Processing of urinary pheromones in Antechinus stuartii (Marsupialia: Dasyuridae): Functional magnetic resonance imaging of the brain

Little is known of the neural mechanisms of marsupial olfaction. However, functional magnetic resonance imaging (fMRI) has made it possible to visualize dynamic brain function in mammals without invasion. In this study, central processing of urinary pheromones was investigated in the brown antechinus, Antechinus stuartii, using fMRI. Images were obtained from 18 subjects (11 males, 7 females) in response to conspecific urinary olfactory stimuli. Significant indiscriminate activation occurred in the accessory olfactory bulb, entorhinal, frontal, and parietal cortices in response to both male and female urine. The paraventricular nucleus of hypothalamus, ventrolateral thalamic nucleus, and medial preoptic area were only activated in response to male urine. Results of this MRI study indicate that projections of accessory olfactory system are activated by chemo-sensory cues. Furthermore, it appears that, based on these experiments, urinary pheromones may act on the hypothalamo-pituitary-adrenocortical axis via the paraventricular nucleus of the hypothalamus and may play an important role in the unique life history pattern of A. stuartii. Finally, this study has demonstrated that fMRI may be a powerful tool for investigations of olfactory processes in mammals.

Methods for prediction of peptide binding to MHC molecules: A comparative study

Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.

Local-global processing in early-onset schizophrenia: Evidence for an impairment in shifting the spatial scale of attention

In this study we report the results of two experiments on visual attention conducted with patients with early-onset schizophrenia. These experiments investigated the effect of irrelevant spatial-scale information upon the processing of relevant spatial-scale information, and the ability to shift the spatial scale of attention, across consecutive trials, between different levels of the hierarchical stimulus. Twelve patients with early-onset schizophrenia and matched controls performed local-global tasks under: (1) directed attention conditions with a consistency manipulation and (2) divided-attention conditions. In the directed-attention paradigm, the early-onset patients exhibited the normal patterns of global advantage and interference, and were not unduly affected by the consistency manipulation. Under divided-attention conditions, however, the early-onset patients exhibited a local-processing deficit. The source of this local processing deficit lay in the prolonged reaction time to local targets, when these had been preceded by a global target, but not when preceded by a local target. These findings suggest an impaired ability to shift the spatial scale of attention from a global to a local spatial scale in early-onset schizophrenia. (C) 2003 Elsevier Science (USA). All rights reserved.

Predicting energy requirements in the clinical setting: Are current methods evidence based?

Estimating energy requirements is necessary in clinical practice when indirect calorimetry is impractical. This paper systematically reviews current methods for estimating energy requirements. Conclusions include: there is discrepancy between the characteristics of populations upon which predictive equations are based and current populations; tools are not well understood, and patient care can be compromised by inappropriate application of the tools. Data comparing tools and methods are presented and issues for practitioners are discussed. (C) 2003 International Life Sciences Institute.

Formal methods within a totally functional approach to programming

Taking functional programming to its extremities in search of simplicity still requires integration with other development (e.g. formal) methods. Induction is the key to deriving and verifying functional programs, but can be simplified through packaging proofs with functions, particularly folds, on data (structures). Totally Functional Programming avoids the complexities of interpretation by directly representing data (structures) as platonic combinators - the functions characteristic to the data. The link between the two simplifications is that platonic combinators are a kind of partially-applied fold, which means that platonic combinators inherit fold-theoretic properties, but with some apparent simplifications due to the platonic combinator representation. However, despite observable behaviour within functional programming that suggests that TFP is widely-applicable, significant work remains before TFP as such could be widely adopted.

Multiresolution spatial databases: Making web-based spatial applications faster

Spatial data has now been used extensively in the Web environment, providing online customized maps and supporting map-based applications. The full potential of Web-based spatial applications, however, has yet to be achieved due to performance issues related to the large sizes and high complexity of spatial data. In this paper, we introduce a multiresolution approach to spatial data management and query processing such that the database server can choose spatial data at the right resolution level for different Web applications. One highly desirable property of the proposed approach is that the server-side processing cost and network traffic can be reduced when the level of resolution required by applications are low. Another advantage is that our approach pushes complex multiresolution structures and algorithms into the spatial database engine. That is, the developer of spatial Web applications needs not to be concerned with such complexity. This paper explains the basic idea, technical feasibility and applications of multiresolution spatial databases.

Assessing cost-effectiveness - Mental health: introduction to the study and methods

Objective: The Assessing Cost-Effectiveness - Mental Health (ACE-MH) study aims to assess from a health sector perspective, whether there are options for change that could improve the effectiveness and efficiency of Australia's current mental health services by directing available resources toward 'best practice' cost-effective services. Method: The use of standardized evaluation methods addresses the reservations expressed by many economists about the simplistic use of League Tables based on economic studies confounded by differences in methods, context and setting. The cost-effectiveness ratio for each intervention is calculated using economic and epidemiological data. This includes systematic reviews and randomised controlled trials for efficacy, the Australian Surveys of Mental Health and Wellbeing for current practice and a combination of trials and longitudinal studies for adherence. The cost-effectiveness ratios are presented as cost (A$) per disability-adjusted life year (DALY) saved with a 95% uncertainty interval based on Monte Carlo simulation modelling. An assessment of interventions on 'second filter' criteria ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') allows broader concepts of 'benefit' to be taken into account, as well as factors that might influence policy judgements in addition to cost-effectiveness ratios. Conclusions: The main limitation of the study is in the translation of the effect size from trials into a change in the DALY disability weight, which required the use of newly developed methods. While comparisons within disorders are valid, comparisons across disorders should be made with caution. A series of articles is planned to present the results.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

Fermentative production of hydrogen from cassava processing wastewater by Clostridium acetobutylicum

This work reports on the effect of initial substrate concentration on COD consumption, pH, and H(2) production during cassava processing wastewater fermentation by Clostridium acetobutylicum ATCC 824. Five initial COD wastewater concentrations, namely 5.0, 7.5, 10.7, 15.0, and 30.0 g/L, were used. The results showed that higher substrate concentrations (30.0 and 15.0 COD/L) led to lower H(2) yield as well as less efficient substrate conversion into H(2). On the other hand, initial COD concentrations of 10.7, 7.5 and 5 g/L furnished 1.34, 1.2 and 2.41 mol H(2)/mol glucose, with efficiency of glucose conversion into H(2) of 34, 30, and 60% (mol/mol), respectively. These results demonstrate that cassava processing wastewater, a highly polluting effluent, can be successfully employed as substrate for H(2) production by C acetobutylicum at lower COD concentrations. (C) 2011 Elsevier Ltd. All rights reserved.

Snakes and kittens in the grass: No evidence for preferential processing of fear-relevant animals in visual search

Ohman and colleagues provided evidence for preferential processing of pictures depicting fear-relevant animals by showing that pictures of snakes and spiders are found faster among pictures of fiowers and mushrooms than vice versa and that the speed of detecting fear-relevant animals was not affected by set size whereas the speed of detecting fiowers/mushrooms was. Experiment 1 replicated this finding. Experiment 2, however, found similar search advantages when pictures of cats and horses or of wolves and big cats were to be found among pictures of flowers and mushrooms. Moreover, Experiment 3, in a within subject comparison, failed to find faster identification of snakes and spiders than of cats and horses among flowers and mushrooms. The present findings seem to indicate that previous reports of preferential processing of pictures of snakes and spiders in a visual search task may reflect a processing advantage for animal pictures in general rather than fear-relevance.

Why fear snakes and spiders? Evidence for a learning-based account of fear-relevant stimulus-processing

Fear-relevant stimuli, such as snakes, spiders and heights, preferentially capture attention as compared to nonfear-relevant stimuli. This is said to reflect an encapsulated mechanism whereby attention is captured by the simple perceptual features of stimuli that have evolutionary significance. Research, using pictures of snakes and spiders, has found some support for this account; however, participants may have had prior fear of snakes and spiders that influenced results. The current research compared responses of snake and spider experts who had little fear of snakes and spiders, and control participants across a series of affective priming and visual search tasks. Experts discriminated between dangerous and nondangerous snakes and spiders, and expert responses to pictures of nondangerous snakes and spiders differed from those of control participants. The current results dispute that stimulus fear relevance is based purely on perceptual features, and provides support for the role of learning and experience.