Nuclear accumulation of myocyte muscle LIM protein is regulated by heme oxygenase 1 and correlates with cardiac function in the transition to failure

Impaired mechanosensing leads to heart failure and we have previously shown that a decreased ratio of cytoplasmic to nuclear CSRP3/Muscle LIM protein (MLP ratio) is associated with a loss of mechanosensitivity. Here we tested whether passive or active stress/strain was important in modulating the MLP ratio and determined whether this correlated with heart function during the transition to failure. We exposed cultured neonatal rat myocytes to 10% cyclic mechanical stretch at 1 Hz, or electrically paced myocytes at 6.8 V (1 Hz) for 48 h. The MLP ratio decreased 50% (P < 0.05, n = 4) only in response to electrical pacing, suggesting impaired mechanosensitivity. Inhibition of contractility with 10 μM blebbistatin resulted in a ∼3 fold increase in the MLP ratio (n = 8, P < 0.05), indicating that myocyte contractility regulates nuclear MLP. Inhibition of histone deacetylase (HDAC) signaling with trichostatin A increased nuclear MLP following passive stretch, suggesting that HDACs block MLP nuclear accumulation. Inhibition of heme-oxygenase1 (HO-1) activity with PPZII blocked MLP nuclear accumulation. To examine how mechanosensitivity changes during the transition to heart failure, we studied a guinea pig model of angiotensin II infusion (400 ng/kg/min) over 12 weeks. Using subcellular fractionation we showed that the MLP ratio increased 88% (n = 4, P < 0.01) during compensated hypertrophy, but decreased significantly during heart failure (P < 0.001, n = 4). The MLP ratio correlated significantly with the E/A ratio (r = 0.71, P < 0.01 n = 12), a clinical measure of diastolic function. These data indicate for the first time that myocyte mechanosensitivity as indicated by the MLP ratio is regulated primarily by myocyte contractility via HO-1 and HDAC signaling.

Exercise improves cardiovascular control in a model of dislipidemia and menopause

The present study investigated the effects of exercise training on arterial pressure, baroreflex sensitivity, cardiovascular autonomic control and metabolic parameters on female LDL-receptor knockout ovariectomized mice. Mice were divided into two groups: sedentary and trained. Trained group was submitted to an exercise training protocol. Blood cholesterol was measured. Arterial pressure (AP) signals were directly recorded in conscious mice. Baroreflex sensitivity was evaluated by tachycardic and bradycardic responses to AP changes. Cardiovascular autonomic modulation was measured in frequency (FFT) and time domains. Maximal exercise capacity was increased in trained as compared to sedentary group. Blood cholesterol was diminished in trained mice (191 +/- 8 mg/dL) when compared to sedentary mice (250 +/- 9 mg/dL, p<0.05). Mean AP and HR were reduced in trained group (101 +/- 3 mmHg and 535 +/- 14 bpm, p<0.05) when compared with sedentary group (125 +/- 3 mmHg and 600 +/- 12 bpm). Exercise training induced improvement in bradycardic reflex response in trained animals (-4.24 +/- 0.62 bpm/mmHg) in relation to sedentary animals (-1.49 +/- 0.15 bpm/mmHg, p<0.01); tachycardic reflex responses were similar between studied groups. Exercise training increased the variance (34 +/- 8 vs. 6.6 +/- 1.5 ms(2) in sedentary, p<0.005) and the high-frequency band (HF) of the pulse interval (IP) (53 +/- 7% vs. 26 +/- 6% in sedentary, p<0.01). It is tempting to speculate that results of this experimental study might represent a rationale for this non-pharmacological intervention in the management of cardiovascular risk factors in dyslipidemic post-menopause women. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

A Time Efficient Optical Model for GATE Simulation of a LYSO Scintillation Matrix Used in PET Applications

A time efficient optical model is proposed for GATE simulation of a LYSO scintillation matrix coupled to a photomultiplier. The purpose is to avoid the excessively long computation time when activating the optical processes in GATE. The usefulness of the model is demonstrated by comparing the simulated and experimental energy spectra obtained with the dual planar head equipment for dosimetry with a positron emission tomograph ( DoPET). The procedure to apply the model is divided in two steps. Firstly, a simplified simulation of a single crystal element of DoPET is used to fit an analytic function that models the optical attenuation inside the crystal. In a second step, the model is employed to calculate the influence of this attenuation in the energy registered by the tomograph. The use of the proposed optical model is around three orders of magnitude faster than a GATE simulation with optical processes enabled. A good agreement was found between the experimental and simulated data using the optical model. The results indicate that optical interactions inside the crystal elements play an important role on the energy resolution and induce a considerable degradation of the spectra information acquired by DoPET. Finally, the same approach employed by the proposed optical model could be useful to simulate a scintillation matrix coupled to a photomultiplier using single or dual readout scheme.

Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents

We introduce a stochastic heterogeneous interacting-agent model for the short-time non-equilibrium evolution of excess demand and price in a stylized asset market. We consider a combination of social interaction within peer groups and individually heterogeneous fundamentalist trading decisions which take into account the market price and the perceived fundamental value of the asset. The resulting excess demand is coupled to the market price. Rigorous analysis reveals that this feedback may lead to price oscillations, a single bounce, or monotonic price behaviour. The model is a rare example of an analytically tractable interacting-agent model which allows LIS to deduce in detail the origin of these different collective patterns. For a natural choice of initial distribution, the results are independent of the graph structure that models the peer network of agents whose decisions influence each other. (C) 2009 Elsevier B.V. All rights reserved.

A Cost Model for the Effect of Setup Time Reduction in Stainless Steel Strip Production

Setup time reduction facilitate the flexibility needed for just-in-time production. An integrated steel mill with meltshop, continuous caster and hot rolling mill is often operated as decoupled processes. Setup time reduction provides the flexibility needed to reduce buffering, shorten lead times and create an integrated process flow. The interdependency of setup times, process flexibility and integration were analysed through system dynamics simulation. The results showed significant reductions of energy consumption and tied capital. It was concluded that setup time reduction in the hot strip mill can aid process integration and hence improve production economy while reducing environmental impact.

A model of online teaching and learning

Deakin University has a long history of supporting distance education with technology. Such presentations have matured from a mix of remote-login/FTP/email in the 1980s through web mediated access in the 1990s to institution-wide learning management systems which are emerging currently. By the commencement of semester I, 2003, online teaching at the University will be supported by a single, institution-wide, learning management system, which is expected to support approximately 28,000 students, who will each be accessing up to 4 of some 1500 undergraduate and 700 postgraduate courses. In this paper we describe a model for online teaching of both on-campus and off-campus students in the Bachelor of Computing, using various technologies to support different aspects of online teaching and learning. This programme has been running in a web-mediated environment for over six years. Each year the administration of the programme has been modified in a reactive manner, based on student feedback and the identification of failure points during the previous semester, resulting in the model maturing over that time. We discuss how the changes have impacted the model, the academics involved in the teaching of the unit and the students' experience of learning in the online environment. We also discuss the advantages and disadvantages of online teaching and learning, as well as some potential pitfalls and how to avoid them, or, at least, minimise their impact.

The brachyspira hyodysenteriae ftnA gene : DNA vaccination and real-time PCR quantification of bacteria in a mouse model of disease

The nucleotide sequence of the Brachyspira hyodysenteriae ftnA gene, encoding a putative ferritin protein (FtnA), was determined. Analysis of the sequence predicted that this gene encoded a protein of 180 amino acids. RT-PCR and Western blot showed that the ftnA gene was expressed in B. hyodysenteriae, and evidence suggests that FtnA stores iron rather than haem. ftnA was delivered as DNA and recombinant protein vaccines in a mouse model of B. hyodysenteriae infection. Vaccine efficacy was monitored by caecal pathology and quantification of B. hyodysenteriae numbers in the caeca of infected mice by real-time PCR.

Time for a change : applying the Good Lives Model of rehabilitation to a high-risk violent offender

In this article we operationalise the theoretical concepts of the Good Lives Model (GLM) of offender rehabilitation by providing a step-by-step framework for assessment, formulation, treatment planning, and monitoring with a high-risk violent offender residing in the community. The case study illustrates how the GLM can be applied to complement and enhance traditional Risk-Management interventions and shows how the GLM's clinical relevance extends from sex offending to broader offending typologies.

Damage identification of civil infrastructure in the time domain using FEM calibrated ARMAX model

Due to environmental loads, mechanical damages, structural aging and human factors, civil infrastructure inevitably deteriorate during their service lives. Since their damage may claim human lives and cause significant economic losses, how to identify damages and assess structural conditions timely and accurately has drawn increasingly more attentions from structural engineering community worldwide. In this study, a fast and sensitive time domain damage identification method will be developed. First, a high quality finite element model is built and the structural responses are simulated under different damage scenarios. Based on the simulated data, an Auto Regressive Moving Average Exogenous (ARMAX) model is then developed and calibrated. The calibrated ARMAX model can be used to identify damage in different scenarios through model updating process using clonal selection algorithm (CSA). The identification results demonstrate the performance of the proposed methodology, which has the potential to be used for damage identification in practices.

Incorporating differences in marginal utilities of time across activities in a time allocation model

Most existing activity time allocation models assume that individuals allocate their time to different activities over a period in such a way that the marginal utilities of time across activities are equal. Their argument is that, if not equal, an individual is free to allocate more time to those activities whose marginal utilities of time are higher and, finally allocates the optimal time to each activity with equal marginal utility. However, such an ideal situation may not always prevail in reality, especially when an individual is under income constraint and/or under intense time pressure. In order to incorporate such differences in marginal utilities of time across activities, we enrich the traditional activity time allocation model by explicitly including income constraint and by adding marginal extension activity choice model. As an application, the developed integrated model is used to estimate the value of activity time during weekends in Tokyo. The results are encouraging in that they forecast the individual time allocation more accurately and estimate realistically the value of activity time for each activity in a set of different activities than do by existing traditional models.