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This review outlines the current use of magnetic resonance (MR) techniques to study digestion and highlights their potential for providing markers of digestive processes such as texture changes and nutrient breakdown. In vivo digestion research can be challenging due to practical constraints and biological complexity. Therefore, digestion is primarily studied using in vitro models. These would benefit from further in vivo validation. NMR is widely used to characterise food systems. MRI is a related technique that can be used to study both in vitro model systems and in vivo gastro-intestinal processes. MRI allows visualisation and quantification of gastric processes such as gastric emptying and coagulation. Both MRI and NMR scan sequences can be configured to be sensitive to different aspects of gastric or intestinal contents. For example, magnetisation transfer and chemical exchange saturation transfer can detect proton (1H) exchange between water and proteins. MRI techniques have the potential to provide molecular-level and quantitative information on in vivo gastric (protein) digestion. This requires careful validation in order to understand what these MR markers of digestion mean in a specific digestion context. Combined with other measures they can be used to validate and inform in vitro digestion models. This may bridge the gap between in vitro and in vivo digestion research and can aid the optimisation of food properties for different applications in health and disease.
The nature of schizophrenia spectrum disorders with an onset in middle or late adulthood remains controversial. The aim of our study was to determine in patients aged 60 and older if clinically relevant subtypes based on age at onset can be distinguished, using admixture analysis, a data-driven technique. We conducted a cross-sectional study in 94 patients aged 60 and older with a diagnosis of schizophrenia or schizoaffective disorder. Admixture analysis was used to determine if the distribution of age at onset in this cohort was consistent with one or more populations of origin and to determine cut-offs for age at onset groups, if more than one population could be identified. Results showed that admixture analysis based on age at onset demonstrated only one normally distributed population. Our results suggest that in older schizophrenia patients, early- and late-onset ages form a continuum.
Health nudge interventions to steer people into healthier lifestyles are increasingly applied by governments worldwide, and it is natural to look to such approaches to improve health by altering what people choose to eat. However, to produce policy recommendations that are likely to be effective, we need to be able to make valid predictions about the consequences of proposed interventions, and for this, we need a better understanding of the determinants of food choice. These determinants include dietary components (e.g. highly palatable foods and alcohol), but also diverse cultural and social pressures, cognitive-affective factors (perceived stress, health attitude, anxiety and depression), and familial, genetic and epigenetic influences on personality characteristics. In addition, our choices are influenced by an array of physiological mechanisms, including signals to the brain from the gastrointestinal tract and adipose tissue, which affect not only our hunger and satiety but also our motivation to eat particular nutrients, and the reward we experience from eating. Thus, to develop the evidence base necessary for effective policies, we need to build bridges across different levels of knowledge and understanding. This requires experimental models that can fill in the gaps in our understanding that are needed to inform policy, translational models that connect mechanistic understanding from laboratory studies to the real life human condition, and formal models that encapsulate scientific knowledge from diverse disciplines, and which embed understanding in a way that enables policy-relevant predictions to be made. Here we review recent developments in these areas.
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