The Importance of LDL and Cholesterol Metabolism for Prostate Epithelial Cell Growth

Cholesterol-lowering treatment has been suggested to delay progression of prostate cancer by decreasing serum LDL. We studied in vitro the effect of extracellular LDL-cholesterol on the number of prostate epithelial cells and on the expression of key regulators of cholesterol metabolism. Two normal prostatic epithelial cell lines (P96E, P97E), two in vitro immortalized epithelial cell lines (PWR-1E, RWPE-1) and two cancer cell lines (LNCaP and VCaP) were grown in cholesterol-deficient conditions. Cells were treated with 1–50 µg/ml LDL-cholesterol and/or 100 nM simvastatin for seven days. Cell number relative to control was measured with crystal violet staining. Changes in mRNA and protein expression of key effectors in cholesterol metabolism (HMGCR, LDLR, SREBP2 and ABCA1) were measured with RT-PCR and immunoblotting, respectively. LDL increased the relative cell number of prostate cancer cell lines, but reduced the number of normal epithelial cells at high concentrations. Treatment with cholesterol-lowering simvastatin induced up to 90% reduction in relative cell number of normal cell lines but a 15–20% reduction in relative number of cancer cells, an effect accompanied by sharp upregulation of HMGCR and LDLR. These effects were prevented by LDL. Compared to the normal cells, prostate cancer cells showed high expression of cholesterol-producing HMGCR but failed to express the major cholesterol exporter ABCA1. LDL increased relative cell number of cancer cell lines, and these cells were less vulnerable than normal cells to cholesterol-lowering simvastatin treatment. Our study supports the importance of LDL for prostate cancer cells, and suggests that cholesterol metabolism in prostate cancer has been reprogrammed to increased production in order to support rapid cell growth

Reconstructing the 2003/2004 H3N2 influenza epidemic in Switzerland with a spatially explicit, individual-based model

ABSTRACT: BACKGROUND: Simulation models of influenza spread play an important role for pandemic preparedness. However, as the world has not faced a severe pandemic for decades, except the rather mild H1N1 one in 2009, pandemic influenza models are inherently hypothetical and validation is, thus, difficult. We aim at reconstructing a recent seasonal influenza epidemic that occurred in Switzerland and deem this to be a promising validation strategy for models of influenza spread. METHODS: We present a spatially explicit, individual-based simulation model of influenza spread. The simulation model bases upon (i) simulated human travel data, (ii) data on human contact patterns and (iii) empirical knowledge on the epidemiology of influenza. For model validation we compare the simulation outcomes with empirical knowledge regarding (i) the shape of the epidemic curve, overall infection rate and reproduction number, (ii) age-dependent infection rates and time of infection, (iii) spatial patterns. RESULTS: The simulation model is capable of reproducing the shape of the 2003/2004 H3N2 epidemic curve of Switzerland and generates an overall infection rate (14.9 percent) and reproduction numbers (between 1.2 and 1.3), which are realistic for seasonal influenza epidemics. Age and spatial patterns observed in empirical data are also reflected by the model: Highest infection rates are in children between 5 and 14 and the disease spreads along the main transport axes from west to east. CONCLUSIONS: We show that finding evidence for the validity of simulation models of influenza spread by challenging them with seasonal influenza outbreak data is possible and promising. Simulation models for pandemic spread gain more credibility if they are able to reproduce seasonal influenza outbreaks. For more robust modelling of seasonal influenza, serological data complementing sentinel information would be beneficia

Microcutting of living tissue slices and stem cell colonies by using mechanical tool

There is a growing need for methods to cut living tissues in vitro and cell cultures in microscale in biological and medical research. This paper presents two different microrobotic methods for cutting: mechanical microdissection using a sharp needle and liquid jet cutting utilizing a pressured liquid jet. Test devices for both the methods were built and the experiments were conducted with thin tissue slices and stem cell colonies. The devices built as well as the structure of the experiments and the results gained are discussed in this paper and the methods are compared with each other.Peer reviewe