Life in soil by the actinorhizal root nodule endophyte Frankia

Frankia is a genus of soil actinomycetes famous for its ability to form N2-fixing root nodule symbioses with actinorhizal plants. Although Frankia strains diplay a high diversity in terms of ecological niches in soil, current knowledge about Frankia is dominated by its life as an endophyte in root nodules. Increased use of molecular methods has refined and expanded insights into endophyte-host specificities and Frankia phylogeny. This review has focus on Frankia as a soil organism, including its part of microbial consortia, and how to study Frankia in soil. We highlight the use of nodulation tests and molecular methods to reveal population size and genetic diversity of Frankia in soil and discuss how autoregulation of nodulation and interactions with other soil microorganisms may influence the results. A comprehensive record of published interactions between Frankia and other soil microbes is summarized

Draft Genome Sequence of Frankia sp. Strain BCU110501, a Nitrogen-Fixing Actinobacterium Isolated from Nodules of Discaria trinevis

Frankia forms a nitrogen-fixing symbiosis with actinorhizal plants. We report a draft genome sequence for Frankia sp. strain BCU110501, a nitrogen-fixing actinobacterium isolated from nodules of Discaria trinevis grown in the Patagonia region of Argentina

Negotiating stigmatisation of deviant behaviour: an exploration of locals’ perceptions of nude tourists

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Extraction of pharmacokinetic evidence of drug-drug interactions from the literature

Drug-drug interaction (DDI) is a major cause of morbidity and mortality and a subject of intense scientific interest. Biomedical literature mining can aid DDI research by extracting evidence for large numbers of potential interactions from published literature and clinical databases. Though DDI is investigated in domains ranging in scale from intracellular biochemistry to human populations, literature mining has not been used to extract specific types of experimental evidence, which are reported differently for distinct experimental goals. We focus on pharmacokinetic evidence for DDI, essential for identifying causal mechanisms of putative interactions and as input for further pharmacological and pharmacoepidemiology investigations. We used manually curated corpora of PubMed abstracts and annotated sentences to evaluate the efficacy of literature mining on two tasks: first, identifying PubMed abstracts containing pharmacokinetic evidence of DDIs; second, extracting sentences containing such evidence from abstracts. We implemented a text mining pipeline and evaluated it using several linear classifiers and a variety of feature transforms. The most important textual features in the abstract and sentence classification tasks were analyzed. We also investigated the performance benefits of using features derived from PubMed metadata fields, various publicly available named entity recognizers, and pharmacokinetic dictionaries. Several classifiers performed very well in distinguishing relevant and irrelevant abstracts (reaching F10.93, MCC0.74, iAUC0.99) and sentences (F10.76, MCC0.65, iAUC0.83). We found that word bigram features were important for achieving optimal classifier performance and that features derived from Medical Subject Headings (MeSH) terms significantly improved abstract classification. We also found that some drug-related named entity recognition tools and dictionaries led to slight but significant improvements, especially in classification of evidence sentences. Based on our thorough analysis of classifiers and feature transforms and the high classification performance achieved, we demonstrate that literature mining can aid DDI discovery by supporting automatic extraction of specific types of experimental evidence.National Institutes of Health, National Library of Medicine Program, grant 01LM011945-01 "BLR: Evidence-based Drug-Interaction Discovery: In-Vivo, In-Vitro and Clinical," a grant from the Indiana University Collaborative Research Program 2013, "Drug-Drug Interaction Prediction from Large-scale Mining of Literature and Patient Records," as well as a grant from the joint program between the Fundação Luso-Americana para o Desenvolvimento (Portugal) and National Science Foundation (USA), 2012-2014, "Network Mining For Gene Regulation And Biochemical Signaling.

Evolutionary Dynamics of Human Toll-Like Receptors and Their Different Contributions to Host Defense

Infectious diseases have been paramount among the threats to health and survival throughout human evolutionary history. Natural selection is therefore expected to act strongly on host defense genes, particularly on innate immunity genes whose products mediate the direct interaction between the host and the microbial environment. In insects and mammals, the Toll-like receptors (TLRs) appear to play a major role in initiating innate immune responses against microbes. In humans, however, it has been speculated that the set of TLRs could be redundant for protective immunity. We investigated how natural selection has acted upon human TLRs, as an approach to assess their level of biological redundancy. We sequenced the ten human TLRs in a panel of 158 individuals from various populations worldwide and found that the intracellular TLRs—activated by nucleic acids and particularly specialized in viral recognition—have evolved under strong purifying selection, indicating their essential non-redundant role in host survival. Conversely, the selective constraints on the TLRs expressed on the cell surface—activated by compounds other than nucleic acids—have been much more relaxed, with higher rates of damaging nonsynonymous and stop mutations tolerated, suggesting their higher redundancy. Finally, we tested whether TLRs have experienced spatially-varying selection in human populations and found that the region encompassing TLR10-TLR1-TLR6 has been the target of recent positive selection among non-Africans. Our findings indicate that the different TLRs differ in their immunological redundancy, reflecting their distinct contributions to host defense. The insights gained in this study foster new hypotheses to be tested in clinical and epidemiological genetics of infectious disease

Setting research priorities to improve global newborn health and prevent stillbirths by 2025.

BACKGROUND: In 2013, an estimated 2.8 million newborns died and 2.7 million were stillborn. A much greater number suffer from long term impairment associated with preterm birth, intrauterine growth restriction, congenital anomalies, and perinatal or infectious causes. With the approaching deadline for the achievement of the Millennium Development Goals (MDGs) in 2015, there was a need to set the new research priorities on newborns and stillbirth with a focus not only on survival but also on health, growth and development. We therefore carried out a systematic exercise to set newborn health research priorities for 2013-2025. METHODS: We used adapted Child Health and Nutrition Research Initiative (CHNRI) methods for this prioritization exercise. We identified and approached the 200 most productive researchers and 400 program experts, and 132 of them submitted research questions online. These were collated into a set of 205 research questions, sent for scoring to the 600 identified experts, and were assessed and scored by 91 experts. RESULTS: Nine out of top ten identified priorities were in the domain of research on improving delivery of known interventions, with simplified neonatal resuscitation program and clinical algorithms and improved skills of community health workers leading the list. The top 10 priorities in the domain of development were led by ideas on improved Kangaroo Mother Care at community level, how to improve the accuracy of diagnosis by community health workers, and perinatal audits. The 10 leading priorities for discovery research focused on stable surfactant with novel modes of administration for preterm babies, ability to diagnose fetal distress and novel tocolytic agents to delay or stop preterm labour. CONCLUSION: These findings will assist both donors and researchers in supporting and conducting research to close the knowledge gaps for reducing neonatal mortality, morbidity and long term impairment. WHO, SNL and other partners will work to generate interest among key national stakeholders, governments, NGOs, and research institutes in these priorities, while encouraging research funders to support them. We will track research funding, relevant requests for proposals and trial registers to monitor if the priorities identified by this exercise are being addressed

Setting research priorities to improve global newborn health and prevent stillbirths by 2025

Background In 2013, an estimated 2.8 million newborns died and 2.7 million were stillborn. A much greater number suffer from long term impairment associated with preterm birth, intrauterine growth restriction, congenital anomalies, and perinatal or infectious causes. With the approaching deadline for the achievement of the Millennium Development Goals (MDGs) in 2015, there was a need to set the new research priorities on newborns and stillbirth with a focus not only on survival but also on health, growth and development. We therefore carried out a systematic exercise to set newborn health research priorities for 2013-2025. Methods We used adapted Child Health and Nutrition Research Initiative (CHNRI) methods for this prioritization exercise. We identified and approached the 200 most productive researchers and 400 program experts, and 132 of them submitted research questions online. These were collated into a set of 205 research questions, sent for scoring to the 600 identified experts, and were assessed and scored by 91 experts. Results Nine out of top ten identified priorities were in the domain of research on improving delivery of known interventions, with simplified neonatal resuscitation program and clinical algorithms and improved skills of community health workers leading the list. The top 10 priorities in the domain of development were led by ideas on improved Kangaroo Mother Care at community level, how to improve the accuracy of diagnosis by community health workers, and perinatal audits. The 10 leading priorities for discovery research focused on stable surfactant with novel modes of administration for preterm babies, ability to diagnose fetal distress and novel tocolytic agents to delay or stop preterm labour. Conclusion These findings will assist both donors and researchers in supporting and conducting research to close the knowledge gaps for reducing neonatal mortality, morbidity and long term impairment. WHO, SNL and other partners will work to generate interest among key national stakeholders, governments, NGOs, and research institutes in these priorities, while encouraging research funders to support them. We will track research funding, relevant requests for proposals and trial registers to monitor if the priorities identified by this exercise are being addressed

Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

Publisher Copyright: © 2021, The Author(s).Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change.Peer reviewe