Effect of a multidisciplinary lifestyle intervention on body composition in people with osteoarthritis: Secondary analysis of the "Plants for Joints" randomized controlled trial.

Objective: The Plants for Joints (PFJ) intervention significantly improved pain, stiffness, and physical function, and metabolic outcomes, in people with metabolic syndrome-associated osteoarthritis (MSOA). This secondary analysis investigated its effects on body composition.

Method: In the randomized PFJ study, people with MSOA followed a 16-week intervention based on a whole-food plant-based diet, physical activity, and stress management, or usual care.

Intrapancreatic fat deposition is unrelated to liver steatosis in metabolic dysfunction-associated steatotic liver disease.

Background & Aims: Individuals with obesity may develop intrapancreatic fat deposition (IPFD) and fatty pancreas disease (FPD). Whether this causes inflammation and fibrosis and leads to pancreatic dysfunction is less established than for liver damage in metabolic dysfunction-associated steatotic liver disease (MASLD). Moreover, the interrelations of FPD and MASLD are poorly understood.

Sex Steroids Regulate Liver Fat Content and Body Fat Distribution in Both Men and Women: A Study in Transgender Persons.

Context: Liver fat content and visceral fat volume are associated with insulin resistance and cardiovascular disease and are higher in men than in women.

Objective: To determine the effect of estradiol and testosterone treatment on liver fat and visceral fat in transgender persons.

Design: Open-label intervention study (SHAMVA) with a 1-year follow-up.

A natural history study of paediatric non-alcoholic fatty liver disease over 10 years.

Background & Aims: The long-term outcome of paediatric non-alcoholic fatty liver disease (NAFLD) has not been well established. Between 2008 and 2012, an unselected cohort of 133 children with severe obesity was screened for NAFLD. The aim of this study was to determine the 10-year natural history of NAFLD in this cohort.

Self-supervised neural network improves tri-exponential intravoxel incoherent motion model fitting compared to least-squares fitting in non-alcoholic fatty liver disease.

Recent literature suggests that tri-exponential models may provide additional information and fit liver intravoxel incoherent motion (IVIM) data more accurately than conventional bi-exponential models. However, voxel-wise fitting of IVIM results in noisy and unreliable parameter maps. For bi-exponential IVIM, neural networks (NN) were able to produce superior parameter maps than conventional least-squares (LSQ) generated images.