Spatial patterns of microbial diversity and activity in an aged creosote-contaminated site

Restoration of polluted sites via in situ bioremediation relies heavily on the indigenous microbes and their activities. Spatial heterogeneity of microbial populations, contaminants and soil chemical parameters on such sites is a major hurdle in optimizing and implementing an appropriate bioremediation regime. We performed a grid-based sampling of an aged creosote-contaminated site followed by geostatistical modelling to illustrate the spatial patterns of microbial diversity and activity and to relate these patterns to the distribution of pollutants. Spatial distribution of bacterial groups unveiled patterns of niche differentiation regulated by patchy distribution of pollutants and an east-to-west pH gradient at the studied site. Proteobacteria clearly dominated in the hot spots of creosote pollution, whereas the abundance of Actinobacteria, TM7 and Planctomycetes was considerably reduced from the hot spots. The pH preferences of proteobacterial groups dominating in pollution could be recognized by examining the order and family-level responses. Acidobacterial classes came across as generalists in hydrocarbon pollution whose spatial distribution seemed to be regulated solely by the pH gradient. Although the community evenness decreased in the heavily polluted zones, basal respiration and fluorescein diacetate hydrolysis rates were higher, indicating the adaptation of specific indigenous microbial populations to hydrocarbon pollution. Combining the information from the kriged maps of microbial and soil chemistry data provided a comprehensive understanding of the long-term impacts of creosote pollution on the subsurface microbial communities. This study also highlighted the prospect of interpreting taxa-specific spatial patterns and applying them as indicators or proxies for monitoring polluted sites

A stochastic transcriptional switch model for single cell imaging data

Gene expression is made up of inherently stochastic processes within single cells and can be modeled through stochastic reaction networks (SRNs). In particular, SRNs capture the features of intrinsic variability arising from intracellular biochemical processes. We extend current models for gene expression to allow the transcriptional process within an SRN to follow a random step or switch function which may be estimated using reversible jump Markov chain Monte Carlo (MCMC). This stochastic switch model provides a generic framework to capture many different dynamic features observed in single cell gene expression. Inference for such SRNs is challenging due to the intractability of the transition densities. We derive a model-specific birth-death approximation and study its use for inference in comparison with the linear noise approximation where both approximations are considered within the unifying framework of state-space models. The methodology is applied to synthetic as well as experimental single cell imaging data measuring expression of the human prolactin gene in pituitary cells

Uncoupled dual hardening model for clays considering the effect of overconsolidation and intermediate principal stress

A constitutive model is proposed for clays based on the experimental observations from a series of flexible boundary true triaxial shear tests on cubical specimens of light to heavily overconsolidated kaolin clay. The proposed model adequately captures the combined effect of overconsolidation and intermediate principal stress. Overconsolidated clays often exhibit nonlinear stress–strain response at much lower stress levels than what is predicted by the existing constitutive theories/models. Experimental results for kaolin clay demonstrated sudden failure response before reaching the critical state, which became more prominent for higher relative magnitudes of intermediate principal stress. The observed stress state at failure is governed by the third invariant of stress tensor and the pre-failure yielding of the material by the second invariant of deviatoric stress tensor. The proposed constitutive model considers these issues with a few simplifying assumptions. The assumed yield surface has a droplet shape in q–p′ stress space with hardening based on both plastic volumetric and shear deformations. A dynamic failure criterion is employed in the current formulation that grows in size as a function of consolidation history. Pre-failure yielding is governed by a reference surface, which is different from the failure surface.by Amit Prashant and Dayakar Penumad

Working with Adult Survivor of Childhood Sexual Abuse: Creating a Safe Place, Building Strengths

Experiencing sexual abuse often creates a feeling of powerlessness in the child, leaving the child with the perception of having little control over what happens. Physiological effects of childhood sexual abuse have also been found, such as long-term dysregulation of physiological stress response systems. With the varied and unique experiences of each person, adult survivors of child sexual abuse are not a homogeneous group. There is little agreement in the literature on the best therapeutic approach for adult survivors of child sexual abuse. Individual, group and family counselling and cognitive-behavioural interventions have been found to be effective with some clients. Phase-based treatment has also been suggested, in which the initial phase focuses on establishing therapeutic alliance and stabilizing and preparing the client, before moving into more in-depth work in later phase. This chapter describes appropriate assessment and intervention with an adult survivor of childhood sexual abuse