Glucocorticoid-induced pancreatic-hepatic trans-differentiation in a human cell line in vitro.

The rodent pancreatic AR42J-B13 (B-13) cell line differentiates into non-replicative hepatocyte-like cells in response to glucocorticoid mediated via the glucocorticoid receptor (GR). The aims of this study were to identify a human cell line that responds similarly and investigate the mechanisms underpinning any alteration in differentiation. Exposing the human pancreatic adenocarcinoma (HPAC) cell line to 1-10 µM concentrations of dexamethasone (DEX) resulted an inhibition of proliferation, suppressed carcinoembryonic antigen expression, limited expression of pancreatic acinar and hepatic gene expression and significant induction of the constitutively-expressed hepatic CYP3A5 mRNA transcript. These changes were associated with a pulse of genomic DNA methylation and suppressed notch signalling activity. HPAC cells expressed high levels of GR transcript in contrast to other nuclear receptors - such as the glucocorticoid-activated pregnane X receptor (PXR) - and GR transcriptional function was activated by DEX in HPAC cells. Expression of selected hepatocyte transcripts in response to DEX was blocked by co-treatment with the GR antagonist RU486. These data indicate that the HPAC response to glucocorticoid exposure includes an inhibition in proliferation, alterations in notch signalling and a limited change in the expression of genes associated with an acinar and hepatic phenotype. This is the first demonstration of a human cell responding to similarly to the rodent B-13 cell regarding formation of hepatocyte-like cells in response to glucocorticoid. Identifying and modulating the ablating factor(s) may enhance the hepatocyte-like forming capacity of HPAC cells after exposure to glucocorticoid and generate an unlimited in vitro supply of human hepatocytes for toxicology studies and a variety of clinical applications.

Influence of urban forests on residential property values: A systematic review of remote sensing-based studies.

Urban forests provide direct and indirect benefits to human well-being that are increasingly captured in residential property values. Remote Sensing (RS) can be used to measure a wide range of forest and vegetation parameters that allows for a more detailed and better understanding of their specific influences on housing prices. Herein, through a systematic literature review approach, we reviewed 89 papers (from 2010 to 2022) from 21 different countries that used RS data to quantify vegetation indices, forest and tree parameters of urban forests and estimated their influence on residential property values. The main aim of this study was to understand and provide insights into how urban forests influence residential property values based on RS studies. Although more studies were conducted in developed (n = 55, 61.7%) than developing countries (n = 34, 38.3%), the results indicated for the most part that increasing tree canopy cover on property and neighborhood level, forest size, type, greenness, and proximity to urban forests increased housing prices. RS studies benefited from spatially explicit repetitive data that offer superior efficiency to quantify vegetation, forest, and tree parameters of urban forests over large areas and longer periods compared to studies that used field inventory data. Through this work, we identify and underscore that urban forest benefits outweigh management costs and have a mostly positive influence on housing prices. Thus, we encourage further discussions about prioritizing reforestation and conservation of urban forests during the urban planning of cities and suburbs, which could support UN Sustainable Development Goals (SDGs) and urban policy reforms.