Country-wise differences in perception of health-related messages in cereal-based food products

The objective of the present study was to explore the impact of health-related messages on the perceived overall healthiness and consumers' likelihood to buy cereal-based products or non-cereal products containing beneficial compounds from grains, across four European countries. The data were collected from a sample of 2392 members of the public in Finland, Germany, Italy and the UK. The results from a conjoint task with a main effects additive model were reported. In general, the presence of a verbal health claim on foods had positive influence on respondents perception of healthiness and on likelihood to buy the products, whereas the pictorial health claims were found to have a weak influence on the two dependent variables. However, the findings showed that health-related information on food labels differently influenced the healthiness perception and the likelihood to buy the product across the four countries, suggesting that different cultures, traditions, and eating habits have to be taken into account before positioning cereal-based products containing beneficial compounds from grains on the market. (C) 2009 Elsevier Ltd. All rights reserved.

Rejecting the label: A social constructionist analysis

Research has shown that people often do not claim labels associated with mental retardation or learning difficulties. We discussed the interpretation that this rejection is an example of a denial process, the purpose of which is to protect self-esteem. Alternative explanations for this lack of identification were offered, based on an understanding of the socially constructed nature of diagnostic labels and on the distinction between diagnostic labels and social categories. Some of the problems in using the label as a descriptive or explanatory resource are illustrated using quotes from a study in which people who have been labeled discussed the label.

Is low self-esteem an inevitable consequence of stigma? An example from women with chronic mental health problems

It is often assumed that membership in a stigmatized group has negative consequences for the self-concept. However, this relationship is neither straightforward nor inevitable, and there is evidence suggesting that negative consequences may not necessarily occur (Psychol. Rev. 96(4) (1989) 608). This paper argues that the relationship has not been sufficiently theorized, and that a more detailed analysis is called for in order to understand the relationship between stigma and the self. The paper presents a critical examination of modified labeling theory (Am. Sociol. Rev. 52 (1987) 96), with examples from a study examining perceptions of stigma and their relationship to self-evaluation in women with chronic mental health problems. Open-ended interviews and qualitative analyses were used in preference to global measures of self-esteem. It was found that although the women were aware of society's unfavorable representations of mental illness, and the effects this had on their lives, they did not accept these representations as valid and therefore rejected them as applicable to the self. The participants did not deny their mental health problems, but their acceptance of labels was critical and pragmatic. Labels were rejected when they were perceived as carrying an unrealistic and negative stereotype, or when the women felt that their symptoms did not fit with the diagnostic criteria. The research illustrates the importance of considering people's subjective understandings of stigmatized conditions and societal reactions in order to understand the relation between stigma and the self. (C) 2002 Elsevier Science Ltd. All rights reserved.

Algorithmic computation of knot polynomials of secondary structure elements of proteins

The classification of protein structures is an important and still outstanding problem. The purpose of this paper is threefold. First, we utilize a relation between the Tutte and homfly polynomial to show that the Alexander-Conway polynomial can be algorithmically computed for a given planar graph. Second, as special cases of planar graphs, we use polymer graphs of protein structures. More precisely, we use three building blocks of the three-dimensional protein structure-alpha-helix, antiparallel beta-sheet, and parallel beta-sheet-and calculate, for their corresponding polymer graphs, the Tutte polynomials analytically by providing recurrence equations for all three secondary structure elements. Third, we present numerical results comparing the results from our analytical calculations with the numerical results of our algorithm-not only to test consistency, but also to demonstrate that all assigned polynomials are unique labels of the secondary structure elements. This paves the way for an automatic classification of protein structures.

Reintegrative and Disintegrative Shaming:Legal and Ethical Issues

Abstract
This chapter considers a range of legal and ethical issues raised by the use of reintegrative and disintegrative shaming techniques (Braithwaite, 1989) with sex offenders. ‘Disintegrative shaming’ labels and stigmatises offenders, ostracises them from the local community and may result in violence directed towards offenders (McAlinden, 2005, 2007). ‘Reintegrative shaming’, on the other hand, focuses on rehabilitating the offender within a supportive community environment and assisting the offender in their efforts to change. The former is evident in the range of recent legislative responses designed to protect the community from sex offenders such as notification as well as the popular demand for measures which ‘name and shame’ known sex offenders. The latter is more clearly related to restorative measures such as circles of support and accountability. This chapter argues that although traditionally at opposite ends of the intervention spectrum, each type of mechanism gives rise to potentially difficult legal and ethical considerations.

Extracting Query Interfaces Based on Form Structures and Semantic Similarity

Web databases are now pervasive. Such a database can be accessed via its query interface (usually HTML query form) only. Extracting Web query interfaces is a critical step in data integration across multiple Web databases, which creates a formal representation of a query form by extracting a set of query conditions in it. This paper presents a novel approach to extracting Web query interfaces. In this approach, a generic set of query condition rules are created to define query conditions that are semantically equivalent to SQL search conditions. Query condition rules represent the semantic roles that labels and form elements play in query conditions, and how they are hierarchically grouped into constructs of query conditions. To group labels and form elements in a query form, we explore both their structural proximity in the hierarchy of structures in the query form, which is captured by a tree of nested tags in the HTML codes of the form, and their semantic similarity, which is captured by various short texts used in labels, form elements and their properties. We have implemented the proposed approach and our experimental results show that the approach is highly effective.

Communicating the benefits of wholegrain and functional grain products to European consumers

In order to increase the consumption of wholegrain products or grain products with functional properties, it is important to understand consumer beliefs about such products and the impact of health claims. In a series of consumer studies several differences were found between countries. While consumers in Finland, Italy and the UK saw wholegrain products as having positive attributes, those in Finland had more negative beliefs about refined grain products. Health claims and wholegrain labels increased perceived healthiness but had a less positive impact on likelihood of buying, and in Italy both health claims and wholegrain labels even decreased the likelihood of buying.

Growth of Gold Nanocrystals Incorporated with Magnetic Microbead-based Separation as a Tool for Quantification of Biological Interactions

Au nanoparticles (AuNPs) have been widely used not only as optical labels or ‘weight” labels for the detections of biorecognition events but also an amplifier of surface plasmon resonance biosensors. The intrinsic property of gold nuclei composing of a group of Au atoms to catalyze the reduction of metal ions on the NPs and thereby to enlarge the metallic nanoparticles is employed in different biosensing paths. In a solution containing Au+ ions (e.g. HAuCl4) and the Au clusters, hydrated electrons which are reduced from oxidation of reducers (H2O2, sodium citrate, ascorbic acid, or NaBH4) will be used to reduce the Au+ ion leading to the deposition of Au+ to the Au0 (Au clusters). The reaction will be catalyzed continuously by the Au0 until the Au+ ions and hydrated electrons are exhausted. As a result, the AuNPs will be grown and their optical properties are also changed. If the AuNP nanoclusters are used as probes, the color change will be dependent on amount of analytes, thus give a quantitative monitoring of the analytes.

In this study, we incorporate the use of magnetic beads with the nanocrystalline growth to quantify a target protein based on immunoreactions. Prostate specific antigen (PSA) is chosen as the target analyte because of its values in diagnosis of prostate cancer. A double-sandwiched immunoassay is performed by gold-tagged monoclonal PSA antibody-PSA antigen – magnetic bead-tagged polyclonal PSA antibody interactions. After the immunoreactions, the target analytes are preconcentrated and separated by the magnetic beads while the nanogrowth plays a role of colorimetric signal developer.

The result shows that this is a very sensitive, robust and excellent strategy to detect biological interactions. PSA antigen is detected at femtomolar level with very high specificity under the presence of undesired proteins of crude samples. Furthermore, the method also shows great potential to detect other biological interactions. More details will be described in our presentation.

One-Pot, High-Yield Synthesis of Convex Au Octahedra by H2O2 - Mediated Process In Solution Phase

A simple, non-seeding and high-yield synthesis of convex gold octahedra with size of ca. 50 nm in aqueous solution is described. The octahedral nanoparticles were systematically prepared by reduction of HAuCl4 using ascorbic acid (AA) in the presence of cetyltrimethylammonium bromide (CTAB) as the stabilizing surfactant while concentrations of Au3+ were fixed. The synthesizing process is especially different to other wet synthesis of metallic nanoparticles because it is mediated by H2O2. Mechanism of the H2O2 – mediated process will be described in details. The gold octahedra were shown to be single crystals with all 8 faces belonging to {111} family. Moreover, the single crystalline particles also showed attractive optical properties towards LSPR that should find uses as labels for microscopic imaging, materials for colorimetric biosensings, or nanosensor developments.

Tyrosine nitration of prostacyclin synthase is associated with enhanced retinal cell apoptosis in diabetes

The risk of diabetic retinopathy is associated with the presence of both oxidative stress and toxic eicosanoids. Whether oxidative stress actually causes diabetic retinopathy via the generation of toxic eicosanoids, however, remains unknown. The aim of the present study was to determine whether tyrosine nitration of prostacyclin synthase (PGIS) contributes to retinal cell death in vitro and in vivo. Exposure of human retinal pericytes to heavily oxidized and glycated LDL (HOG-LDL), but not native forms of LDL (N-LDL), for 24 hours significantly increased pericyte apoptosis, accompanied by increased tyrosine nitration of PGIS and decreased PGIS activity. Inhibition of the thromboxane receptor or cyclooxygenase-2 dramatically attenuated HOG-LDL-induced apoptosis without restoring PGIS activity. Administration of superoxide dismutase (to scavenge superoxide anions) or L-N(G)-nitroarginine methyl ester (L-NAME, a nonselective nitric oxide synthase inhibitor) restored PGIS activity and attenuated pericyte apoptosis. In Akita mouse retinas, diabetes increased intraretinal levels of oxidized LDL and glycated LDL, induced PGIS nitration, enhanced apoptotic cell death, and impaired blood-retinal barrier function. Chronic administration of tempol, a superoxide scavenger, reduced intraretinal oxidized LDL and glycated LDL levels, PGIS nitration, and retina cell apoptosis, thereby preserving the integrity of blood-retinal barriers. In conclusion, oxidized LDL-mediated PGIS nitration and associated thromboxane receptor stimulation might be important in the initiation and progression of diabetic retinopathy.

Nile blue-based nano-sized pH sensors for simultaneous far-red and near-infrared live bioimaging

Diblock copolymer vesicles are tagged with pH-responsive Nile Blue-based labels and used as a new type of pH-responsive colorimetric/fluorescent biosensor for far-red and near-infrared imaging of live cells. The diblock copolymer vesicles described herein are based on poly(2-(methacryloyloxy)ethyl phosphorylcholine-block-2-(diisopropylamino)ethyl methacrylate) [PMPC-PDPA]: the biomimetic PMPC block is known to facilitate rapid cell uptake for a wide range of cell lines, while the PDPA block constitutes the pH-responsive component that enables facile vesicle self-assembly in aqueous solution. These biocompatible vesicles can be utilized to detect interstitial hypoxic/acidic regions in a tumor model via a pH-dependent colorimetric shift. In addition, they are also useful for selective intracellular staining of lysosomes and early endosomes via subtle changes in fluorescence emission. Such nanoparticles combine efficient cellular uptake with a pH-responsive Nile Blue dye label to produce a highly versatile dual capability probe. This is in marked contrast to small molecule dyes, which are usually poorly uptaken by cells, frequently exhibit cytotoxicity, and are characterized by intracellular distributions invariably dictated by their hydrophilic/hydrophobic balance.

Food miles or carbon emissions? Exploring labeling preference for food transport footprint with a stated choice study

The ecological footprint of food transport can be communicated using carbon dioxide emissions (CO2 label) or by providing information about both the length of time and the mileage travelled (food miles label). We use stated choice data to estimate conventional unobserved taste heterogeneity models and extend them to a specification that also addresses attribute nonattendance. The implied posterior distributions of the marginal willingness to pay values are compared graphically and are used in validation regressions. We find strong bimodality of taste distribution as the emerging feature, with different groups of subjects having low and high valuations for these labels. The best fitting model shows that CO2 and food miles valuations are much correlated. CO2 valuations can be high even for those respondents expressing low valuations for food miles. However, the reverse is not true. Taken together, the results suggest that consumers tend to value the CO2 label at least as much and sometimes more than the food miles label.

AGWAN: A Generative Model for Labelled, Weighted Graphs

Real-world graphs or networks tend to exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Much effort has been directed into creating realistic and tractable models for unlabelled graphs, which has yielded insights into graph structure and evolution. Recently, attention has moved to creating models for labelled graphs: many real-world graphs are labelled with both discrete and numeric attributes. In this paper, we present AGWAN (Attribute Graphs: Weighted and Numeric), a generative model for random graphs with discrete labels and weighted edges. The model is easily generalised to edges labelled with an arbitrary number of numeric attributes. We include algorithms for fitting the parameters of the AGWAN model to real-world graphs and for generating random graphs from the model. Using the Enron “who communicates with whom” social graph, we compare our approach to state-of-the-art random labelled graph generators and draw conclusions about the contribution of discrete vertex labels and edge weights to the structure of real-world graphs.

What’s in a (Party) Name?: Examining preferences, discipline, and social identity in a parliamentary free vote

In trying to understand the effects of political parties on shaping the voting behaviour of legislators, research has attempted the difficult task of separating the effects of preferences from rules used by party leaders to enforce discipline. However, little research has explored the prospect that party labels also reflect a social identity that is independent of legislators’ preferences and the rules used by party leaders to enforce discipline. In this study we examine that possibility, employing a data set that permits us to control both for leadership-based effects and legislator preferences on a 2000 free vote dealing with stem cell research. Using the British Representation Studies 1997 – which interviewed Members of Parliament regarding their preferences on several key issues related to the bill – we find significant evidence that party-as-identification plays a role in shaping how legislators vote, even after preferences and discipline are accounted for.

AGWAN: A Generative Model for Labelled, Weighted Graphs

Real-world graphs or networks tend to exhibit a well-known set of properties, such as heavy-tailed degree distributions, clustering and community formation. Much effort has been directed into creating realistic and tractable models for unlabelled graphs, which has yielded insights into graph structure and evolution. Recently, attention has moved to creating models for labelled graphs: many real-world graphs are labelled with both discrete and numeric attributes. In this paper, we presentAgwan (Attribute Graphs: Weighted and Numeric), a generative model for random graphs with discrete labels and weighted edges. The model is easily generalised to edges labelled with an arbitrary number of numeric attributes. We include algorithms for fitting the parameters of the Agwanmodel to real-world graphs and for generating random graphs from the model. Using real-world directed and undirected graphs as input, we compare our approach to state-of-the-art random labelled graph generators and draw conclusions about the contribution of discrete vertex labels and edge weights to graph structure.