Minimising the gender status effects on performance for women in leadership

This study explores how different workplace structures are institutionalised such that women in leadership are better able to address lower status assessments associated with the gender stereotype. Using a sample of 27 women leaders across industries, the study found that legitimate workplace structures such as opportunities for promotion into high status roles, increased opportunities to participate, equality and mentoring practices embedded in HRM policies, confuse and challenge the subliminal status effects of gender on perceived task or role performance. For instance, when institutionalised practices were prevalent, the study found that the link between the subliminal gender status and performance was irrelevant and inconsequential with women leaders displaying as much influence as men. When workplace structures were absent by comparison, women leaders had to work harder to overcome common stereotypes that they were less competent and less suited to senior roles. The study outcomes have major benefits for organisations wishing to legitimise HRM policies that help to formalise workplace structures and counter prevailing gender stereotypes

Can institutionalized workplace structures benefit senior women leaders?

Drawing on interviews conducted with a sample of 27 senior women leaders from across Australian industries, this study found that legitimate workplace structures disrupt and challenge the subliminal status effects of gender on perceived task or role performance. This related to structures such as increased opportunities for promotion into higher status roles and opportunities to participate in unstructured group-task roles. These findings were in stark contrast to traditional workplace structures where senior women leaders relied on their ability alone to reach the top. Our findings have significant implications for organizations wishing to legitimize and replicate HRM policy levers that help to formalize workplace structures of equality and counter prevailing gender stereotypes

Competent women, subliminal group hierarchies and executive leadership

Objective: We analysed the experiences of successful executive women leaders to ascertain how they attained appointments to roles as high as the C-suite and boardroom. Theoretical focus: Sociologists use ‘status characteristics theory’ (SCT) to explain the influence of status beliefs based on salient characteristics, such as gender, on the assessment of a person’s competency in group task situations (Berger et al. 1980). SCT suggests women can elevate their position from their stereotypically assigned place in the subliminal group hierarchy by shortening the path of relevance (Berger et al. 1980) between perceptions of their gender and their competence to perform a leadership role. Research question: What strategies do successful executive women use to overcome subliminal, gender-influenced assessments of their leadership competency? Method: In 2016, we interviewed 25 women who held positions within the executive suite and/or on the Board of Australian companies and government departments. A thematic analysis adhering to a ‘contextualist’ approach (Braun & Clarke, 2006) was applied to examine the participants’ responses. Major conclusions: The women demonstrated their competence via two overarching strategies: active demonstrations with associated internal dialogues. Under these two strategies sit four sets of mirror-imaged tactics: balanced career choices; outcome driven; image management; and leveraged relationships. Combined, these inputs reflect physical and mental manoeuvres women have used to achieve shortened paths of relevance, suggesting that they reconfigured the cognitive, stereotypical status assessment of being less competent than the men in the group, to being viewed as a person capable of an executive leadership role

On the Independent Domination Number of Regular Graphs

A set S of vertices in a graph G is an independent dominating set of G if S is an independent set and every vertex not in S is adjacent to a vertex in S. In this paper, we consider questions about independent domination in regular graphs

Rapid and Accurate Assessment of GPCR-Ligand Interactions Using the Fragment Molecular Orbital-Based Density-Functional Tight-Binding Method

The reliable and precise evaluation of receptor–ligand interactions and pair-interaction energy is an essential element of rational drug design. While quantum mechanical (QM) methods have been a promising means by which to achieve this, traditional QM is not applicable for large biological systems due to its high computational cost. Here, the fragment molecular orbital (FMO) method has been used to accelerate QM calculations, and by combining FMO with the density-functional tight-binding (DFTB) method we are able to decrease computational cost 1000 times, achieving results in seconds, instead of hours. We have applied FMO-DFTB to three different GPCR–ligand systems. Our results correlate well with site directed mutagenesis data and findings presented in the published literature, demonstrating that FMO-DFTB is a rapid and accurate means of GPCR–ligand interactions

Meta-analysis of genome-wide expression patterns associated with behavioral maturation in honey bees

<p>Abstract</p> <p>Background</p> <p>The information from multiple microarray experiments can be integrated in an objective manner <it>via </it>meta-analysis. However, multiple meta-analysis approaches are available and their relative strengths have not been directly compared using experimental data in the context of different gene expression scenarios and studies with different degrees of relationship. This study investigates the complementary advantages of meta-analysis approaches to integrate information across studies, and further mine the transcriptome for genes that are associated with complex processes such as behavioral maturation in honey bees. Behavioral maturation and division of labor in honey bees are related to changes in the expression of hundreds of genes in the brain. The information from various microarray studies comparing the expression of genes at different maturation stages in honey bee brains was integrated using complementary meta-analysis approaches.</p> <p>Results</p> <p>Comparison of lists of genes with significant differential expression across studies failed to identify genes with consistent patterns of expression that were below the selected significance threshold, or identified genes with significant yet inconsistent patterns. The meta-analytical framework supported the identification of genes with consistent overall expression patterns and eliminated genes that exhibited contradictory expression patterns across studies. Sample-level meta-analysis of normalized gene-expression can detect more differentially expressed genes than the study-level meta-analysis of estimates for genes that were well described by similar model parameter estimates across studies and had small variation across studies. Furthermore, study-level meta-analysis was well suited for genes that exhibit consistent patterns across studies, genes that had substantial variation across studies, and genes that did not conform to the assumptions of the sample-level meta-analysis. Meta-analyses confirmed previously reported genes and helped identify genes (e.g. <it>Tomosyn</it>, <it>Chitinase 5, Adar, Innexin 2, Transferrin 1</it>, <it>Sick</it>, <it>Oatp26F</it>) and Gene Ontology categories (e.g. purine nucleotide binding) not previously associated with maturation in honey bees.</p> <p>Conclusion</p> <p>This study demonstrated that a combination of meta-analytical approaches best addresses the highly dimensional nature of genome-wide microarray studies. As expected, the integration of gene expression information from microarray studies using meta-analysis enhanced the characterization of the transcriptome of complex biological processes.</p

NeuroPred: a tool to predict cleavage sites in neuropeptide precursors and provide the masses of the resulting peptides

NeuroPred is a web application designed to predict cleavage sites at basic amino acid locations in neuropeptide precursor sequences. The user can study one amino acid sequence or multiple sequences simultaneously, selecting from several prediction models and optional, user-defined functions. Logistic regression models are trained on experimentally verified or published cleavage data from mollusks, mammals and insects, and amino acid motifs reported to be associated with cleavage. Confidence interval limits of the probabilities of cleavage indicate the precision of the predictions; these predictions are transformed into cleavage or non-cleavage events according to user-defined thresholds. In addition to the precursor sequence, NeuroPred accepts user-specified cleavage information, providing model accuracy statistics based on observed and predicted cleavages. Neuropred also computes the mass of the predicted peptides, including user-selectable post-translational modifications. The resulting mass list aids the discovery and confirmation of new neuropeptides using mass spectrometry techniques. The NeuroPred application, manual, reference manuscripts and training sequences are available at

COMPLEXO: identifying the missing heritability of breast cancer via next generation collaboration

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Characterising Inter-helical Interactions of G Protein-Coupled Receptors with the Fragment Molecular Orbital Method

G-protein coupled receptors (GPCRs) are the largest superfamily of membrane proteins, regulating almost every aspect of cellular activity and serving as key targets for drug discovery. We have identified an accurate and reliable computational method to characterise the strength and chemical nature of the inter-helical interactions between the residues of transmembrane (TM) domains during different receptor activation states, something that cannot be characterised solely by visual inspection of structural information. Using the fragment molecular orbital (FMO) quantum mechanics method to analyse 35 crystal structures representing different branches of the class A GPCR family, we have identified 69 topologically-equivalent TM residues that form a consensus network of 51 inter-TM interactions, providing novel results that are consistent with and help to rationalise experimental data. This discovery establishes a comprehensive picture of how defined molecular forces govern specific inter-helical interactions which, in turn, support the structural stability, ligand binding and activation of GPCRs

Voluntary Wheel Running Reverses Age-Induced Changes in Hippocampal Gene Expression

Normal aging alters expression of numerous genes within the brain. Some of these transcription changes likely contribute to age-associated cognitive decline, reduced neural plasticity, and the higher incidence of neuropathology. Identifying factors that modulate brain aging is crucial for improving quality of life. One promising intervention to counteract negative effects of aging is aerobic exercise. Aged subjects that exercise show enhanced cognitive performance and increased hippocampal neurogenesis and synaptic plasticity. Currently, the mechanisms behind the anti-aging effects of exercise are not understood. The present study conducted a microarray on whole hippocampal samples from adult (3.5-month-old) and aged (18-month-old) male BALB/c mice that were individually housed with or without running wheels for 8 weeks. Results showed that aging altered genes related to chromatin remodeling, cell growth, immune activity, and synapse organization compared to adult mice. Exercise was found to modulate many of the genes altered by aging, but in the opposite direction. For example, wheel running increased expression of genes related to cell growth and attenuated expression of genes involved in immune function and chromatin remodeling. Collectively, findings show that even late-onset exercise may attenuate age-related changes in gene expression and identifies possible pathways through which exercise may exert its beneficial effects