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NAFLD and NASH Biomarkers in Detection, Diagnosis and Monitoring [electronic resource]

Romero-Gomez, Manuel

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개인저자Romero-Gomez, Manuel.,editor.
단체저자명SpringerLink (Online service).
서명/저자사항NAFLD and NASH [electronic resource] : Biomarkers in Detection, Diagnosis and Monitoring / edited by Manuel Romero-Gomez.
판사항1st ed. 2020.
형태사항X, 236 p. 18 illus., 17 illus. in color:online resource.
기본자료 저록Springer Nature eBook
기타형태 저록Printed edition:9783030371722Printed edition:9783030371746Printed edition:9783030371753
ISBN9783030371739
기타표준부호10.1007/978-3-030-37173-9
내용주기Foreword -- 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.
요약This 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.
일반주제명Internal medicine.
Endocrinology.
Bioinformatics.
Internal Medicine.
Endocrinology.
Computational and Systems Biology.
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