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Otten, W.

Publications and source records attributed to Otten, W..

2 recordsLinked to original sources

The inner dynamics of positive human-animal interactions: investigating the roles of oxytocin, opioids, dopamine, serotonin and the proteome

Research on the neuroendocrine basis of positive interactions has predominantly focused on oxytocin (OT), although dopamine (DA) and opioids also play crucial roles. Furthermore, these neurotransmitters are known to interact with each other but have seldom been studied concurrently. In this study, we quantified longitudinal changes in these neurotransmitters using a within-subject, 2 x 2 factorial design by varying human familiarity (familiar versus unfamiliar) and contact type (positive contacts versus ignoring) for 10 min human-pig interaction sessions. We repeatedly sampled cerebrospinal fluid from 10 pigs through a spinal catheter 65 and 5 min before the test and at 10, 30, 60, 120 and 240 min after the start of the test. Samples at various timepoints were analysed for OT, DA metabolites 3,4-dihydroxyphenylacetic acid (DOPAC) and homovanillic acid (HVA), serotonin metabolite 5-hydroxyindoleacetic acid (5-HIAA), {beta}-endorphin opioids concentrations, and using proteomics to explore novel protein candidates. The test condition (human familiarity x contact type) had a significant effect on the concentration of {beta}-endorphin (F1,118.59 = 4.45; P = 0.04) and 5-HIAA (F1,73.47 = 5.02; P = 0.03), and tended to affect the concentration of oxytocin (F1, 119.8 = 3.19; P = 0.08) and DOPAC (F1,70.57 = 3.31; P = 0.07), but pair-wise comparisons were not significant. There was only a minor effect on the pigs behaviour, which suggests that the test conditions may have had limited effect. Nevertheless, this approach provides a valuable method to study neurotransmitter changes over time and simultaneously. Highlights- Oxytocin was higher when pigs were ignored than when they had positive contacts - Oxytocin was highest in the novel condition of an unfamiliar human ignoring the pig - Human familiarity and contact type affected {beta}-endorphin and 5-HIAA concentrations - Dopamine metabolites and the proteome were not affected by the test conditions

animal behavior and cognition↗

Linking rhizosphere processes across scales: Opinion

PurposeSimultaneously interacting small-scale rhizosphere processes determine emergent plant-scale behaviour, including growth, transpiration, nutrient uptake, soil carbon storage and transformation by microorganisms. Current advances in modelling and experimental methods open the path to unravel and link those processes. MethodsWe present a series of examples of state-of-the art simulations addressing this multi-scale, multi-process problem from a modelling point of view, as well as from the point of view of integrating newly available rhizosphere data and images. ResultsEach example includes a model that links scales and experimental data to set-up simulations that explain and predict spatial and temporal distribution of rhizodeposition as driven by root architecture development, soil structure, presence of root hairs, soil water content and distribution of soil water. Furthermore, two models explicitly simulate the impact of the rhizodeposits on plant nutrient uptake and soil microbial activity, respectively. This exemplifies the currently available state of the art modelling tools in this field: image-based modelling, pore-scale modelling, continuum scale modelling and functional-structural plant modelling. We further show how to link the pore scale to the continuum scale by homogenisation or by deriving effective physical parameters like viscosity from nano-scale chemical properties. ConclusionModelling allows to integrate and make use of new experimental data across different rhizosphere processes (and thus across different disciplines) and scales. Described models are tools to test hypotheses and consequently improve our mechanistic understanding of how rhizosphere processes impact plant-scale behaviour. Linking multiple scales and processes is the logical next step for future research.

bioengineering↗