpha but also by impairing the protective Th1 response, which ultimately restricts mycobacterial growth.

Aerobic Exercise Training-Induced Left Ventricular Hypertrophy Involves Regulatory MicroRNAs, Decreased Angiotensin-Converting Enzyme-Angiotensin II, and Synergistic Regulation of Angiotensin-Converting Enzyme 2-Angiotensin (1-7)

Aerobic exercise training leads to a physiological, nonpathological left ventricular hypertrophy; however, the underlying biochemical and molecular mechanisms of physiological left ventricular hypertrophy are unknown. The role of microRNAs regulating the classic and the novel cardiac renin-angiotensin (Ang) system was studied in trained rats assigned to 3 groups: (1) sedentary; (2) swimming trained with protocol 1 (T1, moderate-volume training); and (3) protocol 2 (T2, high-volume training). Cardiac Ang I levels, Ang-converting enzyme (ACE) activity, and protein expression, as well as Ang II levels, were lower in T1 and T2; however, Ang II type 1 receptor mRNA levels (69% in T1 and 99% in T2) and protein expression (240% in T1 and 300% in T2) increased after training. Ang II type 2 receptor mRNA levels (220%) and protein expression (332%) were shown to be increased in T2. In addition, T1 and T2 were shown to increase ACE2 activity and protein expression and Ang (1-7) levels in the heart. Exercise increased microRNA-27a and 27b, targeting ACE and decreasing microRNA-143 targeting ACE2 in the heart. Left ventricular hypertrophy induced by aerobic training involves microRNA regulation and an increase in cardiac Ang II type 1 receptor without the participation of Ang II. Parallel to this, an increase in ACE2, Ang (1-7), and Ang II type 2 receptor in the heart by exercise suggests that this nonclassic cardiac renin-angiotensin system counteracts the classic cardiac renin-angiotensin system. These findings are consistent with a model in which exercise may induce left ventricular hypertrophy, at least in part, altering the expression of specific microRNAs targeting renin-angiotensin system genes. Together these effects might provide the additional aerobic capacity required by the exercised heart. (Hypertension. 2011;58:182-189.).

Experimental tuberculosis: Designing a better model to test vaccines against tuberculosis

Experimental models of infection are good tools for establishing immunological parameters that have an effect on the host-pathogen relationship and also for designing new vaccines and immune therapies. In this work, we evaluated the evolution of experimental tuberculosis in mice infected with increasing bacterial doses or via distinct routes. We showed that mice infected with low bacterial doses by the intratracheal route were able to develop a progressive infection that was proportional to the inoculum size. In the initial phase of disease, mice developed a specific Th1-driven immune response independent of inoculum concentration. However, in the late phase, mice infected with higher concentrations exhibited a mixed Th1/Th2 response, while mice infected with lower concentrations sustained the Th1 pattern. Significant IL-10 concentrations and a more preeminent T regulatory cell recruitment were also detected at 70 days post-infection with high bacterial doses. These results suggest that mice infected with higher concentrations of bacilli developed an immune response similar to the pattern described for human tuberculosis wherein patients with progressive tuberculosis exhibit a down modulation of IFN-gamma production accompanied by increased levels of IL-4. Thus, these data indicate that the experimental model is important in evaluating the protective efficacy of new vaccines and therapies against tuberculosis. (C) 2010 Elsevier Ltd. All rights reserved.

Host genetic background affects regulatory T-cell activity that influences the magnitude of cellular immune response against Mycobacterium tuberculosis

Using two mouse strains with different abilities to generate interferon (IFN)-gamma production after Mycobacterium tuberculosis infection, we tested the hypothesis that the frequency and activity of regulatory T (Treg) cells are influenced by genetic background. Our results demonstrated that the suppressive activity of spleen Treg cells from infected or uninfected BALB/c mice was enhanced, inhibiting IFN-gamma and interleukin (IL)-2 production. Infected C57BL/6 mice exhibited a decrease in the frequency of lung Treg cells and an increased ratio CD4(+):CD4(+)Foxp3(+) cells compared with infected BALB/c mice and uninfected C57BL/6 mice. Moreover, infected C57BL/6 mice also had a decrease in the immunosuppressive capacity of spleen Treg cells, higher lung IFN-gamma and IL-17 production, and restricted the infection better than BALB/c mice. Adoptive transfer of BALB/c Treg cells into BALB/c mice induced an increase in bacterial colony-forming unit (CFU) counts. Furthermore, BALB/c mice treated with anti-CD25 antibody exhibited lung CFU counts significantly lower than mice treated with irrelevant antibody. Our results show that in BALB/c mice, the Treg cells have a stronger influence than that in C57BL/6 mice. These data suggest that BALB/c and C57BL/6 mice may use some different mechanisms to control M. tuberculosis infection. Therefore, the role of Treg cells should be explored during the development of immune modulators, both from the perspective of the pathogen and the host. Immunology and Cell Biology (2011) 89, 526-534; doi:10.1038/icb.2010.116; published online 19 October 2010