Charge-state distribution of Li ions from the β\beta decay of laser-trapped 6^{6}He atoms

Background: The accurate determination of atomic final states following nuclear $\beta$ decay plays an important role in many experiments. In particular, the charge state distributions of ions following nuclear $\beta$ decay are important for determinations of the $\beta-\nu$ angular correlation with improved precision. Purpose: Our measurement aims at providing benchmarks to test theoretical calculations. Method: The kinematics of Li$^{n+}$ ions produced following the $\beta$ decay of $^6{\rm He}$ within an electric field were measured using $^6{\rm He}$ atoms in the metastable $(1s2s,~{^3S_1})$ and in the $(1s2p,~{^3P_2})$ states confined by a magneto-optical trap. The electron shake-off probabilities were deduced including their dependence on ion energy. Results: We find significant discrepancies on the fractions of Li ions in the different charge states with respect to a recent calculation and discuss a plausible explanation. We also point out that there is no explanation for a large discrepancy between the same calculation and a previous measurement of the Li-ion energy dependence of the charge distribution from decays of the electronic ground state

Nematophagous fungus Arthrobotrys oligospora mimics olfactory cues of sex and food to lure its nematode prey

To study the molecular basis for predator-prey coevolution, we investigated how Caenorhabditis elegans responds to the predatory fungus Arthrobotrys oligospora. C. elegans and other nematodes were attracted to volatile compounds produced by A. oligospora. Gas-chromatographic mass-spectral analyses of A. oligospora-derived volatile metabolites identified several odors mimicking food cues attractive to nematodes. One compound, methyl 3-methyl-2-butenoate (MMB) additionally triggered strong sex- and stage-specific attraction in several Caenorhabditis species. Furthermore, when MMB is present, it interferes with nematode mating, suggesting that MMB might mimic sex pheromone in Caenorhabditis species. Forward genetic screening suggests that multiple receptors are involved in sensing MMB. Response to fungal odors involves the olfactory neuron AWCs. Single-cell RNA-seq revealed the GPCRs expressed in AWC. We propose that A. oligospora likely evolved the means to use olfactory mimicry to attract its nematode prey through the olfactory neurons in C. elegans and related species

Empirical and theoretical investigation into the potential impacts of insecticide resistance on the effectiveness of insecticide-treated bed nets.

In spite of widespread insecticide resistance in vector mosquitoes throughout Africa, there is limited evidence that long-lasting insecticidal bed nets (LLINs) are failing to protect against malaria. Here, we showed that LLIN contact in the course of host-seeking resulted in higher mortality of resistant Anopheles spp. mosquitoes than predicted from standard laboratory exposures with the same net. We also found that sublethal contact with an LLIN caused a reduction in blood feeding and subsequent host-seeking success in multiple lines of resistant mosquitoes from the laboratory and the field. Using a transmission model, we showed that when these LLIN-related lethal and sublethal effects were accrued over mosquito lifetimes, they greatly reduced the impact of resistance on malaria transmission potential under conditions of high net coverage. If coverage falls, the epidemiological impact is far more pronounced. Similarly, if the intensity of resistance intensifies, the loss of malaria control increases nonlinearly. Our findings help explain why insecticide resistance has not yet led to wide-scale failure of LLINs, but reinforce the call for alternative control tools and informed resistance management strategies

Gas depletion in Local Group dwarfs on ~250 kpc scales: Ram pressure stripping assisted by internal heating at early times

A recent survey of the Galaxy and M31 reveals that more than 90% of dwarf galaxies within 270 kpc of their host galaxy are deficient in HI gas. At such an extreme radius, the coronal halo gas is an order of magnitude too low to remove HI gas through ram-pressure stripping for any reasonable orbit distribution. However, all dwarfs are known to have an ancient stellar population (\geq 10 Gyr) from early epochs of vigorous star formation which, through heating of HI, could allow the hot halo to remove this gas. Our model looks at the evolution of these dwarf galaxies analytically as the host-galaxy dark matter halo and coronal halo gas builds up over cosmic time. The dwarf galaxies - treated as spherically symmetric, smooth distributions of dark matter and gas - experience early star formation, which sufficiently heats the gas allowing it to be removed easily through tidal stripping by the host galaxy, or ram-pressure stripping by a tenuous hot halo (n_H = 3x10^{-4} cm^{-3} at 50 kpc). This model of evolution is able to explain the observed radial distribution of gas-deficient and gas-rich dwarfs around the Galaxy and M31 if the dwarfs fell in at high redshifts (z~3-10).Comment: ApJ accepted. 32 pages, 11 figure

Fourhorned pelycosaurian from the Permian of Texas

p. 183-185 : 1 ill. ; 24 cm

Communal Innovations : Inspiring Neighborhoods of Hope and Advocacy

Innovations promise a better future, which may generate feelings of hope and inspire advocacy. Some innovations are more communal in nature: attempting to address a social problem, through community engagement and wide-spread adoption. For such innovations, the social processes that involve collective aspects of community life may play important roles in fostering hope and interpersonal advocacy. This study uses communication infrastructure theory and discrete emotions theory to investigate hope and advocacy within a field trial for a salient, visible, community-bound innovation to reduce transmission of malaria. Heads of households in one community (N = 119) in West Africa were interviewed. Results showed that innovation hope was predicted by appraisals of innovation attributes. Better appraisals of the innovation's attributes, greater perceived collective efficacy, and recent malaria illness predicted more innovation advocacy. The spatial analysis showed that innovation advocacy was geographically clustered within the community, but hope was not. The implications for theory and practice are discussed

A practical, bioinformatic workflow system for large data sets generated by next-generation sequencing

Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic workflow system, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This workflow system provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This system is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism

A practical, bioinformatic workflow system for large data sets generated by next-generation sequencing

Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic workflow system, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This workflow system provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This system is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism