Romero-Gomez, Manuel
자료유형 | 단행본 |
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개인저자 | Romero-Gomez, Manuel.,editor. |
단체저자명 | SpringerLink (Online service). |
서명/저자사항 | NAFLD and NASH [electronic resource] : Biomarkers in Detection, Diagnosis and Monitoring / edited by Manuel Romero-Gomez. |
판사항 | 1st ed. 2020. |
형태사항 | X, 236 p. 18 illus., 17 illus. in color:online resource. |
기본자료 저록 | Springer Nature eBook |
기타형태 저록 | Printed edition:9783030371722Printed edition:9783030371746Printed edition:9783030371753 |
ISBN | 9783030371739 |
기타표준부호 | 10.1007/978-3-030-37173-9 |
내용주기 | Foreword -- Biochemical biomarkers of NAFLD/NASH -- MR based-Imaging Biomarkers in NAFLD/NASH -- Detection of NAFLD/NASH in general population -- Micro-vesicles in the diagnosis and monitoring of NASH -- Non-invasive biomarkers for monitoring NASH: NASH resolution and Fibrosis regression -- From transcriptome to proteomic in the development of biomarkers in NAFLD/NASH -- Transient elastography and ultrasound as imaging biomarkers in NAFLD/NASH -- Early detection of HCC in patients with NAFLD/NASH -- Genes and NAFLD/NASH progression -- Geometry of nutrition: micronutrients and NAFLD progression -- Psychological biomarkers profile in NAFLD/NASH with advanced fibrosis -- Integrative proposal of biomarkers use in clinical practice management of NAFLD/NASH. |
요약 | This book provides a comprehensive overview of the diagnosis and management of Non-alcoholic Fatty Liver Disease (NAFLD) and Non-Alcoholic Steatohepatis (NASH). Basic principles of disease progression, the genetic and nutritional basis of NAFLD and NASH are explained along with the proteomic principles underlying biomarker development. Chapters cover both biochemical and imaging biomarkers used in elastrography and ultrasound and discuss how these are applicable to early diagnosis and monitoring of NASH and NAFLD. This is a useful resource for hepatologists, primary care providers with an interest in metabolic disease, diabetologists and endocrinologists in their daily clinical practice. |
일반주제명 | Internal medicine. Endocrinology. Bioinformatics. Internal Medicine. Endocrinology. Computational and Systems Biology. |
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