University of Kiel

About: University of Kiel is a education organization based out in Kiel, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 27816 authors who have published 57114 publications receiving 2061802 citations. The organization is also known as: Christian Albrechts University & Christian-Albrechts-Universität zu Kiel.

Regulatory networks define phenotypic classes of human stem cell lines

Abstract: Hundreds of different human cell lines are grouped under the catch-all term 'stem cells'. They can be from embryos, fetuses or adults. And they can be pluripotent — able to produce a broad range of cells — or fated to produce a limited repertoire of cell types. Muller et al. set out to establish a 'stem cell diagnostic' to bring order to the characterization and classification of human stem cells, based on a database of transcriptional profiles derived from more than 150 cell samples. Bioinformatic analyses revealed that pluripotent stem cell lines share many properties and all possess a characteristic protein–protein network, dubbed 'PluriNet'. Other cell types, including brain-derived neural stem cell lines, are much more diverse. These results offer a new strategy for classifying stem cells and support the idea that pluripotency and self-renewal are under tight control by specific molecular networks. Stem cells are defined as self-renewing cell populations that can differentiate into multiple distinct cell types. However, hundreds of different human cell lines from embryonic, fetal and adult sources have been called stem cells, even though they range from pluripotent cells—typified by embryonic stem cells, which are capable of virtually unlimited proliferation and differentiation—to adult stem cell lines, which can generate a far more limited repertoire of differentiated cell types. The rapid increase in reports of new sources of stem cells and their anticipated value to regenerative medicine1,2 has highlighted the need for a general, reproducible method for classification of these cells3. We report here the creation and analysis of a database of global gene expression profiles (which we call the ‘stem cell matrix’) that enables the classification of cultured human stem cells in the context of a wide variety of pluripotent, multipotent and differentiated cell types. Using an unsupervised clustering method4,5 to categorize a collection of ∼150 cell samples, we discovered that pluripotent stem cell lines group together, whereas other cell types, including brain-derived neural stem cell lines, are very diverse. Using further bioinformatic analysis6 we uncovered a protein–protein network (PluriNet) that is shared by the pluripotent cells (embryonic stem cells, embryonal carcinomas and induced pluripotent cells). Analysis of published data showed that the PluriNet seems to be a common characteristic of pluripotent cells, including mouse embryonic stem and induced pluripotent cells and human oocytes. Our results offer a new strategy for classifying stem cells and support the idea that pluripotency and self-renewal are under tight control by specific molecular networks.

Complex plasmas: a laboratory for strong correlations

Abstract: Strong correlations—cooperative behavior due to many-particle interactions—are omnipresent in nature. They occur in electrolytic solutions, dense plasmas, ultracold ions and atomic gases in traps, complex (dusty) plasmas, electrons and excitons in quantum dots and the quark–gluon plasma. Correlation effects include the emergence of long-range order, of liquid-like or crystalline structures and collective dynamic properties (collective modes). The observation and experimental analysis of strong correlations are often difficult, requiring, in many cases, extreme conditions such as very low temperatures or high densities. An exception is complex plasmas where strong coupling can be easily achieved, even at room temperature. These systems feature the strongest correlations reported so far and experiments allow for an unprecedented precision and full single-particle resolution of the stationary and time-dependent many-particle behavior. The governing role of the interactions in strongly correlated systems gives rise to many universal properties observed in all of them. This makes the analysis of one particular system interesting for many others. This motivates the goal of this paper which is to give an overview on recent experimental and theoretical results in complex plasmas including liquid-like behavior, crystal formation, structural and dynamic properties. It is expected that many of these effects will be of interest also to researchers in other fields where strong correlations play a prominent role. (Some figures in this article are in colour only in the electronic version) This article was invited by Gordon Baym.