Antiulcerogenic Activity of the Essential Oil of Baccharis dracunculifolia on Different Experimental Models in Rats

Baccharis dracunculifolia DC (Asteraceae), a native plant from Brazil, commonly known as `Alecrim-do-campo` is widely used in folk medicine to treat inflammation, hepatic disorders and stomach ulcers, and it is the most important botanical source of Southeastern Brazilian propolis, known as green propolis. Its essential oil is composed of non-oxygenated and oxygenated terpenes. In this work, the effects of the essential oil obtained from the aerial parts of R dracunculifolia on gastric ulcers were evaluated. The antiulcer assays were undertaken using the following protocols in rats: nonsteroidal antiinflammatory drug (NSAID)-induced ulcer, ethanol-induced ulcer, stress-induced ulcer, and determination of gastric secretion using ligated pylorus. The treatment in the doses of 50, 250 and 500 mg/kg of R dracunculifolia essential oil significantly diminished the lesion index, the total lesion area and the percentage of lesions in comparison with both positive and negative control groups. With regard to the model of gastric secretion a reduction of gastric juice volume and total acidity was observed, as well as an increase in the gastric pH. No sign of toxicity was observed in the acute toxicity study. Considering the results, it is suggested that the essential oil of B. dracunculifolia could probably be a good therapeutic agent for the development of new phytotherapeutic medicine for the treatment of gastric ulcer. Copyright (C) 2009 John Wiley & Sons, Ltd.

Defining a role for the subthalamic nucleus within operative theoretical models of subcortical participation in language

Objective:To investigate the effects of bilateral, surgically induced functional inhibition of the subthalamic nucleus (STN) on general language, high level linguistic abilities, and semantic processing skills in a group of patients with Parkinson’s disease. Methods:Comprehensive linguistic profiles were obtained up to one month before and three months after bilateral implantation of electrodes in the STN during active deep brain stimulation (DBS) in five subjects with Parkinson’s disease (mean age, 63.2 years). Equivalent linguistic profiles were generated over a three month period for a non-surgical control cohort of 16 subjects with Parkinson’s disease (NSPD) (mean age, 64.4 years). Education and disease duration were similar in the two groups. Initial assessment and three month follow up performance profiles were compared within subjects by paired t tests. Reliability change indices (RCI), representing clinically significant alterations in performance over time, were calculated for each of the assessment scores achieved by the five STN-DBS cases and the 16 NSPD controls, relative to performance variability within a group of 16 non-neurologically impaired adults (mean age, 61.9 years). Proportions of reliable change were then compared between the STN-DBS and NSPD groups. Results:Paired comparisons within the STN-DBS group showed prolonged postoperative semantic processing reaction times for a range of word types coded for meanings and meaning relatedness. Case by case analyses of reliable change across language assessments and groups revealed differences in proportions of change over time within the STN-DBS and NSPD groups in the domains of high level linguistics and semantic processing. Specifically, when compared with the NSPD group, the STN-DBS group showed a proportionally significant (p

Redefining functional models of basal ganglia organisation: Role for the posteroventral pallidum in linguistic processing?

Traditionally the basal ganglia have been implicated in motor behavior, as they are involved in both the execution of automatic actions and the modification of ongoing actions in novel contexts. Corresponding to cognition, the role of the basal ganglia has not been defined as explicitly. Relative to linguistic processes, contemporary theories of subcortical participation in language have endorsed a role for the globus pallidus internus (GPi) in the control of lexical-semantic operations. However, attempts to empirically validate these postulates have been largely limited to neuropsychological investigations of verbal fluency abilities subsequent to pallidotomy. We evaluated the impact of bilateral posteroventral pallidotomy (BPVP) on language function across a range of general and high-level linguistic abilities, and validated/extended working theories of pallidal participation in language. Comprehensive linguistic profiles were compiled up to 1 month before and 3 months after BPVP in 6 subjects with Parkinson's disease (PD). Commensurate linguistic profiles were also gathered over a 3-month period for a nonsurgical control cohort of 16 subjects with PD and a group of 16 non-neurologically impaired controls (NC). Nonparametric between-groups comparisons were conducted and reliable change indices calculated, relative to baseline/3-month follow-up difference scores. Group-wise statistical comparisons between the three groups failed to reveal significant postoperative changes in language performance. Case-by-case data analysis relative to clinically consequential change indices revealed reliable alterations in performance across several language variables as a consequence of BPVP. These findings lend support to models of subcortical participation in language, which promote a role for the GPi in lexical-semantic manipulation mechanisms. Concomitant improvements and decrements in postoperative performance were interpreted within the context of additive and subtractive postlesional effects. Relative to parkinsonian cohorts, clinically reliable versus statistically significant changes on a case by case basis may provide the most accurate method of characterizing the way in which pathophysiologically divergent basal ganglia linguistic circuits respond to BPVP.

Titanium phosphate for Fuel Cell Proton Conduction Membranes

Environmental issues due to increases in emissions of air pollutants and greenhouse gases are driving the development of clean energy delivery technologies such as fuel cells. Low temperature Proton Exchange Membrane Fuel Cells (PEMFC) use hydrogen as a fuel and their only emission is water. While significant advances have been made in recent years, a major limitation of the current technology is the cost and materials limitations of the proton conduction membrane. The proton exchange membrane performs three critical functions in the PEMFC membrane electrode assembly (MEA): (i) conduction of protons with minimal resistance from the anode (where they are generated from hydrogen) to the cathode (where they combine with oxygen and electrons, from the external circuit or load), (ii) providing electrical insulation between the anode and cathode to prevent shorting, and (iii) providing a gas impermeable barrier to prevent mixing of the fuel (hydrogen) and oxidant. The PFSA (perfluorosulphonic acid) family of membranes is currently the best developed proton conduction membrane commercially available, but these materials are limited to operation below 100oC (typically 80oC, or lower) due to the thermochemical limitations of this polymer. For both mobile and stationary applications, fuel cell companies require more durable, cost effective membrane technologies capable of delivering enhanced performance at higher temperatures (typically 120oC, or higher. This is driving research into a wide range of novel organic and inorganic materials with the potential to be good proton conductors and form coherent membranes. There are several research efforts recently reported in the literature employing inorganic nanomaterials. These include functionalised silica phosphates [1,2], fullerene [3] titania phosphates [4], zirconium pyrophosphate [5]. This work addresses the functionalisation of titania particles with phosphoric acid. Proton conductivity measurements are given together with structural properties.

Functionalisation of nanoparticles as electrolytes in fuel cells

Inorganic metal oxide materials are generally poor proton conductors as conductivities are lower than 10-5-10-6 S.cm-1. However, by functionalising Silica, Zirconia or Titania, proton conduction increases by up to 5 orders of magnitude. Hence, functionalised nanomaterials are becoming very competitive against conventional electrolyte materials such as Nafion. In this work, sol-gel processes are employed to produce silica phosphate, zirconia phosphate and titania phosphate functionalised nanoparticles. Furthermore, conductivities at hydrate conditions are investigated, and nanoparticle formation and functionalisation effects on proton conductivity are discussed. Results show conductivities up to 10-1 S.cm-1 (95% RH). Proton conduction increases with the functionalisation content, however heat treatment of nanoparticles locks the functionality in the crystal phase, thus inhibiting proton conduction. Controlling the mesopore phase allows for high proton conduction at hydrated conditions, clearly indicating facilitated ion transport through the pore channels.

Nanocomposite Nafion-Silica membranes for direct methanol fuel cells

Commercially available proton exchange membranes such as Nafion do not meet the requirements for high power density direct methanol fuel cells, partly due to their high methanol permeability. The aim of this work is to develop a new class of high-proton conductivity membranes, with thermal and mechanical stability similar to Nafion and reduced methanol permeability. Nanocomposite membranes were produced by the in-situ sol-gel synthesis of silicon dioxide particles in preformed Nafion membranes. Microstructural modification of Nafion membranes with silica nanoparticles was shown in this work to reduce methanol crossover from 7.48x10-6 cm2s^-1 for pure Nafion® to 2.86 x10-6 cm2s^-1 for nanocomposite nafion membranes (Methanol 50% (v/v) solution, 75 degrees C). Best results were achieved with a silica composition of 2.6% (w/w). We propose that silica inhibits the conduction of methanol through Nafion by blocking sites necessary for methanol diffusion through the polymer electrolyte membrane. Effects of surface chemistry, nanoparticle formation and interactions with Nafion matrix are further addressed.

Hydrostability and Scaling Up Molecular Sieve Silica (MSS) Membranes for H2/CO Separation in Fuel Cell Systems

MSS membranes are a good candidate for CO cleanup in fuel cell fuel processing systems due to their ability to selectively permeate H2 over CO via molecular sieving. Successfully scaled up tubular membranes were stable under dry conditions to 400°C with H2 permeance as high as 2 x 10-6 mol.m-2.s^-1.Pa^-1 at 200 degrees C and H2/CO selectivity up to 6.4, indicating molecular sieving was the dominant mechanism. A novel carbonised template molecular sieve silica (CTMSS) technology gave the scaled up membranes resilience in hydrothermal conditions up to 400 degrees C in 34% steam and synthetic reformate, which is required for use in fuel cell CO cleanup systems.

A modified discrete random pore model allowing for different initial surface reactivity

We investigate here a modification of the discrete random pore model [Bhatia SK, Vartak BJ, Carbon 1996;34:1383], by including an additional rate constant which takes into account the different reactivity of the initial pore surface having attached functional groups and hydrogens, relative to the subsequently exposed surface. It is observed that the relative initial reactivity has a significant effect on the conversion and structural evolution, underscoring the importance of initial surface chemistry. The model is tested against experimental data on chemically controlled char oxidation and steam gasification at various temperatures. It is seen that the variations of the reaction rate and surface area with conversion are better represented by the present approach than earlier random pore models. The results clearly indicate the improvement of model predictions in the low conversion region, where the effect of the initially attached functional groups and hydrogens is more significant, particularly for char oxidation. It is also seen that, for the data examined, the initial surface chemistry is less important for steam gasification as compared to the oxidation reaction. Further development of the approach must also incorporate the dynamics of surface complexation, which is not considered here.

Elliptic Gaudin models and elliptic KZ equations

The Gaudin models based on the face-type elliptic quantum groups and the XYZ Gaudin models are studied. The Gaudin model Hamiltonians are constructed and are diagonalized by using the algebraic Bethe ansatz method. The corresponding face-type Knizhnik–Zamolodchikov equations and their solutions are given.

Algebraic Bethe ansatz method for the exact calculation of energy spectra and form factors: applications to models of Bose-Einstein condensates and metallic nanograins

In this review we demonstrate how the algebraic Bethe ansatz is used for the calculation of the-energy spectra and form factors (operator matrix elements in the basis of Hamiltonian eigenstates) in exactly solvable quantum systems. As examples we apply the theory to several models of current interest in the study of Bose-Einstein condensates, which have been successfully created using ultracold dilute atomic gases. The first model we introduce describes Josephson tunnelling between two coupled Bose-Einstein condensates. It can be used not only for the study of tunnelling between condensates of atomic gases, but for solid state Josephson junctions and coupled Cooper pair boxes. The theory is also applicable to models of atomic-molecular Bose-Einstein condensates, with two examples given and analysed. Additionally, these same two models are relevant to studies in quantum optics; Finally, we discuss the model of Bardeen, Cooper and Schrieffer in this framework, which is appropriate for systems of ultracold fermionic atomic gases, as well as being applicable for the description of superconducting correlations in metallic grains with nanoscale dimensions.; In applying all the above models to. physical situations, the need for an exact analysis of small-scale systems is established due to large quantum fluctuations which render mean-field approaches inaccurate.

Review of recent results on excursion set models

Many images consist of two or more 'phases', where a phase is a collection of homogeneous zones. For example, the phases may represent the presence of different sulphides in an ore sample. Frequently, these phases exhibit very little structure, though all connected components of a given phase may be similar in some sense. As a consequence, random set models are commonly used to model such images. The Boolean model and models derived from the Boolean model are often chosen. An alternative approach to modelling such images is to use the excursion sets of random fields to model each phase. In this paper, the properties of excursion sets will be firstly discussed in terms of modelling binary images. Ways of extending these models to multi-phase images will then be explored. A desirable feature of any model is to be able to fit it to data reasonably well. Different methods for fitting random set models based on excursion sets will be presented and some of the difficulties with these methods will be discussed.

Language policy spread: Learning from health and social policy models

Except for a few large scale projects, language planners have tended to talk and argue among themselves rather than to see language policy development as an inherently political process. A comparison with a social policy example, taken from the United States, suggests that it is important to understand the problem and to develop solutions in the context of the political process, as this is where decisions will ultimately be made.

Polytomous item response theory models

Polytomous Item Response Theory Models provides a unified, comprehensive introduction to the range of polytomous models available within item response theory (IRT). It begins by outlining the primary structural distinction between the two major types of polytomous IRT models. This focuses on the two types of response probability that are unique to polytomous models and their associated response functions, which are modeled differently by the different types of IRT model. It describes, both conceptually and mathematically, the major specific polytomous models, including the Nominal Response Model, the Partial Credit Model, the Rating Scale model, and the Graded Response Model. Important variations, such as the Generalized Partial Credit Model are also described as are less common variations, such as the Rating Scale version of the Graded Response Model. Relationships among the models are also investigated and the operation of measurement information is described for each major model. Practical examples of major models using real data are provided, as is a chapter on choosing an appropriate model. Figures are used throughout to illustrate important elements as they are described.