DISC1-dependent switch from progenitor proliferation to migration in the developing cortex

Regulatory mechanisms governing the sequence from progenitor cell proliferation to neuronal migration during corticogenesis are poorly understood. Here we report that phosphorylation of DISC1, a major susceptibility factor for several mental disorders, acts as a molecular switch from maintaining proliferation of mitotic progenitor cells to activating migration of postmitotic neurons in mice. Unphosphorylated DISC1 regulates canonical Wnt signalling via an interaction with GSK3β, whereas specific phosphorylation at serine 710 (S710) triggers the recruitment of Bardet-Biedl syndrome (BBS) proteins to the centrosome. In support of this model, loss of BBS1 leads to defects in migration, but not proliferation, whereas DISC1 knockdown leads to deficits in both. A phospho-dead mutant can only rescue proliferation, whereas a phospho-mimic mutant rescues exclusively migration defects. These data highlight a dual role for DISC1 in corticogenesis and indicate that phosphorylation of this protein at S710 activates a key developmental switch.     

Targeted gene correction of α1-antitrypsin deficiency in induced pluripotent stem cells

Human induced pluripotent stem cells (iPSCs) represent a unique opportunity for regenerative medicine because they offer the prospect of generating unlimited quantities of cells for autologous transplantation, with potential application in treatments for a broad range of disorders. However, the use of human iPSCs in the context of genetically inherited human disease will require the correction of disease-causing mutations in a manner that is fully compatible with clinical applications. The methods currently available, such as homologous recombination, lack the necessary efficiency and also leave residual sequences in the targeted genome. Therefore, the development of new approaches to edit the mammalian genome is a prerequisite to delivering the clinical promise of human iPSCs. Here we show that a combination of zinc finger nucleases (ZFNs) and piggyBac technology in human iPSCs can achieve biallelic correction of a point mutation (Glu342Lys) in the α(1)-antitrypsin (A1AT, also known as SERPINA1) gene that is responsible for α(1)-antitrypsin deficiency. Genetic correction of human iPSCs restored the structure and function of A1AT in subsequently derived liver cells in vitro and in vivo. This approach is significantly more efficient than any other gene-targeting technology that is currently available and crucially prevents contamination of the host genome with residual non-human sequences. Our results provide the first proof of principle, to our knowledge, for the potential of combining human iPSCs with genetic correction to generate clinically relevant cells for autologous cell-based therapies.     

A Computational Model of the Belief System Under the Scope of Social Communication

This paper presents an approach to the belief system based on a computational framework in three levels: first, the logic level with the definition of binary local rules, second, the arithmetic level with the definition of recursive functions and finally the behavioural level with the definition of a recursive construction pattern. Social communication is achieved when different beliefs are expressed, modified, propagated and shared through social nets. This approach is useful to mimic the belief system because the defined functions provide different ways to process the same incoming information as well as a means to propagate it. Our model also provides a means to cross different beliefs so, any incoming information can be processed many times by the same or different functions as it occurs is social nets.     

TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis

Although there has been much success in identifying genetic variants associated with common diseases using genome-wide association studies (GWAS), it has been difficult to demonstrate which variants are causal and what role they have in disease. Moreover, the modest contribution that these variants make to disease risk has raised questions regarding their medical relevance. Here we have investigated a single nucleotide polymorphism (SNP) in the TNFRSF1A gene, that encodes tumour necrosis factor receptor 1 (TNFR1), which was discovered through GWAS to be associated with multiple sclerosis (MS), but not with other autoimmune conditions such as rheumatoid arthritis, psoriasis and Crohn’s disease. By analysing MS GWAS data in conjunction with the 1000 Genomes Project data we provide genetic evidence that strongly implicates this SNP, rs1800693, as the causal variant in the TNFRSF1A region. We further substantiate this through functional studies showing that the MS risk allele directs expression of a novel, soluble form of TNFR1 that can block TNF. Importantly, TNF-blocking drugs can promote onset or exacerbation of MS, but they have proven highly efficacious in the treatment of autoimmune diseases for which there is no association with rs1800693. This indicates that the clinical experience with these drugs parallels the disease association of rs1800693, and that the MS-associated TNFR1 variant mimics the effect of TNF-blocking drugs. Hence, our study demonstrates that clinical practice can be informed by comparing GWAS across common autoimmune diseases and by investigating the functional consequences of the disease-associated genetic variation.     

Improving ONS spatial referencing--the impact on 2000 births and deaths data

This article describes the improvements in the way that ONS will be allocating births and deaths data to administrative and health areas in England and Wales, beginning with data for 2001. Births and deaths registered in 2000 are used to examine the differences in area allocations at ward, local authority and health authority levels, which this change will introduce. Differences in the geographical characteristics of births and deaths are also described.     

Testing and forecasting the degree of integration in the US inflation rate

In this article we model the log of the US inflation rate by means of fractionally integrated processes. We use the tests of Robinson (1994) for testing this type of hypothesis, which include, as particular cases, the I(0) and I(1) specifications, and which also, unusually, have standard null and local limit distributions. A model selection criterion is established to determine which may be the best model specification of the series, and the forecasting properties of the selected models are also examined. The results vary substantially depending on how we specify the disturbances. Thus, if they are white noise, the series is I(d) with d fluctuating around 0.25; however, imposing autoregressive disturbances, the log of the US inflation rate seems to be anti‐persistent, with an order of integration smaller than zero. Looking at the forecasting properties, those models based on autocorrelated disturbances (with d < 0) predict better over a short horizon, while those based on white noise disturbances (with d > 0) seem to predict better over longer periods of time. Copyright © 2005 John Wiley & Sons, Ltd.