Life, Death and Preferential Attachment

Scientific communities are characterized by strong stratification. The highly skewed frequency distribution of citations of published scientific papers suggests a relatively small number of active, cited papers embedded in a sea of inactive and uncited papers. We propose an analytically soluble model which allows for the death of nodes. This model provides an excellent description of the citation distributions for live and dead papers in the SPIRES database. Further, this model suggests a novel and general mechanism for the generation of power law distributions in networks whenever the fraction of active nodes is small.Comment: 5 pages, 2 figure

Promoting Partnerships for Student Success: Lessons from the SSPIRE Initiative

The Student Support Partnership Integrating Resources and Education (SSPIRE) initiative aimed to increase the success of young, low-income, and academically underprepared California community college students by helping colleges strengthen their support services and better integrate these services with academic instruction. This report describes what the nine participating community colleges did to meet the goals of SSPIRE and offers lessons for other institutions drawn from MDRC's research on the initiative

MODELING DISPERSAL OF YELLOW STARTHISTLE IN THE CANYON GRASSLANDS OF NORTH CENTRAL IDAHO

Yellow starthistle is an invasive plant species that reduces productivity and plant diversity within the canyon grasslands of Idaho. Early detection of yellow starthistle and predicting its spread have important managerial implications that could greatly reduce the economic/environmental losses due to this weed. The spread of an invasive plant species depends on its ability to reproduce and disperse seed into new areas. Typically, information on the factors that directly affect a plant’s ability to reproduce and subsequently disperse seed is not available or difficult to obtain. Alternatively, topographic factors, such as slope and aspect as well as competitive correlates such as vegetation indices related to plant community biomass could be used to model plant survival and seed movement. In this research, several spatial network models incorporating these variables were considered for the prediction of yellow starthistle dispersal. Models will differed in their assessment of plant movement costs, which can be separated into two processes, survival to reproduction and seed dispersal. The candidate models were evaluated based on their predictive ability and biological relevance. Topographical variables, slope and aspect, were found to be significant contributors to yellow starthistle dispersal models, whereas vegetation indices did not improve the prediction process. The optimal model was applied to an area in central Idaho for predicting the dispersal of yellow starthistle in 1987 given a known 1981 infestation

Comparison of the spinels Co3O4 and NiCo2O4 as bifunctional oxygen catalysts in alkaline media

Data from experiments with both rotating disc electrodes (RDEs) and gas diffusion electrodes (GDEs) are used to investigate the properties of the spinels, Co3O4 and NiCo2O4, as bifunctional oxygen electrocatalysts. Emphasis is placed on catalyst compositions and electrode structures free of carbon. Oxygen evolution and reduction occur at surfaces where the transition metals are in different oxidation states but the surface can be repeatedly cycled between these two states without significant change. It is shown that carbon-free, NiCo2O4 catalysed GDEs can be fabricated using structures based on stainless steel cloth or nickel foam. Those based on nickel foam can be cycled extensively and allow both O2 evolution and reduction at current densities up to 100 mA cm?2

Transcriptomic analysis of longitudinal Burkholderia pseudomallei infecting the cystic fibrosis lung

The melioidosis bacterium, Burkholderia pseudomallei, is increasingly being recognised as a pathogen in patients with cystic fibrosis (CF). We have recently catalogued genome-wide variation of paired, isogenic B. pseudomallei isolates from seven Australasian CF cases, which were collected between 4 and 55 months apart. Here, we extend this investigation by documenting the transcriptomic changes in B. pseudomallei in five cases. Following growth in an artificial CF sputum medium, four of the five paired isolates exhibited significant differential gene expression (DE) that affected between 32 and 792 genes. The greatest number of DE events was observed between the strains from patient CF9, consistent with the hypermutator status of the latter strain, which is deficient in the DNA mismatch repair protein MutS. Two patient isolates harboured duplications that concomitantly increased expression of the β-lactamase-encoding gene penA, and a 35 kb deletion in another abolished expression of 29 genes. Convergent expression profiles in the chronically-adapted isolates identified two significantly downregulated and 17 significantly upregulated loci, including the resistance-nodulation-division (RND) efflux pump BpeEF-OprC, the quorum-sensing hhqABCDE operon, and a cyanide- and pyocyanin-insensitive cytochrome bd quinol oxidase. These convergent pathoadaptations lead to increased expression of pathways that may suppress competing bacterial and fungal pathogens, and that enhance survival in oxygen-restricted environments, the latter of which may render conventional antibiotics less effective in vivo. Treating chronically adapted B. pseudomallei infections with antibiotics designed to target anaerobic infections, such as the nitroimidazole class of antibiotics, may significantly improve pathogen eradication attempts by exploiting this Achilles heel

Taking the next-gen step: Comprehensive antimicrobial resistance detection from Burkholderia pseudomallei

Background: Antimicrobial resistance (AMR) poses a major threat to human health. Whole-genome sequencing holds great potential for AMR identification; however, there remain major gaps in accurately and comprehensively detecting AMR across the spectrum of AMR-conferring determinants and pathogens. Methods: Using 16 wild-type Burkholderia pseudomallei and 25 with acquired AMR, we first assessed the performance of existing AMR software (ARIBA, CARD, ResFinder, and AMRFinderPlus) for detecting clinically relevant AMR in this pathogen. B. pseudomallei was chosen due to limited treatment options, high fatality rate, and AMR caused exclusively by chromosomal mutation (i.e. single-nucleotide polymorphisms [SNPs], insertions-deletions [indels], copy-number variations [CNVs], inversions, and functional gene loss). Due to poor performance with existing tools, we developed ARDaP (Antimicrobial Resistance Detection and Prediction) to identify the spectrum of AMR-conferring determinants in B. pseudomallei. Findings: CARD, ResFinder, and AMRFinderPlus failed to identify any clinically-relevant AMR in B. pseudomallei; ARIBA identified AMR encoded by SNPs and indels that were manually added to its database. However, none of these tools identified CNV, inversion, or gene loss determinants, and ARIBA could not differentiate AMR determinants from natural genetic variation. In contrast, ARDaP accurately detected all SNP, indel, CNV, inversion, and gene loss AMR determinants described in B. pseudomallei (n≈50). Additionally, ARDaP accurately predicted three previously undescribed determinants. In mixed strain data, ARDaP identified AMR to as low as ~5% allelic frequency. Interpretation: Existing AMR software packages are inadequate for chromosomal AMR detection due to an inability to detect resistance conferred by CNVs, inversions, and functional gene loss. ARDaP overcomes these major shortcomings. Further, ARDaP enables AMR prediction from mixed sequence data down to 5% allelic frequency, and can differentiate natural genetic variation from AMR determinants. ARDaP databases can be constructed for any microbial species of interest for comprehensive AMR detection

Tracing melioidosis back to the source: using whole-genome sequencing to investigate an outbreak originating from a contaminated domestic water supply

Melioidosis, a disease of public health importance in Southeast Asia and northern Australia, is caused by the Gram-negative soil bacillus Burkholderia pseudomallei. Melioidosis is typically acquired through environmental exposure, and case clusters are rare, even in regions where the disease is endemic. B. pseudomallei is classed as a tier 1 select agent by the Centers for Disease Control and Prevention; from a biodefense perspective, source attribution is vital in an outbreak scenario to rule out a deliberate release. Two cases of melioidosis within a 3-month period at a residence in rural northern Australia prompted an investigation to determine the source of exposure. B. pseudomallei isolates from the property's groundwater supply matched the multilocus sequence type of the clinical isolates. Whole-genome sequencing confirmed the water supply as the probable source of infection in both cases, with the clinical isolates differing from the likely infecting environmental strain by just one single nucleotide polymorphism (SNP) each. For the first time, we report a phylogenetic analysis of genomewide insertion/deletion (indel) data, an approach conventionally viewed as problematic due to high mutation rates and homoplasy. Our whole-genome indel analysis was concordant with the SNP phylogeny, and these two combined data sets provided greater resolution and a better fit with our epidemiological chronology of events. Collectively, this investigation represents a highly accurate account of source attribution in a melioidosis outbreak and gives further insight into a frequently overlooked reservoir of B. pseudomallei. Our methods and findings have important implications for outbreak source tracing of this bacterium and other highly recombinogenic pathogens

Comparative genomics of Burkholderia singularis sp. nov., a low G+C content, free-living bacterium that defies taxonomic dissection of the genus Burkholderia

Four Burkholderia pseudomallei-like isolates of human clinical origin were examined by a polyphasic taxonomic approach that included comparative whole genome analyses. The results demonstrated that these isolates represent a rare and unusual, novel Burkholderia species for which we propose the name B. singularis. The type strain is LMG 28154(T) (=CCUG 65685(T)). Its genome sequence has an average mol% G+C content of 64.34%, which is considerably lower than that of other Burkholderia species. The reduced G+C content of strain LMG 28154(T) was characterized by a genome wide AT bias that was not due to reduced GC-biased gene conversion or reductive genome evolution, but might have been caused by an altered DNA base excision repair pathway. B. singularis can be differentiated from other Burkholderia species by multilocus sequence analysis, MALDI-TOF mass spectrometry and a distinctive biochemical profile that includes the absence of nitrate reduction, a mucoid appearance on Columbia sheep blood agar, and a slowly positive oxidase reaction. Comparisons with publicly available whole genome sequences demonstrated that strain TSV85, an Australian water isolate, also represents the same species and therefore, to date, B. singularis has been recovered from human or environmental samples on three continents

Voltammetric studies of the mechanism of the oxygen reduction in alkaline media at the spinels Co3O4and NiCo2O4

The mechanism of O2 reduction at the spinels, Co3O4 and NiCo2O4, in KOH electrolyte is probed using voltammetry at rotating disc and rotating ring-disc electrodes by examination of the rotation rate dependent limiting currents. The analysis shows that the products and mechanisms at the two spinels are quite different. At the cobalt spinel, a substantial amount of the 2e? reduction product, H2O2, is formed while at NiCo2O4 the 4e? reduction strongly predominates. In terms of both the overpotential for reduction and its limiting current density, the mixed spinel is a substantially better electrocatalyst. It is proposed that the differences arise from an enhanced rate of O-O bond cleavage early in the reduction process at NiCo2O4