A parallel genetic algorithm for the Steiner Problem in Networks

This paper presents a parallel genetic algorithm to the Steiner Problem in Networks. Several previous papers have proposed the adoption of GAs and others metaheuristics to solve the SPN demonstrating the validity of their approaches. This work differs from them for two main reasons: the dimension and the characteristics of the networks adopted in the experiments and the aim from which it has been originated. The reason that aimed this work was namely to build a comparison term for validating deterministic and computationally inexpensive algorithms which can be used in practical engineering applications, such as the multicast transmission in the Internet. On the other hand, the large dimensions of our sample networks require the adoption of a parallel implementation of the Steiner GA, which is able to deal with such large problem instances.

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.

Restrictions to the adaptation of influenza A virus H5 hemagglutinin to the human host

The binding specificities of a panel of avian influenza virus subtype H5 hemagglutinin (RA) proteins bearing mutations at key residues in the receptor binding site were investigated. The results demonstrate that two simultaneous mutations in the receptor binding site resulted in H5 RA binding in a pattern similar to that shown by human viruses. Coexpression of the ion channel protein, M2, from most avian and human strains tested protected H5 RA conformation during trafficking, indicating that no genetic barrier to the reassortment of the H5 surface antigen gene with internal genes of human viruses existed at this level.

Dietary fat composition and cardiovascular disease

Cardiovascular disease (CVD), which includes coronary heart disease and stroke, remains the major killer in the EU, being responsible for 42% of total mortality. The amount and composition of dietary fat is arguably the most important dietary factor contributing to disease risk. A significant body of consistent evidence indicates that a decrease in dietary saturated fat:unsaturated (polyunsaturated + monounsaturated) ratio and an increased intake of long-chain n-3 polyunsaturated fatty acids (LC n-3 PUFA) found in fish, is cardioprotective. Furthermore, although the evidence is currently less convincing, such a strategy is also likely to improve insulin sensitivity, the central metabolic defect in diabetes. Currently in the UK only 12% of men, 17% of women and 8% of children have an SFA intakes <10% of energy. The average intake of LC n-3 PUFA is <0.2 g/day, which is less than half the current conservative recommendation of a minimum of 0.45 g/day. Public health strategies to reverse these dietary fatty acid imbalances, aimed at educating and motivating the consumer and making affordable and acceptable food products with an ‘enhanced’ fatty acid profile more widely available, must remain a public health priority in the ‘fight’ against CVD.

Comparative genome analysis provides insights into the evolution and adaptation of Pseudomonas syringae pv. aesculi on Aesculus hippocastanum.

A recently emerging bleeding canker disease, caused by Pseudomonas syringae pathovar aesculi (Pae), is threatening European horse chestnut in northwest Europe. Very little is known about the origin and biology of this new disease. We used the nucleotide sequences of seven commonly used marker genes to investigate the phylogeny of three strains isolated recently from bleeding stem cankers on European horse chestnut in Britain (E-Pae). On the basis of these sequences alone, the E-Pae strains were identical to the Pae type-strain (I-Pae), isolated from leaf spots on Indian horse chestnut in India in 1969. The phylogenetic analyses also showed that Pae belongs to a distinct clade of P. syringae pathovars adapted to woody hosts. We generated genome-wide Illumina sequence data from the three E-Pae strains and one strain of I-Pae. Comparative genomic analyses revealed pathovar-specific genomic regions in Pae potentially implicated in virulence on a tree host, including genes for the catabolism of plant-derived aromatic compounds and enterobactin synthesis. Several gene clusters displayed intra-pathovar variation, including those encoding type IV secretion, a novel fatty acid biosynthesis pathway and a sucrose uptake pathway. Rates of single nucleotide polymorphisms in the four Pae genomes indicate that the three E-Pae strains diverged from each other much more recently than they diverged from I-Pae. The very low genetic diversity among the three geographically distinct E-Pae strains suggests that they originate from a single, recent introduction into Britain, thus highlighting the serious environmental risks posed by the spread of an exotic plant pathogenic bacterium to a new geographic location. The genomic regions in Pae that are absent from other P. syringae pathovars that infect herbaceous hosts may represent candidate genetic adaptations to infection of the woody parts of the tree.

Genetic least squares for system identification

The recursive least-squares algorithm with a forgetting factor has been extensively applied and studied for the on-line parameter estimation of linear dynamic systems. This paper explores the use of genetic algorithms to improve the performance of the recursive least-squares algorithm in the parameter estimation of time-varying systems. Simulation results show that the hybrid recursive algorithm (GARLS), combining recursive least-squares with genetic algorithms, can achieve better results than the standard recursive least-squares algorithm using only a forgetting factor.

Variable selection for financial distress classification using a genetic algorithm

This paper is concerned with the use of a genetic algorithm to select financial ratios for corporate distress classification models. For this purpose, the fitness value associated to a set of ratios is made to reflect the requirements of maximizing the amount of information available for the model and minimizing the collinearity between the model inputs. A case study involving 60 failed and continuing British firms in the period 1997-2000 is used for illustration. The classification model based on ratios selected by the genetic algorithm compares favorably with a model employing ratios usually found in the financial distress literature.

Genetic algorithms for optimal control of beer fermentation

This paper uses genetic algorithms to optimise the mathematical model of a beer fermentation process that operates in batch mode. The optimisation is based in adjusting the temperature profile of the mixture during a fixed period of time in order to reach the required ethanol levels but considering certain operational and quality restrictions.

An insight into the public acceptance of nutrigenomic-based personalised nutrition.

It is predicted that non-communicable diseases will account for over 73 % of global mortality in 2020. Given that the majority of these deaths occur in developed countries such as the UK, and that up to 80 % of chronic disease could be prevented through improvements in diet and lifestyle, it is imperative that dietary guidelines and disease prevention strategies are reviewed in order to improve their efficacy. Since the completion of the human genome project our understanding of complex interactions between environmental factors such as diet and genes has progressed considerably, as has the potential to individualise diets using dietary, phenotypic and genotypic data. Thus, there is an ambition for dietary interventions to move away from population-based guidance towards 'personalised nutrition'. The present paper reviews current evidence for the public acceptance of genetic testing and personalised nutrition in disease prevention. Health and clear consumer benefits have been identified as key motivators in the uptake of genetic testing, with individuals reporting personal experience of disease, such as those with specific symptoms, being more willing to undergo genetic testing for the purpose of personalised nutrition. This greater perceived susceptibility to disease may also improve motivation to change behaviour which is a key barrier in the success of any nutrition intervention. Several consumer concerns have been identified in the literature which should be addressed before the introduction of a nutrigenomic-based personalised nutrition service. Future research should focus on the efficacy and implementation of nutrigenomic-based personalised nutrition.

Inhibition of LRRK2 kinase activity stimulates macroautophagy

Leucine Rich Repeat Kinase 2 (LRRK2) is one of the most important genetic contributors to Parkinson's disease. LRRK2 has been implicated in a number of cellular processes, including macroautophagy. To test whether LRRK2 has a role in regulating autophagy, a specific inhibitor of the kinase activity of LRRK2 was applied to human neuroglioma cells and downstream readouts of autophagy examined. The resulting data demonstrate that inhibition of LRRK2 kinase activity stimulates macroautophagy in the absence of any alteration in the translational targets of mTORC1, suggesting that LRRK2 regulates autophagic vesicle formation independent of canonical mTORC1 signaling. This study represents the first pharmacological dissection of the role LRRK2 plays in the autophagy/lysosomal pathway, emphasizing the importance of this pathway as a marker for LRRK2 physiological function. Moreover it highlights the need to dissect autophagy and lysosomal activities in the context of LRRK2 related pathologies with the final aim of understanding their aetiology and identifying specific target for disease modifying therapies in patients.

Dietary patterns and cardiovascular disease

Despite strong prospective epidemiology and mechanistic evidence for the benefits of certain micronutrients in preventing CVD, neutral and negative outcomes from secondary intervention trials have undermined the efficacy of supplemental nutrition in preventing CVD. In contrast, evidence for the positive impact of specific diets in CVD prevention, such as the Dietary Approaches to Stop Hypertension (DASH) diet, has focused attention on the potential benefits of whole diets and specific dietary patterns. These patterns have been scored on the basis of current guidelines for the prevention of CVD, to provide a quantitative evaluation of the relationship between diet and disease. Using this approach, large prospective studies have reported reductions in CVD risk ranging from 10 to 60% in groups whose diets can be variously classified as 'Healthy', 'Prudent', Mediterranean' or 'DASH compliant'. Evaluation of the relationship between dietary score and risk biomarkers has also been informative with respect to underlying mechanisms. However, although this analysis may appear to validate whole-diet approaches to disease prevention, it must be remembered that the classification of dietary scores is based on current understanding of diet-disease relationships, which may be incomplete or erroneous. Of particular concern is the limited number of high-quality intervention studies of whole diets, which include disease endpoints as the primary outcome. The aims of this review are to highlight the limitations of dietary guidelines based on nutrient-specific data, and the persuasive evidence for the benefits of whole dietary patterns on CVD risk. It also makes a plea for more randomised controlled trials, which are designed to support food and whole dietary-based approaches for preventing CVD.

Natural genetic variation in caesium (Cs) accumulation by Arabidopsis thaliana

Ingestion of caesium (Cs) radioisotopes poses a health risk to humans. Crop varieties that accumulate less Cs in their edible tissues may provide a useful countermeasure. This study was performed to determine whether quantitative genetics on a model plant (Arabidopsis thaliana) might inform such 'safe'-crop strategies. Arabidopsis accessions and recombinant inbred lines (RILs), from Landsberg erecta (Ler) x Cape Verdi Island (Cvi), Ler x Columbia (Col), and Niederzenz (Nd) x Col mapping populations, were grown on agar supplemented with subtoxic levels of Cs. Shoot Cs concentration varied up to three-fold, and shoot f. wt varied up to 25-fold within populations. The heritability of growth and Cs accumulation traits ranged from 0.06 to 0.28. Four quantitative trait loci (QTL) accounted for > 80 of the genetic contribution to the total phenotypic variation in shoot Cs concentration in the Ler x Col population. QTL identified in this study, in particular, QTL co-localizing to the top and bottom regions of Chromosomes I and V in two different mapping populations, are amenable to positional cloning and, through collinearity, may inform selection or breeding strategies for the development of 'safe' crops.

The aluminium content of breast tissue taken from women with breast cancer

The aetiology of breast cancer is multifactorial. While there are known genetic predispositions to the disease it is probable that environmental factors are also involved. Recent research has demonstrated a regionally specific distribution of aluminium in breast tissue mastectomies while other work has suggested mechanisms whereby breast tissue aluminium might contribute towards the aetiology of breast cancer. We have looked to develop microwave digestion combined with a new form of graphite furnace atomic absorption spectrometry as a precise, accurate and reproducible method for the measurement of aluminium in breast tissue biopsies. We have used this method to test the thesis that there is a regional distribution of aluminium across the breast in women with breast cancer. Microwave digestion of whole breast tissue samples resulted in clear homogenous digests perfectly suitable for the determination of aluminium by graphite furnace atomic absorption spectrometry. The instrument detection limit for the method was 0.48 μg/L. Method blanks were used to estimate background levels of contamination of 14.80 μg/L. The mean concentration of aluminium across all tissues was 0.39 μg Al/g tissue dry wt. There were no statistically significant regionally specific differences in the content of aluminium. We have developed a robust method for the precise and accurate measurement of aluminium in human breast tissue. There are very few such data currently available in the scientific literature and they will add substantially to our understanding of any putative role of aluminium in breast cancer. While we did not observe any statistically significant differences in aluminium content across the breast it has to be emphasised that herein we measured whole breast tissue and not defatted tissue where such a distribution was previously noted. We are very confident that the method developed herein could now be used to provide accurate and reproducible data on the aluminium content in defatted tissue and oil from such tissues and thereby contribute towards our knowledge on aluminium and any role in breast cancer.

Language in genetic syndromes and cognitive modularity

In recent years, research into the impact of genetic abnormalities on cognitive development, including language, has become recognized for its potential to make valuable contributions to our understanding of the brain–behaviour relationships underlying language acquisition as well as to understanding the cognitive architecture of the human mind. The publication of Fodor’s ( 1983 ) book The Modularity of Mind has had a profound impact on the study of language and the cognitive architecture of the human mind. Its central claim is that many of the processes involved in comprehension are undertaken by special brain systems termed ‘modules’. This domain specificity of language or modularity has become a fundamental feature that differentiates competing theories and accounts of language acquisition (Fodor 1983 , 1985 ; Levy 1994 ; Karmiloff-Smith 1998 ). However, although the fact that the adult brain is modularized is hardly disputed, there are different views of how brain regions become specialized for specific functions. A question of some interest to theorists is whether the human brain is modularized from the outset (nativist view) or whether these distinct brain regions develop as a result of biological maturation and environmental input (neuroconstructivist view). One source of insight into these issues has been the study of developmental disorders, and in particular genetic syndromes, such as Williams syndrome (WS) and Down syndrome (DS). Because of their uneven profiles characterized by dissociations of different cognitive skills, these syndromes can help us address theoretically significant questions. Investigations into the linguistic and cognitive profiles of individuals with these genetic abnormalities have been used as evidence to advance theoretical views about innate modularity and the cognitive architecture of the human mind. The present chapter will be organized as follows. To begin, two different theoretical proposals in the modularity debate will be presented. Then studies of linguistic abilities in WS and in DS will be reviewed. Here, the emphasis will be mainly on WS due to the fact that theoretical debates have focused primarily on WS, there is a larger body of literature on WS, and DS subjects have typically been used for the purposes of comparison. Finally, the modularity debate will be revisited in light of the literature review of both WS and DS. Conclusions will be drawn regarding the contribution of these two genetic syndromes to the issue of cognitive modularity, and in particular innate modularity.

Cognitive and environmental factors influencing the process of spatial knowledge acquisition within virtual reality environments

As the fidelity of virtual environments (VE) continues to increase, the possibility of using them as training platforms is becoming increasingly realistic for a variety of application domains, including military and emergency personnel training. In the past, there was much debate on whether the acquisition and subsequent transfer of spatial knowledge from VEs to the real world is possible, or whether the differences in medium during training would essentially be an obstacle to truly learning geometric space. In this paper, the authors present various cognitive and environmental factors that not only contribute to this process, but also interact with each other to a certain degree, leading to a variable exposure time requirement in order for the process of spatial knowledge acquisition (SKA) to occur. The cognitive factors that the authors discuss include a variety of individual user differences such as: knowledge and experience; cognitive gender differences; aptitude and spatial orientation skill; and finally, cognitive styles. Environmental factors discussed include: Size, Spatial layout complexity and landmark distribution. It may seem obvious that since every individual's brain is unique - not only through experience, but also through genetic predisposition that a one size fits all approach to training would be illogical. Furthermore, considering that various cognitive differences may further emerge when a certain stimulus is present (e.g. complex environmental space), it would make even more sense to understand how these factors can impact spatial memory, and to try to adapt the training session by providing visual/auditory cues as well as by changing the exposure time requirements for each individual. The impact of this research domain is important to VE training in general, however within service and military domains, guaranteeing appropriate spatial training is critical in order to ensure that disorientation does not occur in a life or death scenario.