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BACKGROUND/OBJECTIVES: The research question addressed in this paper is how different reference amounts utilised in front of package nutrition labelling influence evaluation of product healthfulness. SUBJECTS/METHODS: A total of 13 117 participants from six European countries (Germany, UK, Spain, France, Poland and Sweden) were recruited via online panels. A mixed between/within-subject factorial design was employed with food (biscuits, sandwiches, yogurts), healthfulness and presence of Guideline Daily Amounts as within-subjects factors and reference amount ('per 100 g', 'typical portion', 'half portion') and country as between-subjects factors. RESULTS: Overall, people correctly ranked foods according to their objective healthfulness as defined by risk nutrients alone, and could distinguish between more and less healthful variants of foods. General healthfulness associations with the three product categories do not appear to have had a strong influence on product ratings. This study shows that where the reference amount of 'per 100 g' is very different from the 'typical' portion size, as was the case for biscuits, products with a 'per 100 g' label are rated significantly less healthful than the 'typical' or 'half typical' portions. CONCLUSION: The results indicate that across the three food categories, consumers do factor the reference amount, that is, the quantity of food for which the nutritional information is being presented, into their judgements of healthfulness. Therefore, appropriate reference amounts are also of importance for the effective presentation of nutritional information. European Journal of Clinical Nutrition (2015) 69, 619-625; doi: 10.1038/ejcn.2014.190; published online 5 November 2014, INTRODUCTION On both back of package and front of package (FoP), the reference amount chosen forms an integral part of the nutrition information displayed on packaging. As the provision of [...]

Author(s): A Kaur; P Scarborough; S Hieke; A Kusar; I Pravst; M Raats; M Rayner Correction to: European Journal of Clinical Nutrition advance online publication 13 July 2016; doi:/doifinder/10.1038/ejcn.2016.114 Updated [...]

The thermal stability of evaporated copper-chromium alloy films was studied by correlating hardness trends from nanoindentation to nanostructural-compositional changes from transmission electron microscopy. In particular, the hardness evolution with ageing time at ambient and elevated temperatures of two compositions, dilute (CuCr) and chromium-rich (CuCr) solutions, was studied. Due to the negligible mutual miscibility of copper and chromium, the chosen solid solutions are trapped in metastable states as supersaturated solid solutions with face-centred cubic and body-centred cubic phases. Nano-mechanical probing of the nanostructural evolution as a function of temperature provided interesting insights into the phase separation of these systems. [ABSTRACT FROM AUTHOR]

The article presents a case study which examines the cost of implementation of cloud computing technologies in a biometry department. It explores the advantage of the cloud computing technologies provided by Amazon Web Services LLC which offers cost effective technologies for biometry research units. It mentions that the cost of the cloud computing resources set up in biomedical researches depends upon the hardware of the cloud computing technologies.

Objective: As a means of empowering consumers, nutrition labelling has become a widely discussed topic. Simplicity and uniformity of labelling systems are regarded as the prevailing demands from the consumer side. In the present study, we analyse the effects of the traffic light signposting scheme on consumers' food choices.Design: In an online survey, respondents first rated the understandability of the traffic light signposting scheme. In a following conjoint experiment, they indicated which products they would select as the healthiest of the presented products, based on the nutritive information provided by the traffic light signposting scheme.Setting: A major German university.Subjects: In total 2002 undergraduate students participated in the survey. Two-thirds (69 %) of the respondents were female and the majority of the respondents (70 %) were between 18 and 24 years old. Seventy-seven per cent of the participants indicated that they had a higher level of education.Results: Overall, the participants rated the understandability of the traffic light nutrition signposting scheme fairly high (5.9 out of 7). Sugar and fat were found to be the most important attributes of the scheme. Participants placed greater emphases on a change in a product's nutrient characteristic from 'amber to 'red' compared with a change from 'green' to 'amber'.Conclusions: Our results confirm the signalling effect of colour coding as it helps reduce the complexity of decision making. Our findings shed new light on the ongoing discussion concerning appropriate and efficient nutrition labelling and provide interesting insights for further research as well as implications for public policy making. [ABSTRACT FROM AUTHOR]

Taking a point of departure in the idea that technology features can act as cues for sensemaking, we explore how the public makes sense of new active packaging technologies; technologies that absorb or release substances from or into the packaging atmosphere, preserving the freshness and safety of food products. Based on data from ten focus groups across five countries (Ireland, Denmark, Italy, Spain and China), we show that sensemaking occurs at two feature-proximity levels. At the first level, we observe the production of proximal representations , where salient technology features drive the sensemaking process and how the individuals come to understand the essence of the technology. At the second level, we observe the production of distal representations , where distinct technology features become less salient, and the holistic understanding of the technology takes over in how individuals come to understand the locus of the technology in broader contexts. Our insights contribute to theory regarding public sensemaking of novel technologies and have practical implications for stakeholders who aim to increase their adoption prospects.

This work presents the synthesis of MoO 2 /MoS 2 core/shell nanoparticles within a carbon nanotube network and their detailed electron microscopy investigation in up to three dimensions. The triple-hybrid core/shell material was prepared by atomic layer deposition of molybdenum oxide onto carbon nanotube networks, followed by annealing in a sulfur-containing gas atmosphere. High-resolution transmission electron microscopy together with electron diffraction, supported by chemical analysis via energy dispersive X-ray and electron energy loss spectroscopy, gave proof of a MoO 2 core covered by few layers of a MoS 2 shell within an entangled network of carbon nanotubes. To gain further insights into this complex material, the analysis was completed with 3D electron tomography. By using Z -contrast imaging, distinct reconstruction of core and shell material was possible, enabling the analysis of the 3D structure of the material. These investigations showed imperfections in the nanoparticles which can impact material performance, i.e. for faradaic charge storage or electrocatalysis., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

How a catalyst behaves microscopically under reaction conditions, and what kinds of active sites transiently exist on its surface, is still very much a mystery to the scientific community. Here we present an in situ study on the red-ox behaviour of copper in the model reaction of hydrogen oxidation. Direct imaging combined with on-line mass spectroscopy shows that activity emerges near a phase boundary, where complex spatio-temporal dynamics are induced by the competing action of simultaneously present oxidizing and reducing agents. Using a combination of in situ imaging with in situ X-ray absorption spectroscopy and scanning photoemission microscopy, we reveal the relation between chemical and morphological dynamics and demonstrate that a static picture of active sites is insufficient to describe catalytic function of redox-active metal catalysts. The observed oscillatory redox dynamics provide a unique insight on phase-cooperation and a convenient and general mechanism for constant re-generation of transient active sites.

Prognosis is usually expressed in terms of the probability that a patient will or will not have experienced an event of interest t years after diagnosis of a disease. This quantity, however, is of little informative value for a patient who is still event-free after a number of years. Such a patient would be much more interested in the conditional probability of being event-free in the upcoming t years, given that he/she did not experience the event in the s years after diagnosis, called "conditional survival." It is the simplest form of a dynamic prediction and can be dealt with using straightforward extensions of standard time-to-event analyses in clinical cohort studies. For a healthy individual, a related problem with further complications is the so-called "age-conditional probability of developing cancer" in the next t years. Here, the competing risk of dying from other diseases has to be taken into account. For both situations, the hazard function provides the central dynamic concept, which can be further extended in a natural way to build dynamic prediction models that incorporate both baseline and time-dependent characteristics. Such models are able to exploit the most current information accumulating over time in order to accurately predict the further course or development of a disease. In this article, the biostatistical challenges as well as the relevance and importance of dynamic prediction are illustrated using studies of multiple myeloma, a hematologic malignancy with a formerly rather poor prognosis which has improved over the last few years., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Despite the fact that front-of-pack nutrition labels such as health claims and symbols have received growing attention in consumer behavior research, comprehensive conclusions could not yet be drawn to develop concrete policy actions, owing to the complexity of the subject and a constantly changing market environment. In this study, evidence-based policy recommendations and communication guidelines have been derived from the findings of the EU FP7 project CLYMBOL ("Role of health-related CLaims and sYMBOLs in consumer behavior", Grant Agreement 311963), and have been evaluated and prioritized by European stakeholders using a three-round Delphi method. A moderate level of consensus was achieved and results suggest that policy priority should focus on ways to improve consumer motivation and interest in healthy eating. Consumers' interest in healthy eating could be increased by adopting appropriate communication strategies such as using innovative ways to communicate the importance of healthy eating, which may aim to change the possible negative association between healthiness and tastiness. The highest-rated finding was related to consumers' favorable attitude towards health claims with shorter and less complex messages and health symbols with a visible endorsement. Meanwhile, there was a clear consensus that health claims need to be scientifically substantiated and credible but phrased without using overly complex scientific wordings, in order to be meaningful for consumers. Furthermore, stakeholders from academia and industry believe that consumer awareness about existing health claims should be increased. The identified policy recommendations and communication guidelines stem from recent empirical evidence and provide useful insights that guide future policy development aligning consumer protection issues as well as public health and food marketing communication interests.

Background: Nutrition-related knowledge (NRK) and nutrition-related attitudes (NRAs) are necessary for dietary changes toward healthier dietary patterns. In turn, healthier dietary patterns can be beneficial in maintaining health of older adults. Therefore, the aim of this cross-sectional study was to investigate whether NRK and NRAs were associated with lifestyle and health features among older adults (65+ years) from five European countries (France, Italy, Poland, the Netherlands and United Kingdom). Methods: Within the European project NU-AGE, 1,144 healthy elderly volunteers (65-79 years) were randomly assigned to two groups: intervention (NU-AGE diet) or control. After 1-year of follow-up, both NRK and NRAs were assessed during exit interviews, in combination with a number of lifestyle and health variables (e.g., physical activity, smoking, alcohol use, BMI, self-assessed health status). Multivariable linear regression models were used in data analysis. Results: In the NU-AGE study sample, good NRK was associated with lower BMI and higher physical activity. More positive NRAs were related to lower BMI and self-reported very good or good appetite. Moreover, both NRK and NRAs were associated with some socio-economic determinants, like financial situation, age, education, living area (for NRK), and country (for NRAs). Participants in the intervention group showed a better NRK (β = 0.367 [95% CI: 0.117; 0.617], p = 0.004) and more positive NRAs (β = 0.838 [95% CI: 0.318; 1.358], p = 0.002) than those in the control group. Higher self-evaluated knowledge was also significantly related to more positive NRAs ( p < 0.001). The most popular sources of nutrition information were food labels, books and magazines on health, the dietitian and the doctor's office, although their importance varied significantly among countries, and, to a lesser extent, between women and men and between intervention and control group. Conclusion: Higher NRK and NRA scores were associated with lower BMI and higher physical activity level. Therefore, a good nutrition-related knowledge and positive nutrition-related attitudes can strongly and positively influence the health status and quality of life among the older population. These results offer a great opportunity for policy makers to implement educational programs in order to counteract the epidemic of obesity and to improve the health span of European population.

Purpose: To test the effectiveness of a central venous catheter (CVC) insertion strategy and a hand hygiene (HH) improvement strategy to prevent central venous catheter-related bloodstream infections (CRBSI) in European intensive care units (ICUs), measuring both process and outcome indicators., Methods: Adult ICUs from 14 hospitals in 11 European countries participated in this stepped-wedge cluster randomised controlled multicentre intervention study. After a 6 month baseline, three hospitals were randomised to one of three interventions every quarter: (1) CVC insertion strategy (CVCi); (2) HH promotion strategy (HHi); and (3) both interventions combined (COMBi). Primary outcome was prospective CRBSI incidence density. Secondary outcomes were a CVC insertion score and HH compliance., Results: Overall 25,348 patients with 35,831 CVCs were included. CRBSI incidence density decreased from 2.4/1000 CVC-days at baseline to 0.9/1000 (p < 0.0001). When adjusted for patient and CVC characteristics all three interventions significantly reduced CRBSI incidence density. When additionally adjusted for the baseline decreasing trend, the HHi and COMBi arms were still effective. CVC insertion scores and HH compliance increased significantly with all three interventions., Conclusions: This study demonstrates that multimodal prevention strategies aiming at improving CVC insertion practice and HH reduce CRBSI in diverse European ICUs. Compliance explained CRBSI reduction and future quality improvement studies should encourage measuring process indicators.

With growing numbers of elderly multiple myeloma patients, reliable tools to assess their vulnerability are required. The objective of the analysis herein was to develop and validate an easy to use myeloma risk score (revised Myeloma Comorbidity Index) that allows for risk prediction of overall survival and progression-free survival differences in a large patient cohort. We conducted a comprehensive comorbidity, frailty and disability evaluation in 801 consecutive myeloma patients, including comorbidity risks obtained at diagnosis. The cohort was examined within a training and validation set. Multivariate analysis determined renal, lung and Karnofsky Performance Status impairment, frailty and age as significant risks for overall survival. These were combined in a weighted revised Myeloma Comorbidity Index, allowing for the identification of fit (revised Myeloma Comorbidity Index ≤3 [n=247, 30.8%]), intermediate-fit (revised Myeloma Comorbidity Index 4-6 [n=446, 55.7%]) and frail patients (revised Myeloma Comorbidity Index >6 [n=108, 13.5%]): these subgroups, confirmed via validation analysis, showed median overall survival rates of 10.1, 4.4 and 1.2 years, respectively. The revised Myeloma Comorbidity Index was compared to other commonly used comorbidity indices (Charlson Comorbidity Index, Hematopoietic Cell Transplantation-Specific Comorbidity Index, Kaplan-Feinstein Index): if each were divided in risk groups based on 25% and 75% quartiles, highest hazard ratios, best prediction and Brier scores were achieved with the revised Myeloma Comorbidity Index. The advantages of the revised Myeloma Comorbidity Index include its accurate assessment of patients' physical conditions and simple clinical applicability. We propose the revised Myeloma Comorbidity Index to be tested with the "reference" International Myeloma Working Group frailty score in multicenter analyses and future clinical trials. The study was registered at the German Clinical Trials Register (DRKS-00003868)., (Copyright© Ferrata Storti Foundation.)

Background: High-throughput technology allows for genome-wide measurements at different molecular levels for the same patient, e.g. single nucleotide polymorphisms (SNPs) and gene expression. Correspondingly, it might be beneficial to also integrate complementary information from different molecular levels when building multivariable risk prediction models for a clinical endpoint, such as treatment response or survival. Unfortunately, such a high-dimensional modeling task will often be complicated by a limited overlap of molecular measurements at different levels between patients, i.e. measurements from all molecular levels are available only for a smaller proportion of patients., Results: We propose a sequential strategy for building clinical risk prediction models that integrate genome-wide measurements from two molecular levels in a complementary way. To deal with partial overlap, we develop an imputation approach that allows us to use all available data. This approach is investigated in two acute myeloid leukemia applications combining gene expression with either SNP or DNA methylation data. After obtaining a sparse risk prediction signature e.g. from SNP data, an automatically selected set of prognostic SNPs, by componentwise likelihood-based boosting, imputation is performed for the corresponding linear predictor by a linking model that incorporates e.g. gene expression measurements. The imputed linear predictor is then used for adjustment when building a prognostic signature from the gene expression data. For evaluation, we consider stability, as quantified by inclusion frequencies across resampling data sets. Despite an extremely small overlap in the application example with gene expression and SNPs, several genes are seen to be more stably identified when taking the (imputed) linear predictor from the SNP data into account. In the application with gene expression and DNA methylation, prediction performance with respect to survival also indicates that the proposed approach might work well., Conclusions: We consider imputation of linear predictor values to be a feasible and sensible approach for dealing with partial overlap in complementary integrative analysis of molecular measurements at different levels. More generally, these results indicate that a complementary strategy for integrating different molecular levels can result in more stable risk prediction signatures, potentially providing a more reliable insight into the underlying biology.

Clinical cohorts with time-to-event endpoints are increasingly characterized by measurements of a number of single nucleotide polymorphisms that is by a magnitude larger than the number of measurements typically considered at the gene level. At the same time, the size of clinical cohorts often is still limited, calling for novel analysis strategies for identifying potentially prognostic SNPs that can help to better characterize disease processes. We propose such a strategy, drawing on univariate testing ideas from epidemiological case-controls studies on the one hand, and multivariable regression techniques as developed for gene expression data on the other hand. In particular, we focus on stable selection of a small set of SNPs and corresponding genes for subsequent validation. For univariate analysis, a permutation-based approach is proposed to test at the gene level. We use regularized multivariable regression models for considering all SNPs simultaneously and selecting a small set of potentially important prognostic SNPs. Stability is judged according to resampling inclusion frequencies for both the univariate and the multivariable approach. The overall strategy is illustrated with data from a cohort of acute myeloid leukemia patients and explored in a simulation study. The multivariable approach is seen to automatically focus on a smaller set of SNPs compared to the univariate approach, roughly in line with blocks of correlated SNPs. This more targeted extraction of SNPs results in more stable selection at the SNP as well as at the gene level. Thus, the multivariable regression approach with resampling provides a perspective in the proposed analysis strategy for SNP data in clinical cohorts highlighting what can be added by regularized regression techniques compared to univariate analyses.