Cytochrome P450 2E1-derived reactive oxygen species mediate paracrine stimulation of collagen I protein synthesis by hepatic stellate cells.

To evaluate possible fibrogenic effects of CYP2E1-dependent generation of reactive oxygen species, a model was developed using co-cultures of HepG2 cells, which do (E47 cells) or do not (C34 cells) express cytochrome P450 2E1 (CYP2E1) with stellate cells. There was an increase in intra- and extracellular H(2)O(2), lipid peroxidation, and collagen type I protein in stellate cells co-cultured with E47 cells compared with stellate cells alone or co-cultured with C34 cells. The increase in collagen was prevented by antioxidants and a CYP2E1 inhibitor. CYP3A4 did not mimic the stimulatory effects found with CYP2E1. Collagen mRNA levels remained unchanged, and pulse-chase analysis indicated similar half-lives of collagen I protein between both co-cultures. However, collagen protein synthesis was increased in E47 co-culture. Hepatocytes from pyrazole-treated rats (with high levels of CYP2E1) induced collagen protein in primary stellate cells, and antioxidants and CYP2E1 inhibitors blocked this effect. These results suggest that increased translation of collagen mRNA by CYP2E1-derived reactive oxygen species is responsible for the increase in collagen protein produced by the E47 co-culture. These co-culture models may be useful for understanding the impact of CYP2E1-derived ROS on stellate cell function and activation.     

Lipase-catalyzed transamidation of non-activated amides in organic solvent

A novel biocatalytic reaction of transamidation of non-activated amides with amines is reported. Among 45 different lipolytic and proteolytic enzymes tested, only the lipase from Candida antarcticawas able to catalyze this reaction. The reaction proceeded with up to ca. 80% conversion in anhydrous methyl tert-butyl ether and worked with both N-substituted and unsubstituted amides. The biocatalytic transamidation is an equilibrium process and, therefore, higher conversions to the desired amide were achieved by using increased concentrations of the amine nucleophile.     

Expression of Mitochondrial Regulators PGC1α and TFAM as Putative Markers of Subtype and Chemoresistance in Epithelial Ovarian Carcinoma

Epithelial ovarian carcinoma (EOC), the major cause of gynaecological cancer death, is a heterogeneous disease classified into five subtypes. Each subtype has distinct clinical characteristics and is associated with different genetic risk factors and molecular events, but all are treated with surgery and platinum/taxane regimes. Tumour progression and chemoresistance is generally associated with major metabolic alterations, notably altered mitochondrial function(s). Here, we report for the first time that the expression of the mitochondrial regulators PGC1α and TFAM varies between EOC subtypes; furthermore, we have identified a profile in clear-cell carcinoma consisting of undetectability of PGC1α/TFAM, and low ERα/Ki-67. By contrast, high-grade serous carcinomas were characterised by a converse state of PGC1α/TFAM, ERα positivity and a high Ki-67 index. Interestingly, loss of PGC1α/TFAM and ERα was found also in a non-clear cell EOC cell line made highly resistant to platinum in vitro. Similar to clear-cell carcinomas, these resistant cells also showed accumulation of glycogen. Altogether, our data provide mechanistic insights into the chemoresistant nature of ovarian clear-cell carcinomas. Furthermore, these findings corroborate the need to take into account the diversity of EOC and to develop subtype specific treatment strategies.     

A MONTE CARLO SIMULATION OF CLONE GROWTH

A Monte Carlo simulation of clone growth is discussed from the point of view of clonal volume. It is shown that clone volume is a good representation of the number of cells per clone for a wide range of single cell growth equations. However, the rate at which the coefficient of variation in clonal volume approaches that of cell number per clone is strongly dependent upon the particular growth equation.     

MBAT: A scalable informatics system for unifying digital atlasing workflows

Background  

Digital atlases provide a common semantic and spatial coordinate system that can be leveraged to compare, contrast, and correlate data from disparate sources. As the quality and amount of biological data continues to advance and grow, searching, referencing, and comparing this data with a researcher's own data is essential. However, the integration process is cumbersome and time-consuming due to misaligned data, implicitly defined associations, and incompatible data sources. This work addressing these challenges by providing a unified and adaptable environment to accelerate the workflow to gather, align, and analyze the data.