| Chapter title |
A Mouse Model of Diet-Induced Obesity and Insulin Resistance
|
|---|---|
| Chapter number | 27 |
| Book title |
mTOR
|
| Published in |
Methods in molecular biology, September 2011
|
| DOI | 10.1007/978-1-61779-430-8_27 |
| Pubmed ID | |
| Book ISBNs |
978-1-61779-429-2, 978-1-61779-430-8
|
| Authors |
Chao-Yung Wang, James K. Liao |
| Editors |
Thomas Weichhart |
| Abstract |
Obesity is reaching pandemic proportions in Western society. It has resulted in increasing health care burden and decreasing life expectancy. Obesity is a complex, chronic disease, involving decades of pathophysiological changes and adaptation. Therefore, it is difficult ascertain the exact mechanisms for this long-term process in humans. To circumvent some of these issues, several surrogate models are available, including murine genetic loss-of-function mutations, transgenic gain-of-function mutations, polygenic models, and different environmental exposure models. The mouse model of diet-induced obesity has become one of the most important tools for understanding the interplay of high-fat Western diets and the development of obesity. The diet-induced obesity model closely mimics the increasingly availability of the high-fat/high-density foods in modern society over the past two decades, which are main contributors to the obesity trend in human. This model has lead to many discoveries of the important signalings in obesity, such as Akt and mTOR. The chapter describes protocols for diet induced-obesity model in mice and protocols for measuring insulin resistance and sensitivity. |
X Demographics
Geographical breakdown
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|---|---|---|
| Canada | 1 | 25% |
| United States | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
Geographical breakdown
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|---|---|---|
| Denmark | 3 | <1% |
| France | 1 | <1% |
| United Kingdom | 1 | <1% |
| South Africa | 1 | <1% |
| China | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 771 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 155 | 20% |
| Student > Bachelor | 113 | 15% |
| Student > Master | 108 | 14% |
| Researcher | 80 | 10% |
| Student > Doctoral Student | 45 | 6% |
| Other | 97 | 12% |
| Unknown | 181 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 183 | 23% |
| Agricultural and Biological Sciences | 131 | 17% |
| Medicine and Dentistry | 93 | 12% |
| Pharmacology, Toxicology and Pharmaceutical Science | 31 | 4% |
| Neuroscience | 24 | 3% |
| Other | 99 | 13% |
| Unknown | 218 | 28% |