Mithun Das – författare

Obesity is a major risk for both cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM). Obesity has reached epidemic proportions globally, and evidence suggests that the situation is likely to get worse in both developed and developing countries. It is considered to be a predisposing factor for several chronic diseases which include CVD, ischemic stroke, hypertension, T2DM, vascular dysfunction, and proinflammatory and prothrombotic state. This is where Syndrome X intersects with obesity and plays the role of a common denominator for CVD and T2DM. Persons with Syndrome X are more susceptible to CVD and T2DM. It is particularly relevant to recognize that variation in disease susceptibility among individuals in the population at large is a consequence of the intersection of the distribution of genotypes with the distribution of past environmental exposures and future environmental trajectories. For instance, many individuals who have a genotype that is found in those with disease will remain healthy because of the compensatory effects of a different environmental history on the same initial conditions. Similarly, individuals who do not have a high risk genotype may develop a disease of an adverse environmental history. That is, interaction between a particular genotype and particular environmental exposures. In the thrifty genotype hypothesis as proposed by Neel (1962), entire populations have an increased predisposition to T2DM due to genetic selection. They are better adapted to different nutritional circumstances than those they experience today. In the thrifty phenotype hypothesis (also known as Barker’s Hypothesis), maladaptive responses occur as a result of environmentally induced alteration of physiology in the early life of the individual. Both hypotheses offer explanations of why the frequency of diabetes and obesity may differ in different populations and why predisposition to diabetes is common, albeit by very different mechanisms. A third hypothesis called the “common soil” hypothesis as mentioned by Lebovitz (2006) that diabetes and CVD might share an underlying cause(s) is also described. Insulin resistance is central both to the progression from normal glucose tolerance to T2DM and to a constellation of CVD risk factors known as Syndrome X or Metabolic Syndrome. Then there is the epigenome that directly impacts gene expression and can be modified by both genetic and environmental factors. It is the potentially heritable changes in gene expression that does not involve changes to the underlying DNA sequences – a change in phenotype without a change in genotype. The epigenoytpe is dynamic and varies over time and tissues as a result of environmental exposure, aging, and diseases and other factors. The present book is an assembly of the vast knowledge that has been generated over the last decade worldwide in the field of obesity and metabolic syndrome related disorders, and an attempt to translate research findings into a clinically useful tool for better diagnosis, intervention, and prevention of this global public health burden. We hope this book will not only expand the practice in the coming years, but that it will create new avenues for future research as well.

The syndrome X or metabolic syndrome may be defined as a constellation of several interrelated risk factors of metabolic origin which includes centrally distributed obesity, decreased high density lipoprotein cholesterol, elevated triglycerides, elevated blood pressure and hyperglycemia. Persons with syndrome X are at twice the risk of developing cardiovascular disease, and are at about five-fold the risk of type 2 diabetes mellitus as compare to persons with this syndrome. There are considerable evidences of important ethnic differences in the prevalence of syndrome X, its components and sequelae. The prevalence varied between ethnic groups even within the same geographical location. Apart from multifactorial (genetic vs. environmental) nature, there are intriguing metabolic and anthropometric differences found across different ethnic groups. The estimates vary by ethnicity, for instance, high prevalence in non‐European groups such as Black African‐Caribbeans, Hispanics, indigenous populations of North America, South Asians, and the Western Pacific Region and lower prevalence in Chinese populations, and European‐White. Public health strategies that are well known to be important for chronic disease prevention in general can substantially reduce the prevalence of syndrome X. Population-specific studies will be important in identifying subgroups for which syndrome X is a health issue and for which disease management strategies are needed. Simultaneously, studies to identify different biomarkers associated with syndrome X that are linked with the development of specific chronic diseases, such as CVD and diabetes, will significantly enhance the early detection of these diseases. Existing preventions strategies, if implemented in population subgroups at highest risk, may have a substantial effect on reducing these trends. The prevalence of syndrome X increases with advancing age suggests that the efforts to increase awareness of prevention strategies must begin early. Intensive treatment and effective targeting efforts would help in avoiding future sequelae of syndrome X across different ethnicity. This book will be an assemblage of similarities and differences in the risk of syndrome X and related disorders among different ethnic groups worldwide, and reviews potential mechanisms for ethnic differences. It would certain help in translational research for early intervention and better prevention of syndrome X and its associated public health burden worldwide.

This book informs readers on how to understand, detect, and mitigate hate speech in online social media. The authors first cover the definition of hate speech and how its prevalence can be measured on online social media platforms using text and graph-based methods. The book then describes the process of detecting hate speech and presents a comprehensive account of the AI models that are currently being used. Further, the authors discuss the associated challenges that must be overcome while using these models. The book concludes with an overview of the mitigation techniques for hate speech, including blocking or suspension of the accounts (hard technique) and counterspeech (soft technique), and a discussion of the effects of these techniques on social media platforms.