Visualising the subcellular distribution of antibiotics against tuberculosis

Tuberculosis (TB), caused by the intracellular pathogen Mycobacterium tuberculosis (Mtb), remains the world’s deadliest infectious disease. Although treatable, effective chemotherapy requires at least six months of treatment with a minimum of four antibiotics. Novel antibiotics are needed to quell the pandemic. However, we do not fully understand why current treatments take so long to work in patients. Mtb has a dynamic intracellular lifestyle, and this thesis tests the hypothesis that not all antibiotics penetrate into, or are effective within, all compartments containing Mtb during infection. Our understanding of the intracellular pharmacokinetics of drugs against TB has been limited by a lack of technologies for studying the subcellular distribution of antibiotics. This work developed a correlative imaging workflow incorporating fluorescence, electron and nanoscale ion microscopy (CLEIM) to map the subcellular distribution of two antibiotics, bedaquiline (BDQ) and pyrazinamide (PZA), at sub-micrometre resolution in Mtb-infected human macrophages. This workflow was complemented with orthogonal methods, including high-content live-cell imaging, to study the dynamic processes that contribute to antibiotic activity. BDQ accumulated primarily in host cell lipid droplets (LD), but heterogeneously in Mtb within a variety of intracellular compartments. Surprisingly, LD did not sequester the antibiotic but constituted a transferable reservoir that enhanced antibacterial efficacy. Lipid binding therefore facilitated drug trafficking by host organelles to an intracellular target. PZA is a pro-drug, and the accumulation of its active metabolite pyrazinoic acid has been hypothesised to depend on the bacteria being in an acidic environment. Direct analysis of antibiotic accumulation by ion microscopy, combined with live-cell imaging at the single cell level, revealed that, whilst acidic intracellular environments support PZA activity, they are not necessary for antibiotic efficacy. Many intracellular pathogens interact with LD or reside in partially acidified vacuoles, and these results therefore have broad implications for our understanding of antibiotic activity

Discovery of a lipid synthesising organ in the auditory system of an insect

Weta possess typical Ensifera ears. Each ear comprises three functional parts: two equally sized tympanal membranes, an underlying system of modified tracheal chambers, and the auditory sensory organ, the crista acustica. This organ sits within an enclosed fluid-filled channel–previously presumed to be hemolymph. The role this channel plays in insect hearing is unknown. We discovered that the fluid within the channel is not actually hemolymph, but a medium composed principally of lipid from a new class. Three-dimensional imaging of this lipid channel revealed a previously undescribed tissue structure within the channel, which we refer to as the olivarius organ. Investigations into the function of the olivarius reveal de novo lipid synthesis indicating that it is producing these lipids in situ from acetate. The auditory role of this lipid channel was investigated using Laser Doppler vibrometry of the tympanal membrane, which shows that the displacement of the membrane is significantly increased when the lipid is removed from the auditory system. Neural sensitivity of the system, however, decreased upon removal of the lipid–a surprising result considering that in a typical auditory system both the mechanical and auditory sensitivity are positively correlated. These two results coupled with 3D modelling of the auditory system lead us to hypothesize a model for weta audition, relying strongly on the presence of the lipid channel. This is the first instance of lipids being associated with an auditory system outside of the Odentocete cetaceans, demonstrating convergence for the use of lipids in hearing

The Role of the Environmental Manager in Advancing Environmental Sustainability and Social Responsibility in the Organization

A changing business climate has led many organizations to embrace environmental sustainability and social responsibility; however, organizational roles and responsibilities in sustainability initiatives have not been clearly defined. This paper specifically examines the role of environmental managers in advancing environmental sustainability and social responsibility. It is part of a broader study to identify the extent to which various departments or functional units within an organization are prepared to play a role in these initiatives based on a survey of various professionals in relation to activities and action items derived from the ISO 26000 standard on social responsibility. As expected, the findings indicate that environmental managers are positioned to play a critical role in advancing environmental sustainability and social responsibility in their organizations. However, there appears to be disparity between the role that environmental managers indicated they are prepared to play and the perceptions of their role held by others in the organization. While environmental managers indicated that they would support or play a major role in 18 of the 35 action items on which they were surveyed, professionals from other functional units indicated that environmental managers would be involved in only a few key areas focused on traditional environmental issues associated with pollution prevention and waste management. This suggests that environmental managers are prepared to play a much broader role in the organization’s sustainability and social responsibility efforts but may not be fully utilized in this capacity

Integrative Analysis of Gene Expression Data Including an Assessment of Pathway Enrichment for Predicting Prostate Cancer

Background: Microarray technology has been previously used to identify genes that are differentially expressed between tumour and normal samples in a single study, as well as in syntheses involving multiple studies. When integrating results from several Affymetrix microarray datasets, previous studies summarized probeset-level data, which may potentially lead to a loss of information available at the probe-level. In this paper, we present an approach for integrating results across studies while taking probe-level data into account. Additionally, we follow a new direction in the analysis of microarray expression data, namely to focus on the variation of expression phenotypes in predefined gene sets, such as pathways. This targeted approach can be helpful for revealing information that is not easily visible from the changes in the individual genes. Results: We used a recently developed method to integrate Affymetrix expression data across studies. The idea is based on a probe-level based test statistic developed for testing for differentially expressed genes in individual studies. We incorporated this test statistic into a classic random-effects model for integrating data across studies. Subsequently, we used a gene set enrichment test to evaluate the significance of enriched biological pathways in the differentially expressed genes identified from the integrative analysis. We compared statistical and biological significance of the prognostic gene expression signatures and pathways identified in the probe-level model (PLM) with those in the probeset-level model (PSLM). Our integrative analysis of Affymetrix microarray data from 110 prostate cancer samples obtained from three studies reveals thousands of genes significantly correlated with tumour cell differentiation. The bioinformatics analysis, mapping these genes to the publicly available KEGG database, reveals evidence that tumour cell differentiation is significantly associated with many biological pathways. In particular, we observed that by integrating information from the insulin signalling pathway into our prediction model, we achieved better prediction of prostate cancer. Conclusions: Our data integration methodology provides an efficient way to identify biologically sound and statistically significant pathways from gene expression data. The significant gene expression phenotypes identified in our study have the potential to characterize complex genetic alterations in prostate cancer

Using the ratio of means as the effect size measure in combining results of microarray experiments

<p>Abstract</p> <p>Background</p> <p>Development of efficient analytic methodologies for combining microarray results is a major challenge in gene expression analysis. The widely used effect size models are thought to provide an efficient modeling framework for this purpose, where the measures of association for each study and each gene are combined, weighted by the standard errors. A significant disadvantage of this strategy is that the quality of different data sets may be highly variable, but this information is usually neglected during the integration. Moreover, it is widely known that the estimated standard deviations are probably unstable in the commonly used effect size measures (such as standardized mean difference) when sample sizes in each group are small.</p> <p>Results</p> <p>We propose a re-parameterization of the traditional mean difference based effect measure by using the log ratio of means as an effect size measure for each gene in each study. The estimated effect sizes for all studies were then combined under two modeling frameworks: the quality-unweighted random effects models and the quality-weighted random effects models. We defined the quality measure as a function of the detection p-value, which indicates whether a transcript is reliably detected or not on the Affymetrix gene chip. The new effect size measure is evaluated and compared under the quality-weighted and quality-unweighted data integration frameworks using simulated data sets, and also in several data sets of prostate cancer patients and controls. We focus on identifying differentially expressed biomarkers for prediction of cancer outcomes.</p> <p>Conclusion</p> <p>Our results show that the proposed effect size measure (log ratio of means) has better power to identify differentially expressed genes, and that the detected genes have better performance in predicting cancer outcomes than the commonly used effect size measure, the standardized mean difference (SMD), under both quality-weighted and quality-unweighted data integration frameworks. The new effect size measure and the quality-weighted microarray data integration framework provide efficient ways to combine microarray results.</p

Linkage and association analysis in pedigrees from different populations

Using the Genetic Analysis Workshop 14 simulated datasets we carried out nonparametric linkage analyses and applied a log-linear method for analysis of case-parent-triad data with stratification on parental mating type. We proposed and applied a random effect modelling approach to explore the impact of population heterogeneity on tests of association between genetic markers and disease status. The estimated genetic effect may appear to be strongly significant in one population but nonsignificant in another population, leading to confusion about interpretation. However, when results are interpreted in the light of a random effects model, both studies may be making similar statements about a genetic effect that varies depending on environment and background

Nuclear quantum effects in water

In this work, a path integral Car-Parrinello molecular dynamics simulation of liquid water is performed. It is found that the inclusion of nuclear quantum effects systematically improves the agreement of first principles simulations of liquid water with experiment. In addition, the proton momentum distribution is computed utilizing a recently developed open path integral molecular dynamics methodology. It is shown that these results are in good agreement with neutron Compton scattering data for liquid water and ice.Comment: 4 page

“Recalled to Life”: Postmodernism in Lennox Robinson’s The Lost Leader (1918)

Despite playing a pivotal role in the development of Irish theatre, especially through his association with the Abbey Theatre (as writer, manager, director, and member of the Board of Directors), Lennox Robinson (1886-1958), is a largely forgotten figure, both within the public domain and within Irish scholarship. As the title, “Recalled to Life”, implies, this article constitutes a reminder of the contributions this intriguing and innovative playwright made to the Irish stage. When Robinson is sporadically name-checked by scholars, he is primarily remembered for the realist plays of his early career, perpetuating a reputation that disregards the dramatist’s later, experimental and unorthodox endeavours. Focusing on the 1918 play, The Lost Leader (in which the central character, may, or may not be, the “resurrected” Charles Stewart Parnell), the article explores Robinson’s subversion of dramatic protocols, highlighting the playwright’s use of techniques, primarily associated with postmodernism (intertextuality, an open form, self-reflexivity, metatheatre). In this way, Robinson self-consciously invites comparisons between the construction and function of the play-text, and the synthesis and propagation of ideological constructs, thereby, providing a much-needed intervention in an era of political upheavals

Identifying cis- and trans-acting single-nucleotide polymorphisms controlling lymphocyte gene expression in humans

Assuming multiple loci play a role in regulating the expression level of a single phenotype, we propose a new approach to identify cis- and trans-acting loci that regulate gene expression. Using the Problem 1 data set made available for Genetic Analysis Workshop 15 (GAW15), we identified many expression phenotypes that have significant evidence of association and linkage to one or more chromosomal regions. In particular, six of ten phenotypes that we found to be regulated by cis- and trans-acting loci were also mapped by a previous analysis of these data in which a total of 27 phenotypes were identified with expression levels regulated by cis-acting determinants. However, in general, the p-values associated with these regulators identified in our study were larger than in their studies, since we had also identified other factors regulating expression. In fact, we found that most of the gene expression phenotypes are influenced by at least one trans-acting locus. Our study also shows that much of the observable heritability in the phenotypes could be explained by simple single-nucleotide polymorphism associations; residual heritability was reduced and the remaining heritability may represent complex regulation systems with interactions or noise

Reward and punishment enhance motor adaptation in stroke

Background and objective: The effects of motor learning, such as motor adaptation, in stroke rehabilitation are often transient, thus mandating approaches that enhance the amount of learning and retention. Previously, we showed in young individuals that reward and punishment feedback have dissociable effects on motor adaptation, with punishment improving adaptation and reward enhancing retention. If these findings were able to generalise to patients with stroke, they would provide a way to optimise motor learning in these patients. Therefore, we tested this in 45 patients with chronic stroke allocated in three groups. / Methods: Patients performed reaching movements with their paretic arm with a robotic manipulandum. After training (day 1), day 2 involved adaptation to a novel force field. During the adaptation phase, patients received performance-based feedback according to the group they were allocated: reward, punishment or no feedback (neutral). On day 3, patients readapted to the force field but all groups now received neutral feedback. / Results: All patients adapted, with reward and punishment groups displaying greater adaptation and readaptation than the neutral group, irrespective of demographic, cognitive or functional differences. Remarkably, the reward and punishment groups adapted to similar degree as healthy controls. Finally, the reward group showed greater retention. / Conclusions: This study provides, for the first time, evidence that reward and punishment can enhance motor adaptation in patients with stroke. Further research on reinforcement-based motor learning regimes is warranted to translate these promising results into clinical practice and improve motor rehabilitation outcomes in patients with stroke