156 research outputs found

    Learning to Generate Genotypes with Neural Networks

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    Neural networks and evolutionary computation have a rich intertwined history. They most commonly appear together when an evolutionary algorithm optimises the parameters and topology of a neural network for reinforcement learning problems, or when a neural network is applied as a surrogate fitness function to aid the evolutionary optimisation of expensive fitness functions. In this paper we take a different approach, asking the question of whether a neural network can be used to provide a mutation distribution for an evolutionary algorithm, and what advantages this approach may offer? Two modern neural network models are investigated, a Denoising Autoencoder modified to produce stochastic outputs and the Neural Autoregressive Distribution Estimator. Results show that the neural network approach to learning genotypes is able to solve many difficult discrete problems, such as MaxSat and HIFF, and regularly outperforms other evolutionary techniques

    A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers

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    © 2015, Springer Science+Business Media New York. Learning classifier systems (LCS) are population-based reinforcement learners that were originally designed to model various cognitive phenomena. This paper presents an explicitly cognitive LCS by using spiking neural networks as classifiers, providing each classifier with a measure of temporal dynamism. We employ a constructivist model of growth of both neurons and synaptic connections, which permits a genetic algorithm to automatically evolve sufficiently-complex neural structures. The spiking classifiers are coupled with a temporally-sensitive reinforcement learning algorithm, which allows the system to perform temporal state decomposition by appropriately rewarding “macro-actions”, created by chaining together multiple atomic actions. The combination of temporal reinforcement learning and neural information processing is shown to outperform benchmark neural classifier systems, and successfully solve a robotic navigation task

    Quantitative trait analysis of the development of pulmonary tolerance to inhaled zinc oxide in mice

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    BACKGROUND: Individuals may develop tolerance to the induction of adverse pulmonary effects following repeated exposures to inhaled toxicants. Previously, we demonstrated that genetic background plays an important role in the development of pulmonary tolerance to inhaled zinc oxide (ZnO) in inbred mouse strains, as assessed by polymorphonuclear leukocytes (PMNs), macrophages, and total protein in bronchoalveolar lavage (BAL) phenotypes. The BALB/cByJ (CBy) and DBA/2J (D2) strains were identified as tolerant and non-tolerant, respectively. The present study was designed to identify candidate genes that control the development of pulmonary tolerance to inhaled ZnO. METHODS: Genome-wide linkage analyses were performed on a CByD2F2 mouse cohort phenotyped for BAL protein, PMNs, and macrophages following 5 consecutive days of exposure to 1.0 mg/m(3 )inhaled ZnO for 3 hours/day. A haplotype analysis was carried out to determine the contribution of each quantitative trait locus (QTL) and QTL combination to the overall BAL protein phenotype. Candidate genes were identified within each QTL interval using the positional candidate gene approach. RESULTS: A significant quantitative trait locus (QTL) on chromosome 1, as well as suggestive QTLs on chromosomes 4 and 5, for the BAL protein phenotype, was established. Suggestive QTLs for the BAL PMN and macrophage phenotypes were also identified on chromosomes 1 and 5, respectively. Analysis of specific haplotypes supports the combined effect of three QTLs in the overall protein phenotype. Toll-like receptor 5 (Tlr5) was identified as an interesting candidate gene within the significant QTL for BAL protein on chromosome 1. Wild-derived Tlr5-mutant MOLF/Ei mice were tolerant to BAL protein following repeated ZnO exposure. CONCLUSION: Genetic background is an important influence in the acquisition of pulmonary tolerance to BAL protein, PMNs, and macrophages following ZnO exposure. Promising candidate genes exist within the identified QTL intervals that would be good targets for additional studies, including Tlr5. The implications of tolerance to health risks in humans are numerous, and this study furthers the understanding of gene-environment interactions that are likely to be important factors from person-to-person in regulating the development of pulmonary tolerance to inhaled toxicants

    Effects of Ionomycin on Egg Activation and Early Development in Starfish

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    Ionomycin is a Ca2+-selective ionophore that is widely used to increase intracellular Ca2+ levels in cell biology laboratories. It is also occasionally used to activate eggs in the clinics practicing in vitro fertilization. However, neither the precise molecular action of ionomycin nor its secondary effects on the eggs' structure and function is well known. In this communication we have studied the effects of ionomycin on starfish oocytes and zygotes. By use of confocal microscopy, calcium imaging, as well as light and transmission electron microscopy, we have demonstrated that immature oocytes exposed to ionomycin instantly increase intracellular Ca2+ levels and undergo structural changes in the cortex. Surprisingly, when microinjected into the cells, ionomycin produced no Ca2+ increase. The ionomycin-induced Ca2+ rise was followed by fast alteration of the actin cytoskeleton displaying conspicuous depolymerization at the oocyte surface and in microvilli with concomitant polymerization in the cytoplasm. In addition, cortical granules were disrupted or fused with white vesicles few minutes after the addition of ionomycin. These structural changes prevented cortical maturation of the eggs despite the normal progression of nuclear envelope breakdown. At fertilization, the ionomycin-pretreated eggs displayed reduced Ca2+ response, no elevation of the fertilization envelope, and the lack of orderly centripetal translocation of actin fibers. These alterations led to difficulties in cell cleavage in the monospermic zygotes and eventually to a higher rate of abnormal development. In conclusion, ionomycin has various deleterious impacts on egg activation and the subsequent embryonic development in starfish. Although direct comparison is difficult to make between our findings and the use of the ionophore in the in vitro fertilization clinics, our results call for more defining investigations on the issue of a potential risk in artificial egg activation

    Using hippocampal microRNA expression differences between mouse inbred strains to characterise miRNA function

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    Micro-RNAs (miRNAs) are short, single-stranded, noncoding RNAs that are involved in the regulation of protein-coding genes at the level of messenger RNA (mRNA). They are involved in the regulation of numerous traits, including developmental timing, apoptosis, immune function, and neuronal development. To better understand how the expression of the miRNAs themselves is regulated, we looked for miRNA expression differences among four mouse inbred strains, A/J, BALB/cJ, C57BL/6J, and DBA/2J, in one tissue, the hippocampus. A total of 166 miRNA RT-PCR assays were used to screen RNA pools for each strain. Twenty miRNA species that were markedly different between strains were further investigated using eight individual samples per strain, and 11 miRNAs showed significant differences across strains (p < 0.05). This is the first observation of miRNA expression differences across inbred mice strains. We conducted an in silico correlation analysis of the expression of these differentially expressed miRNAs with phenotype data and mRNA expression to better characterise the effects of these miRNAs on both phenotype and the regulation of mRNA expression. This approach has allowed us to nominate miRNAs that have potential roles in anxiety, exploration, and learning and memory

    The multi-peak adaptive landscape of crocodylomorph body size evolution

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    Background: Little is known about the long-term patterns of body size evolution in Crocodylomorpha, the > 200-million-year-old group that includes living crocodylians and their extinct relatives. Extant crocodylians are mostly large-bodied (3–7 m) predators. However, extinct crocodylomorphs exhibit a wider range of phenotypes, and many of the earliest taxa were much smaller ( Results: Crocodylomorphs reached an early peak in body size disparity during the Late Jurassic, and underwent an essentially continual decline since then. A multi-peak Ornstein-Uhlenbeck model outperforms all other evolutionary models fitted to our data (including both uniform and non-uniform), indicating that the macroevolutionary dynamics of crocodylomorph body size are better described within the concept of an adaptive landscape, with most body size variation emerging after shifts to new macroevolutionary regimes (analogous to adaptive zones). We did not find support for a consistent evolutionary trend towards larger sizes among lineages (i.e., Cope’s rule), or strong correlations of body size with climate. Instead, the intermediate to large body sizes of some crocodylomorphs are better explained by group-specific adaptations. In particular, the evolution of a more aquatic lifestyle (especially marine) correlates with increases in average body size, though not without exceptions. Conclusions: Shifts between macroevolutionary regimes provide a better explanation of crocodylomorph body size evolution on large phylogenetic and temporal scales, suggesting a central role for lineage-specific adaptations rather than climatic forcing. Shifts leading to larger body sizes occurred in most aquatic and semi-aquatic groups. This, combined with extinctions of groups occupying smaller body size regimes (particularly during the Late Cretaceous and Cenozoic), gave rise to the upward-shifted body size distribution of extant crocodylomorphs compared to their smaller-bodied terrestrial ancestors.</p

    A thin-slice of institutionalised police brutality: a tradition of excessive force in the Chicago Police Department

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    In the Chicago Police Department, a sustained tradition of tolerating violent conduct has contributed to the fostering of a police culture in which the use of force is celebrated. Evidence suggests that there has been a historical reluctance to take action to discipline officers accused of misconduct – many of whom are highly decorated veterans of the Chicago Police Department. It is the contention of this article that the long-standing endorsement of excessive force in Chicago policing has compromised officers’ ability to thin-slice, a psychological process in which people are able to draw on their experiences and socio-cultural context to make quick decisions under pressure. Instead, officers are instinctively drawn to engage in misconduct as a means to an end, with the confidence that their actions will not attract the sanction of their superiors

    Concentration addition, independent action and generalized concentration addition models for mixture effect prediction of sex hormone synthesis in vitro

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    Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals
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