A hierarchical Bayesian model for predicting the functional consequences of amino-acid polymorphisms

Genetic polymorphisms in deoxyribonucleic acid coding regions may have a phenotypic effect on the carrier, e.g. by influencing susceptibility to disease. Detection of deleterious mutations via association studies is hampered by the large number of candidate sites; therefore methods are needed to narrow down the search to the most promising sites. For this, a possible approach is to use structural and sequence-based information of the encoded protein to predict whether a mutation at a particular site is likely to disrupt the functionality of the protein itself. We propose a hierarchical Bayesian multivariate adaptive regression spline (BMARS) model for supervised learning in this context and assess its predictive performance by using data from mutagenesis experiments on lac repressor and lysozyme proteins. In these experiments, about 12 amino-acid substitutions were performed at each native amino-acid position and the effect on protein functionality was assessed. The training data thus consist of repeated observations at each position, which the hierarchical framework is needed to account for. The model is trained on the lac repressor data and tested on the lysozyme mutations and vice versa. In particular, we show that the hierarchical BMARS model, by allowing for the clustered nature of the data, yields lower out-of-sample misclassification rates compared with both a BMARS and a frequen-tist MARS model, a support vector machine classifier and an optimally pruned classification tree.

A genetic linkage map of microsatellite, gene-specific and morphological markers in diploid Fragaria

Diploid Fragaria provide a potential model for genomic studies in the Rosaceae. To develop a genetic linkage map of diploid Fragaria, we scored 78 markers (68 microsatellites, one sequence-characterised amplified region, six gene-specific markers and three morphological traits) in an interspecific F2 population of 94 plants generated from a cross of F.vesca f. semperflorens × F. nubicola. Co-segregation analysis arranged 76 markers into seven discrete linkage groups covering 448 cM, with linkage group sizes ranging from 100.3 cM to 22.9 cM. Marker coverage was generally good; however some clustering of markers was observed on six of the seven linkage groups. Segregation distortion was observed at a high proportion of loci (54%), which could reflect the interspecific nature of the progeny and, in some cases, the self-incompatibility of F. nubicola. Such distortion may also account for some of the marker clustering observed in the map. One of the morphological markers, pale-green leaf (pg) has not previously been mapped in Fragaria and was located to the mid-point of linkage group VI. The transferable nature of the markers used in this study means that the map will be ideal for use as a framework for additional marker incorporation aimed at enhancing and resolving map coverage of the diploid Fragaria genome. The map also provides a sound basis for linkage map transfer to the cultivated octoploid strawberry.

A pressure-jump time-resolved x-ray diffraction study of cubic-cubic transition kinetics in monoolein

In the past two decades, the geometric pathways involved in the transformations between inverse bicontinuous cubic phases in amphiphilic systems have been extensively theoretically modeled. However, little experimental data exists on the cubic-cubic transformation in pure lipid systems. We have used pressure-jump time-resolved X-ray diffraction to investigate the transition between the gyroid Q(II)(G) and double-diamond Q(II)(D) phases in mixtures of 1-monoolein in 30 wt% water. We find for this system that the cubic-cubic transition occurs without any detectable intermediate structures. In addition, we have determined the kinetics of the transition, in both the forward and reverse directions, as a function of pressure-jump amplitude, temperature, and water content. A recently developed model allows (at least in principle) the calculation of the activation energy for lipid phase transitions from such data. The analysis is applicable only if kinetic reproducibility is achieved, at least within one sample, and achievement of such kinetic reproducibility is shown here, by carrying out prolonged pressure-cycling. The rate of transformation shows clear and consistent trends with pressure-jump amplitude, temperature, and water content, all of which are shown to be in agreement with the effect of the shift in the position of the cubic-cubic phase boundary following a change in the thermodynamic parameters.

Key performance indicators (KPIs) and priority setting in using the multi-attribute approach for assessing sustainable intelligent buildings

The main objectives of this paper are to: firstly, identify key issues related to sustainable intelligent buildings (environmental, social, economic and technological factors); develop a conceptual model for the selection of the appropriate KPIs; secondly, test critically stakeholder's perceptions and values of selected KPIs intelligent buildings; and thirdly develop a new model for measuring the level of sustainability for sustainable intelligent buildings. This paper uses a consensus-based model (Sustainable Built Environment Tool- SuBETool), which is analysed using the analytical hierarchical process (AHP) for multi-criteria decision-making. The use of the multi-attribute model for priority setting in the sustainability assessment of intelligent buildings is introduced. The paper commences by reviewing the literature on sustainable intelligent buildings research and presents a pilot-study investigating the problems of complexity and subjectivity. This study is based upon a survey perceptions held by selected stakeholders and the value they attribute to selected KPIs. It is argued that the benefit of the new proposed model (SuBETool) is a ‘tool’ for ‘comparative’ rather than an absolute measurement. It has the potential to provide useful lessons from current sustainability assessment methods for strategic future of sustainable intelligent buildings in order to improve a building's performance and to deliver objective outcomes. Findings of this survey enrich the field of intelligent buildings in two ways. Firstly, it gives a detailed insight into the selection of sustainable building indicators, as well as their degree of importance. Secondly, it tesst critically stakeholder's perceptions and values of selected KPIs intelligent buildings. It is concluded that the priority levels for selected criteria is largely dependent on the integrated design team, which includes the client, architects, engineers and facilities managers.

Knowledge communication and translation- A knowledge transfer model

Purpose – The purpose of this paper is to propose a process model for knowledge transfer in using theories relating knowledge communication and knowledge translation. Design/methodology/approach – Most of what is put forward in this paper is based on a research project titled “Procurement for innovation and knowledge transfer (ProFIK)”. The project is funded by a UK government research council – The Engineering and Physical Sciences Research Council (EPSRC). The discussions are mainly grounded on a thorough review of literature accomplished as part of the research project. Findings – The process model developed in this paper has built upon the theory of knowledge transfer and the theory of communication. Knowledge transfer, per se, is not a mere transfer of knowledge. It involves different stages of knowledge transformation. Depending on the context of knowledge transfer, it can also be influenced by many factors; some positive and some negative. The developed model of knowledge transfer attempts to encapsulate all these issues in order to create a holistic framework. Originality/value of paper – An attempt has been made in the paper to combine some of the significant theories or findings relating to knowledge transfer together, making the paper an original and valuable one.

Qualitative modelling of sustainable energy scenarios: An application and extension of the Bon Qualitative Input-Output model

Climate change is one of the major challenges facing economic systems at the start of the 21st century. Reducing greenhouse gas emissions will require both restructuring the energy supply system (production) and addressing the efficiency and sufficiency of the social uses of energy (consumption). The energy production system is a complicated supply network of interlinked sectors with 'knock-on' effects throughout the economy. End use energy consumption is governed by complex sets of interdependent cultural, social, psychological and economic variables driven by shifts in consumer preference and technological development trajectories. To date, few models have been developed for exploring alternative joint energy production-consumption systems. The aim of this work is to propose one such model. This is achieved in a methodologically coherent manner through integration of qualitative input-output models of production, with Bayesian belief network models of consumption, at point of final demand. The resulting integrated framework can be applied either (relatively) quickly and qualitatively to explore alternative energy scenarios, or as a fully developed quantitative model to derive or assess specific energy policy options. The qualitative applications are explored here.

A novel repair model for imperfect maintenance

The basic repair rate models for repairable systems may be homogeneous Poisson processes, renewal processes or nonhomogeneous Poisson processes. In addition to these models, geometric processes are studied occasionally. Geometric processes, however, can only model systems with monotonously changing (increasing, decreasing or constant) failure intensity. This paper deals with the reliability modelling of the failure process of repairable systems when the failure intensity shows a bathtub type non-monotonic behaviour. A new stochastic process, an extended Poisson process, is introduced. Reliability indices and parameter estimation are presented. A comparison of this model with other repair models based on a dataset is made.

Predicting the thermal inactivation of bacteria in a solid matrix: simulation studies on the relative effects of microbial thermal resistance parameters and process conditions

A combined mathematical model for predicting heat penetration and microbial inactivation in a solid body heated by conduction was tested experimentally by inoculating agar cylinders with Salmonella typhimurium or Enterococcus faecium and heating in a water bath. Regions of growth where bacteria had survived after heating were measured by image analysis and compared with model predictions. Visualisation of the regions of growth was improved by incorporating chromogenic metabolic indicators into the agar. Preliminary tests established that the model performed satisfactorily with both test organisms and with cylinders of different diameter. The model was then used in simulation studies in which the parameters D, z, inoculum size, cylinder diameter and heating temperature were systematically varied. These simulations showed that the biological variables D, z and inoculum size had a relatively small effect on the time needed to eliminate bacteria at the cylinder axis in comparison with the physical variables heating temperature and cylinder diameter, which had a much greater relative effect. (c) 2005 Elsevier B.V All rights reserved.

Gut fermentation products of insulin-derived prebiotics beneficially modulate markers of tumour progression in human colon tumour cells

Insulin is a prebiotic food ingredient, which suppresses colon tumour growth and development in rats. In the gut lumen, it is fermented to lactic acid and short chain fatty acids (SCFA). Of these, butyrate has suppressing agent activities, but little is known concerning cellular responses to complex fermentation samples. To investigate the effects of fermentation products of insulin on cellular responses related to colon carcinogenesis. Fermentations were performed in anaerobic batch cultures or in a three-stage fermentation model that simulates conditions in colon-segments (proximal, transverse, distal). Substrate was insulin enriched with oligofructose (Raftilose® Synergy1), fermented with probiotics (Bifidobacterium lactis Bb12, Lactobacillus rhamnosus GG), and/or faecal inocula. HT29 or CaCo-2 cells were incubated with supernatants of the fermented samples (2.5%-25% v/v, 24-72 hours). Cellular parameters of survival, differentiation, tumour progression, and invasive growth were determined. Fermentation supernatants derived from probiotics and Synergy1 were more effective than with glucose. The additional fermentation with faecal slurries produced supernatants with lower toxicity, higher SCFA contents, and distinct cellular functions. The supernatant derived from the gut model vessel representing the distal colon, was most effective for all parameters, probably on account of higher butyrate-concentrations. Biological effects of insulin upon colon cells may be mediated not only by growth stimulation of the lactic acid-producing bacteria and/or production of butyrate, but also by other bacteria and products of the gut lumen. These newly reported properties of the supernatants to inhibit growth and metastases in colon tumour cells are important mechanisms of tumour suppression.

Liposomes and skin: From drug delivery to model membranes

The early eighties saw the introduction of liposomes as skin drug delivery systems, initially promoted primarily for localised effects with minimal systemic delivery. Subsequently, a novel ultradeformable vesicular system (termed "Transfersomes" by the inventors) was reported for transdermal delivery with an efficiency similar to subcutaneous injection. Further research illustrated that the mechanisms of liposome action depended on the application regime and the vesicle composition and morphology. Ethical, health and supply problems with human skin have encouraged researchers to use skin models. 'IYaditional models involved polymer membranes and animal tissue, but whilst of value for release studies, such models are not always good mimics for the complex human skin barrier, particularly with respect to the stratum corneal intercellular lipid domains. These lipids have a multiply bilayered organization, a composition and organization somewhat similar to liposomes, Consequently researchers have used vesicles as skin model membranes. Early work first employed phospholipid liposomes and tested their interactions with skin penetration enhancers, typically using thermal analysis and spectroscopic analyses. Another approach probed how incorporation of compounds into liposomes led to the loss of entrapped markers, analogous to "fluidization" of stratum corneum lipids on treatment with a penetration enhancer. Subsequently scientists employed liposomes formulated with skin lipids in these types of studies. Following a brief description of the nature of the skin barrier to transdermal drug delivery and the use of liposomes in drug delivery through skin, this article critically reviews the relevance of using different types of vesicles as a model for human skin in permeation enhancement studies, concentrating primarily on liposomes after briefly surveying older models. The validity of different types of liposome is considered and traditional skin models are compared to vesicular model membranes for their precision and accuracy as skin membrane mimics. (c) 2008 Elsevier B.V. All rights reserved.

Humans ignore motion and stereo cues in favor of a fictional stable world

As we move through the world, our eyes acquire a sequence of images. The information from this sequence is sufficient to determine the structure of a three-dimensional scene, up to a scale factor determined by the distance that the eyes have moved [1, 2]. Previous evidence shows that the human visual system accounts for the distance the observer has walked [3,4] and the separation of the eyes [5-8] when judging the scale, shape, and distance of objects. However, in an immersive virtual-reality environment, observers failed to notice when a scene expanded or contracted, despite having consistent information about scale from both distance walked and binocular vision. This failure led to large errors in judging the size of objects. The pattern of errors cannot be explained by assuming a visual reconstruction of the scene with an incorrect estimate of interocular separation or distance walked. Instead, it is consistent with a Bayesian model of cue integration in which the efficacy of motion and disparity cues is greater at near viewing distances. Our results imply that observers are more willing to adjust their estimate of interocular separation or distance walked than to accept that the scene has changed in size.

An instructional design model for constructivist learning

The emergent requirements for effective e-learning calls for a paradigm shift for instructional design. Constructivist theory and semiotics offer a sound underpinning to enable such revolutionary change by employing the concepts of Learning Objects. E-learning guidelines adopted by the industry have led successfully to the development of training materials. Inadequacy and deficiency of those methods for Higher Education have been identified in this paper. Based on the best practice in industry and our empirical research, we present an instructional design model with practical templates for constructivist learning.