Method of determining cosmological parameter ranges with samples of candles with an intrinsic distribution

In this paper, the effect of the intrinsic distribution of cosmological candles is investigated. We find that, in the case of a narrow distribution, the deviation of the observed modulus of sources from the expected central value could be estimated within a ceratin range. We thus introduce a lower and upper limits of $\chi ^{2}$, $\chi_{\min}^{2}$ and $\chi_{\max}^{2}$, to estimate cosmological parameters by applying the conventional minimizing $\chi ^{2}$ method. We apply this method to a gamma-ray burst (GRB) sample as well as to a combined sample including this GRB sample and an SN Ia sample. Our analysis shows that: a) in the case of assuming an intrinsic distribution of candles of the GRB sample, the effect of the distribution is obvious and should not be neglected; b) taking into account this effect would lead to a poorer constraint of the cosmological parameter ranges. The analysis suggests that in the attempt of constraining the cosmological model with current GRB samples, the results tend to be worse than what previously thought if the mentioned intrinsic distribution does exist.Comment: 6 pages,4 figures,1 tables.Data updated. Main conclusion unchange

Nation, Migration, Identity: Learning from the Cross-Strait Context

It has been argued that globalisation, with its flexible landscapes of production, consumption and mobility, has favoured the emergence of new forms of belonging and identity that are not necessarily built on such principles of the nation state. In this paper, we argue that this process is more likely to happen when movements occur between states that are not in conflictual relations with each other. When the relations between two nations are shaped by conflicts, for instance due to disputes about sovereignty over a territory, nationalism may remain a crucial factor shaping identification and belonging of those who move between the two territories. In this paper, by taking the case of migrants moving between the People’s Republic of China and Taiwan, we will shed light on how the issue of “unresolved sovereignty” may eventually lead these actors to reinforce nationalist ideals and identities in their daily narratives and practices, instead of favouring the generation of hybrid identities

Strong Neutral Spatial Effects Shape Tree Species Distributions across Life Stages at Multiple Scales

Traditionally, ecologists use lattice (regional summary) count data to simulate tree species distributions to explore species coexistence. However, no previous study has explicitly compared the difference between using lattice count and basal area data and analyzed species distributions at both individual species and community levels while simultaneously considering the combined scenarios of life stage and scale. In this study, we hypothesized that basal area data are more closely related to environmental variables than are count data because of strong environmental filtering effects. We also address the contribution of niche and the neutral (i.e., solely dependent on distance) factors to species distributions. Specifically, we separately modeled count data and basal area data while considering life stage and scale effects at the two levels with simultaneous autoregressive models and variation partitioning. A principal coordinates of neighbor matrix (PCNM) was used to model neutral spatial effects at the community level. The explained variations of species distribution data did not differ significantly between the two types of data at either the individual species level or the community level, indicating that the two types of data can be used nearly identically to model species distributions. Neutral spatial effects represented by spatial autoregressive parameters and the PCNM eigenfunctions drove species distributions on multiple scales, different life stages and individual species and community levels in this plot. We concluded that strong neutral spatial effects are the principal mechanisms underlying the species distributions and thus shape biodiversity spatial patterns

A Novel Escherichia coli O157:H7 Clone Causing a Major Hemolytic Uremic Syndrome Outbreak in China

An Escherichia coli O157:H7 outbreak in China in 1999 caused 177 deaths due to hemolytic uremic syndrome. Sixteen outbreak associated isolates were found to belong to a new clone, sequence type 96 (ST96), based on multilocus sequence typing of 15 housekeeping genes. Whole genome sequencing of an outbreak isolate, Xuzhou21, showed that the isolate is phylogenetically closely related to the Japan 1996 outbreak isolate Sakai, both of which share the most recent common ancestor with the US outbreak isolate EDL933. The levels of IL-6 and IL-8 of peripheral blood mononuclear cells induced by Xuzhou21 and Sakai were significantly higher than that induced by EDL933. Xuzhou21 also induced a significantly higher level of IL-8 than Sakai while both induced similar levels of IL-6. The expression level of Shiga toxin 2 in Xuzhou21 induced by mitomycin C was 68.6 times of that under non-inducing conditions, twice of that induced in Sakai (32.7 times) and 15 times higher than that induced in EDL933 (4.5 times). Our study shows that ST96 is a novel clone and provided significant new insights into the evolution of virulence of E. coli O157:H7

Genetic Networks of Liver Metabolism Revealed by Integration of Metabolic and Transcriptional Profiling

Although numerous quantitative trait loci (QTL) influencing disease-related phenotypes have been detected through gene mapping and positional cloning, identification of the individual gene(s) and molecular pathways leading to those phenotypes is often elusive. One way to improve understanding of genetic architecture is to classify phenotypes in greater depth by including transcriptional and metabolic profiling. In the current study, we have generated and analyzed mRNA expression and metabolic profiles in liver samples obtained in an F2 intercross between the diabetes-resistant C57BL/6 leptinob/ob and the diabetes-susceptible BTBR leptinob/ob mouse strains. This cross, which segregates for genotype and physiological traits, was previously used to identify several diabetes-related QTL. Our current investigation includes microarray analysis of over 40,000 probe sets, plus quantitative mass spectrometry-based measurements of sixty-seven intermediary metabolites in three different classes (amino acids, organic acids, and acyl-carnitines). We show that liver metabolites map to distinct genetic regions, thereby indicating that tissue metabolites are heritable. We also demonstrate that genomic analysis can be integrated with liver mRNA expression and metabolite profiling data to construct causal networks for control of specific metabolic processes in liver. As a proof of principle of the practical significance of this integrative approach, we illustrate the construction of a specific causal network that links gene expression and metabolic changes in the context of glutamate metabolism, and demonstrate its validity by showing that genes in the network respond to changes in glutamine and glutamate availability. Thus, the methods described here have the potential to reveal regulatory networks that contribute to chronic, complex, and highly prevalent diseases and conditions such as obesity and diabetes

Causative agent distribution and antibiotic therapy assessment among adult patients with community acquired pneumonia in Chinese urban population

<p>Abstract</p> <p>Background</p> <p>Knowledge of predominant microbial patterns in community-acquired pneumonia (CAP) constitutes the basis for initial decisions about empirical antimicrobial treatment, so a prospective study was performed during 2003–2004 among CAP of adult Chinese urban populations.</p> <p>Methods</p> <p>Qualified patients were enrolled and screened for bacterial, atypical, and viral pathogens by sputum and/or blood culturing, and by antibody seroconversion test. Antibiotic treatment and patient outcome were also assessed.</p> <p>Results</p> <p>Non-viral pathogens were found in 324/610 (53.1%) patients among whom <it>M. pneumoniae </it>was the most prevalent (126/610, 20.7%). Atypical pathogens were identified in 62/195 (31.8%) patients carrying bacterial pathogens. Respiratory viruses were identified in 35 (19%) of 184 randomly selected patients with adenovirus being the most common (16/184, 8.7%). The nonsusceptibility of <it>S. pneumoniae </it>to penicillin and azithromycin was 22.2% (Resistance (R): 3.2%, Intermediate (I): 19.0%) and 79.4% (R: 79.4%, I: 0%), respectively. Of patients (312) from whom causative pathogens were identified and antibiotic treatments were recorded, clinical cure rate with β-lactam antibiotics alone and with combination of a β-lactam plus a macrolide or with fluoroquinolones was 63.7% (79/124) and 67%(126/188), respectively. For patients having mixed <it>M. pneumoniae </it>and/or <it>C. pneumoniae </it>infections, a better cure rate was observed with regimens that are active against atypical pathogens (e.g. a β-lactam plus a macrolide, or a fluoroquinolone) than with β-lactam alone (75.8% vs. 42.9%, <it>p </it>= 0.045).</p> <p>Conclusion</p> <p>In Chinese adult CAP patients, <it>M. pneumoniae </it>was the most prevalent with mixed infections containing atypical pathogens being frequently observed. With <it>S. pneumoniae</it>, the prevalence of macrolide resistance was high and penicillin resistance low compared with data reported in other regions.</p