409 research outputs found

    Influence of Cutting Date on Phenotypic Variation in Fatty Acid Concentrations of Perennial Ryegrass Genotypes from a Breeding Population

    Get PDF
    Breeding forages for increased fatty acid (FA) concentrations has the potential to improve the FA profile of ruminant products (meat and milk). Twenty perennial ryegrass genotypes from an ‘experimental’ breeding population and four genotypes from a ‘benchmark’ mapping population were used to assess genotypic variation in FAs across a growing season. Mean total FA (TFA) concentration for cuts 1 through 5 were 29.0, 31.7, 31.1, 34.4 and 42.0 g kg−1 DM, respectively. Six main individual FAs, namely palmitic acid (C16:0), trans-3-hexadecenoic acid (C16:1Δt3), stearic acid (C18:0), oleic acid (C18:1Δc9), linoleic acid (C18:2Δc9,12) and α-linolenic acid (C18:3Δc9,12,15), accounted for between 90% to 96% of TFA. Population means differed (p < 0.001) for TFA and all individual FAs, expect for C18:2Δc9,12 (p = 0.106). ‘Benchmark’ mapping population on average had 8-44% higher FA concentrations compared to the ‘experimental’ breeding population, except for C18:0 where the mapping population had lower concentrations. Individual genotypes from each population differed for all individual FAs and TFA (p < 0.05); with differences between the lowest and highest concentrations ranging from 8 to 23% amongst the mapping population genotypes and between 20 and 39% for the breeding population genotypes. Cutting date had a strong effect on population and genotype means (p <0.001) with an overall trend for FA concentrations to increase through the season. However, several significant population and genotype x cutting date interactions were also found highlighting the need for further investigations to strengthen our knowledge and understanding of how genetics and environment interact for this particular trait. Nevertheless, candidate ‘high-lipid’ genotypes were able to be identified using multivariate analysis which could be taken forward into a breeding program aimed at increasing forage FAs

    Unsupervised machine learning of integrated health and social care data from the Macmillan Improving the Cancer Journey service in Glasgow

    Get PDF
    Background: Improving the Cancer Journey (ICJ) was launched in 2014 by Glasgow City Council and Macmillan Cancer Support. As part of routine service, data is collected on ICJ users including demographic and health information, results from holistic needs assessments and quality of life scores as measured by EQ-5D health status. There is also data on the number and type of referrals made and feedback from users on the overall service. By applying artificial intelligence and interactive visualization technologies to this data, we seek to improve service provision and optimize resource allocation.Method: An unsupervised machine-learning algorithm was deployed to cluster the data. The classical k-means algorithm was extended with the k-modes technique for categorical data, and the gap heuristic automatically identified the number of clusters. The resulting clusters are used to summarize complex data sets and produce three-dimensional visualizations of the data landscape. Furthermore, the traits of new ICJ clients are predicted by approximately matching their details to the nearest existing cluster center.Results: Cross-validation showed the model’s effectiveness over a wide range of traits. For example, the model can predict marital status, employment status and housing type with an accuracy between 2.4 to 4.8 times greater than random selection. One of the most interesting preliminary findings is that area deprivation (measured through Scottish Index of Multiple Deprivation-SIMD) is a better predictor of an ICJ client’s needs than primary diagnosis (cancer type).Conclusion: A key strength of this system is its ability to rapidly ingest new data on its own and derive new predictions from those data. This means the model can guide service provision by forecasting demand based on actual or hypothesized data. The aim is to provide intelligent person-centered recommendations. The machine-learning model described here is part of a prototype software tool currently under development for use by the cancer support community.Disclosure: Funded by Macmillan Cancer Support</p

    The environmental context of the Neolithic monuments on the Brodgar Isthmus, Mainland, Orkney

    Get PDF
    This work was funded in part by Historic Environment Scotland.The World Heritage Sites of Orkney, Scotland contain iconic examples of Neolithic monumentality that have provided significant information about this period of British prehistory. However, currently, a complete understanding of the sites remains to be achieved. This is, in part, because the monuments lack an adequate context within the broader palaeolandscape. Recent investigations (seismic geophysical survey, microfossil analysis and 14C dating) in and around the Brodgar Isthmus, both onshore and offshore, are used to reconstruct the landscapes at a time when sea-level, climate and vegetation were different to that experienced today. Results show that in the early Neolithic the isthmus between the Ring of Brodgar and Stones of Stenness was broader with a smaller loch to the west. Furthermore this landscape contained sandstone outcrops that would have provided a potential source of stone for monument construction. Microfossil analysis and radiocarbon dates demonstrate that the Loch of Stenness was transformed from freshwater to brackish during the early Neolithic, perhaps immediately preceding construction of the major monuments. Finally, the analysis of our data suggests that sediment influx to the loch shows a tenfold increase coincident with widespread vegetation change that straddles the Mesolithic/Neolithic transition at c. 8 ka cal. B.P. These results provide, for the first time, a landscape context for the Neolithic sites on the isthmus.PostprintPeer reviewe

    Lung cancer::a new frontier for microbiome research and clinical translation

    Get PDF
    The lung microbiome has been shown to reflect a range of pulmonary diseases—for example: asthma, chronic obstructive pulmonary disease (COPD) and cystic fibrosis. Studies have now begun to show microbiological changes in the lung that correlate with lung cancer (LC) which could provide new insights into lung carcinogenesis and new biomarkers for disease screening. Clinical studies have suggested that infections with tuberculosis or pneumonia increased the risk of LC possibly through inflammatory or immunological changes. These have now been superseded by genomic-based microbiome sequencing studies based on bronchoalveolar lavage, sputum or saliva samples. Although some discrepancies exist, many have suggested changes in particular bacterial genera in LC samples particularly, Granulicatella, Streptococcus and Veillonella. Granulicatella is of particular interest, as it appeared to show LC stage-specific increases in abundance. We propose that these microbial community changes are likely to reflect biochemical changes in the LC lung, linked to an increase in anaerobic environmental niches and altered pyridoxal/polyamine/nitrogenous metabolism to which Granulicatella could be particularly responsive. These are clearly preliminary observations and many more expansive studies are required to develop our understanding of the LC microbiome

    Teleworking practice in small and medium-sized firms: Management style and worker autonomy

    Get PDF
    In an empirical study of teleworking practices amongst small and medium-sized enterprises (SMEs) in West London, organisational factors such as management attitudes, worker autonomy and employment flexibility were found to be more critical than technological provision in facilitating successful implementation. Consequently, we argue that telework in most SMEs appears as a marginal activity performed mainly by managers and specialist mobile workers

    Amplified Sediment waves in the Irish Sea (AmSedIS)

    Get PDF
    Exceptionally high, straight-crested and trochoidal sediment waves have recently been observed on shelf seas world-wide, and reach heights of up to 36 m in the Irish Sea. It is uncertain how the interplay between geological, biogeochemical and hydrodynamic processes influences the migration and extreme growth of these sediment waves. The AmSedIS project thus sets out to (1) investigate the role of sediment granulometry and sedimentavailability on both “extreme” and “normal” sediment wave development and (2) investigate the potential association of methane derived carbonate formation with extreme sediment wave growth. The preliminary findings are: (1) The crests of unusually high and trochoidal sediment waves still migrate over several meters per year and they consist of coarser, more poorly sorted sediments in comparison to the "normal" sediments waves; (2) Methane seepage is not considered a factor in extreme sediment wave development; (3) The excess of mobile sediment supply seems to allow for "extreme" sediment wave growth, and is linked to palaeo-tunnel valleys and the finer sediments that fill them or with converging sediment transport pathways; (4) The variation in sediment from sediment wave trough to crest to trough will form the basis for more advanced numerical modelling

    A pilot study using metagenomic sequencing of the sputum microbiome suggests potential bacterial biomarkers for lung cancer

    Get PDF
    BBSRC (UK) support (BBS/E/W/10964A01A)Lung cancer (LC) is the most prevalent cancer worldwide, and responsible for over 1.3 million deaths each year. Currently, LC has a low five year survival rates relative to other cancers, and thus, novel methods to screen for and diagnose malignancies are necessary to improve patient outcomes. Here, we report on a pilot-sized study to evaluate the potential of the sputum microbiome as a source of non-invasive bacterial biomarkers for lung cancer status and stage. Spontaneous sputum samples were collected from ten patients referred with possible LC, of which four were eventually diagnosed with LC (LC+), and six had no LC after one year (LC-). Of the seven bacterial species found in all samples, Streptococcus viridans was significantly higher in LC+ samples. Seven further bacterial species were found only in LC-, and 16 were found only in samples from LC+. Additional taxonomic differences were identified in regards to significant fold changes between LC+ and LC-cases, with five species having significantly higher abundances in LC+, with Granulicatella adiacens showing the highest level of abundance change. Functional differences, evident through significant fold changes, included polyamine metabolism and iron siderophore receptors. G. adiacens abundance was correlated with six other bacterial species, namely Enterococcus sp. 130, Streptococcus intermedius, Escherichia coli, S. viridans, Acinetobacter junii, and Streptococcus sp. 6, in LC+ samples only, which could also be related to LC stage. Spontaneous sputum appears to be a viable source of bacterial biomarkers which may have utility as biomarkers for LC status and stagepublishersversionPeer reviewe

    Effect of dietary seaweed (Ascophyllum nodosum) supplementation on milk mineral concentrations, transfer efficiency, and hematological parameters in lactating Holstein cows

    Get PDF
    This study investigated the effect of feeding seaweed (Ascophyllum nodosum) to dairy cows on milk mineral concentrations, feed-to-milk mineral transfer efficiencies and hematological parameters. Lactating Holstein cows (n = 46) were allocated to one of 2 diets (n = 23 each): (i) control (CON; without seaweed), and (ii) seaweed (SWD; replacing 330 g/d of dried corn meal in CON with 330 g/d dried A. nodosum). All cows were fed the CON diet for 4 weeks before the experiment (adaptation period); and animals were then fed the experimental diets for 9 weeks. Samples included sequential 3-week composite feed samples, a composite milk sample on the last day of each week, and a blood sample at the end of the study. Data were statistically analyzed using a linear mixed effects model with diet, week, and their interaction as fixed factors; cow (nested within diet) as a random factor and data collected on the last day of the adaptation period as covariates. Feeding SWD increased milk concentrations of Mg (+6.6 mg/kg), P (+56 mg/kg), and I (+1720 μg/kg). It also reduced transfer efficiency of Ca, Mg, P, K, Mn, and Zn, and increased transfer efficiency of Mo. Feeding SWD marginally reduced milk protein concentrations while there was no effect of SWD feeding on cows' hematological parameters. Feeding A. nodosum increased milk I concentrations, which can be beneficial when feed I concentration is limited or in demographics or populations with increased risk of I deficiency (e.g., female adolescents, pregnant women, nursing mothers). However, care should also be taken when feeding SWD to dairy cows because, in the present study, milk I concentrations were particularly high and could result in I intakes that pose a health risk for children consuming milk.The project leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 730924 (SmartCow). The analysis of macrominerals and trace elements in feed, milk, and blood plasma was funded by the University of Reading (Reading, UK); special thanks go to the laboratory personnel at the University of Reading who supported the analysis of feed, milk, and blood plasma. This output reflects only the authors' views, and the European Union cannot be held responsible for any use that may be made of the information contained therein. The data set supporting the conclusions of this article is available on request from the corresponding authors. Eric E. Newton: conceptualization, methodology, software, validation, formal analysis, investigation, data curation, writing–original draft, writing–review and editing, visualization. Katerina Theodoridou: conceptualization, methodology, resources, writing–review and editing, supervision, project administration, funding acquisition. Marta Terré: project administration, investigation, resources, writing–review and editing. Sharon Huws: writing–review and editing. Partha Ray: conceptualization, methodology, software, supervision. Christopher K. Reynolds: writing–review and editing, supervision. N. Prat: investigation, resources. D. Sabrià: investigation, resources. Sokratis Stergiadis: conceptualization, methodology, resources, data curation, writing–original draft, writing–review and editing, visualization, supervision, project administration. All authors reviewed and approved the manuscript. Animals were managed with common rearing conditions under the supervision of Institute of Agrifood Research and Technology (IRTA, Monells, Spain) technicians and the approval of the Animal Care Committee of the Government of Catalonia (authorization code 11392). The authors have not stated any conflicts of interest.info:eu-repo/semantics/publishedVersio
    corecore