A transcriptomic analysis of the phylum Nematoda

The phylum Nematoda occupies a huge range of ecological niches, from free-living microbivores to human parasites. We analyzed the genomic biology of the phylum using 265,494 expressed-sequence tag sequences, corresponding to 93,645 putative genes, from 30 species, including 28 parasites. From 35% to 70% of each species' genes had significant similarity to proteins from the model nematode Caenorhabditis elegans. More than half of the putative genes were unique to the phylum, and 23% were unique to the species from which they were derived. We have not yet come close to exhausting the genomic diversity of the phylum. We identified more than 2,600 different known protein domains, some of which had differential abundances between major taxonomic groups of nematodes. We also defined 4,228 nematode-specific protein families from nematode-restricted genes: this class of genes probably underpins species- and higher-level taxonomic disparity. Nematode-specific families are particularly interesting as drug and vaccine targets.     

On a family of finite moving‐average trend filters for the ends of series

A family of finite end filters is constructed using a minimum revisions criterion and based on a local dynamic model operating within the span of a given finite central filter. These end filters are equivalent to evaluating the central filter with unavailable future observations replaced by constrained optimal linear predictions. Two prediction methods are considered: best linear unbiased prediction and best linear biased prediction where the bias is time invariant. The properties of these end filters are determined. In particular, they are compared to X‐11 end filters and to the case where the central filter is evaluated with unavailable future observations predicted by global ARIMA models as in X‐11‐ARIMA or X‐12‐ARIMA. Copyright © 2002 John Wiley & Sons, Ltd.     

Association between pregnancy-associatedα 2-glycoprotein (α 2-PAG) and mixed leucocyte reaction determinants on the leucocyte surface

Summary ₂-PAG is present on the surface of mononuclear blood leucocytes and can be demonstrated predominantly on B-lymphocytes and monocytes. Pretreatment of cells with antibody to ₂-PAG leads to a marked reduction in Fc-rosette formation. Competitive blocking experiments with specific antisera reveal a particularly close asociation between ₂-PAG and MLR (mixed leucocyte reaction) determinants on the cell surface. These findings suggest one mechanism whereby ₂-PAG may modify cell-mediated immune responses.     

孤儿药的经济潜力

随着《美国孤儿药法案》的颁布以及世界多个国家相类似法案的出台,刺激了世界范围的孤儿药研究,为制药公司针对罕见病治疗的药物开发提供了潜在的利益刺激。该报告对孤儿药开发和商业运作的经济和投资进行了分析。表明尽管孤儿药比传统主流药物针对的人群小得多,但高昂的治疗费用及各种具有诱惑力的开发动力,如政府的鼓励、临床试验规模小且时间短、独占期长及审核成功率高等,让顶级孤儿药同非孤儿药一样具有生命力。     

Shigella sonnei genome sequencing and phylogenetic analysis indicate recent global dissemination from Europe

Shigella are human-adapted Escherichia coli that have gained the ability to invade the human gut mucosa and cause dysentery, spreading efficiently via low-dose fecal-oral transmission. Historically, S. sonnei has been predominantly responsible for dysentery in developed countries but is now emerging as a problem in the developing world, seeming to replace the more diverse Shigella flexneri in areas undergoing economic development and improvements in water quality. Classical approaches have shown that S. sonnei is genetically conserved and clonal. We report here whole-genome sequencing of 132 globally distributed isolates. Our phylogenetic analysis shows that the current S. sonnei population descends from a common ancestor that existed less than 500 years ago and that diversified into several distinct lineages with unique characteristics. Our analysis suggests that the majority of this diversification occurred in Europe and was followed by more recent establishment of local pathogen populations on other continents, predominantly due to the pandemic spread of a single, rapidly evolving, multidrug-resistant lineage.     

Forecasting load-duration curves

A new method is proposed for forecasting electricity load-duration curves. The approach first forecasts the load curve and then uses the resulting predictive densities to forecast the load-duration curve. A virtue of this procedure is that both load curves and load-duration curves can be predicted using the same model, and confidence intervals can be generated for both predictions. The procedure is applied to the problem of predicting New Zealand electricity consumption. A structural time-series model is used to forecast the load curve based on half-hourly data. The model is tailored to handle effects such as daylight savings, holidays and weekends, as well as trend, annual, weekly and daily cycles. Time-series methods, including Kalman filtering, smoothing and prediction, are used to fit the model and to achieve the desired forecasts of the load-duration curve.