Magnetic resonance imaging-based balance analysis of linoleate utilization during weight loss in obese humans

Lipids ◽  
1999 ◽  
Vol 34 (S1) ◽  
pp. S89-S90 ◽  
Author(s):  
S. C. Cunnane ◽  
R. Ross ◽  
J. L. Bannister ◽  
D. J. A. Jenkins
Keyword(s):  
Magnetic Resonance Imaging ◽  
Weight Loss ◽  
Magnetic Resonance ◽  
Resonance Imaging ◽  
Balance Analysis

Water Dynamics in Turbot (Scophthalmus maximus) Flesh during Baking and Microwave Heating: Nuclear Magnetic Resonance and Magnetic Resonance Imaging Studies

2017 ◽  
Vol 13 (7) ◽  
Author(s):  
Kexin Xia ◽  
Haitao Wang ◽  
Linlin Huang ◽  
Wei Xu ◽  
Xiu Zang ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Nuclear Magnetic Resonance ◽  
Weight Loss ◽  
Magnetic Resonance ◽  
Microwave Heating ◽  
Shear Force ◽  
Protein Denaturation ◽  
Water Dynamics ◽  
Resonance Imaging ◽  
Loss Color

AbstractTurbot is a valuable commercial species because of its high nutrition content. Water redistribution during heating was attributed to temperature-induced protein denaturation and structural shrinkage. Therefore, knowledge about water dynamics provides valuable information related to flesh physical properties (weight loss, color and shear force). Herein, water dynamics in turbot during baking and microwave heating were elucidated by using low field nuclear magnetic resonance (LF-NMR) and magnetic resonance imaging (MRI). Four distinct water populations with relaxation times of 0.20–0.60 ms, 2.00–6.00 ms, 30.00–60.00 ms, and 250.00–560.00 ms were identified. The dramatic variation of water populations during baking and microwave heating indicated protein denaturation and structural shrinkage, which was further verified by MRI and microscopic examination. Furthermore, good linear correlations were observed between NMR parameters and weight loss, color and shear force. The results revealed that the water mobility and distribution in turbot provided valuable information for quality analysis during baking and microwave heating.

scholarly journals Effect of Weight Loss on Magnetic Resonance Imaging Estimation of Liver Fat and Volume in Patients With Nonalcoholic Steatohepatitis

2015 ◽  
Vol 13 (3) ◽  
pp. 561-568.e1 ◽  
Author(s):  
Niraj S. Patel ◽  
Iliana Doycheva ◽  
Michael R. Peterson ◽  
Jonathan Hooker ◽  
Tatiana Kisselva ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Weight Loss ◽  
Magnetic Resonance ◽  
Nonalcoholic Steatohepatitis ◽  
Liver Fat ◽  
Resonance Imaging

scholarly journals Three different genetic risk scores based on Fatty Liver Index, Magnetic Resonance Imaging and lipidomic for a nutrigenetic personalized management of NAFLD: the Fatty Liver in Obesity study

2021 ◽  
Author(s):  
Nuria Pérez-Díaz-del-Campo ◽  
Jose I. Riezu-Boj ◽  
Bertha Araceli Marin-Alejandre ◽  
J. Ignacio Monreal ◽  
Mariana Elorz ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Weight Loss ◽  
Magnetic Resonance ◽  
Dietary Intake ◽  
Fatty Liver ◽  
Genetic Risk ◽  
Risk Scores ◽  
Resonance Imaging ◽  
Personalized Management ◽  
Fatty Liver Index

Abstract Background Non-alcoholic fatty liver disease (NAFLD) affects 25% of the global population. The pathogenesis of NAFLD is complex where available data unveils that genetics and ascribed interactions with environmental factors may play an important role in the development of this morbid condition. The purpose of this investigation was to assess genetic and non-genetic determinants putatively involved in the onset and progression of NAFLD after a 6-months weight-loss nutritional treatment. Methods A group of 86 overweight/obese subjects with NAFLD from the Fatty Liver in Obesity (FLiO) study were enrolled and metabolically evaluated at baseline and after 6-months. Also, a total of 95 single nucleotide polymorphisms (SNPs) related to obesity and weight loss were analyzed by a targeted next-generation sequencing system. Three genetic risk scores (GRS) concerning the improvement on hepatic health evaluated by minimally invasive methods such as the Fatty Liver Index (FLI) (GRSFLI), lipidomic-OWLiver®-test (GRSOWL) and Magnetic Resonance Imaging (MRI) (GRSMRI), were derived by adding the risk alleles genotypes. Body composition, liver injury-related markers and dietary intake were also monitored. Results Overall, 26 SNPs were independently associated with the change on FLI, 16 SNPs with OWLiver®-test and 8 SNPs with MRI, which were specific for every diagnosis tool. After adjusting for gender, age and other related predictors (insulin resistance, inflammatory biomarkers and dietary intake at baseline) the calculated GRSFLI, GRSOWL and GRSMRI were major contributors of the improvement on hepatic status. Thus, fitted linear regression models showed a variance of 53% (adj. R2 = 0.53) in hepatic functionality (FLI), 16% (adj. R2 = 0.16) in lipidomic metabolism (OWLiver®-test) and 34% (adj. R2 = 0.34) in liver fat content (MRI). Conclusion These results demonstrate that three different genetic scores can be useful for the personalized management of NAFLD, whose treatment must rely on specific dietary recommendations guided by the measurement of specific genetic biomarkers. Trial registration: The FLiO study: Fatty Liver in Obesity study, NCT03183193. Registered 12 June 2017 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03183193

scholarly journals Abdominal diameters as indicators of visceral fat: comparison between magnetic resonance imaging and anthropometry

1993 ◽  
Vol 70 (1) ◽  
pp. 47-58 ◽  
Author(s):  
Karin Van Der Kooy ◽  
Rianne Leenen ◽  
Jaap C. Seidell ◽  
Paul Deurenberg ◽  
Marjolein Visser
Keyword(s):  
Magnetic Resonance Imaging ◽  
Weight Loss ◽  
Magnetic Resonance ◽  
Waist Circumference ◽  
Visceral Fat ◽  
Serum Lipids ◽  
Subcutaneous Fat ◽  
Strongly Correlated ◽  
Resonance Imaging ◽  
Sagittal Diameter

The aim of the present study was to investigate the usefulness of abdominal diameters to indicate visceral fat, their relationship with serum lipids and their capability of detecting changes in visceral fat. Before and after weight loss, visceral and subcutaneous fat, and the sagittal and transverse diameters were assessed by magnetic resonance imaging (MRI) in forty-seven obese men and forty-seven premenopausal obese women with an initial body mass index of 31·0 (SD2·4) kg/m2. In a subsample (n21), diameters, were also measured by anthropometry in the standing and supine positions. They were strongly correlated with the diameters derived from the MRI scans. Serum levels of total and HDL-cholesterol and triacylglycerol were measured before weight loss. In women the sagittal diameter correlated less strongly with visceral fat than anthropometrically-assessed waist circumference and waist:hip ratio (WHR). In men these associations were comparable. Changes in visceral fat with weight loss were more strongly correlated with changes in the sagittal diameter and sagittal:transverse diameter ratio (STR) than with changes in waist circumference or WHR in men. In women, changes in the anthropometric variables and the separate diameters (except STR) were not associated with visceral fat loss. In men, but not in women, both the sagittal diameter and the visceral fat area were related to serum lipids. It is concluded that the sagittal diameter and STR may have advantages over waist circumference and WHR in men, particularly in assessing changes in visceral fat, but this could not be demonstrated in women. The ability to predict visceral fat from circumferences and diameters or their ratios is, however, limited in obese men and women.

scholarly journals Three Different Genetic Risk Scores Based on Fatty Liver Index, Magnetic Resonance Imaging and Lipidomic for a Nutrigenetic Personalized Management of NAFLD: The Fatty Liver in Obesity Study

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1083
Author(s):  
Nuria Perez-Diaz-del-Campo ◽  
Jose I. Riezu-Boj ◽  
Bertha Araceli Marin-Alejandre ◽  
J. Ignacio Monreal ◽  
Mariana Elorz ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Weight Loss ◽  
Magnetic Resonance ◽  
Dietary Intake ◽  
Fatty Liver ◽  
Genetic Risk ◽  
Risk Scores ◽  
Resonance Imaging ◽  
Personalized Management ◽  
Fatty Liver Index

Non-alcoholic fatty liver disease (NAFLD) affects 25% of the global population. The pathogenesis of NAFLD is complex; available data reveal that genetics and ascribed interactions with environmental factors may play an important role in the development of this morbid condition. The purpose of this investigation was to assess genetic and non-genetic determinants putatively involved in the onset and progression of NAFLD after a 6-month weight loss nutritional treatment. A group of 86 overweight/obese subjects with NAFLD from the Fatty Liver in Obesity (FLiO) study were enrolled and metabolically evaluated at baseline and after 6 months. A pre-designed panel of 95 genetic variants related to obesity and weight loss was applied and analyzed. Three genetic risk scores (GRS) concerning the improvement on hepatic health evaluated by minimally invasive methods such as the fatty liver index (FLI) (GRSFLI), lipidomic-OWLiver®-test (GRSOWL) and magnetic resonance imaging (MRI) (GRSMRI), were derived by adding the risk alleles genotypes. Body composition, liver injury-related markers and dietary intake were also monitored. Overall, 23 SNPs were independently associated with the change in FLI, 16 SNPs with OWLiver®-test and 8 SNPs with MRI, which were specific for every diagnosis tool. After adjusting for gender, age and other related predictors (insulin resistance, inflammatory biomarkers and dietary intake at baseline) the calculated GRSFLI, GRSOWL and GRSMRI were major contributors of the improvement in hepatic status. Thus, fitted linear regression models showed a variance of 53% (adj. R2 = 0.53) in hepatic functionality (FLI), 16% (adj. R2 = 0.16) in lipidomic metabolism (OWLiver®-test) and 34% (adj. R2 = 0.34) in liver fat content (MRI). These results demonstrate that three different genetic scores can be useful for the personalized management of NAFLD, whose treatment must rely on specific dietary recommendations guided by the measurement of specific genetic biomarkers.

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