Despite extensive laboratory investigations in patients with respiratory tract infections, no microbiological cause can be identified in a significant proportion of patients. In the past 3 years, several novel respiratory viruses, including human metapneumovirus, severe acute respiratory syndrome (SARS) coronavirus (SARSCoV), and human coronavirus NL63, were discovered. Here we report the discovery of another novel coronavirus, coronavirus HKU1 (CoV-HKU1), from a 71-year-old man with pneumonia who had just returned from Shenzhen, China. Quantitative reverse transcription-PCR showed that the amount of CoV-HKU1 RNA was 8.5 to 9.6 ؋ 10 6 copies per ml in his nasopharyngeal aspirates (NPAs) during the first week of the illness and dropped progressively to undetectable levels in subsequent weeks. He developed increasing serum levels of specific antibodies against the recombinant nucleocapsid protein of CoV-HKU1, with immunoglobulin M (IgM) titers of 1:20, 1:40, and 1:80 and IgG titers of <1:1,000, 1:2,000, and 1:8,000 in the first, second and fourth weeks of the illness, respectively. Isolation of the virus by using various cell lines, mixed neuron-glia culture, and intracerebral inoculation of suckling mice was unsuccessful. The complete genome sequence of CoV-HKU1 is a 29,926-nucleotide, polyadenylated RNA, with G؉C content of 32%, the lowest among all known coronaviruses with available genome sequence. Phylogenetic analysis reveals that CoV-HKU1 is a new group 2 coronavirus. Screening of 400 NPAs, negative for SARS-CoV, from patients with respiratory illness during the SARS period identified the presence of CoV-HKU1 RNA in an additional specimen, with a viral load of 1.13 ؋ 10 6 copies per ml, from a 35-year-old woman with pneumonia. Our data support the existence of a novel group 2 coronavirus associated with pneumonia in humans.Since no microbiological cause can be identified for a significant proportion of patients with respiratory tract infections (18, 29), research has been conducted to identify novel agents. Of the three novel agents identified in recent 3 years, including human metapneumovirus (36), severe acute respiratory syndrome (SARS) coronavirus (SARS-CoV) (25), and human coronavirus NL63 (HCoV-NL63) (6, 37), two were coronaviruses. Coronaviruses possess the largest genomes of all RNA viruses, consisting of about 30 kb. As a result of their unique mechanism of viral replication, coronaviruses have a high frequency of recombination.Based on genotypic and serological characterization, coronaviruses were divided into three distinct groups, with human coronavirus 229E (HCoV-229E) being a group 1 coronavirus and human coronavirus OC43 (HCoV-OC43) being a group 2 coronavirus (16). They account for 5 to 30% of human respiratory tract infections. In late 2002 and 2003, the epidemic caused by SARS-CoV affected more than 8,000 people with 750 deaths (23-25, 44, 45, 51). We have also reported the isolation of SARS-CoV-like viruses from Himalayan palm civets, which suggested that animals could be the reservoir fo...

Much effort and interest have focused on assessing the importance of natural selection, particularly positive natural selection, in shaping the human genome. Although scans for positive selection have identified candidate loci that may be associated with positive selection in humans, such scans do not indicate whether adaptation is frequent in general in humans. Studies based on the reasoning of the MacDonald–Kreitman test, which, in principle, can be used to evaluate the extent of positive selection, suggested that adaptation is detectable in the human genome but that it is less common than in Drosophila or Escherichia coli. Both positive and purifying natural selection at functional sites should affect levels and patterns of polymorphism at linked nonfunctional sites. Here, we search for these effects by analyzing patterns of neutral polymorphism in humans in relation to the rates of recombination, functional density, and functional divergence with chimpanzees. We find that the levels of neutral polymorphism are lower in the regions of lower recombination and in the regions of higher functional density or divergence. These correlations persist after controlling for the variation in GC content, density of simple repeats, selective constraint, mutation rate, and depth of sequencing coverage. We argue that these results are most plausibly explained by the effects of natural selection at functional sites—either recurrent selective sweeps or background selection—on the levels of linked neutral polymorphism. Natural selection at both coding and regulatory sites appears to affect linked neutral polymorphism, reducing neutral polymorphism by 6% genome-wide and by 11% in the gene-rich half of the human genome. These findings suggest that the effects of natural selection at linked sites cannot be ignored in the study of neutral human polymorphism.

Notch signaling is an area of great interest in oncology. RO4929097 is a potent and selective inhibitor of γ-secretase, producing inhibitory activity of Notch signaling in tumor cells. The RO4929097 IC50 in cell-free and cellular assays is in the low nanomolar range with >100-fold selectivity with respect to 75 other proteins of various types (receptors, ion channels, and enzymes). RO4929097 inhibits Notch processing in tumor cells as measured by the reduction of intracellular Notch expression by Western blot. This leads to reduced expression of the Notch transcriptional target gene Hes1. RO4929097 does not block tumor cell proliferation or induce apoptosis but instead produces a less transformed, flattened, slower-growing phenotype. RO4929097 is active following oral dosing. Antitumor activity was shown in 7 of 8 xenografts tested on an intermittent or daily schedule in the absence of body weight loss or Notch-related toxicities. Importantly, efficacy is maintained after dosing is terminated. Angiogenesis reverse transcription-PCR array data show reduced expression of several key angiogenic genes. In addition, comparative microarray analysis suggests tumor cell differentiation as an additional mode of action. These preclinical results support evaluation of RO4929097 in clinical studies using an intermittent dosing schedule. A multicenter phase I dose escalation study in oncology is under way.

Motivation: Identifying drug–drug interactions (DDIs) is a critical process in drug administration and drug development. Clinical support tools often provide comprehensive lists of DDIs, but they usually lack the supporting scientific evidences and different tools can return inconsistent results. In this article, we propose a novel approach that integrates text mining and automated reasoning to derive DDIs. Through the extraction of various facts of drug metabolism, not only the DDIs that are explicitly mentioned in text can be extracted but also the potential interactions that can be inferred by reasoning.Results: Our approach was able to find several potential DDIs that are not present in DrugBank. We manually evaluated these interactions based on their supporting evidences, and our analysis revealed that 81.3% of these interactions are determined to be correct. This suggests that our approach can uncover potential DDIs with scientific evidences explaining the mechanism of the interactions.Contact: luis.tari@roche.com