1,444 research outputs found

    Bar coding MS2 spectra for metabolite identification

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    [Image: see text] Metabolite identifications are most frequently achieved in untargeted metabolomics by matching precursor mass and full, high-resolution MS(2) spectra to metabolite databases and standards. Here we considered an alternative approach for establishing metabolite identifications that does not rely on full, high-resolution MS(2) spectra. First, we select mass-to-charge regions containing the most informative metabolite fragments and designate them as bins. We then translate each metabolite fragmentation pattern into a binary code by assigning 1’s to bins containing fragments and 0’s to bins without fragments. With 20 bins, this binary-code system is capable of distinguishing 96% of the compounds in the METLIN MS(2) library. A major advantage of the approach is that it extends untargeted metabolomics to low-resolution triple quadrupole (QqQ) instruments, which are typically less expensive and more robust than other types of mass spectrometers. We demonstrate a method of acquiring MS(2) data in which the third quadrupole of a QqQ instrument cycles over 20 wide isolation windows (coinciding with the location and width of our bins) for each precursor mass selected by the first quadrupole. Operating the QqQ instrument in this mode yields diagnostic bar codes for each precursor mass that can be matched to the bar codes of metabolite standards. Furthermore, our data suggest that using low-resolution bar codes enables QqQ instruments to make MS(2)-based identifications in untargeted metabolomics with a specificity and sensitivity that is competitive to high-resolution time-of-flight technologies

    Fishers who rely on mangroves: Modelling and mapping the global intensity of mangrove-associated fisheries

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    Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor on the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial datasets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America

    Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences

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    The geometries and topologies of leaves, flowers, roots, shoots, and their arrangements have fascinated plant biologists and mathematicians alike. As such, plant morphology is inherently mathematical in that it describes plant form and architecture with geometrical and topological techniques. Gaining an understanding of how to modify plant morphology, through molecular biology and breeding, aided by a mathematical perspective, is critical to improving agriculture, and the monitoring of ecosystems is vital to modeling a future with fewer natural resources. In this white paper, we begin with an overview in quantifying the form of plants and mathematical models of patterning in plants. We then explore the fundamental challenges that remain unanswered concerning plant morphology, from the barriers preventing the prediction of phenotype from genotype to modeling the movement of leaves in air streams. We end with a discussion concerning the education of plant morphology synthesizing biological and mathematical approaches and ways to facilitate research advances through outreach, cross-disciplinary training, and open science. Unleashing the potential of geometric and topological approaches in the plant sciences promises to transform our understanding of both plants and mathematics

    Processing emotion from abstract art in frontotemporal lobar degeneration

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    Abstract art may signal emotions independently of a biological or social carrier: it might therefore constitute a test case for defining brain mechanisms of generic emotion decoding and the impact of disease states on those mechanisms. This is potentially of particular relevance to diseases in the frontotemporal lobar degeneration (FTLD) spectrum. These diseases are often led by emotional impairment despite retained or enhanced artistic interest in at least some patients. However, the processing of emotion from art has not been studied systematically in FTLD. Here we addressed this issue using a novel emotional valence matching task on abstract paintings in patients representing major syndromes of FTLD (behavioural variant frontotemporal dementia, n=11; sematic variant primary progressive aphasia (svPPA), n=7; nonfluent variant primary progressive aphasia (nfvPPA), n=6) relative to healthy older individuals (n=39). Performance on art emotion valence matching was compared between groups taking account of perceptual matching performance and assessed in relation to facial emotion matching using customised control tasks. Neuroanatomical correlates of art emotion processing were assessed using voxel-based morphometry of patients' brain MR images. All patient groups had a deficit of art emotion processing relative to healthy controls; there were no significant interactions between syndromic group and emotion modality. Poorer art emotion valence matching performance was associated with reduced grey matter volume in right lateral occopitotemporal cortex in proximity to regions previously implicated in the processing of dynamic visual signals. Our findings suggest that abstract art may be a useful model system for investigating mechanisms of generic emotion decoding and aesthetic processing in neurodegenerative diseases

    GA4GH: International policies and standards for data sharing across genomic research and healthcare.

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    The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits

    A global map of mangrove forest soil carbon at 30 m spatial resolution

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    With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30 m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250 m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kg m−3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha−1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies

    The Habitable Exoplanet Observatory (HabEx) Mission Concept Study Final Report

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    The Habitable Exoplanet Observatory, or HabEx, has been designed to be the Great Observatory of the 2030s. For the first time in human history, technologies have matured sufficiently to enable an affordable space-based telescope mission capable of discovering and characterizing Earthlike planets orbiting nearby bright sunlike stars in order to search for signs of habitability and biosignatures. Such a mission can also be equipped with instrumentation that will enable broad and exciting general astrophysics and planetary science not possible from current or planned facilities. HabEx is a space telescope with unique imaging and multi-object spectroscopic capabilities at wavelengths ranging from ultraviolet (UV) to near-IR. These capabilities allow for a broad suite of compelling science that cuts across the entire NASA astrophysics portfolio. HabEx has three primary science goals: (1) Seek out nearby worlds and explore their habitability; (2) Map out nearby planetary systems and understand the diversity of the worlds they contain; (3) Enable new explorations of astrophysical systems from our own solar system to external galaxies by extending our reach in the UV through near-IR. This Great Observatory science will be selected through a competed GO program, and will account for about 50% of the HabEx primary mission. The preferred HabEx architecture is a 4m, monolithic, off-axis telescope that is diffraction-limited at 0.4 microns and is in an L2 orbit. HabEx employs two starlight suppression systems: a coronagraph and a starshade, each with their own dedicated instrument

    The Habitable Exoplanet Observatory (HabEx) Mission Concept Study Final Report

    Get PDF
    The Habitable Exoplanet Observatory, or HabEx, has been designed to be the Great Observatory of the 2030s. For the first time in human history, technologies have matured sufficiently to enable an affordable space-based telescope mission capable of discovering and characterizing Earthlike planets orbiting nearby bright sunlike stars in order to search for signs of habitability and biosignatures. Such a mission can also be equipped with instrumentation that will enable broad and exciting general astrophysics and planetary science not possible from current or planned facilities. HabEx is a space telescope with unique imaging and multi-object spectroscopic capabilities at wavelengths ranging from ultraviolet (UV) to near-IR. These capabilities allow for a broad suite of compelling science that cuts across the entire NASA astrophysics portfolio. HabEx has three primary science goals: (1) Seek out nearby worlds and explore their habitability; (2) Map out nearby planetary systems and understand the diversity of the worlds they contain; (3) Enable new explorations of astrophysical systems from our own solar system to external galaxies by extending our reach in the UV through near-IR. This Great Observatory science will be selected through a competed GO program, and will account for about 50% of the HabEx primary mission. The preferred HabEx architecture is a 4m, monolithic, off-axis telescope that is diffraction-limited at 0.4 microns and is in an L2 orbit. HabEx employs two starlight suppression systems: a coronagraph and a starshade, each with their own dedicated instrument.Comment: Full report: 498 pages. Executive Summary: 14 pages. More information about HabEx can be found here: https://www.jpl.nasa.gov/habex

    Fishers who rely on mangroves: Modelling and mapping the global intensity of mangrove-associated fisheries

    Get PDF
    Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor on the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial datasets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America
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