Analysis of postprandial lipemia as a Cardiovascular Disease risk factor using genetic and clinical information: an Artificial Neural Network perspective

Clinical studies indicate that exaggerated postprandial lipemia is linked to the progression of atherosclerosis, leading cause of Cardiovascular Diseases (CVD). CVD is a multi-factorial disease with complex etiology and according to the literature postprandial Triglycerides (TG) can be used as an independent CVD risk factor. Aim of the current study is to construct an Artificial Neural Network (ANN) based system for the identification of the most important gene-gene and/or gene-environmental interactions that contribute to a fast or slow postprandial metabolism of TG in blood and consequently to investigate the causality of postprandial TG response. The design and development of the system is based on a dataset of 213 subjects who underwent a two meals fatty prandial protocol. For each of the subjects a total of 30 input variables corresponding to genetic variations, sex, age and fasting levels of clinical measurements were known. Those variables provide input to the system, which is based on the combined use of Parameter Decreasing Method (PDM) and an ANN. The system was able to identify the ten (10) most informative variables and achieve a mean accuracy equal to 85.21%.

The stable isotopic composition of Daphnia ephippia reflects changes in δ13C and δ18O values of food and water

The stable isotopic composition of fossil resting eggs (ephippia) of Daphnia spp. is being used to reconstruct past environmental conditions in lake ecosystems. However, the underlying assumption that the stable isotopic composition of the ephippia reflects the stable isotopic composition of the parent Daphnia, of their diet and of the environmental water have yet to be confirmed in a controlled experimental setting. We performed experiments with Daphnia pulicaria cultures, which included a control treatment conducted at 12 °C in filtered lake water and with a diet of fresh algae and three treatments in which we manipulated the stable carbon isotopic composition (δ13C value) of the algae, stable oxygen isotopic composition (δ18O value) of the water and the water temperature, respectively. The stable nitrogen isotopic composition (δ15N value) of the algae was similar for all treatments. At 12 °C, differences in algal δ13C values and in δ18O values of water were reflected in those of Daphnia. The differences between ephippia and Daphnia stable isotope ratios were similar in the different treatments (δ13C: +0.2 ± 0.4 ‰ (standard deviation); δ15N: −1.6 ± 0.4 ‰; δ18O: −0.9 ± 0.4 ‰), indicating that changes in dietary δ13C values and in δ18O values of water are passed on to these fossilizing structures. A higher water temperature (20 °C) resulted in lower δ13C values in Daphnia and ephippia than in the other treatments with the same food source and in a minor change in the difference between δ13C values of ephippia and Daphnia (to −1.3 ± 0.3 ‰). This may have been due to microbial processes or increased algal respiration rates in the experimental containers, which may not affect Daphnia in natural environments. There was no significant difference in the offset between δ18O and δ15N values of ephippia and Daphnia between the 12 and 20 °C treatments, but the δ18O values of Daphnia and ephippia were on average 1.2 ‰ lower at 20 °C than at 12 °C. We conclude that the stable isotopic composition of Daphnia ephippia provides information on that of the parent Daphnia and of the food and water they were exposed to, with small offsets between Daphnia and ephippia relative to variations in Daphnia stable isotopic composition reported from downcore studies. However, our experiments also indicate that temperature may have a minor influence on the δ13C, δ15N and δ18O values of Daphnia body tissue and ephippia. This aspect deserves attention in further controlled experiments.

Soil and land information: How to support decision-making?

Soils are fundamental to ensuring water, energy and food security. Within the context of sus- tainable food production, it is important to share knowledge on existing and emerging tech- nologies that support land and soil monitoring. Technologies, such as remote sensing, mobile soil testing, and digital soil mapping, have the potential to identify degraded and non- /little-responsive soils, and may also provide a basis for programmes targeting the protection and rehabilitation of soils. In the absence of such information, crop production assessments are often not based on the spatio-temporal variability in soil characteristics. In addition, uncertain- ties in soil information systems are notable and build up when predictions are used for monitor- ing soil properties or biophysical modelling. Consequently, interpretations of model-based results have to be done cautiously. As such they provide a scientific, but not always manage- able, basis for farmers and/or policymakers. In general, the key incentives for stakeholders to aim for sustainable management of soils and more resilient food systems are complex at farm as well as higher levels. The same is true of drivers of soil degradation. The decision- making process aimed at sustainable soil management, be that at farm or higher level, also in- volves other goals and objectives valued by stakeholders, e.g. land governance, improved envi- ronmental quality, climate change adaptation and mitigation etc. In this dialogue session we will share ideas on recent developments in the discourse on soils, their functions and the role of soil and land information in enhancing food system resilience.