Brainstem oxytocinergic modulation of heart rate control in rats: effects of hypertension and exercise training

Oxytocinergic brainstem projections participate in the autonomic control of the circulation. We investigated the effects of hypertension and training on cardiovascular parameters after oxytocin (OT) receptor blockade within the nucleus tractus solitarii (NTS) and NTS OT and OT receptor expression. Male spontaneously hypertensive rats (SHR) and Wistar-Kyoto (WKY) rats were trained (55% of maximal exercise capacity) or kept sedentary for 3 months and chronically instrumented (NTS and arterial cannulae). Mean arterial blood pressure (MAP) and heart rate (HR) were measured at rest and during an acute bout of exercise after NTS pretreatment with vehicle or OT antagonist (20 pmol of OT antagonist (200 nl of vehicle)-1). Oxytocin and OT receptor were quantified (35S-oligonucleotide probes, in situ hybridization) in other groups of rats. The SHR exhibited high MAP and HR (P < 0.05). Exercise training improved treadmill performance and reduced basal HR (on average -11%) in both groups, but did not change basal MAP. Blockade of NTS OT receptor increased exercise tachycardia only in trained groups, with a larger effect on trained WKY rats (+31 +/- 9 versus +12 +/- 3 beats min-1 in the trained SHR). Hypertension specifically reduced NTS OT receptor mRNA density (-46% versus sedentary WKY rats, P < 0.05); training did not change OT receptor density, but significantly increased OT mRNA expression (+2.5-fold in trained WKY rats and +15% in trained SHR). Concurrent hypertension- and training-induced plastic (peptide/receptor changes) and functional adjustments (HR changes) of oxytocinergic control support both the elevated basal HR in the SHR group and the slowing of the heart rate (rest and exercise) observed in trained WKY rats and SHR.

Augmented muscle vasodilatory responses in obese children with Glu27 beta(2)-adrenoceptor polymorphism

This study examined forearm vasodilatation during mental challenge and exercise in 72 obese children (OC; age = 10 +/- 0.1 years) homozygous with polymorphism in the allele 27 of the beta(2)-adrenoceptors: Gln27 (n = 61) and Glu27 (n = 11). Forearm blood flow was recorded during 3 min of each using the Stroop color-word test (MS) and handgrip isometric exercise. Baseline hemodynamic and vascular measurements were similar. During the MS, peak forearm vascular conductance was significantly greater in group Glu27 (Delta = 0.35 +/- 0.4 vs. 0.12 +/- 0.1 units, respectively, p = .042). Similar results were found during exercise (Delta = 0.64 +/- 0.1 vs. 0.13 +/- 0.1 units, respectively, p = .035). Glu27 OC increased muscle vasodilatory responsiveness upon the MS and exercise.

In silico analysis of candidate genes involved in light sensing and signal transduction pathways in soybean

Several aspects of photoperception and light signal transduction have been elucidated by studies with model plants. However, the information available for economically important crops, such as Fabaceae species, is scarce. In order to incorporate the existing genomic tools into a strategy to advance soybean research, we have investigated publicly available expressed sequence tag ( EST) sequence databases in order to identify Glycine max sequences related to genes involved in light-regulated developmental control in model plants. Approximately 38,000 sequences from open-access databases were investigated, and all bona fide and putative photoreceptor gene families were found in soybean sequence databases. We have identified G. max orthologs for several families of transcriptional regulators and cytoplasmic proteins mediating photoreceptor-induced responses, although some important Arabidopsis phytochrome-signaling components are absent. Moreover, soybean and Arabidopsis gene-family homologs appear to have undergone a distinct expansion process in some cases. We propose a working model of light perception, signal transduction and response-eliciting in G. max, based on the identified key components from Arabidopsis. These results demonstrate the power of comparative genomics between model systems and crop species to elucidate several aspects of plant physiology and metabolism.

Metastatic melanoma positively influences pregnancy outcome in a mouse model: could a deadly tumor support embryo life?

The incidence of melanoma is increasing worldwide. It is one of the leading cancers in pregnancy and the most common malignancy to metastasize to placenta and fetus. There are no publications about experimental models of melanoma and pregnancy. We propose a new experimental murine model to study the effects of melanoma on pregnancy and its metastatic process. We tested several doses of melanoma cells until we arrived at the optimal dose, which produced tumor growth and allowed animal survival to the end of pregnancy. Two control groups were used: control (C) and stress control (SC) and three different routes of inoculation: intravenous (IV), intraperitoneal (IP) and subcutaneous (SC). All the fetuses and placentas were examined macroscopically and microscopically. The results suggest that melanoma is a risk factor for intrauterine growth restriction but does not affect placental weight. When inoculated by the SC route, the tumor grew only in the site of implantation. The IP route produced peritoneal tumoral growth and also ovarian and uterine metastases in 60% of the cases. The IV route produced pulmonary tumors. No placental or fetal metastases were obtained, regardless of the inoculation route. The injection of melanoma cells by any route did not increase the rate of fetal resorptions. Surprisingly, animals in the IV groups had no resorptions and a significantly higher number of fetuses. This finding may indicate that tumoral factors released in the host organism to favor tumor survival may also have a pro-gestational action and consequently improve the reproductive performance of these animals.

Simvastatin-induced cardiac autonomic control improvement in fructose-fed female rats

OBJECTIVE: Because autonomic dysfunction has been found to lead to cardiometabolic disorders and because studies have reported that simvastatin treatment has neuroprotective effects, the objective of the present study was to investigate the effects of simvastatin treatment on cardiovascular and autonomic changes in fructose-fed female rats. METHODS: Female Wistar rats were divided into three groups: controls (n=8), fructose (n=8), and fructose+ simvastatin (n=8). Fructose overload was induced by supplementing the drinking water with fructose (100 mg/L, 18 wks). Simvastatin treatment (5 mg/kg/day for 2 wks) was performed by gavage. The arterial pressure was recorded using a data acquisition system. Autonomic control was evaluated by pharmacological blockade. RESULTS: Fructose overload induced an increase in the fasting blood glucose and triglyceride levels and insulin resistance. The constant rate of glucose disappearance during the insulin intolerance test was reduced in the fructose group (3.4+ 0.32%/min) relative to that in the control group (4.4+ 0.29%/min). Fructose+simvastatin rats exhibited increased insulin sensitivity (5.4+0.66%/min). The fructose and fructose+simvastatin groups demonstrated an increase in the mean arterial pressure compared with controls rats (fructose: 124+2 mmHg and fructose+simvastatin: 126 + 3 mmHg vs. controls: 112 + 2 mmHg). The sympathetic effect was enhanced in the fructose group (73 + 7 bpm) compared with that in the control (48 + 7 bpm) and fructose+simvastatin groups (31+8 bpm). The vagal effect was increased in fructose+simvastatin animals (84 + 7 bpm) compared with that in control (49 + 9 bpm) and fructose animals (46+5 bpm). CONCLUSION: Simvastatin treatment improved insulin sensitivity and cardiac autonomic control in an experimental model of metabolic syndrome in female rats. These effects were independent of the improvements in the classical plasma lipid profile and of reductions in arterial pressure. These results support the hypothesis that statins reduce the cardiometabolic risk in females with metabolic syndrome.

Allosteric Control of Gating Mechanisms Revisited: The Large Conductance Ca(2+)-Activated K(+) Channel

Large-conductance Ca(2+)-activated K(+) channels (BK) play a fundamental role in modulating membrane potential in many cell types. The gating of BK channels and its modulation by Ca(2+) and voltage has been the subject of intensive research over almost three decades, yielding several of the most complicated kinetic mechanisms ever proposed. A large number of open and closed states disposed, respectively, in two planes, named tiers, characterize these mechanisms. Transitions between states in the same plane are cooperative and modulated by Ca(2+). Transitions across planes are highly concerted and voltage-dependent. Here we reexamine the validity of the two-tiered hypothesis by restricting attention to the modulation by Ca(2+). Large single channel data sets at five Ca(2+) concentrations were simultaneously analyzed from a Bayesian perspective by using hidden Markov models and Markov-chain Monte Carlo stochastic integration techniques. Our results support a dramatic reduction in model complexity, favoring a simple mechanism derived from the Monod-Wyman-Changeux allosteric model for homotetramers, able to explain the Ca(2+) modulation of the gating process. This model differs from the standard Monod-Wyman-Changeux scheme in that one distinguishes when two Ca(2+) ions are bound to adjacent or diagonal subunits of the tetramer.

Cost risk benefit analysis to support chemoprophylaxis policy for travellers to malaria endemic countries

Background: In a number of malaria endemic regions, tourists and travellers face a declining risk of travel associated malaria, in part due to successful malaria control. Many millions of visitors to these regions are recommended, via national and international policy, to use chemoprophylaxis which has a well recognized morbidity profile. To evaluate whether current malaria chemo-prophylactic policy for travellers is cost effective when adjusted for endemic transmission risk and duration of exposure. a framework, based on partial cost-benefit analysis was used Methods: Using a three component model combining a probability component, a cost component and a malaria risk component, the study estimated health costs avoided through use of chemoprophylaxis and costs of disease prevention (including adverse events and pre-travel advice for visits to five popular high and low malaria endemic regions) and malaria transmission risk using imported malaria cases and numbers of travellers to malarious countries. By calculating the minimal threshold malaria risk below which the economic costs of chemoprophylaxis are greater than the avoided health costs we were able to identify the point at which chemoprophylaxis would be economically rational. Results: The threshold incidence at which malaria chemoprophylaxis policy becomes cost effective for UK travellers is an accumulated risk of 1.13% assuming a given set of cost parameters. The period a travellers need to remain exposed to achieve this accumulated risk varied from 30 to more than 365 days, depending on the regions intensity of malaria transmission. Conclusions: The cost-benefit analysis identified that chemoprophylaxis use was not a cost-effective policy for travellers to Thailand or the Amazon region of Brazil, but was cost-effective for travel to West Africa and for those staying longer than 45 days in India and Indonesia.

Melatonin treatment decreases c-fos expression in a headache model induced by capsaicin

The aim of the present work was to analyze c-fos response within the trigeminal nucleus caudalis (TNC) of pinealectomized rats and animals that received intraperitoneal melatonin, after intracisternal infusion of capsaicin, used to induce intracranial trigeminovascular stimulation. Experimental groups consisted of animals that received vehicle solution (saline-ethanol-Tween 80, 8:1:1, diluted 1:50) only (VEI, n = 5); animals that received capsaicin solution (200 nM) only (CAP, n = 6); animals submitted to pinealectomy (PX, n = 5); sham-operated animals (SH, n = 5); animals submitted to pinealectomy followed by capsaicin stimulation (200 nM) after 15 days (PX + CAP, n = 7); and animals that received capsaicin solution (200 nM) and intraperitoneal melatonin (10 mg/kg) (CAP + MEL, n = 5). Control rats, receiving vehicle in the cisterna magna, showed a small number of c-fos-positive cells in the TNC (layer I/II) as well as the sham-operated and pinealectomized rats, when compared to animals stimulated by capsaicin. On the other hand, pinealectomized rats, which received capsaicin, presented the highest number of c-fos-positive cells. Animals receiving capsaicin and melatonin treatment had similar expression of the vehicle group. Our data provide experimental evidence to support the role of melatonin and pineal gland in the pathophysiology of neurovascular headaches.

Control of interceptive actions is based on expectancy of time to target arrival

In this study the hypothesis that interceptive movements are controlled on the basis of expectancy of time to target arrival was tested. The study was conducted through assessment of temporal errors and kinematics of interceptive movements to a moving virtual target. Initial target velocity was kept unchanged in part of the trials, and in the others it was decreased 300 ms before the due time of target arrival at the interception position, increasing in 100 ms time to target arrival. Different probabilities of velocity decrease ranging from 25 to 100% were compared. The results revealed that while there were increasing errors between probabilities of 25 and 75% for unchanged target velocity, the opposite relationship was observed for target velocity decrease. Kinematic analysis indicated that movement timing adjustments to target velocity decrease were made online. These results support the conception that visuomotor integration in the interception of moving targets is mediated by an internal forward model whose weights can be flexibly adjusted according to expectancy of time to target arrival.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.

Real time optimization (RTO) with model predictive control (MPC)

This paper studies a simplified methodology to integrate the real time optimization (RTO) of a continuous system into the model predictive controller in the one layer strategy. The gradient of the economic objective function is included in the cost function of the controller. Optimal conditions of the process at steady state are searched through the use of a rigorous non-linear process model, while the trajectory to be followed is predicted with the use of a linear dynamic model, obtained through a plant step test. The main advantage of the proposed strategy is that the resulting control/optimization problem can still be solved with a quadratic programming routine at each sampling step. Simulation results show that the approach proposed may be comparable to the strategy that solves the full economic optimization problem inside the MPC controller where the resulting control problem becomes a non-linear programming problem with a much higher computer load. (C) 2010 Elsevier Ltd. All rights reserved.

Optimizing model predictive control of an industrial distillation column

The main scope of this work is the implementation of an MPC that integrates the control and the economic optimization of the system. The two problems are solved simultaneously through the modification of the control cost function that includes an additional term related to the economic objective. The optimizing MPC is based on a quadratic program (QP) as the conventional MPC and can be solved with the available QP solvers. The method was implemented in an industrial distillation system, and the results show that the approach is efficient and can be used, in several practical cases. (C) 2011 Elsevier Ltd. All rights reserved.

Stable Model Predictive Control for Integrating Systems with Optimizing Targets

This paper concern the development of a stable model predictive controller (MPC) to be integrated with real time optimization (RTO) in the control structure of a process system with stable and integrating outputs. The real time process optimizer produces Optimal targets for the system inputs and for Outputs that Should be dynamically implemented by the MPC controller. This paper is based oil a previous work (Comput. Chem. Eng. 2005, 29, 1089) where a nominally stable MPC was proposed for systems with the conventional control approach where only the outputs have set points. This work is also based oil the work of Gonzalez et at. (J. Process Control 2009, 19, 110) where the zone control of stable systems is studied. The new control for is obtained by defining ail extended control objective that includes input targets and zone controller the outputs. Additional decision variables are also defined to increase the set of feasible solutions to the control problem. The hard constraints resulting from the cancellation of the integrating modes Lit the end of the control horizon are softened,, and the resulting control problem is made feasible to a large class of unknown disturbances and changes of the optimizing targets. The methods are illustrated with the simulated application of the proposed,approaches to a distillation column of the oil refining industry.

Robust model predictive control with zone control

Model predictive control (MPC) is usually implemented as a control strategy where the system outputs are controlled within specified zones, instead of fixed set points. One strategy to implement the zone control is by means of the selection of different weights for the output error in the control cost function. A disadvantage of this approach is that closed-loop stability cannot be guaranteed, as a different linear controller may be activated at each time step. A way to implement a stable zone control is by means of the use of an infinite horizon cost in which the set point is an additional variable of the control problem. In this case, the set point is restricted to remain inside the output zone and an appropriate output slack variable is included in the optimisation problem to assure the recursive feasibility of the control optimisation problem. Following this approach, a robust MPC is developed for the case of multi-model uncertainty of open-loop stable systems. The controller is devoted to maintain the outputs within their corresponding feasible zone, while reaching the desired optimal input target. Simulation of a process of the oil re. ning industry illustrates the performance of the proposed strategy.

Distributed power control algorithm for multiple access systems based on Verhulst model

In this paper the continuous Verhulst dynamic model is used to synthesize a new distributed power control algorithm (DPCA) for use in direct sequence code division multiple access (DS-CDMA) systems. The Verhulst model was initially designed to describe the population growth of biological species under food and physical space restrictions. The discretization of the corresponding differential equation is accomplished via the Euler numeric integration (ENI) method. Analytical convergence conditions for the proposed DPCA are also established. Several properties of the proposed recursive algorithm, such as Euclidean distance from optimum vector after convergence, convergence speed, normalized mean squared error (NSE), average power consumption per user, performance under dynamics channels, and implementation complexity aspects, are analyzed through simulations. The simulation results are compared with two other DPCAs: the classic algorithm derived by Foschini and Miljanic and the sigmoidal of Uykan and Koivo. Under estimated errors conditions, the proposed DPCA exhibits smaller discrepancy from the optimum power vector solution and better convergence (under fixed and adaptive convergence factor) than the classic and sigmoidal DPCAs. (C) 2010 Elsevier GmbH. All rights reserved.