University of Jena

About: University of Jena is a education organization based out in Jena, Thüringen, Germany. It is known for research contribution in the topics: Laser & Population. The organization has 22198 authors who have published 45159 publications receiving 1401514 citations. The organization is also known as: Friedrich-Schiller-Universität Jena & Friedrich Schiller University Jena.

Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME.

Abstract: This review encompasses the most important advances in liver functions and hepatotoxicity and analyzes which mechanisms can be studied in vitro. In a complex architecture of nested, zonated lobules, the liver consists of approximately 80 % hepatocytes and 20 % non-parenchymal cells, the latter being involved in a secondary phase that may dramatically aggravate the initial damage. Hepatotoxicity, as well as hepatic metabolism, is controlled by a set of nuclear receptors (including PXR, CAR, HNF-4α, FXR, LXR, SHP, VDR and PPAR) and signaling pathways. When isolating liver cells, some pathways are activated, e.g., the RAS/MEK/ERK pathway, whereas others are silenced (e.g. HNF-4α), resulting in up- and downregulation of hundreds of genes. An understanding of these changes is crucial for a correct interpretation of in vitro data. The possibilities and limitations of the most useful liver in vitro systems are summarized, including three-dimensional culture techniques, co-cultures with non-parenchymal cells, hepatospheres, precision cut liver slices and the isolated perfused liver. Also discussed is how closely hepatoma, stem cell and iPS cell-derived hepatocyte-like-cells resemble real hepatocytes. Finally, a summary is given of the state of the art of liver in vitro and mathematical modeling systems that are currently used in the pharmaceutical industry with an emphasis on drug metabolism, prediction of clearance, drug interaction, transporter studies and hepatotoxicity. One key message is that despite our enthusiasm for in vitro systems, we must never lose sight of the in vivo situation. Although hepatocytes have been isolated for decades, the hunt for relevant alternative systems has only just begun.

Overview of the European and North American studies on HPV testing in primary cervical cancer screening.

Abstract: Several studies suggest that HPV testing is more sensitive than cytology in primary cervical screening. These studies had different designs and were reported in different ways. Individual patient data were collected for all European and North American studies in which cytology was routinely performed and HPV testing was included as an additional parallel test. More than 60,000 women were included. The sensitivity and specificity of HPV testing were compared with routine cytology, both overall and for ages <35, 35–49 and 50+. The age-specific prevalence of high risk HPV (hr-HPV) was also analysed. HPV testing was substantially more sensitive in detecting CIN2+ than cytology (96.1% vs. 53.0%) but less specific (90.7% vs. 96.3%). The sensitivity of HPV testing was similar in all studies carried out in different areas of Europe and North America, whereas the sensitivity of cytology was highly variable. HPV sensitivity was uniformly high at all ages, whereas the sensitivity of cytology was substantially better in women over the age of 50 than in younger women (79.3% vs. 59.6%). The specificity of both tests increased with age. Positivity rates for HPV testing in women without high-grade CIN were region dependent. These results support the use of HPV testing as the sole primary screening test, with cytology reserved for women who test HPV positive. Large demonstration projects are needed to fully evaluate this strategy. © 2006 Wiley-Liss, Inc.

The Biosynthetic Logic of Polyketide Diversity

Abstract: Molecular Lego: Polyketides represent a highly diverse group of natural products with structurally intriguing carbon skeletons (see picture) which are assembled from simple acyl building blocks. A combination of chemical, biochemical, and genetics studies have provided exciting new insights into the programming of polyketide assembly and the sophisticated enzymatic machineries involved. This review highlights recent developments in the field.Polyketides constitute one of the major classes of natural products. Many of these compounds or derivatives thereof have become important therapeutics for clinical use; in contrast, various polyketides are infamous food-spoiling toxins or virulence factors. What is particularly remarkable about this heterogeneous group of compounds comprising of polyethers, polyenes, polyphenols, macrolides, and enediynes is that they are mainly derived from one of the simplest building blocks available in nature: acetic acid. Investigations at the chemical, genetic, and biochemical levels have shed light on the biosynthetic programs that lead to the large structural diversity of polyketides .This review highlights recently unveiled biosynthetic mechanisms to generate highly diverse and complex molecules.

rptR: repeatability estimation and variance decomposition by generalized linear mixed-effects models

Abstract: Summary Intra-class correlations (ICC) and repeatabilities (R) are fundamental statistics for quantifying the reproducibility of measurements and for understanding the structure of biological variation. Linear mixed effects models offer a versatile framework for estimating ICC and R. However, while point estimation and significance testing by likelihood ratio tests is straightforward, the quantification of uncertainty is not as easily achieved. A further complication arises when the analysis is conducted on data with non-Gaussian distributions because the separation of the mean and the variance is less clear-cut for non-Gaussian than for Gaussian models. Nonetheless, there are solutions to approximate repeatability for the most widely used families of generalized linear mixed models (GLMMs). Here, we introduce the R package rptR for the estimation of ICC and R for Gaussian, binomial and Poisson-distributed data. Uncertainty in estimators is quantified by parametric bootstrapping and significance testing is implemented by likelihood ratio tests and through permutation of residuals. The package allows control for fixed effects and thus the estimation of adjusted repeatabilities (that remove fixed effect variance from the estimate) and enhanced agreement repeatabilities (that add fixed effect variance to the denominator). Furthermore, repeatability can be estimated from random-slope models. The package features convenient summary and plotting functions. Besides repeatabilities, the package also allows the quantification of coefficients of determination R2 as well as of raw variance components. We present an example analysis to demonstrate the core features and discuss some of the limitations of rptR.