Early foetal thrombosis induced by Thalidomide in mouse: Possible explanation for teratogenicity

Summary Mouse foetuses were treated by Thalidomide on days 11–12 in order to verify whether the drug would induce blood abnormalities leading to circulatory troubles. About 18% of the treated foetuses showed both severe limb haemorrhages on day 14, and obvious alterations of the nucleated red blood cells of vitelline origin. These blood abnormalities, occurring suddenly during the well-known critical stage of foetal development, could be responsible for circulatory blocks leading to necrosis.     

An integrated semiconductor device enabling non-optical genome sequencing

The seminal importance of DNA sequencing to the life sciences, biotechnology and medicine has driven the search for more scalable and lower-cost solutions. Here we describe a DNA sequencing technology in which scalable, low-cost semiconductor manufacturing techniques are used to make an integrated circuit able to directly perform non-optical DNA sequencing of genomes. Sequence data are obtained by directly sensing the ions produced by template-directed DNA polymerase synthesis using all-natural nucleotides on this massively parallel semiconductor-sensing device or ion chip. The ion chip contains ion-sensitive, field-effect transistor-based sensors in perfect register with 1.2 million wells, which provide confinement and allow parallel, simultaneous detection of independent sequencing reactions. Use of the most widely used technology for constructing integrated circuits, the complementary metal-oxide semiconductor (CMOS) process, allows for low-cost, large-scale production and scaling of the device to higher densities and larger array sizes. We show the performance of the system by sequencing three bacterial genomes, its robustness and scalability by producing ion chips with up to 10 times as many sensors and sequencing a human genome.     

Mutations in the polyglutamine binding protein 1 gene cause X-linked mental retardation

We found mutations in the gene PQBP1 in 5 of 29 families with nonsyndromic (MRX) and syndromic (MRXS) forms of X-linked mental retardation (XLMR). Clinical features in affected males include mental retardation, microcephaly, short stature, spastic paraplegia and midline defects. PQBP1 has previously been implicated in the pathogenesis of polyglutamine expansion diseases. Our findings link this gene to XLMR and shed more light on the pathogenesis of this common disorder.     

Regulatory networks define phenotypic classes of human stem cell lines

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 medicine has highlighted the need for a general, reproducible method for classification of these cells. 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 method to categorize a collection of approximately 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 analysis 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.     

Substance graphs are optimal simple-graph representations of metabolism

One approach to study the system-wide organization of biochemistry is to use statistical graph theory. In such heavily simplified methods, which disregard most of the dynamic aspects of biochemistry, one is faced with fundamental questions. One such question is how the chemical reaction systems should be reduced to a graph retaining as much functional information as possible from the original reaction system. In these graph representations, should the edges go between substrates and products, or substrates and substrates, or both? Should vertices represent substances or reactions? Different representations encode different information about the reaction system and affect network measures in different ways. This paper investigates which representation reflects the functional organization of the metabolic system in the best way, according to the defined criteria. Four different graph representations of metabolism (three where the vertices are metabolites, one where the vertices are reactions) are evaluated using data from different organisms and databases. The graph representations are evaluated by comparing the overlap between clusters (network modules) and annotated functions, and also by comparing the set of identified currency metabolites with those that other authors have identified using qualitative biological arguments. It is found that a “substance network”, where all metabolites participating in a reaction are connected, is better than others, evaluated with respect to both the functional overlap between modules and functions and to the number and identity of the identified currency metabolites.     

A Model for Design of Human Activity Systems

A background is given to the common failures of management information systems and the authors' view of the causes behind these failures. There seems to be a lack of effective methods for analyzing information requirements. Different scientific methods are discussed as to their propensity for analyzing the information requirements. The importance of the systems design approach instead of the system improvement approach is emphasized. The concept of Human Activity Systems is discussed and an analysis of the interdependence of the soft and hard parts of these systems indicates that an integrated view is necessary. A methodology based on a systemic and systematic analysis of the information requirements in an organization is proposed. This methodology focuses the settings of the decisions on all levels in organizations and also indicates organizational discrepancies and information imbalances. The methodology can be regarded as a dynamic, learning system.