Background: Liver models that closely mimic the in vivo microenvironment are useful for understanding liver functions, capabilities, and intercellular communication processes. Three-dimensional (3D) liver models assembled using hepatocytes and liver sinusoidal endothelial cells (LSECs) separated by a polyelectrolyte multilayer (PEM) provide a functional system while also permitting isolation of individual cell types for proteomic analyses.
Methods: To better understand the mechanisms and processes that underlie liver model function, hepatocytes were maintained as monolayers and 3D PEM-based formats in the presence or absence of primary LSECs. The resulting hepatocyte proteomes, the proteins in the PEM, and extracellular levels of urea, albumin and glucose after three days of culture were compared.
Results: All systems were ketogenic and found to release glucose. The presence of the PEM led to increases in proteins associated with both mitochondrial and peroxisomal-based β-oxidation. The PEMs also limited production of structural and migratory proteins associated with dedifferentiation. The presence of LSECs increased levels of Phase I and Phase II biotransformation enzymes as well as several proteins associated with the endoplasmic reticulum and extracellular matrix remodeling. The proteomic analysis of the PEMs indicated that there was no significant change after three days of culture. These results are discussed in relation to liver model function.
Conclusions: Heterotypic cell-cell and cell-ECM interactions exert different effects on hepatocyte functions and phenotypes.
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http://dx.doi.org/10.1186/s12953-017-0120-6 | DOI Listing |
JMIR Med Inform
January 2025
Department of Endocrinology and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Background: Many tools have been developed to predict the risk of diabetes in a population without diabetes; however, these tools have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, and low sensitivity or specificity.
Objective: We aimed to develop and validate an easy, systematic index for predicting diabetes risk in the Asian population.
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BMC Gastroenterol
January 2025
Department of Pediatrics, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, 710061, China.
Background: The increased apoptosis of bile duct epithelial cells (BECs) due to some damage factors is considered the initiating factor in the occurrence and progression of biliary atresia (BA). Vitamin D receptor (VDR) is thought to play a crucial role in maintaining the intrinsic immune balance and integrity of bile duct epithelial cells (BECs). To investigate the role of VDRs in the pathogenesis and progression of BA using in vitro and in vivo models.
View Article and Find Full Text PDFBMC Gastroenterol
January 2025
Department of Gastroenterology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a primary cause of chronic liver disease, with potential progression to cirrhosis and hepatocellular carcinoma (HCC). Although systemic inflammatory biomarkers are associated with liver diseases, their specific role in MASLD remains unclear. This study examines the association between systemic inflammatory biomarkers and MASLD.
View Article and Find Full Text PDFSci Rep
January 2025
School of Sports and Health, Nanjing Sport Institute, Nanjing, China.
A high-calorie diet and lack of exercise are the most important risk factors contributing to metabolic dysfunction-associated steatotic liver disease (MASLD) initiation and progression. The precise molecular mechanisms of mitochondrial function alteration during MASLD development remain to be fully elucidated. In this study, a total of 60 male C57BL/6J mice were maintained on a normal or amylin liver NASH (AMLN) diet for 6 or 10 weeks.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA.
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics if clinicians over or under rely on AI. To investigate such collaborative decision-making process, we conducted a Human-AI interaction study on response-adaptive radiotherapy for non-small cell lung cancer and hepatocellular carcinoma.
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