Chapter title |
Assessment of Fatty Liver in Models of Disease Programming
|
---|---|
Chapter number | 15 |
Book title |
Investigations of Early Nutrition Effects on Long-Term Health
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7614-0_15 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7613-3, 978-1-4939-7614-0
|
Authors |
Kimberley D. Bruce, Karen R. Jonscher |
Abstract |
Nonalcoholic fatty liver disease (NAFLD) is currently the most common cause of chronic liver disease worldwide and is present in a third of the general population and the majority of individuals with obesity and type 2 diabetes. Importantly, NAFLD can progress to severe nonalcoholic steatohepatitis (NASH), associated with liver failure and hepatocellular carcinoma. Recent research efforts have extensively focused on identifying factors contributing to the additional "hit" required to promote NALFD disease progression. The maternal diet, and in particular a high-fat diet (HFD), may be one such hit "priming" the development of severe fatty liver disease, a notion supported by the increasing incidence of NAFLD among children and adolescents in Westernized countries. In recent years, a plethora of key studies have used murine models of maternal obesity to identify fundamental mechanisms such as lipogenesis, mitochondrial function, inflammation, and fibrosis that may underlie the developmental priming of NAFLD. In this chapter, we will address key considerations for constructing experimental models and both conventional and advanced methods of quantifying NAFLD disease status. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 22 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Postgraduate | 3 | 14% |
Student > Ph. D. Student | 3 | 14% |
Student > Bachelor | 2 | 9% |
Student > Master | 2 | 9% |
Other | 1 | 5% |
Other | 3 | 14% |
Unknown | 8 | 36% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 4 | 18% |
Nursing and Health Professions | 2 | 9% |
Computer Science | 2 | 9% |
Biochemistry, Genetics and Molecular Biology | 1 | 5% |
Decision Sciences | 1 | 5% |
Other | 3 | 14% |
Unknown | 9 | 41% |