Interaction of metal salts with cytoskeletal motor protein systems

Interactions of chemicals with the microtubular network of cells may lead to genotoxicity. Micronuclei (MN) might be caused by interaction of metals with tubulin and/or kinesin. The genotoxic effects of inorganic lead and mercury salts were studied using the MN assay and the CREST analysis in V79 Chinese hamster fibroblasts. Effects on the functional activity of motor protein systems were examined by measurement of tubulin assembly and kinesin-driven motility. Lead and mercury salts induced MN dose-dependently. The no-effect-concentration for MN induction was 1.1 μM PbCl2, 0.05 μM Pb(OAc)2 and 0.01 μM HgCl2. The in vitro results obtained for PbCl2 correspond to reported MN induction in workers occupationally exposed to lead, starting at 1.2 μM Hg(II) (Vaglenov et al., 2001, Environ. Health Perspect. 109, 295-298). The CREST Analysis indicate aneugenic effects of Pb(II) and aneugenic and additionally clastogenic effects of Hg(II). Lead (chloride, acetate, and nitrate) and mercury (chloride and nitrate) interfered dose-dependently with tubulin assembly in vitro. The no-effect-concentration for lead salts in this assay was 10 μM. Inhibition of tubulin assembly by mercury started at 2 μM. The gliding velocity of microtubules along immobilised kinesin molecules was affected by 25 μM Pb(NO3)2 and 0.1 μM HgCl2 in a dose-dependent manner. Our data support the hypothesis that lead and mercury genotoxicity may result, at least in part, via disturbance of chromosome segregation via interaction with cytoskeletal proteins.

Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets

Analytically or computationally intractable likelihood functions can arise in complex statistical inferential problems making them inaccessible to standard Bayesian inferential methods. Approximate Bayesian computation (ABC) methods address such inferential problems by replacing direct likelihood evaluations with repeated sampling from the model. ABC methods have been predominantly applied to parameter estimation problems and less to model choice problems due to the added difficulty of handling multiple model spaces. The ABC algorithm proposed here addresses model choice problems by extending Fearnhead and Prangle (2012, Journal of the Royal Statistical Society, Series B 74, 1–28) where the posterior mean of the model parameters estimated through regression formed the summary statistics used in the discrepancy measure. An additional stepwise multinomial logistic regression is performed on the model indicator variable in the regression step and the estimated model probabilities are incorporated into the set of summary statistics for model choice purposes. A reversible jump Markov chain Monte Carlo step is also included in the algorithm to increase model diversity for thorough exploration of the model space. This algorithm was applied to a validating example to demonstrate the robustness of the algorithm across a wide range of true model probabilities. Its subsequent use in three pathogen transmission examples of varying complexity illustrates the utility of the algorithm in inferring preference of particular transmission models for the pathogens.

Observing the mother-infant feeding interaction

Early parenting is critical to effective attachment and a range of positive developmental outcomes for children. Feeding is a key task of early parenting and increasing evidence indicates that early feeding practices are important for the development of self-regulation of intake and food preferences which in turn are predictors of later obesity risk. However, relatively little is known about the mother-infant interaction at the transition to solids among typically developing children. This study aimed to describe parenting strategies used by mothers at the transition from milk feeding to solid food. Twenty mother-infant dyads were video-taped during a feeding interaction and data was analysed to describe maternal use of parenting strategies. It was predicted that positive feeding strategies would be correlated with lower levels of Infant Food Refusal (IFR), higher maternal sensitivity, and better overall parenting scores. The opposite was predicted for negative feeding strategies. It was found that positive strategy use and general parenting scores were significantly correlated in the predicted direction, however maternal instruction, aversive contact and ineffective strategy use were significantly correlated with and predictive of IFR. Additionally, it was hypothesised that maternal strategy use would deteriorate towards the end of the interaction, and this hypothesis was partially supported: significantly more negative strategy use was observed in the last third of the interaction, whilst positive strategy use remained consistent through the feeding interaction. The findings have important implications for early feeding parent education and intervention programs.

The plasticity of NBS resistance genes in sorghum is driven by multiple evolutionary processes

Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.

Spatially varying ground motion effects on seismic response of adjacent structures considering soil-structure interaction

Spatial variation of seismic ground motions is caused by incoherence effect, wave passage, and local site conditions. This study focuses on the effects of spatial variation of earthquake ground motion on the responses of adjacent reinforced concrete (RC) frame structures. The adjacent buildings are modeled considering soil-structure interaction (SSI) so that the buildings can be interacted with each other under uniform and non-uniform ground motions. Three different site classes are used to model the soil layers of SSI system. Based on fast Fourier transformation (FFT), spatially correlated non-uniform ground motions are generated compatible with known power spectrum density function (PSDF) at different locations. Numerical analyses are carried out to investigate the displacement responses and the absolute maximum base shear forces of adjacent structures subjected to spatially varying ground motions. The results are presented in terms of related parameters affecting the structural response using three different types of soil site classes. The responses of adjacent structures have changed remarkably due to spatial variation of ground motions. The effect can be significant on rock site rather than clay site.

Plant diversity predicts beta but not alpha diversity of soil microbes across grasslands worldwide

Aboveground–belowground interactions exert critical controls on the composition and function of terrestrial ecosystems, yet the fundamental relationships between plant diversity and soil microbial diversity remain elusive. Theory predicts predominantly positive associations but tests within single sites have shown variable relationships, and associations between plant and microbial diversity across broad spatial scales remain largely unexplored. We compared the diversity of plant, bacterial, archaeal and fungal communities in one hundred and forty-five 1 m2 plots across 25 temperate grassland sites from four continents. Across sites, the plant alpha diversity patterns were poorly related to those observed for any soil microbial group. However, plant beta diversity (compositional dissimilarity between sites) was significantly correlated with the beta diversity of bacterial and fungal communities, even after controlling for environmental factors. Thus, across a global range of temperate grasslands, plant diversity can predict patterns in the composition of soil microbial communities, but not patterns in alpha diversity.

The co-transcriptome of uropathogenic Escherichia coli-infected mouse macrophages reveals new insights into host-pathogen interactions

Urinary tract infections (UTI) are among the most common infections in humans. Uropathogenic Escherichia coli (UPEC) can invade and replicate within bladder epithelial cells, and some UPEC strains can also survive within macrophages. To understand the UPEC transcriptional program associated with intramacrophage survival, we performed host–pathogen co-transcriptome analyses using RNA sequencing. Mouse bone marrow-derived macrophages (BMMs) were challenged over a 24 h time course with two UPEC reference strains that possess contrasting intramacrophage phenotypes: UTI89, which survives in BMMs, and 83972, which is killed by BMMs. Neither of these strains caused significant BMM cell death at the low multiplicity of infection that was used in this study. We developed an effective computational framework that simultaneously separated, annotated, and quantified the mammalian and bacterial transcriptomes. BMMs responded to the two UPEC strains with a broadly similar gene expression program. In contrast, the transcriptional responses of the UPEC strains diverged markedly from each other. We identified UTI89 genes upregulated at 24 h post-infection, and hypothesized that some may contribute to intramacrophage survival. Indeed, we showed that deletion of one such gene (pspA) significantly reduced UTI89 survival within BMMs. Our study provides a technological framework for simultaneously capturing global changes at the transcriptional level in co-cultures, and has generated new insights into the mechanisms that UPEC use to persist within the intramacrophage environment.

Soil–pile interaction of pile embedded in deep-layered marine sediment under seismic excitation

This paper investigates the soil–pile interaction of a pile embedded in a deep multi-layered soil under seismic excitation considering both kinematic and inertial interaction effects. A comprehensive three-dimensional finite element model is developed and validated using existing results in the literature. The response of the pile in the deep multi-layered soil profile is investigated with respect to pile head response, deflection modes and maximum deflections along the pile. Results show that the pile exhibits complex deflection patterns and that the pile response is influenced by the properties of both the soil profile and the seismic excitation. It is also evident that kinematic interaction effects have a greater influence on the pile response than the inertial interaction effects.

A Likelihood-Maximizing Framework for Enhanced In-Car Speech Recognition Based on Speech Dialog System Interaction

Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating noncritical in-car systems. Under such conditions, however, speech recognition accuracy degrades significantly, and techniques such as speech enhancement are required to improve these accuracies. Likelihood-maximizing (LIMA) frameworks optimize speech enhancement algorithms based on recognized state sequences rather than traditional signal-level criteria such as maximizing signal-to-noise ratio. LIMA frameworks typically require calibration utterances to generate optimized enhancement parameters that are used for all subsequent utterances. Under such a scheme, suboptimal recognition performance occurs in noise conditions that are significantly different from that present during the calibration session – a serious problem in rapidly changing noise environments out on the open road. In this chapter, we propose a dialog-based design that allows regular optimization iterations in order to track the ever-changing noise conditions. Experiments using Mel-filterbank noise subtraction (MFNS) are performed to determine the optimization requirements for vehicular environments and show that minimal optimization is required to improve speech recognition, avoid over-optimization, and ultimately assist with semireal-time operation. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session only.

Denhaminols A–H, dihydro-β-agarofurans from the endemic Australian rainforest plant Denhamia celastroides

Eight new dihydro-β-agarofurans, denhaminols A–H (1–8), were isolated from the leaves of the Australian rainforest tree Denhamia celastroides. The chemical structures of 1–8 were elucidated following analysis of 1D/2D NMR and MS data. The absolute configuration of denhaminol A (1) was determined by single-crystal X-ray crystallography. All compounds were evaluated for cytotoxic activity against the human prostate cancer cell line LNCaP, using live-cell imaging and metabolic assays. Denhaminols A (1) and G (7) were also tested for their effects on the lipid content of LNCaP cells. This is the first report of secondary metabolites from D. celastroides.

Interaction of erythrocyte eicosapentaenoic acid and physical activity predicts reduced risk of mild cognitive impairment

Objectives To evaluate relationships between self-reported physical activity, proportions of long-chain omega-3 polyunsaturated fatty acids (LCn3) in erythrocyte content (percentage of total fatty acids) and risk of mild cognitive impairment (MCI) in older adults. Method A cross-sectional study was conducted. Community-dwelling male and female (n = 84) participants over the age of 65 years with and without MCI were tested for erythrocyte proportions of the LCn3s eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Physical activity was measured using a validated questionnaire. Results The interaction between erythrocyte EPA, but not DHA, and increased physical activity was associated with increased odds of a non-MCI classification. Conclusion An interaction between physical activity and erythrocyte EPA content (percentage of fatty acids) significantly predicted MCI status in older adults. Randomised control trials are needed to examine the potential for supplementation with EPA in combination with increased physical activity to mitigate the risk of MCI in ageing adults.