Antidepressant-like effects of an apolar extract and chow enriched with Nepeta cataria (catnip) in mice

Nepeta cataria (catnip) is a plant used in pet toys and to treat human diseases. Catnip has also been used in the treatment of some depressive disorders. In this paper, we studied the antidepressant, anxiogenic, and motor activity effects of acute and repeated feeding of chow enriched with 10% N. cataria leaves and the acute and repeated administration of apolar and polar extracts of N. cataria leaves in male mice. The results showed that repeated feeding and acute and repeated administration with the apolar extract reduced immobility in the behavioral despair test but did not alter elevated plus maze and open-field parameters. Acute feeding and the acute and repeated administration of the polar extracts of N. cataria leaves did not alter the behavior of mice. These data suggest that N. cataria has antidepressant properties. Moreover, this antidepressant activity was present in the apolar extract.

Identification of a Highly Antigenic Linear B Cell Epitope within Plasmodium vivax Apical Membrane Antigen 1 (AMA-1)

Apical membrane antigen 1 (AMA-1) is considered to be a major candidate antigen for a malaria vaccine. Previous immunoepidemiological studies of naturally acquired immunity to Plasmodium vivax AMA-1 (PvAMA-1) have shown a higher prevalence of specific antibodies to domain II (DII) of AMA-1. In the present study, we confirmed that specific antibody responses from naturally infected individuals were highly reactive to both full-length AMA-1 and DII. Also, we demonstrated a strong association between AMA-1 and DII IgG and IgG subclass responses. We analyzed the primary sequence of PvAMA-1 for B cell linear epitopes co-occurring with intrinsically unstructured/ disordered regions (IURs). The B cell epitope comprising the amino acid sequence 290-307 of PvAMA-1 (SASDQPTQYEEEMTDYQK), with the highest prediction scores, was identified in domain II and further selected for chemical synthesis and immunological testing. The antigenicity of the synthetic peptide was identified by serological analysis using sera from P. vivax-infected individuals who were knowingly reactive to the PvAMA-1 ectodomain only, domain II only, or reactive to both antigens. Although the synthetic peptide was recognized by all serum samples specific to domain II, serum with reactivity only to the full-length protein presented 58.3% positivity. Moreover, IgG reactivity against PvAMA-1 and domain II after depletion of specific synthetic peptide antibodies was reduced by 18% and 33% (P = 0.0001 for both), respectively. These results suggest that the linear epitope SASDQPTQYEEEMTDYQK is highly antigenic during natural human infections and is an important antigenic region of the domain II of PvAMA-1, suggesting its possible future use in pre-clinical studies.

Formulating Mixed Models for Experiments, Including Longitudinal Experiments

Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.

Tram at South Brisbane station, Brisbane Australia

Three men inspecting tram at South Brisbane station, Brisbane Australia, during No War Toys outing. WILPF (Womens International League for Peace and Freedom) banner can be seen on the front of the tram. The Women's International League for Peace and Freedom was founded in 1915. It works towards disarmament, political solutions to international conflicts, equal participation of women in activities, economic justice and the elimination of racism and discrimination. To achieve these goals, the Women's International League for Peace and Freedom organises meetings, conferences and campaigns.

Tram leaving South Brisbane Station

Tram leaving South Brisbane Station, Brisbane, Australia during "No war toys" outing.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

A computational study of shock speeds in high-performance shock tubes

This paper describes U2DE, a finite-volume code that numerically solves the Euler equations. The code was used to perform multi-dimensional simulations of the gradual opening of a primary diaphragm in a shock tube. From the simulations, the speed of the developing shock wave was recorded and compared with other estimates. The ability of U2DE to compute shock speed was confirmed by comparing numerical results with the analytic solution for an ideal shock tube. For high initial pressure ratios across the diaphragm, previous experiments have shown that the measured shock speed can exceed the shock speed predicted by one-dimensional models. The shock speeds computed with the present multi-dimensional simulation were higher than those estimated by previous one-dimensional models and, thus, were closer to the experimental measurements. This indicates that multi-dimensional flow effects were partly responsible for the relatively high shock speeds measured in the experiments.

Solution structure of amyloid beta-peptide(1-40) in a water-micelle environment. Is the membrane-spanning domain where we think it is?

The three-dimensional solution structure of the 40 residue amyloid beta-peptide, A beta(1-40), has been determined using NMR spectroscopy at pH 5.1, in aqueous sodium dodecyl sulfate (SDS) micelles, In this environment, which simulates to some extent a water-membrane medium, the peptide is unstructured between residues 1 and 14 which are mainly polar and likely solvated by water. However, the rest of the protein adopts an alpha-helical conformation between residues 15 and 36 with a kink or hinge at 25-27. This largely hydrophobic region is likely solvated by SDS. Based on the derived structures, evidence is provided in support of a possible new location for the transmembrane domain of A beta within the amyloid precursor protein (APP). Studies between pH 4.2 and 7.9 reveal a pH-dependent helix-coil conformational switch. At the lower pH values, where the carboxylate residues are protonated, the helix is uncharged, intact, and lipid-soluble. As the pH increases above 6.0, part of the helical region (15-24) becomes less structured, particularly near residues E22 and D23 where deprotonation appears to facilitate unwinding of the helix. This pH-dependent unfolding to a random coil conformation precedes any tendency of this peptide to aggregate to a beta-sheet as the pH increases. The structural biology described herein for A beta(1-40) suggests that (i) the C-terminal two-thirds of the peptide is an alpha-helix in membrane-like environments, (ii) deprotonation of two acidic amino acids in the helix promotes a helix-coil conformational transition that precedes aggregation, (iii) a mobile hinge exists in the helical region of A beta(1-40) and this may be relevant to its membrane-inserting properties and conformational rearrangements, and (iv) the location of the transmembrane domain of amyloid precursor proteins may be different from that accepted in the Literature. These results may provide new insight to the structural properties of amyloid beta-peptides of relevance to Alzheimer's disease.

Behavior and interactions of children in cooperative groups in lower and middle elementary grades

The study investigated the behaviors and interactions of children in structured and unstructured groups as they worked together on a 6-week social studies activity each term for 3 school terms. Two hundred and twelve children in Grade 1 and 184 children in Grade 3 participated in the study. Stratified random assignment occurred so that each gender-balanced group consisted of 1 high-, 2 medium-, and 1 low-ability student. The results show that the children in the structured groups were consistently more cooperative and they provided more elaborated and nonelaborated help than did their peers in the unstructured groups. The children in the structured groups in Grade 3 obtained higher reading and learning outcome scores than their peers in the unstructured groups.

Identification of initiation sites for T4 lysozyme folding using CD and NMR spectroscopy of peptide fragments

Using CD and 2D H-1 NMR spectroscopy, we have identified potential initiation sites for the folding of T4 lysozyme by examining the conformational preferences of peptide fragments corresponding to regions of secondary structure. CD spectropolarimetry showed most peptides were unstructured in water, but adopted partial helical conformations in TFE and SDS solution. This was also consistent with the H-1 NMR data which showed that the peptides were predominantly disordered in water, although in some cases, nascent or small populations of partially folded conformations could be detected. NOE patterns, coupling constants, and deviations from random coil Her chemical shift values complemented the CD data and confirmed that many of the peptides were helical in TFE and SDS micelles. In particular, the peptide corresponding to helix E in the native enzyme formed a well-defined helix in both TFE and SDS, indicating that helix E potentially forms an initiation site for T4 lysozyme folding. The data for the other peptides indicated that helices D, F, G, and H are dependent on tertiary interactions for their folding and/or stability. Overall, the results from this study, and those of our earlier studies, are in agreement with modeling and IID-deuterium exchange experiments, and support an hierarchical model of folding for T4 lysozyme.

Solution structures in aqueous SDS micelles of two amyloid beta peptides of A beta(1-28) mutated at the alpha-secretase cleavage site (K16E, K16F)

NMR solution structures are reported for two mutants (K16E, K16F) of the soluble amyloid beta peptide A beta(1-28). The structural effects of these mutations of a positively charged residue to anionic and hydrophobic residues at the alpha-secretase cleavage site (Lys16-Leu17) were examined in the membrane-simulating solvent aqueous SDS micelles. Overall the three-dimensional structures were similar to that for the native A beta(1-28) sequence in that they contained an unstructured N-terminus and a helical C-terminus. These structural elements are similar to those seen in the corresponding regions of full-length A beta peptides A beta(1-40) and A beta(1-42), showing that the shorter peptides are valid model systems. The K16E mutation, which might be expected to stabilize the macrodipole of the helix, slightly increased the helix length (residues 13-24) relative to the K16F mutation, which shortened the helix to between residues 16 and 24. The observed sequence-dependent control over conformation in this region provides an insight into possible conformational switching roles of mutations in the amyloid precursor protein from which A beta peptides are derived. In addition, if conformational transitions from helix to random coil to sheet precede aggregation of A beta peptides in vivo, as they do in vitro, the conformation-inducing effects of mutations at Lys16 may also influence aggregation and fibril formation. (C) 2000 Academic Press.

Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

Conformational analysis of LYS(11-36), a peptide derived from the beta-sheet region of T4 lysozyme, in TFE and SDS

The solution conformation of a peptide LYS(11-36), which corresponds to the beta-sheet region in T4 lysozyme, has been examined in aqueous solution, TFE, and SDS micelles by CD and H-1 NMR spectroscopy. Secondary structure predictions suggest some beta-sheet and turn character in aqueous solution but predict a helical conformation in a more hydrophobic environment. The predictions were supported by the CD and NMR studies which showed the peptide to be relatively unstructured in aqueous solution, although there was some evidence of a beta-turn conformer which was maintained in 200 mM SDS and, to a lesser extent, in 50% TFE. The peptide was significantly helical in the presence of either 50% TFE or 200 mM SDS. TFE and SDS titrations showed that the peptide could form helical, sheet, or extended structure depending on the TFE or SDS concentration. The studies indicate that peptide environment is the determining factor in secondary structure adopted by LYS(11-36).

Clinical supervision in four mental health professions: A review of the evidence

This paper examines a range of theoretical issues and the empirical evidence relating to clinical supervision in four mental health professions, namely clinical psychology, occupational therapy, social work, and speech pathology. Despite the widespread acceptance of the value of supervision among practitioners and the large quantity of literature on the topic, there is very little empirical evidence in this area. It is not clear whether supervision actually produces a change in clinician behaviour, nor whether it produces benefits in terms of client outcomes. To date, there is insufficient evidence to demonstrate which styles of supervision are most beneficial for particular types of staff, in terms of their level of experience or learning style. The data suggest that directive forms of supervision, rather than unstructured approaches, are preferred by relatively inexperienced practitioners, and that experienced clinicians also value direct supervision methods when learning new skills or dealing with complex or crisis situations. The available evidence suggests that supervisors typically receive little training in supervision methods. However, to date, we have little information to guide us as to the most effective ways of training supervisors. While acknowledging the urgent need for research, the paper concludes that supervision is likely to form a valuable component of professional development for mental health professionals.

Achieving effective supervision

Super vision probably does have benefits both for the maintenance and improvement of clinical skills and for job satisfaction, but the data are very thin and almost non-existent in the area of alcohol and other drugs services. Because of the potential complexity of objectives and roles in super vision, a structured agreement appears to be an important part of the effective supervision relationship. Because sessions can degenerate easily into unstructured socialization, agendas and session objectives may also be important. While a working alliance based on mutual respect and trust is an essential base for the supervision relationship, procedures for direct observation of clinical skills, demonstration of new procedures and skills practice with detailed feedback appear critical to super vision's impact on practice. To ensure effective super vision, there needs not only to be a minimum of personnel and resources, but also a compatibility with the values and procedures of management and staff, access to supervision training and consultation and sufficient incentives to ensure it continues.