Impact of sorbic acid on germinant receptor-dependent and -independent germination pathways in Bacillus cereus

Amino acid- and inosine-induced germination of Bacillus cereus ATCC 14579 spores was reversibly inhibited in the presence of 3 mM undissociated sorbic acid. Exposure to high hydrostatic pressure, Ca-dipicolinic acid (DPA), and bryostatin, an activator of PrkC kinase, negated this inhibition, pointing to specific blockage of signal transduction in germinant receptor-mediated germination

The relationship between in-store marketing and observed sales for organic versus fair trade products

To stimulate sales of sustainable products, such as organic and fair trade products, retailers need to know whether their in-store instruments effectively enhance market shares. This study uses sales data and a multilevel modeling approach to explain the market shares of sustainable products according to shelf layout factors, price level, price promotions, and consumer demographics. It argues that the effect of these variables differs between organic versus fair trade products, as buying motives might differ, organic buyers tend to be more loyal, and price is a more informative signal of quality for organic products. Results show that the number of facings has a positive relationship with the market share of fair trade brands, but not with the market share of organic brands. The same holds for the price difference with the leading brand, which is important for fair trade brands but not for organic brands. In contrast, an arrangement of the product category by brand is associated with higher market share for organic brands but not for fair trade brands. Additionally, placement at eye level and clustering of items benefits both types of sustainable brands, whereas they appear to be not very sensitive to price promotions. Finally, higher sales of sustainable products are found in areas where the customer base is older and has a higher education level. Keywords Organic . Fair trade . Shelf layout . Price promotions . Market share . Sales dat

Distributed SUSY Breaking: Dark Energy, Newton's Law and the LHC

We identify the underlying symmetry mechanism that suppresses the low-energy effective 4D cosmological constant within 6D supergravity models, leading to results suppressed by powers of the KK scale relative to the much larger masses associated with particles localized on codimension-2 branes. In these models the conditions for unbroken supersymmetry can be satisfied locally everywhere within the extra dimensions, but are obstructed by global conditions like flux quantization or the mutual inconsistency of boundary conditions at the various branes. Consequently quantities forbidden by supersymmetry cannot be nonzero until wavelengths of order the KK scale are integrated out, since only such long wavelength modes see the entire space and so know that supersymmetry breaks. We verify these arguments by extending earlier rugby-ball calculations of one-loop vacuum energies to more general pairs of branes within two warped extra dimensions. The predicted effective 4D vacuum energy density can be of order C (m Mg/4 pi Mp)^4, where Mg (Mp) is the rationalized 6D (4D) Planck scale and m is the heaviest brane-localized particle. Numerically this is C (5.6 x 10^{-5} eV)^4 if we take m = 173 GeV and take Mg as small as possible (10 TeV corresponding to KK size r < 1 micron), consistent with supernova bounds. C is a constant depending on details of the bulk spectrum, which could be ~ 500 for each of hundreds of fields. The value C ~ 6 x 10^6 gives the observed Dark Energy density

The nicotinic acetylcholine receptor subunit family expressed in the central nervous system of the freshwater snail Lymnaea stagnalis: Molecular and functional diversity of the neuronal nicotinic acetylcholine receptors in a molluscan species

Smit, A.B. [Promotor

Gravitational Forces on a Codimension-2 Brane

We compute the gravitational response of six dimensional gauged, chiral supergravity to localized stress energy on one of two space-filling branes, including the effects of compactifying the extra dimensions and brane back-reaction. We find a broad class of exact solutions, including various black-brane solutions. Several approximate solutions are also described, such as the near-horizon geometry of a small black hole which is argued to be approximately described by a 6D Schwarzschild (or Kerr) black hole, with event horizon appropriately modified to encode the brane back-reaction. The general linearized far-field solutions are found in the 4D regime very far from the source, and all integration constants are related to physical quantities describing the branes and the localized energy source. The localized source determines two of these, corresponding to the source mass and the size of the strength of a coupling to a 4D scalar mode whose mass is parametrically smaller than the KK scale. At large distances the solutions agree with those of 4D general relativity, but for an intermediate range of distances (larger than the KK scale) the solutions better fit a Brans-Dicke theory. For a realistic choice of parameters the KK scale could lie at a micron, while the crossover to Brans-Dicke behaviour could occur at around 10 microns. While allowed by present data this points to potentially measurable changes to Newton's Law arising at distances larger than the KK scale.Comment: 31 pages + appendices, 2 figure

Associated factors of hope in cancer patients during treatment : a systematic literature review

Aim: To identify the associated factors of hope during treatment in cancer patients. Background: Hope is very important to cancer patients at all stages of the disease process. Hope is seen as an important coping mechanism. Most research about hope in cancer patients considered the end of life or in palliative care. Several and different factors are associated with hope. It is not yet sufficiently clear which factors are associated with hope during the treatment. Design: A systematic literature review of quantitative empirical studies on hope in cancer patients during treatment. Data Sources: Search in MEDLINE (PubMed interface), CINAHL (EBSCO interface), Psychinfo and Cochrane (January 2009-December 2018). Review Methods: Empirical quantitative studies were included regardless of the disease stage, written in English or Dutch, measuring hope from the perspective of cancer patients. Two authors independently screened all the studies and assessed their quality. Results: Thirty-three studies were included. Positive relationship has been established between hope and quality of life, social support, spiritual and existential well-being. Hope appears to be negatively associated with symptom burden, psychological distress and depression. There appears to be no relationship between hope and demographic and clinical variables. The relationship between anxiety and hope remains unclear. Conclusions: Hope primarily seems to be a process that takes place in a person's inner being rather than being determined from outside. Impact: Health professionals may want to focus on the meaning of hope for cancer patients in relation to the associated factors. A better understanding of the meaning of hope during treatment can be of great value in supporting cancer patients with regard to treatment decisions, psychosocial support, the experienced quality of life and symptom burden and any wishes they may have with regard to advanced care planning

Modeling Consideration Sets and Brand Choice Using Artificial Neural Networks

The concept of consideration sets makes brand choice a two-step process. House-holds first construct a consideration set which not necessarily includes all available brands and conditional on this set they make a final choice. In this paper we put forward a parametric econometric model for this two-step process, where we take into account that consideration sets usually are not observed. It turns out that our model is an artificial neural network, where the consideration set corresponds with the hidden layer. We discuss representation, parameter estimation and inference.We illustrate our model for the choice between six detergent brands and show that the model improves upon a one-step multinomial logit model, in terms of fit and out-of-sample forecasting.brand choice;consideration set;artificial neural network