Nitric oxide synthase inhibitors improve prepulse inhibition responses of Wistar rats

Introduction: Cognitive and attentional deficits in schizophrenia include impairment of the sensorimotor filter as measured by prepulse inhibition (PPI). In this way, the study of animals that naturally present low PPI responses could be a useful approach for screening new antipsychotic drugs. Several pieces of evidence suggest that dopamine and nitric oxide (NO) can modulate PPI but their role in those animals is unknown. Objectives: The aim of this study was to investigate the role of dopamine and NO in Wistar rats with naturally low PPI response. Methods: Male Wistar rats with low PPI responses received an i.p. injection of the antipsychotics haloperidol (0.1, 0.3 or 1 mg/kg) or clozapine (0.5, 1.5 or 5 mg/kg), the anxiolytic diazepam (1 or 3 mg/kg) or the NO synthase (NOS) inhibitors, N(G)- nitro-L-arginine (L-NOARG; 40 mg/kg, acutely or sub-chronically) or 7-Nitroindazole (7-NI; 3, 10 or 30 mg/kg). All animals were submitted to the PPI test 1 h after injection. Striatal and cortical dopamine, DOPAC, and noradrenaline levels of rats with low PPI responses were compared to rats with normal PPI responses. Results: We found increased levels of catecholamines on the striatum and prefrontal cortex of Wistar rats with low PPI. In these animals, both antipsychotics, typical and atypical, and NOS inhibitors significantly increased PPI. Conclusion: Taken together, our findings suggest that the low PPI phenotype may be driven by an over-active catecholamine system. Additionally, our results corroborate the hypothesis of dopamine and NO interaction on PPI modulation and suggest that Wistar rats with low PPI may represent an interesting non-pharmacological model to evaluate new potential antipsychotics. (C) 2010 Elsevier B.V. All rights reserved.

Single Intranasal Administration of 1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine in C57BL/6 Mice Models Early Preclinical Phase of Parkinson`s Disease

Many studies have shown that deficits in olfactory and cognitive functions precede the classical motor symptoms seen in Parkinson`s disease (PD) and that olfactory testing may contribute to the early diagnosis of this disorder. Although the primary cause of PD is still unknown, epidemiological studies have revealed that its incidence is increased in consequence of exposure to certain environmental toxins. In this study, most of the impairments presented by C57BL/6 mice infused with a single intranasal (i.n.) administration of the proneurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) (1 mg/nostril) were similar to those observed during the early phase of PD, when a moderate loss of nigral dopamine neurons results in olfactory and memory deficits with no major motor impairments. Such infusion decreased the levels of the enzyme tyrosine hydroxylase in the olfactory bulb, striatum, and substantia nigra by means of apoptotic mechanisms, reducing dopamine concentration in different brain structures such as olfactory bulb, striatum, and prefrontal cortex, but not in the hippocampus. These findings reinforce the notion that the olfactory system represents a particularly sensitive route for the transport of neurotoxins into the central nervous system that may be related to the etiology of PD. These results also provide new insights in experimental models of PD, indicating that the i.n. administration of MPTP represents a valuable mouse model for the study of the early stages of PD and for testing new therapeutic strategies to restore sensorial and cognitive processes in PD.

Nitric oxide modulation of methylphenidate-induced disruption of prepulse inhibition in Swiss mice

Drugs that facilitate dopaminergic neurotransmission induce cognitive and attentional deficits which include inability to filter sensory input measured by prepulse inhibition (PPI) Methylphenidate, an amphetamine analog is used in the treatment of attention deficit hyperactivity disorder Given that nitric oxide (NO) modulates dopamine effect our aim is to analyze the nitric oxide synthase (NOS) and soluble guanylate cyclase (sGC) inhibitors effect on PPI disruption induced by methylphenidate The inhibitors effects were compared to those produced by haloperidol and clozapine Male Swiss mice received a first I p. Injection (one hour before testing), of either saline, or N(G) nitro L-arginine (10, 40 or 90 mg/kg) or 7-Nitroindazole (3, 10, 30 or 60 mg/kg). or oxadiazolo-quinoxalin (5 or 10 mg/kg). or haloperidol (1 mg/kg), or clozapine (5 mg/kg) Thirty min later mice received the second injection of either saline or methylphenidate (20 or 30 mg/kg) or amphetamine (5 or 10 mg/kg). One group of mice received intracerebroventricular 7-Nitroindazole (50 or 100 nM) followed by systemic administration of saline or methylphenidate (30 mg/kg) The results revealed a methylphenidate dose-dependent disruption of PPI comparable to amphetamine. The effect was prevented by either nitric oxide synthase or guanilate cyclase inhibitors or clozapine or haloperidol In conclusion, methylphenidate induced a dose-dependent PPI disruption in Swiss mice modulated by dopamine and NO/sGC. The results corroborate the hypothesis of dopamine and NO interacting to modulate sensorimotor gating through central nervous system. It may be useful to understand methylphenidate and other psychostimulants effects (C) 2009 Elsevier B.V All rights reserved

Contrasting models of land use regulation: Community, government and tourism development

This paper assesses the capacity of local communities and sub-national governments to influence patterns of tourism development, within the context of a globalizing economy. Through a comparison of the contrasting examples of Hawaii and Queensland, the paper indicates the consequences of different approaches to land use regulation. It points to the importance of planning and policy processes that integrate community interests, in order to achieve long-term, sustainable tourism development. Effective regulation of development can minimize the social and environmental impacts of tourism. The paper illustrates how community organizations and sub-national governments can articulate local interests, despite the global demands of investors for more deregulated markets in land.

Models involving two inverse Weibull distributions

In this paper, we look at three models (mixture, competing risk and multiplicative) involving two inverse Weibull distributions. We study the shapes of the density and failure-rate functions and discuss graphical methods to determine if a given data set can be modelled by one of these models. (C) 2001 Elsevier Science Ltd. All rights reserved.

Effect of probe stimulus intensity on the dissociation between autonomic orienting and secondary probe reaction time

Information processing accounts propose that autonomic orienting reflects the amount of resources allocated to process a stimulus. However, secondary task reaction time (RT), a supposed measure of processing resources, has shown a dissociation from autonomic orienting. The present study tested the hypothesis that secondary task RT reflects a serial processing mechanism. Participants (N = 24) were presented with circle and ellipse shapes and asked to count the number of longer-than-usual presentations of one shape (task-relevant) and to ignore presentations of a second shape (task-irrelevant). Concurrent with the counting task, participants performed a secondary RT task to an auditory probe presented at either a high or low intensity and at two different probe positions following shape onset (50 and 300 ms). Electrodermal orienting was larger during task-relevant shapes than during task-irrelevant shapes, but secondary task RT to the high-intensity probe was slower during the latter. In addition, an underadditive interaction between probe stimulus intensity and probe position was found in secondary RT. The findings are consistent with a serial processing model of secondary RT and suggest that the notion of processing stages should be incorporated into current information-processing models of autonomic orienting.

Differential perturbation of neuronal and glial glutamate transport systems in retinal ischaemia

Glutamate is the major excitatory neurotransmitter in the retina and is removed from the extracellular space by an energy-dependent process involving neuronal and glial cell transporters. The radial glial Muller cells express the glutamate transporter, GLAST, and preferentially accumulate glutamate. However, during an ischaemic episode, extracellular glutamate concentrations may rise to excitotoxic levels. Is this catastrophic rise in extracellular glutamate due to a failure of GLAST? Using immunocytochemistry, we monitored the transport of the glutamate transporter substrate, D-aspartate, in the retina under normal and ischaemic conditions. Two models of compromised retinal perfusion were compared: (1) Anaesthetised rats had their carotid arteries occluded for 7 days to produce a chronic reduction in retinal blood flow. Retinal function was assessed by electroretinography. D-aspartate was injected into the eye for 45 min, Following euthanasia, the retina was processed for D-aspartate. GLAST and glutamate immunocytochemistry. Although reduced retinal perfusion suppresses the electroretinogram b-wave, neither retinal histology, GLAST expression, nor the ability of Muller cells to uptake D-aspartate is affected. As this insult does not appear to cause excitotoxic neuronal damage, these data suggest that GLAST function and glutamate clearance are maintained during periods of reduced retinal perfusion. (2) Occlusion of the central retinal artery for 60 min abolishes retinal perfusion, inducing histological damage and electroretinogram suppression. Although GLAST expression appears to be normal. its ability to transport D-aspartate into Muller cells is greatly reduced. Interestingly, D-aspartate is transported into neuronal cells, i.e. photoreceptors, bipolar and ganglion cells. This suggests that while GLAST is vitally important for the clearance of excess extracellular glutamate, its capability to sustain inward transport is particularly susceptible to an acute ischaemic attack. Manipulation of GLAST function could alleviate the degeneration and blindness that result from ischaemic retinal disease. (C) 2001 Elsevier Science Ltd, All rights reserved.

Large-N solutions of the Heisenberg and Hubbard-Heisenberg models on the anisotropic triangular lattice: application to Cs2CuCl4 and to the layered organic superconductors kappa-(BEDT-TTF)(2)X (BEDT-TTF bis(ethylene-dithio)tetrathiafulvalene); X anion)

We solve the Sp(N) Heisenberg and SU(N) Hubbard-Heisenberg models on the anisotropic triangular lattice in the large-N limit. These two models may describe respectively the magnetic and electronic properties of the family of layered organic materials K-(BEDT-TTF)(2)X, The Heisenberg model is also relevant to the frustrated antiferromagnet, Cs2CuCl4. We find rich phase diagrams for each model. The Sp(N) :antiferromagnet is shown to have five different phases as a function of the size of the spin and the degree of anisotropy of the triangular lattice. The effects of fluctuations at finite N are also discussed. For parameters relevant to Cs2CuCl4 the ground state either exhibits incommensurate spin order, or is in a quantum disordered phase with deconfined spin-1/2 excitations and topological order. The SU(N) Hubbard-Heisenberg model exhibits an insulating dimer phase, an insulating box phase, a semi-metallic staggered flux phase (SFP), and a metallic uniform phase. The uniform and SFP phases exhibit a pseudogap, A metal-insulator transition occurs at intermediate values of the interaction strength.

A systematic approach to error isolation in computerized wastewater simulation models

Activated sludge models are used extensively in the study of wastewater treatment processes. While various commercial implementations of these models are available, there are many people who need to code models themselves using the simulation packages available to them, Quality assurance of such models is difficult. While benchmarking problems have been developed and are available, the comparison of simulation data with that of commercial models leads only to the detection, not the isolation of errors. To identify the errors in the code is time-consuming. In this paper, we address the problem by developing a systematic and largely automated approach to the isolation of coding errors. There are three steps: firstly, possible errors are classified according to their place in the model structure and a feature matrix is established for each class of errors. Secondly, an observer is designed to generate residuals, such that each class of errors imposes a subspace, spanned by its feature matrix, on the residuals. Finally. localising the residuals in a subspace isolates coding errors. The algorithm proved capable of rapidly and reliably isolating a variety of single and simultaneous errors in a case study using the ASM 1 activated sludge model. In this paper a newly coded model was verified against a known implementation. The method is also applicable to simultaneous verification of any two independent implementations, hence is useful in commercial model development.

A Context Noise Model of Episodic Recognition Memory

Item noise models of recognition assert that interference at retrieval is generated by the words from the study list. Context noise models of recognition assert that interference at retrieval is generated by the contexts in which the test word has appeared. The authors introduce the bind cue decide model of episodic memory, a Bayesian context noise model, and demonstrate how it can account for data from the item noise and dual-processing approaches to recognition memory. From the item noise perspective, list strength and list length effects, the mirror effect for word frequency and concreteness, and the effects of the similarity of other words in a list are considered. From the dual-processing perspective, process dissociation data on the effects of length. temporal separation of lists, strength, and diagnosticity of context are examined. The authors conclude that the context noise approach to recognition is a viable alternative to existing approaches. (PsycINFO Database Record (c) 2008 APA, all rights reserved)

Outpatient cognitive behavioural therapy programme for alcohol dependence impact of naltrexone use on outcome

Objective: Cognitive-behavioural therapy (CBT) has been effectively used in the treatment of alcohol dependence. Clinical studies report that the anticraving drug naltrexone, is a useful adjunct to treatment. Currently, few data are available on the impact of adding this medication to programmes in more typical, outpatient, and rehabilitation settings. The objective of this study was to examine the impact on outcome of adding naltrexone to an established outpatient alcohol rehabilitation program which employed CBT. Method: Fifty patients participated in an established 12-week, outpatient, 'contract'-based alcohol abstinence programme which employed CBT. They also received naltrexone 50 mg orally daily (CBT + naltrexone). Outcomes were compared with 50 historical, matched controls, all of whom participated in the same programme without an anticraving medication (CBT alone). All patients met DSM-IV criteria for alcohol dependence. Results: Programme attendance across the eight treatment sessions was lower in the CBT alone group (p < 0.001). Relapse to alcohol use occurred sooner and more frequently in the CBT alone group (p < 0.001). Rehabilitation programme completion at 12 weeks was 88% (CBT + naltrexone) compared with 36% for (CBT alone) (p < 0.001). Alcohol abstinence at 12 weeks was 76% (CBT + naltrexone) compared with 18% (CBT alone) (p < 0.001). Conclusion: When employing the same outpatient rehabilitation programme and comparing outcomes using matched historical controls, the addition of naltrexone substantially improves programme attendance, programme completion and reported alcohol abstinence. In a typical outpatient programme, naltrexone addition was associated with significantly improved programme participation, better outcomes and was well tolerated.

Discrimination of adsorption kinetic models for the description of hydrocarbon adsorption in activated carbon

Five kinetic models for adsorption of hydrocarbons on activated carbon are compared and investigated in this study. These models assume different mass transfer mechanisms within the porous carbon particle. They are: (a) dual pore and surface diffusion (MSD), (b) macropore, surface, and micropore diffusion (MSMD), (c) macropore, surface and finite mass exchange (FK), (d) finite mass exchange (LK), and (e) macropore, micropore diffusion (BM) models. These models are discriminated using the single component kinetic data of ethane and propane as well as the multicomponent kinetics data of their binary mixtures measured on two commercial activated carbon samples (Ajax and Norit) under various conditions. The adsorption energetic heterogeneity is considered for all models to account for the system. It is found that, in general, the models assuming diffusion flux of adsorbed phase along the particle scale give better description of the kinetic data.

Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.