- ItemRooibos (Aspalathus linearis) and honeybush (Cyclopia spp.) : from bush teas to potential therapy for cardiovascular disease(IntechOpen, 2019) Windvogel, ShantalCardiovascular disease (CVD) is a leading cause of worldwide deaths. A number of risk factors for cardiovascular disease as well as type 2 diabetes and stroke present as the metabolic syndrome. Metabolic risk factors include hypertension, abdominal obesity, dyslipidaemia and increased blood glucose levels and may also include risk factors such as vascular dysfunction, insulin resistance, low high density lipoprotein (HDL) cholesterol levels and inflammation. Rooibos (Aspalathus linearis) and honeybush (Cyclopia spp.) are indigenous South African plants whose reported health benefits include anti-tumour, anti-inflammatory, anti-obesity, antioxidant, cardioprotective and anti-diabetic properties. The last two decades have seen worldwide interest and success for these plants, not only as health beverages but also as preservatives, flavourants and skincare products. This review will focus on the current literature supporting the function of these plants as nutraceuticals capable of potentially reducing the risk of cardiovascular disease.
- ItemDietary impact on neuronal autophagy control and brain health(IntechOpen, 2019) Ntsapi, Claudia; Du Toit, Andre; Loos, BenAutophagy is the major intracellular system which is critical for the removal of harmful protein aggregates and malfunctioning organelles. Dysfunctional autophagy is associated with a multitude of human diseases, such as protein aggregation in Alzheimer’s disease and non-successful aging. Major interest exists in the dietary manipulation of the autophagy pathway activity, so as to tune the cell’s protein degradation capabilities and to prevent cell death onset. It has recently become clear that the machinery required to degrade protein cargo has a distinct activity level which can be altered through specific dietary modulation. Moreover, this activity may differ from that of the proteinaceous cargo. Overall, brain health and successful aging are characterized by limited protein aggregation, with a distinct molecular signature of maintained autophagy function. However, it is largely unclear how to control autophagy through dietary interventions with a precision that would allow to maintain minimal levels of toxic proteins, preserving neuronal cell viability and proteostasis. In this chapter, we carefully dissect the relationship between autophagy- modulating drugs, including caloric restriction mimetics and their impact on neuronal autophagy, in the context of preserving brain health.
- ItemUsing rodent models to simulate stress of physiologically relevant severity : when, why and how(InTech, Rijeka, Croatia, 2012) Smith, CarineGiven the demands of modern life, it is no wonder that the concept of stress has become a household topic for discussion. Also in the academic realm the phenomenon which is stress, is topping the charts in terms of research interest. The short term costs as well as the long term maladaptive effects of stress have been a popular topic of research in especially physiology and psychology for the past few decades, ever since Hans Selye defined the term “stress” in 1956 (Selye, 1956). Stress-related chronic disease, such as cardiovascular disease, diabetes and depression, places an ever-increasing burden on society – medically, socially and financially. Therefore, if we are to limit the spread and impact of this “pandemic”, it is imperative to properly manage the effects of stress on our bodies. This of course, is only possible if we have a complete understanding of the body’s response to stress. The response to stress is almost never localised and contained. Rather, a stress response is initiated in response to a local physical (e.g. contusion to skeletal muscle) or mental (e.g. the loss of a loved one) stressor, but always culminates in a wide-spread, systemic response process that affects many organs and systems. Consider for a moment a less complex research model in a different discipline. Metabolic pathways (e.g. the Krebs cycle or glycolysis) can easily be manipulated in cell culture assays using one single cell type at a time, since these pathways (including substrate supply and waste removal systems) are contained in its entirety within each cell. In contrast, with the stress response pathways this is clearly not the case. The stress response is a complex network of events, which is directed via two interlinked pathways, one endocrine (the hypothalamic pituitary adrenal (HPA)-axis) and one neural (the locus coeruleus norepinephrine (LC-NE) or sympatho-adrenal medullary (SAM)- system). While the neural pathway is mainly activated neurally in response to stress perception, leading to the well-known “fight-or-flight” response, the endocrine pathway has many more triggers. Apart from neural activation, the HPA-axis is also activated by a large number of hormones and even chemical messengers, such as interleukin-6, a cytokine and mediator of inflammation, which is known to increase cortisol secretion. A contributing factor to the complexity of the HPA-axis is the fact that cortisol, the main end product of this stress response, has both endocrine and metabolic functions. Although cortisol is commonly known as the “stress hormone” in the context of psychological stress, its main function is actually metabolic – to maintain glucose supply to the brain. Therefore, the HPA-axis is structured not only for activation in response to perceived stress, but also to react to metabolic stimuli. Furthermore, while the stress response should be powerful and fast in an acute stress situation, the response should be controlled and relatively more limited in a situation of chronic stress, to prevent detrimental effects to the organism in the long term. One can appreciate therefore the need for relatively complex signalling networks in this regard, which serves to activate, limit or inhibit the stress response. To achieve this, numerous molecular mechanisms are in place, and react and interact in response to various stress signals. To give just one example, the glucocorticoid receptor, which is present on most cells to enable cortisol’s effect on these cells, is up-regulated in response to acute stress, but down-regulated after a period of chronic stress. Such complexities make the choice of a suitable stress research model both a difficult, and vital one. While some mechanisms, e.g. activation agents of specific adrenal or pituitary cell types, may be elucidated in cell culture, a whole-system model is required in order to assess the net effect of any stressor to these systems. This does not imply that there is no place for ex vivo or in vitro studies in the discipline of stress research, far from it! A large number of cell-based – and more recently organotypic culture-based – studies have contributed substantially to our understanding of specific mechanisms and/or partial pathways relevant to stress. The important point here is that ideally, in vitro work should at some point be followed up by in vivo investigations, in order to test the applicability of results obtained in vitro, to a whole system. The importance of in vivo assessments, and the need for conducting them in a model specifically suitable to answer the question at hand, is clear when one considers the huge number of described animal models in the scientific literature. Apart from more conventional models using genetically “intact” rodents, recent advances in biotechnology have made possible research using non-physiological models such as gene-knock out animals. These animals may be genetically modified to erase the gene coding for a particular protein, so that the researcher may elect to produce animals completely lacking a particular protein of interest (e.g. IL-6 knockout mice), or in some cases lacking it in only one organ or system (e.g. STAT-3 knocked out or “switched off” in skeletal muscle only). These models may be used to shed light on various in vivo mechanisms which could previously not be properly elucidated using the conventional methods. However, these models have their limitations. For example, when doing research on inflammation, an animal in which a proinflammatory cytokine was knocked out, may display increased or decreased basal levels of other pro-inflammatory cytokines, or an altered anti-inflammatory cytokine profile, or even up- or down-regulated cytokine responses on activation, as a spontaneous compensatory mechanism. The resultant net effect of the genetic manipulation therefore may result in a model that is not physiologically accurate, and responses measured may not accurately reflect normal in vivo responses. Furthermore, these compensatory mechanisms and/or the mere absence of an important protein may also result in other – sometimes unanticipated – side-effects (such as severe constipation in IL-6 knockout mice). Apart from being a confounding factor in the intended study, in some cases these undesired outcomes may result in poor health or even shortened life expectancy of the experimental animal, so that it limits the application of such a model even further. Of course, chain-reaction compensatory responses will also limit the extent to which results obtained in such models, may be extrapolated to a (at least genetically) normal situation. Relatively “old-fashioned”, or more conventional methods, when applied optimally, therefore still have an important place in research, both in applied areas such as pharmacology and in areas of basic research. Only when a situation that is physiologically relevant is recreated or simulated, can one realistically assess either the response to a challenge, or the outcome of a remedial intervention. Therefore, in this chapter, I would like to reflect on methods used to simulate a variety of stressors to the body, starting with a variety of models used to simulate psychological stress, ranging in severity from non-extreme (mild) psychological stress to extreme mental trauma. I will also discuss general considerations in picking the appropriate animal model to use, which may determine the difference between success and failure in your research. Details on the various models will be provided, including issues such as repeatability and standardisation. Models will also be discussed in terms of their suitability for different research approaches or objectives, as well as in terms of their limitations. Arguments for and against the use of any particular model will also be illustrated using actual research data.