Use of noise in gene expression as an experimental parameter to test phenotypic effects

During the last decade, the molecular basis for gene expression noise has been mostly deciphered, helping understanding of how gene regulation is controlled and how the generation of cell–cell non‐genetic heterogeneity is modulated through noise. In the same period, the functional importance of phenotypic heterogeneity among cell populations has been recognized and widely involved in major biological phenomena. Surprisingly, only a few studies connect these two highly active research fields, most of them having been obtained using the yeast Saccharomyces cerevisiae. This organism has long been the preferred model for studying many aspects of gene expression noise, especially revealing that evolution seems to act to either increase or decrease gene expression noise, depending on whether the associated phenotypic heterogeneity is beneficial or deleterious to the population. Nevertheless, direct evidences of phenotypic consequences of noise differences are often lacking, in spite of this evolutionary tendency. This rarity is probably due to the complex relationships between mean and noise levels, making the study of the sole effect of noise difficult, and also to problems caused by the detection of cell–cell expression variability of native functional proteins, allowing the testing of specific phenotypic effects. Despite these difficulties, the widespread use of gene expression noise as an experimental parameter at equal mean expression levels to test phenotypic consequences would often help to change explanations of cell population behaviour beyond the simple consideration of average expression levels, and constitute a major step towards single‐cell biology. Copyright © 2016 John Wiley & Sons, Ltd.     

Controlling the Formation of Nanocavities in Kirkendall Nanoobjects through Sequential Thermal Ex Situ Oxidation and In Situ Reduction Reactions

Controlling the porosity, the shape, and the morphology of Kirkendall hollow nanostructures is the key factor to tune the properties of these tailor‐made nanomaterials which allow in turn broadening their applications. It is shown that by applying a continuous oxidation to copper nanowires following a temperature ramp protocol, one can synthesize cuprous oxide nanotubes containing periodic copper nanoparticles. A further oxidation of such nanoobjects allows obtaining cupric oxide nanotubes with a bamboo‐like structure. On the other hand, by applying a sequential oxidation and reduction reactions to copper nanowires, one can synthesize hollow nanoobjects with complex shapes and morphologies that cannot be obtained using the Kirkendall effect alone, such as necklace‐like cuprous oxide nanotubes, periodic solid copper nanoparticles or hollow cuprous oxide nanospheres interconnected with single crystal cuprous oxide nanorods, and aligned and periodic hollow nanospheres embedded in a cuprous oxide nanotube. The strategy demonstrated in this study opens new avenues for the engineering of hollow nanostructures with potential applications in gas sensing, catalysis, and energy storage.     

SMEs' Preference for Innovation Networks: A Choice Experimental Approach

The objective of this paper is to evaluate the importance of selected characteristics of innovation networks in affecting the decision of food SMEs when joining such networks. The paper develops and tests a series of hypotheses through a choice experiment exercise ran on a sample of 231 firms in six EU countries. The results showed that SMEs prefer networks that are composed of manufacturers and supply chain members, where information is shared confidentially among network partners, and when the network provides support to help the firm build its own networks of partners for innovation. In addition, SMEs' choice of the network is also affected by the interaction between specific network attributes and two firm characteristics, i.e. the firm's collaborative experience and innovation objectives. Based on the results, we conclude that the success of inter‐organizational networks depends on the fit between the network's design and the innovation and networking behaviour of the firms.