Subordinates’ Resistance and Managers’ Evaluations of Subordinates’ Performance

The authors explored the validity of two perspectives as to how managers evaluate subordinates who resist downward influence attempts: a uniformly dysfunctional perspective (i.e., managers regard all manifestations of resistance as indicators of ineffective influence and rate subordinates unfavorably when they resist) and a multifunctional perspective (i.e., managers regard some manifestations of resistance as more constructive than others and rate subordinates more favorably when they employ constructive resistance tactics). The results of two studies provided support for an interactive model, which predicts that the uniformly dysfunctional perspective is characteristic of lower quality leader-member exchange (LMX) relationships and that the multifunctional perspective is characteristic of higher quality leader-member exchanges

Subordinates’ Resistance and Managers’ Evaluations of Subordinates’ Performance

The authors explored the validity of two perspectives as to how managers evaluate subordinates who resist downward influence attempts: a uniformly dysfunctional perspective (i.e., managers regard all manifestations of resistance as indicators of ineffective influence and rate subordinates unfavorably when they resist) and a multifunctional perspective (i.e., managers regard some manifestations of resistance as more constructive than others and rate subordinates more favorably when they employ constructive resistance tactics). The results of two studies provided support for an interactive model, which predicts that the uniformly dysfunctional perspective is characteristic of lower quality leader-member exchange (LMX) relationships and that the multifunctional perspective is characteristic of higher quality leader-member exchanges

Differential impact of two risk communications on antipsychotic prescribing to people with dementia in Scotland: segmented regression time series analysis 2001-2011

The two risk communications were associated with reductions in antipsychotic use, in ways which were compatible with marked differences in their content and dissemination. Further research is needed to ensure that the content and dissemination of regulatory risk communications is optimal, and to track their impact on intended and unintended outcomes. Although rates are falling, antipsychotic prescribing in dementia in Scotland remains unacceptably hig

Cross-species gene expression analysis of species specific differences in the preclinical assessment of pharmaceutical compounds

Animals are frequently used as model systems for determination of safety and efficacy in pharmaceutical research and development. However, significant quantitative and qualitative differences exist between humans and the animal models used in research. This is as a result of genetic variation between human and the laboratory animal. Therefore the development of a system that would allow the assessment of all molecular differences between species after drug exposure would have a significant impact on drug evaluation for toxicity and efficacy. Here we describe a cross-species microarray methodology that identifies and selects orthologous probes after cross-species sequence comparison to develop an orthologous cross-species gene expression analysis tool. The assumptions made by the use of this orthologous gene expression strategy for cross-species extrapolation is that; conserved changes in gene expression equate to conserved pharmacodynamic endpoints. This assumption is supported by the fact that evolution and selection have maintained the structure and function of many biochemical pathways over time, resulting in the conservation of many important processes. We demonstrate this cross-species methodology by investigating species specific differences of the peroxisome proliferatoractivator receptor (PPAR) a response in rat and human

The ethics of uncertainty for data subjects

Modern health data practices come with many practical uncertainties. In this paper, I argue that data subjects’ trust in the institutions and organizations that control their data, and their ability to know their own moral obligations in relation to their data, are undermined by significant uncertainties regarding the what, how, and who of mass data collection and analysis. I conclude by considering how proposals for managing situations of high uncertainty might be applied to this problem. These emphasize increasing organizational flexibility, knowledge, and capacity, and reducing hazard

Can hydraulic design explain patterns of leaf water isotopic enrichment in C3 plants?

H2 18 O enrichment develops when leaves transpire, but an accurate generalized mechanistic model has proven elusive. We hypothesized that leaf hydraulic architecture may affect the degree to which gradients in H2 18 O develop within leaves, influencing bulk leaf stable oxygen isotope enrichment (ΔL ) and the degree to which the Péclet effect is relevant in leaves. Leaf hydraulic design predicted the relevance of a Péclet effect to ΔL in 19 of the 21 species tested. Leaves with well-developed hydraulic connections between the vascular tissue and the epidermal cells through bundle sheath extensions and clear distinctions between palisade and spongy mesophyll layers (while the mesophyll is hydraulically disconnected) may have velocities of the transpiration stream such that gradients in H2 18 O develop and are expressed in the mesophyll. In contrast, in leaves where the vascular tissue is hydraulically disconnected from the epidermal layers, or where all mesophyll cells are well connected to the transpiration stream, velocities within the liquid transport pathways may be low enough that gradients in H2 18 O are very small. Prior knowledge of leaf hydraulic design allows informed selection of the appropriate ΔL modelling framework.K.E.L. was supported by an Australian Postgraduate Award and A.S. was supported by an Australian Postgraduate Award and International Postgraduate Research Support. Australian Research Council, Grant/Award Number: DP17010427

Exploratory analysis of protein translation regulatory networks using hierarchical random graphs

Abstract Background Protein translation is a vital cellular process for any living organism. The availability of interaction databases provides an opportunity for researchers to exploit the immense amount of data in silico such as studying biological networks. There has been an extensive effort using computational methods in deciphering the transcriptional regulatory networks. However, research on translation regulatory networks has caught little attention in the bioinformatics and computational biology community. Results In this paper, we present an exploratory analysis of yeast protein translation regulatory networks using hierarchical random graphs. We derive a protein translation regulatory network from a protein-protein interaction dataset. Using a hierarchical random graph model, we show that the network exhibits well organized hierarchical structure. In addition, we apply this technique to predict missing links in the network. Conclusions The hierarchical random graph mode can be a potentially useful technique for inferring hierarchical structure from network data and predicting missing links in partly known networks. The results from the reconstructed protein translation regulatory networks have potential implications for better understanding mechanisms of translational control from a system’s perspective

Phenotypic Variation and Bistable Switching in Bacteria

Microbial research generally focuses on clonal populations. However, bacterial cells with identical genotypes frequently display different phenotypes under identical conditions. This microbial cell individuality is receiving increasing attention in the literature because of its impact on cellular differentiation, survival under selective conditions, and the interaction of pathogens with their hosts. It is becoming clear that stochasticity in gene expression in conjunction with the architecture of the gene network that underlies the cellular processes can generate phenotypic variation. An important regulatory mechanism is the so-called positive feedback, in which a system reinforces its own response, for instance by stimulating the production of an activator. Bistability is an interesting and relevant phenomenon, in which two distinct subpopulations of cells showing discrete levels of gene expression coexist in a single culture. In this chapter, we address techniques and approaches used to establish phenotypic variation, and relate three well-characterized examples of bistability to the molecular mechanisms that govern these processes, with a focus on positive feedback.

Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization.

Do human societies from around the world exhibit similarities in the way that they are structured, and show commonalities in the ways that they have evolved? These are long-standing questions that have proven difficult to answer. To test between competing hypotheses, we constructed a massive repository of historical and archaeological information known as "Seshat: Global History Databank." We systematically coded data on 414 societies from 30 regions around the world spanning the last 10,000 years. We were able to capture information on 51 variables reflecting nine characteristics of human societies, such as social scale, economy, features of governance, and information systems. Our analyses revealed that these different characteristics show strong relationships with each other and that a single principal component captures around three-quarters of the observed variation. Furthermore, we found that different characteristics of social complexity are highly predictable across different world regions. These results suggest that key aspects of social organization are functionally related and do indeed coevolve in predictable ways. Our findings highlight the power of the sciences and humanities working together to rigorously test hypotheses about general rules that may have shaped human history

Quantitative Historical Analysis Uncovers a Single Dimension of Complexity that Structures Global Variation in Human Social Organization

Do human societies from around the world exhibit similarities in the way that they are structured, and show commonalities in the ways that they have evolved? These are long-standing questions that have proven difficult to answer. To test between competing hypotheses, we constructed a massive repository of historical and archaeological information known as “Seshat: Global History Databank.” We systematically coded data on 414 societies from 30 regions around the world spanning the last 10,000 years. We were able to capture information on 51 variables reflecting nine characteristics of human societies, such as social scale, economy, features of governance, and information systems. Our analyses revealed that these different characteristics show strong relationships with each other and that a single principal component captures around three-quarters of the observed variation. Furthermore, we found that different characteristics of social complexity are highly predictable across different world regions. These results suggest that key aspects of social organization are functionally related and do indeed coevolve in predictable ways. Our findings highlight the power of the sciences and humanities working together to rigorously test hypotheses about general rules that may have shaped human history