15
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Therapeutic Delivery of Nanoscale Sulfur to Suppress Disease in Tomatoes: In Vitro Imaging and Orthogonal Mechanistic Investigation

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          <p class="first" id="d1032962e231">Nanoscale sulfur can be a multifunctional agricultural amendment to enhance crop nutrition and suppress disease. Pristine (nS) and stearic acid coated (cS) sulfur nanoparticles were added to soil planted with tomatoes (Solanum lycopersicum) at 200 mg/L soil and infested with Fusarium oxysporum. Bulk sulfur, ionic sulfate, and healthy controls were included. Orthogonal end points were measured in two greenhouse experiments, including agronomic and photosynthetic parameters, disease severity/suppression, mechanistic biochemical and molecular end points including the time-dependent expression of 13 genes related to two S bioassimilation and pathogenesis-response, and metabolomic profiles. Disease reduced the plant biomass by up to 87%, but nS and cS amendment significantly reduced disease as determined by area-under-the-disease-progress curve by 54 and 56%, respectively. An increase in planta S accumulation was evident, with size-specific translocation ratios suggesting different uptake mechanisms. In vivo two-photon microscopy and time-dependent gene expression revealed a nanoscale-specific elemental S bioassimilation pathway within the plant that is separate from traditional sulfate accumulation. These findings correlate well with time-dependent metabolomic profiling, which exhibited increased disease resistance and plant immunity related metabolites only with nanoscale treatment. The linked gene expression and metabolomics data demonstrate a time-sensitive physiological window where nanoscale stimulation of plant immunity will be effective. These findings provide mechanistic understandings of nonmetal nanomaterial-based suppression of plant disease and significantly advance sustainable nanoenabled agricultural strategies to increase food production. </p>

          Related collections

          Most cited references58

          • Record: found
          • Abstract: not found
          • Article: not found

          Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems

            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights

            Since its first release over a decade ago, the MetaboAnalyst web-based platform has become widely used for comprehensive metabolomics data analysis and interpretation. Here we introduce MetaboAnalyst version 5.0, aiming to narrow the gap from raw data to functional insights for global metabolomics based on high-resolution mass spectrometry (HRMS). Three modules have been developed to help achieve this goal, including: (i) a LC–MS Spectra Processing module which offers an easy-to-use pipeline that can perform automated parameter optimization and resumable analysis to significantly lower the barriers to LC-MS1 spectra processing; (ii) a Functional Analysis module which expands the previous MS Peaks to Pathways module to allow users to intuitively select any peak groups of interest and evaluate their enrichment of potential functions as defined by metabolic pathways and metabolite sets; (iii) a Functional Meta-Analysis module to combine multiple global metabolomics datasets obtained under complementary conditions or from similar studies to arrive at comprehensive functional insights. There are many other new functions including weighted joint-pathway analysis, data-driven network analysis, batch effect correction, merging technical replicates, improved compound name matching, etc. The web interface, graphics and underlying codebase have also been refactored to improve performance and user experience. At the end of an analysis session, users can now easily switch to other compatible modules for a more streamlined data analysis. MetaboAnalyst 5.0 is freely available at https://www.metaboanalyst.ca . Graphical Abstract From raw data to statistical and functional insights using MetaboAnalyst 5.0.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Fertility, mortality, migration, and population scenarios for 195 countries and territories from 2017 to 2100: a forecasting analysis for the Global Burden of Disease Study

              Summary Background Understanding potential patterns in future population levels is crucial for anticipating and planning for changing age structures, resource and health-care needs, and environmental and economic landscapes. Future fertility patterns are a key input to estimation of future population size, but they are surrounded by substantial uncertainty and diverging methodologies of estimation and forecasting, leading to important differences in global population projections. Changing population size and age structure might have profound economic, social, and geopolitical impacts in many countries. In this study, we developed novel methods for forecasting mortality, fertility, migration, and population. We also assessed potential economic and geopolitical effects of future demographic shifts. Methods We modelled future population in reference and alternative scenarios as a function of fertility, migration, and mortality rates. We developed statistical models for completed cohort fertility at age 50 years (CCF50). Completed cohort fertility is much more stable over time than the period measure of the total fertility rate (TFR). We modelled CCF50 as a time-series random walk function of educational attainment and contraceptive met need. Age-specific fertility rates were modelled as a function of CCF50 and covariates. We modelled age-specific mortality to 2100 using underlying mortality, a risk factor scalar, and an autoregressive integrated moving average (ARIMA) model. Net migration was modelled as a function of the Socio-demographic Index, crude population growth rate, and deaths from war and natural disasters; and use of an ARIMA model. The model framework was used to develop a reference scenario and alternative scenarios based on the pace of change in educational attainment and contraceptive met need. We estimated the size of gross domestic product for each country and territory in the reference scenario. Forecast uncertainty intervals (UIs) incorporated uncertainty propagated from past data inputs, model estimation, and forecast data distributions. Findings The global TFR in the reference scenario was forecasted to be 1·66 (95% UI 1·33–2·08) in 2100. In the reference scenario, the global population was projected to peak in 2064 at 9·73 billion (8·84–10·9) people and decline to 8·79 billion (6·83–11·8) in 2100. The reference projections for the five largest countries in 2100 were India (1·09 billion [0·72–1·71], Nigeria (791 million [594–1056]), China (732 million [456–1499]), the USA (336 million [248–456]), and Pakistan (248 million [151–427]). Findings also suggest a shifting age structure in many parts of the world, with 2·37 billion (1·91–2·87) individuals older than 65 years and 1·70 billion (1·11–2·81) individuals younger than 20 years, forecasted globally in 2100. By 2050, 151 countries were forecasted to have a TFR lower than the replacement level (TFR <2·1), and 183 were forecasted to have a TFR lower than replacement by 2100. 23 countries in the reference scenario, including Japan, Thailand, and Spain, were forecasted to have population declines greater than 50% from 2017 to 2100; China's population was forecasted to decline by 48·0% (−6·1 to 68·4). China was forecasted to become the largest economy by 2035 but in the reference scenario, the USA was forecasted to once again become the largest economy in 2098. Our alternative scenarios suggest that meeting the Sustainable Development Goals targets for education and contraceptive met need would result in a global population of 6·29 billion (4·82–8·73) in 2100 and a population of 6·88 billion (5·27–9·51) when assuming 99th percentile rates of change in these drivers. Interpretation Our findings suggest that continued trends in female educational attainment and access to contraception will hasten declines in fertility and slow population growth. A sustained TFR lower than the replacement level in many countries, including China and India, would have economic, social, environmental, and geopolitical consequences. Policy options to adapt to continued low fertility, while sustaining and enhancing female reproductive health, will be crucial in the years to come. Funding Bill & Melinda Gates Foundation.
                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                ACS Nano
                ACS Nano
                American Chemical Society (ACS)
                1936-0851
                1936-086X
                July 26 2022
                July 06 2022
                July 26 2022
                : 16
                : 7
                : 11204-11217
                Affiliations
                [1 ]Department of Analytical Chemistry, The Connecticut Agricultural Experiment Station, 123 Huntington Street, New Haven, Connecticut 06504, United States
                [2 ]Environmental Science and Engineering Ph.D. Program, The University of Texas at El Paso, 500 West University Avenue, El Paso, Texas 79968, United States
                [3 ]Department of Plant Pathology and Ecology, The Connecticut Agricultural Experiment Station, 123 Huntington Street, New Haven, Connecticut 06504, United States
                [4 ]Stockbridge School of Agriculture, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States
                [5 ]Department of Physics, The University of Texas at El Paso, 500 West University Avenue, El Paso, Texas 79968, United States
                [6 ]Department of Environmental Sciences, The Connecticut Agricultural Experiment Station, 123 Huntington Street, New Haven, Connecticut 06504, United States
                [7 ]Institute of Environmental Processes and Pollution Control and School of Environment and Civil Engineering, Jiangnan University, Wuxi 214122, China
                [8 ]State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210023, China
                Article
                10.1021/acsnano.2c04073
                35792576
                6d08e9c2-7636-4246-a4c0-e7398464e68f
                © 2022

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-045

                History

                Comments

                Comment on this article