Rapid Cellular Turnover in Adipose Tissue

It was recently shown that cellular turnover occurs within the human adipocyte population. Through three independent experimental approaches — dilution of an inducible histone 2B-green fluorescent protein (H2BGFP), labeling with the cell cycle marker Ki67 and incorporation of BrdU — we characterized the degree of cellular turnover in murine adipose tissue. We observed rapid turnover of the adipocyte population, finding that 4.8% of preadipocytes are replicating at any time and that between 1–5% of adipocytes are replaced each day. In light of these findings, we suggest that adipose tissue turnover represents a possible new avenue of therapeutic intervention against obesity

Network centrality and organizational aspirations: A behavioral interaction in the context of international strategic alliances

Whereas social network analysis has been associated with organizational aspirations, little is known on how firm's structural positioning, and particularly network centrality, affects organizational aspirations to engage in international strategic alliances (ISA). This study examines the impact of network centrality on firm's internationalization behavior within the ISA domain in response to the performance-aspiration gap. We build on social and behavioral perspectives to predict that network centrality and performance-based aspirations will be associated with the number of ISA the firm engages in. Using a sample of 7760 alliance collaborations from the top 81 global pharmaceutical firms for the period of 1991-2012, we find supporting evidence for most of our arguments

Fixed and random effects models: making an informed choice

This paper assesses the options available to researchers analysing multilevel (including longitudinal) data, with the aim of supporting good methodological decision-making. Given the confusion in the literature about the key properties of fixed and random effects (FE and RE) models, we present these models’ capabilities and limitations. We also discuss the within-between RE model, sometimes misleadingly labelled a ‘hybrid’ model, showing that it is the most general of the three, with all the strengths of the other two. As such, and because it allows for important extensions—notably random slopes—we argue it should be used (as a starting point at least) in all multilevel analyses. We develop the argument through simulations, evaluating how these models cope with some likely mis-specifications. These simulations reveal that (1) failing to include random slopes can generate anti-conservative standard errors, and (2) assuming random intercepts are Normally distributed, when they are not, introduces only modest biases. These results strengthen the case for the use of, and need for, these models