Effects of Digested Onion Extracts on Intestinal Gene Expression: An Interspecies Comparison Using Different Intestine Models.

Human intestinal tissue samples are barely accessible to study potential health benefits of nutritional compounds. Numbers of animals used in animal trials, however, need to be minimalized. Therefore, we explored the applicability of in vitro (human Caco-2 cells) and ex vivo intestine models (rat precision cut intestine slices and the pig in-situ small intestinal segment perfusion (SISP) technique) to study the effect of food compounds. In vitro digested yellow (YOd) and white onion extracts (WOd) were used as model food compounds and transcriptomics was applied to obtain more insight into which extent mode of actions depend on the model. The three intestine models shared 9,140 genes which were used to compare the responses to digested onions between the models. Unsupervised clustering analysis showed that genes up- or down-regulated by WOd in human Caco-2 cells and rat intestine slices were similarly regulated by YOd, indicating comparable modes of action for the two onion species. Highly variable responses to onion were found in the pig SISP model. By focussing only on genes with significant differential expression, in combination with a fold change > 1.5, 15 genes showed similar onion-induced expression in human Caco-2 cells and rat intestine slices and 2 overlapping genes were found between the human Caco-2 and pig SISP model. Pathway analyses revealed that mainly processes related to oxidative stress, and especially the Keap1-Nrf2 pathway, were affected by onions in all three models. Our data fit with previous in vivo studies showing that the beneficial effects of onions are mostly linked to their antioxidant properties. Taken together, our data indicate that each of the in vitro and ex vivo intestine models used in this study, taking into account their limitations, can be used to determine modes of action of nutritional compounds and can thereby reduce the number of animals used in conventional nutritional intervention studies

Evaluation of sleep, puberty and mental health in children with long-term melatonin treatment for chronic idiopathic childhood sleep onset insomnia

OBJECTIVES: To establish whether long-term use of melatonin influences pubertal development, sleep quality and mental health development in children as compared with the normal Dutch population of the same age. METHODS: This follow-up research study was conducted in children included in a previous melatonin dose-finding trial. Outcomes were measured using questionnaires (Strength and Difficulties Questionnaire (SDQ), Children's Sleep Habits Questionnaire (CSHQ) and Tanner Stages) adopted for Dutch children. Mean duration of therapy, persistence of effect, adverse events and (other) reasons leading to cessation of therapy were additional objectives of this study. RESULTS: Mean years of usage (n = 51) was 3.1 years (min 1.0 year, max 4.6 years), mean dose 2.69 mg (min 0.3 mg, max 10 mg). Mean SDQ score, mean CSHQ score and Tanner Stages standard deviation scores did not differ in a statistically significant way from published scores of the general Dutch population of the same age and sex. CONCLUSIONS: This follow-up study demonstrates that melatonin treatment in children can be sustained over a long period of time without substantial deviation of the development of children with respect to sleep quality, puberty development and mental health scores, as compared with the general Dutch population

Living Labs for healthy landscapes

Item does not contain fulltext-, 4 september 2018Nijmegen : [S.n.

Optimising First-Class Pattern Matching

Pattern matching is a high-level notation for programs to analyse the shape of data, and can be optimised to efficient low-level instructions. The Stratego language uses first-class pattern matching, a powerful form of pattern matching that traditional optimisation techniques do not apply to directly.In this paper, we investigate how to optimise programs that use first-class pattern matching. Concretely, we show how to map first-class pattern matching to a form close to traditional pattern matching, on which standard optimisations can be applied.Through benchmarks, we demonstrate the positive effect of these optimisations on the run-time performance of Stratego programs. We conclude that the expressive power of first-class pattern matching does not hamper the optimisation potential of a language that features it

WINNER: Living Labs Water Indonesia

We will illustrate and discuss how Living Labs can be used to address so called wicked problems in Delta Areas. We will specifically address the role of students and research in this concept. Participants are challenged by questions and are also asked to think whether and how they could take part in one of the ongoing Living Labs initiatives

Co-creatieve rivierlandschappen

For centuries the Dutch fluvial landscape has been shaped by shipping, agriculture, clay and sand mining. In the eighties of the previous century nature and environmental issues received considerable s o c i e t al and political attention. With the publication of the so-called 'Plan Stork', an ecological approach on river and floodplain management and its natural values were rediscovered. In the slipstream of these developments the fluvial landscape became increasingly interesting for leisure, recreation and housing. Also the number of land use claims in the floodplains increased. Finding a balance between these claims became increasingly difficult after the bankfull discharges of the Meuse and Rhine in 1993 and 1995 which resulted in the evacuation of 250.000 people. After these events the national authorities were looking for ways to increase the water discharge capacity of the river system. It appeared to be quite a challenge to combine the various land use claims into a safe, biodivers and economic viable fluvial landscape. The so-called EMAB experiment (i.e. experiments with adaptive housing/building) was a first attempt. However, an evaluation of EMAB pointed out that only in a few cases this synergy was realized. Probably because the initiators kept the project development to themselves excluding additional ideas, money and efforts. The application of the concept co-creation was more successful in the so-called 'Wealthy Waal'project. In this bottom-up initiative 15 municipalities worked together with knowledge institutes, entrepreneurs and citizens/ NGOs to develop a multifunctional land use plan for the floodplains along the 80 km Rhine-Waal branch. Since then the demand for optimizing co-creation processes in the fluvial landscape has steadily increased. This article briefly describes the outcome of the EMAB and Wealthy Waal experiment and focuses on the latest insights of co-creation; the so-called Living Labs. In The Netherlands a number of universities are collaborating with water boards and other governmental organisati-ons to address complex water related land use issues. This so-called Delta Platform constructed a Living Lab approach which among other issues is used to combine various land use functions in the Dutch urbanized fluvial system. In the process of co-creation choices between different land use scenarios have to be made. Within this context the development of the tool 'RiverScape' is elucidated. Riverscape is a decision support tool calculating the effect of specific land use functions on flood risks, biodiversity, involved costs and the number of land owners involved. A Living Lab approach needs to be tailor made to each socio-cultural context and landscape type, but a number of generic conditions can be identified to make the co-creation successful. The first results of working with this Living Lab methodology are promising (wide public support, streamlining human and financial resources). It requires new skills of Living Lab participants to work in a non-hierarchical, transparent context and to share human and financial resources in a process where the precise final outcome is unknown. It is suggested that in particular knowledge institutes such as universities of applied sciences can play a pivotal role in the initiation and facilitation of Living Labs

Optimising First-Class Pattern Matching

Pattern matching is a high-level notation for programs to analyse the shape of data, and can be optimised to efficient low-level instructions. The Stratego language uses first-class pattern matching, a powerful form of pattern matching that traditional optimisation techniques do not apply to directly.In this paper, we investigate how to optimise programs that use first-class pattern matching. Concretely, we show how to map first-class pattern matching to a form close to traditional pattern matching, on which standard optimisations can be applied.Through benchmarks, we demonstrate the positive effect of these optimisations on the run-time performance of Stratego programs. We conclude that the expressive power of first-class pattern matching does not hamper the optimisation potential of a language that features it.Programming Language