BackgroundThe green microalga Dunaliella salina accumulates a high proportion of β-carotene during abiotic stress conditions. To better understand the intracellular flux distribution leading to carotenoid accumulation, this work aimed at reconstructing a carbon core metabolic network for D. salina CCAP 19/18 based on the recently published nuclear genome and its validation with experimental observations and literature data.ResultsThe reconstruction resulted in a network model with 221 reactions and 212 metabolites within three compartments: cytosol, chloroplast and mitochondrion. The network was implemented in the MATLAB toolbox CellNetAnalyzer and checked for feasibility. Furthermore, a flux balance analysis was carried out for different light and nutrient uptake rates. The comparison of the experimental knowledge with the model prediction revealed that the results of the stoichiometric network analysis are plausible and in good agreement with the observed behavior. Accordingly, our model provides an excellent tool for investigating the carbon core metabolism of D. salina.ConclusionsThe reconstructed metabolic network of D. salina presented in this work is able to predict the biological behavior under light and nutrient stress and will lead to an improved process understanding for the optimized production of high-value products in microalgae.

Gift giving is an effective means to strengthen interpersonal relationships; it also may initiate and enhance customer–brand relationships. Through a field study conducted with an international monobrand retailer of beauty products, a combination of propensity score matching with difference-in-differences estimations, and two experimental scenario studies, this research demonstrates that gift buyers spend 63% more in the year following a gift purchase than a matched sample of customers who purchase for their personal use. Specifically, gift buyers increase their purchase frequency (25%), spend more per shopping trip (41%), and engage in more cross-buying (49%). The sales lift is particularly pronounced among new customers. Identity theory suggests customer gratitude and public commitment as mediating mechanisms. Gift purchase design characteristics (i.e., assistance during gift purchase and branded gift wrapping) influence the strength of the mediating mechanisms.

Self-assembly reactions with low valent early transition metals, leading to neutral multinuclear complexes are rare. Mostly late transition metals like Pt, Pd or Ru together with Nheterocycles or O-donor-based ligands are used to form supramolecular coordination complexes. This paper reports on selfassembly reactions of low valent titanocene and zirconocene units and five-membered N-heterocycles as bridging ligands. These reactions lead to novel molecular triangles and rectangles with the metal centers marking the vertices. Five different imidazole derivatives and four different metallocene precursors were used. For the first time, molecular triangles and architec-Scheme 1. Molecular quadrangle with pyrazine I and 4,4′-bipyridine II and a combination of both III as bridging ligands.[a]

Customer engagement, a customer’s active participation in and connection with a firm’s services, has been promoted as a key driver of customer loyalty. Yet, insights on how to effectively manage engagement are scarce. This article employs an experimental study to assess the loyalty-effect of customer engagement and disentangle the effectiveness of company-initiated versus customer-initiated engagement for different customer types. We establish a positive impact of customer engagement on customer loyalty, mediated by company image. However, adopting a finer-grained view on engagement effectiveness, we show mixed effects of company-initiated engagement contingent on customers’ service category involvement. Specifically, for high involvement customers, company-initiated engagement positively affects loyalty, while it impedes loyalty for low involvement customers. Company image and reactance toward the company act as mediating mechanisms. We provide guidance to managers on how to design and whom to target with their engagement strategies.

Background The green microalga Dunaliella salina accumulates a high proportion of beta-carotene during abiotic stress conditions. To better understand the intracellular flux distribution leading to carotenoid accumulation, this work aimed at reconstructing a carbon core metabolic network for D. salina CCAP 19/18 based on the recently published. Results The reconstruction resulted in a network model with 221 reactions and 212 metabolites within three compartments: cytosol, chloroplast and mitochondrion. The network was implemented in the MATLAB toolbox CellNetAnalyzer and checked for feasibility. Furthermore, a flux balance analysis was carried out for different light and nutrient uptake rates. The comparison of the experimental knowledge with the model prediction revealed that the results of the stoichiometric network analysis are plausible and in good agreement with the observed behavior. Accordingly, our model provides an excellent new tool to interrogate and better understand the carbon core metabolism of D. salina. Conclusions The reconstructed metabolic network of D. salina presented in this work is able to predict the biological behavior under light and nutrient stress and will lead to an improved process understanding for the optimized production of high-value products in microalgae.

Background The green microalga Dunaliella salina accumulates a high proportion of beta-carotene during abiotic stress conditions. To better understand the intracellular flux distribution leading to carotenoid accumulation, this work aimed at reconstructing a carbon core metabolic network for D. salina CCAP 19/18 based on the recently published. Results The reconstruction resulted in a network model with 221 reactions and 212 metabolites within three compartments: cytosol, chloroplast and mitochondrion. The network was implemented in the MATLAB toolbox CellNetAnalyzer and checked for feasibility. Furthermore, a flux balance analysis was carried out for different light and nutrient uptake rates. The comparison of the experimental knowledge with the model prediction revealed that the results of the stoichiometric network analysis are plausible and in good agreement with the observed behavior. Accordingly, our model provides an excellent new tool to interrogate and better understand the carbon core metabolism of D. salina. Conclusions The reconstructed metabolic network of D. salina presented in this work is able to predict the biological behavior under light and nutrient stress and will lead to an improved process understanding for the optimized production of high-value products in microalgae.