Influence of organic and mineral amendments on microbial soil properties and processes

Microbial diversity in soils is considered important for maintaining sustainability of agricultural production systems. However, the links between microbial diversity and ecosystem processes are not well understood. This study was designed to gain better understanding of the effects of short-term management practices on the microbial community and how changes in the microbial community affect key soil processes. The effects of different forms of nitrogen (N) on soil biology and N dynamics was determined in two soils with organic and conventional management histories that varied in soil microbial properties but had the same fertility. The soils were amended with equal amounts of N (100 kg ha⁻¹) in organic (lupin, Lupinus angustifolius L.) and mineral form (urea), respectively. Over a 91-day period, microbial biomass C and N, dehydrogenase enzyme activity, community structure of pseudomondas (sensu stricto), actinomycetes and α proteobacteria (by denaturing gradient gel electrophoresis (DGGE) following PCR amplification of 16S rDNA fragments) and N mineralisation were measured. Lupin amendment resulted in a two- to five-fold increase in microbial biomass and enzyme activity, while these parameters did not differ significantly between the urea and control treatments. The PCR–DGGE analysis showed that the addition of mineral and organic compounds had an influence on the microbial community composition in the short term (up to 10 days) but the effects were not sustained over the 91-day incubation period. Microbial community structure was strongly influenced by the presence or lack of substrate, while the type of amendment (organic or mineral) had an effect on microbial biomass size and activity. These findings show that the addition of green manures improved soil biology by increasing microbial biomass and activity irrespective of management history, that no direct relationship existed among microbial structure, enzyme activity and N mineralisation, and that microbial community structure (by PCR–DGGE) was more strongly influenced by inherent soil and environmental factors than by short-term management practices

FLORA: a novel method to predict protein function from structure in diverse superfamilies

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA) that automatically generates structural motifs associated with different functional sub-families (FSGs) within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2–3 fold increase in coverage at low error rates) popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (α, β, αβ) and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues

Debris Disks: Probing Planet Formation

Debris disks are the dust disks found around ~20% of nearby main sequence stars in far-IR surveys. They can be considered as descendants of protoplanetary disks or components of planetary systems, providing valuable information on circumstellar disk evolution and the outcome of planet formation. The debris disk population can be explained by the steady collisional erosion of planetesimal belts; population models constrain where (10-100au) and in what quantity (>1Mearth) planetesimals (>10km in size) typically form in protoplanetary disks. Gas is now seen long into the debris disk phase. Some of this is secondary implying planetesimals have a Solar System comet-like composition, but some systems may retain primordial gas. Ongoing planet formation processes are invoked for some debris disks, such as the continued growth of dwarf planets in an unstirred disk, or the growth of terrestrial planets through giant impacts. Planets imprint structure on debris disks in many ways; images of gaps, clumps, warps, eccentricities and other disk asymmetries, are readily explained by planets at >>5au. Hot dust in the region planets are commonly found (<5au) is seen for a growing number of stars. This dust usually originates in an outer belt (e.g., from exocomets), although an asteroid belt or recent collision is sometimes inferred.Comment: Invited review, accepted for publication in the 'Handbook of Exoplanets', eds. H.J. Deeg and J.A. Belmonte, Springer (2018

Growing old at home – A randomized controlled trial to investigate the effectiveness and cost-effectiveness of preventive home visits to reduce nursing home admissions: study protocol [NCT00644826]

<p>Abstract</p> <p>Background</p> <p>Regarding demographic changes in Germany it can be assumed that the number of elderly and the resulting need for long term care is increasing in the near future. It is not only an individual's interest but also of public concern to avoid a nursing home admission. Current evidence indicates that preventive home visits can be an effective way to reduce the admission rate in this way making it possible for elderly people to stay longer at home than without home visits. As the effectiveness and cost-effectiveness of preventive home visits strongly depends on existing services in the social and health system existing international results cannot be merely transferred to Germany. Therefore it is necessary to investigate the effectiveness and cost-effectiveness of such an intervention in Germany by a randomized controlled trial.</p> <p>Methods</p> <p>The trial is designed as a prospective multi-center randomized controlled trial in the cities of Halle and Leipzig. The trial includes an intervention and a control group. The control group receives usual care. The intervention group receives three additional home visits by non-physician health professionals (1) geriatric assessment, (2) consultation, (3) booster session.</p> <p>The nursing home admission rate after 18 months will be defined as the primary outcome. An absolute risk reduction from a 20% in the control-group to a 7% admission rate in the intervention group including an assumed drop out rate of 30% resulted in a required sample size of N = 320 (n = 160 vs. n = 160).</p> <p>Parallel to the clinical outcome measurement the intervention will be evaluated economically. The economic evaluation will be performed from a society perspective.</p> <p>Discussion</p> <p>To the authors' knowledge for the first time a trial will investigate the effectiveness and cost-effectiveness of preventive home visits for people aged 80 and over in Germany using the design of a randomized controlled trial. Thus, the trial will contribute to the existing evidence on preventive home visits especially in Germany.</p

Novel Protein-Protein Interactions Inferred from Literature Context

We have developed a method that predicts Protein-Protein Interactions (PPIs) based on the similarity of the context in which proteins appear in literature. This method outperforms previously developed PPI prediction algorithms that rely on the conjunction of two protein names in MEDLINE abstracts. We show significant increases in coverage (76% versus 32%) and sensitivity (66% versus 41% at a specificity of 95%) for the prediction of PPIs currently archived in 6 PPI databases. A retrospective analysis shows that PPIs can efficiently be predicted before they enter PPI databases and before their interaction is explicitly described in the literature. The practical value of the method for discovery of novel PPIs is illustrated by the experimental confirmation of the inferred physical interaction between CAPN3 and PARVB, which was based on frequent co-occurrence of both proteins with concepts like Z-disc, dysferlin, and alpha-actinin. The relationships between proteins predicted by our method are broader than PPIs, and include proteins in the same complex or pathway. Dependent on the type of relationships deemed useful, the precision of our method can be as high as 90%. The full set of predicted interactions is available in a downloadable matrix and through the webtool Nermal, which lists the most likely interaction partners for a given protein. Our framework can be used for prioritizing potential interaction partners, hitherto undiscovered, for follow-up studies and to aid the generation of accurate protein interaction maps

A core outcome set for pre-eclampsia research:an international consensus development study

Objective: To develop a core outcome set for pre-eclampsia. Design: Consensus development study. Setting: International. Population: Two hundred and eight-one healthcare professionals, 41 researchers and 110 patients, representing 56 countries, participated. Methods: Modified Delphi method and Modified Nominal Group Technique. Results: A long-list of 116 potential core outcomes was developed by combining the outcomes reported in 79 pre-eclampsia trials with those derived from thematic analysis of 30 in-depth interviews of women with lived experience of pre-eclampsia. Forty-seven consensus outcomes were identified from the Delphi process following which 14 maternal and eight offspring core outcomes were agreed at the consensus development meeting. Maternal core outcomes: death, eclampsia, stroke, cortical blindness, retinal detachment, pulmonary oedema, acute kidney injury, liver haematoma or rupture, abruption, postpartum haemorrhage, raised liver enzymes, low platelets, admission to intensive care required, and intubation and ventilation. Offspring core outcomes: stillbirth, gestational age at delivery, birthweight, small-for-gestational-age, neonatal mortality, seizures, admission to neonatal unit required and respiratory support. Conclusions: The core outcome set for pre-eclampsia should underpin future randomised trials and systematic reviews. Such implementation should ensure that future research holds the necessary reach and relevance to inform clinical practice, enhance women's care and improve the outcomes of pregnant women and their babies. Tweetable abstract: 281 healthcare professionals, 41 researchers and 110 women have developed #preeclampsia core outcomes @HOPEoutcomes @jamesmnduffy. [Correction added on 29 June 2020, after first online publication: the order has been corrected.].</p

Conditional Stat1 Ablation Reveals the Importance of Interferon Signaling for Immunity to Listeria monocytogenes Infection

Signal transducer and activator of transcription 1 (Stat1) is a key player in responses to interferons (IFN). Mutations of Stat1 cause severe immune deficiencies in humans and mice. Here we investigate the importance of Stat1 signaling for the innate and secondary immune response to the intracellular bacterial pathogen Listeria monocytogenes (Lm). Cell type-restricted ablation of the Stat1 gene in naïve animals revealed unique roles in three cell types: macrophage Stat1 signaling protected against lethal Lm infection, whereas Stat1 ablation in dendritic cells (DC) did not affect survival. T lymphocyte Stat1 reduced survival. Type I IFN (IFN-I) signaling in T lymphocytes reportedly weakens innate resistance to Lm. Surprisingly, the effect of Stat1 signaling was much more pronounced, indicating a contribution of Stat1 to pathways other than the IFN-I pathway. In stark contrast, Stat1 activity in both DC and T cells contributed positively to secondary immune responses against Lm in immunized animals, while macrophage Stat1 was dispensable. Our findings provide the first genetic evidence that Stat1 signaling in different cell types produces antagonistic effects on innate protection against Lm that are obscured in mice with complete Stat1 deficiency. They further demonstrate a drastic change in the cell type-dependent Stat1 requirement for memory responses to Lm infection

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.

This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.3448Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.We thank all participants of all the studies included for enabling this research by their participation in these studies. Computer resources for this project have been provided by the high-performance computing centers of the University of Michigan and the University of Regensburg. Group-specific acknowledgments can be found in the Supplementary Note. The Center for Inherited Diseases Research (CIDR) Program contract number is HHSN268201200008I. This and the main consortium work were predominantly funded by 1X01HG006934-01 to G.R.A. and R01 EY022310 to J.L.H