Polyaniline (PANI) is one of the most widely investigated conducting polymers and is considered to be of practical use for many future applications. Here, we first demonstrate that the anisotropic growth of PANI at the nanometer scale can be kinetically controlled by employing a polymeric stabilizer, poly(N-vinylpyrrolidone). The polymerization rate became slower in the presence of the stabilizer (the rate constants calculated at the initial stage decreased with increasing concentration of the stabilizer), yielding PANI nanostructures with lower aspect ratios. Therefore, it is believed that the stabilizer sterically restricts the directional fiber growth mechanism governing PANI chain growth in aqueous solution. Three PANI nanostructures, specifically nanospheres, nanorods, and nanofibers, were fabricated and their oxidation/protonation levels were investigated systematically. It was found that the nanofibers had the most outstanding oxidation/protonation level accompanied by structural ordering (note that the only difference between the polymerization conditions in each case was the concentration of the stabilizer). We also examine the electrochemical properties of PANI nanostructure electrodes in three-electrode and two-electrode (actual capacitor cell) configurations. The intrinsic charge-transport ability of individual nanostructures strongly affected the electrochemical properties of the electrodes. Briefly, the nanofiber electrode had faster electrode kinetics and better capacitance than the nanorods and nanospheres. Lastly, an extrinsic factor, the interparticle contact resistance, also turned out to noticeably influence the capacitances of the electrodes.

Tailoring the morphology of materials in the nanometer regime is vital to realizing enhanced device performance. Here, we demonstrate flexible nerve agent sensors, based on hydroxylated poly(3,4-ethylenedioxythiophene) (PEDOT) nanotubes (HPNTs) with surface substructures such as nanonodules (NNs) and nanorods (NRs). The surface substructures can be grown on a nanofiber surface by controlling critical synthetic conditions during vapor deposition polymerization (VDP) on the polymer nanotemplate, leading to the formation of multidimensional conducting polymer nanostructures. Hydroxyl groups are found to interact with the nerve agents. Representatively, the sensing response of dimethyl methylphosphonate (DMMP) as a simulant for sarin is highly sensitive and reversible from the aligned nanotubes. The minimum detection limit is as low as 10 ppt. Additionally, the sensor had excellent mechanical bendability and durability.

SummarySeed oils have proved recalcitrant to modification for the production of industrially useful lipids. Here, we demonstrate the successful metabolic engineering and subsequent field production of an oilseed crop with the highest accumulation of unusual oil achieved so far in transgenic plants. Previously, expression of the Euonymus alatus diacylglycerol acetyltransferase (EaDAcT) gene in wild-type Arabidopsis seeds resulted in the accumulation of 45 mol% of unusual 3-acetyl-1,2-diacyl-sn-glycerols (acetyl-TAGs) in the seed oil (Durrett et al., 2010 PNAS 107:9464). Expression of EaDAcT in dgat1 mutants compromised in their ability to synthesize regular triacylglycerols increased acetyl-TAGs to 65 mol%. Camelina and soybean transformed with the EaDAcT gene accumulate acetyl-triacylglycerols (acetyl-TAGs) at up to 70 mol% of seed oil. A similar strategy of coexpression of EaDAcT together with RNAi suppression of DGAT1 increased acetyl-TAG levels to up to 85 mol% in field-grown transgenic Camelina. Additionally, total moles of triacylglycerol (TAG) per seed increased 20%. Analysis of the acetyl-TAG fraction revealed a twofold reduction in very long chain fatty acids (VLCFA), consistent with their displacement from the sn-3 position by acetate. Seed germination remained high, and seedlings were able to metabolize the stored acetyl-TAGs as rapidly as regular triacylglycerols. Viscosity, freezing point and caloric content of the Camelina acetyl-TAG oils were reduced, enabling use of this oil in several nonfood and food applications.

Methyl jasmonate (MeJA) treatment increases the levels of plant secondary metabolites, including ginsenosides, which are considered to be the main active compounds in ginseng (Panax ginseng C.A. Meyer). To create a ginseng gene resource that contains the genes involved in the biosynthesis of secondary metabolites, including ginsenosides, we generated 3,134 expression sequence tags (ESTs) from MeJA-treated ginseng hairy roots. These ESTs assembled into 370 clusters and 1,680 singletons. Genes yielding highly abundant transcripts were those encoding proteins involved in fatty acid desaturation, the defense response, and the biosynthesis of secondary metabolites. Analysis of the latter group revealed a number of genes that may be involved in the biosynthesis of ginsenosides, namely, oxidosqualene cyclase (OSC), cytochrome P450, and glycosyltransferase. A novel OSC gene was also identified by this analysis. RNA gel blot analysis confirmed that transcription of this OSC gene, along with squalene synthase (SS) and squalene epoxidase (SE) gene transcription, is increased by MeJA treatment. This ginseng EST data set will also provide important information on the genes that are involved in the biosynthesis of other secondary metabolites and the genes that are responsive to MeJA treatment.

Business ecosystems consist of a heterogeneous and continuously evolving set of entities that are interconnected through a complex, global network of relationships. However, there is no well-established methodology to study the dynamics of this network. Traditional approaches have primarily utilized a single source of data of relatively established firms; however, these approaches ignore the vast number of relevant activities that often occur at the individual and entrepreneurial levels. We argue that a data-driven visualization approach, using both institutionally and socially curated datasets, can provide important complementary, triangulated explanatory insights into the dynamics of interorganizational networks in general and business ecosystems in particular. We develop novel visualization layouts to help decision makers systemically identify and compare ecosystems. Using traditionally disconnected data sources on deals and alliance relationships (DARs), executive and funding relationships (EFRs), and public opinion and discourse (POD), we empirically illustrate our data-driven method of data triangulation and visualization techniques through three cases in the mobile industry Google’s acquisition of Motorola Mobility, the coopetitive relation between Apple and Samsung, and the strategic partnership between Nokia and Microsoft. The article concludes with implications and future research opportunities.