13 research outputs found
Factors contributing to maize and bean yield gaps in Central America vary with site and agroecological context
2018 Fall.Includes bibliographical references.In Central America, the population and associated food demands are rising rapidly, while yields of their staple crops, maize and beans, remain low in a global context. To identify the main limiting factors to crop production in the region, field trials were established in six priority maize- and bean-producing regions in Guatemala, Honduras and El Salvador. Potential yield-limiting factors were evaluated in the 2017 growing season and included: nutrient management, irrigation, planting arrangement, and/or pest and disease control. When considering all sites, improved fertilization and pest and disease control significantly improved yields in maize by 11% and 16% respectively, but did not have a significant overall effect in beans. Irrigation had no effect in the year studied, due to sufficient and evenly distributed rainfall over the growing season. Optimized planting arrangement resulted in an average 18% increase in maize yield overall, making it the most promising factor evaluated in this study. However, the effectiveness of each factor varied across sites and no factor was effective at increasing yield consistently across all sites. Increased production was not always associated with net economic gains due to the relatively high costs of inputs and technology in the region. The study demonstrated that production constraints are highly dependent on local management practices and agroecological context. Therefore, public and private development efforts that seek to increase production should seek to identify site-specific limitations pertinent to each area in question
Participatory evaluation of improved grasses and forage legumes for smallholder livestock production in Central America
Human SCARB2-Mediated Entry and Endocytosis of EV71
Enterovirus (EV) 71 infection is known to cause hand-foot-and-mouth disease (HFMD) and in severe cases, induces neurological disorders culminating in fatality. An outbreak of EV71 in South East Asia in 1997 affected over 120,000 people and caused neurological disorders in a few individuals. The control of EV71 infection through public health interventions remains minimal and treatments are only symptomatic. Recently, human scavenger receptor class B, member 2 (SCARB2) has been reported to be a cellular receptor of EV71. We expressed human SCARB2 gene in NIH3T3 cells (3T3-SCARB2) to study the mechanisms of EV71 entry and infection. We demonstrated that human SCARB2 serves as a cellular receptor for EV71 entry. Disruption of expression of SCARB2 using siRNAs can interfere EV71 infection and subsequent inhibit the expression of viral capsid proteins in RD and 3T3-SCARB2 but not Vero cells. SiRNAs specific to clathrin or dynamin or chemical inhibitor of clathrin-mediated endocytosis were all capable of interfering with the entry of EV71 into 3T3-SCARB2 cells. On the other hand, caveolin specific siRNA or inhibitors of caveolae-mediated endocytosis had no effect, confirming that only clathrin-mediated pathway was involved in EV71 infection. Endocytosis of EV71 was also found to be pH-dependent requiring endosomal acidification and also required intact membrane cholesterol. In summary, the mechanism of EV71 entry through SCARB2 as the receptor for attachment, and its cellular entry is through a clathrin-mediated and pH-dependent endocytic pathway. This study on the receptor and endocytic mechanisms of EV71 infection is useful for the development of effective medications and prophylactic treatment against the enterovirus
Genome-Wide Association Study of White Blood Cell Count in 16,388 African Americans: the Continental Origins and Genetic Epidemiology Network (COGENT)
Total white blood cell (WBC) and neutrophil counts are lower among individuals of African descent due to the common African-derived “null” variant of the Duffy Antigen Receptor for Chemokines (DARC) gene. Additional common genetic polymorphisms were recently associated with total WBC and WBC sub-type levels in European and Japanese populations. No additional loci that account for WBC variability have been identified in African Americans. In order to address this, we performed a large genome-wide association study (GWAS) of total WBC and cell subtype counts in 16,388 African-American participants from 7 population-based cohorts available in the Continental Origins and Genetic Epidemiology Network. In addition to the DARC locus on chromosome 1q23, we identified two other regions (chromosomes 4q13 and 16q22) associated with WBC in African Americans (P<2.5×10−8). The lead SNP (rs9131) on chromosome 4q13 is located in the CXCL2 gene, which encodes a chemotactic cytokine for polymorphonuclear leukocytes. Independent evidence of the novel CXCL2 association with WBC was present in 3,551 Hispanic Americans, 14,767 Japanese, and 19,509 European Americans. The index SNP (rs12149261) on chromosome 16q22 associated with WBC count is located in a large inter-chromosomal segmental duplication encompassing part of the hydrocephalus inducing homolog (HYDIN) gene. We demonstrate that the chromosome 16q22 association finding is most likely due to a genotyping artifact as a consequence of sequence similarity between duplicated regions on chromosomes 16q22 and 1q21. Among the WBC loci recently identified in European or Japanese populations, replication was observed in our African-American meta-analysis for rs445 of CDK6 on chromosome 7q21 and rs4065321 of PSMD3-CSF3 region on chromosome 17q21. In summary, the CXCL2, CDK6, and PSMD3-CSF3 regions are associated with WBC count in African American and other populations. We also demonstrate that large inter-chromosomal duplications can result in false positive associations in GWAS
Junior Recital: Brian Hodgson, bass, Glenn West, bassoon, assisted by James Edmonds, Laurie Eash, piano, Lisa Pinza, violin, Nicholas Brown, cello
Testing the feasibility of quantifying change in agricultural soil carbon stocks through empirical sampling
<p class="MsoNormal">There is disagreement about the potential for regenerative management practices to sequester sufficient soil organic carbon (SOC) to help mitigate climate change. Measuring change in SOC stocks following practice adoption at the grain of farm fields, within the extent of regional agriculture, could help resolve this disagreement. Yet sampling demands to quantify change are considered infeasible primarily because within-field variation in stock sizes is thought to obscure accurate quantification of management effects on incremental SOC accrual. We evaluate this 'infeasibility assumption' using high-density, within-field, sampling data from 45 cropland fields inventoried for SOC. We explore how within-field sampling density, field numbers, and magnitude of simulated change in SOC stocks impacts the ability to accurately quantify management effects on SOC change. We find that (1) stock change estimates for individual fields are inaccurate and variable, where marked losses and gains in SOC stocks are frequently estimated even when no change has occurred. Higher sampling densities narrow the range of estimated stock changes but inaccuracies remain large. (2) The accuracy of stock change estimates at the project level (i.e., multiple fields) were similarly sensitive to sampling density. In contrast to individual fields, however, higher sampling densities (e.g., 1.2 ha sample<sup>-1</sup>), as well as a greater number of fields (e.g., 30), generated robust and accurate, mean project-level estimates of carbon accrual, with ~80% of the estimates falling within 20% of the simulated stock change. Yet such monitoring designs do not account for dynamic baselines, which necessitates measurement of stock changes in control, non-regenerative fields. We find (3) that higher sampling densities, field numbers, and magnitudes of simulated SOC stock change are then collectively required to make accurate estimates of management effects on stock change at the project level. The simulated effect sizes that could be consistently detected included rates of SOC accrual considered achievable and meaningful for climate mitigation (e.g., 3 Mg C ha<sup>-1</sup> 10 y<sup>-1</sup>), using field numbers and sampling densities that are reasonable given current sampling methods. Our findings reveal the potential to use empirical approaches to accurately quantify, at project scales, SOC stock responses to practice change. We provide recommendations for data that government, farmer and corporate entities should measure and share to build confidence in the effects of regenerative practices, freeing the SOC debate from overreliance on theory and data collected at scales mismatched with agricultural management.</p><p>R code is open-source statistical software and can be converted as a text file. Other file types are text for metadata and csv for data.</p><p>Funding provided by: General Mills (United States)<br>Crossref Funder Registry ID: https://ror.org/03kgyg741<br>Award Number: </p><p>Funding provided by: The Earth Fund*<br>Crossref Funder Registry ID: <br>Award Number: </p><p>Funding provided by: King Philanthropies*<br>Crossref Funder Registry ID: <br>Award Number: </p><p>Funding provided by: Arcadia Fund<br>Crossref Funder Registry ID: https://ror.org/051z6e826<br>Award Number: </p><p>Funding provided by: Yale Center for Natural Carbon Capture*<br>Crossref Funder Registry ID: <br>Award Number: </p>
Testing the feasibility of quantifying change in agricultural soil carbon stocks through empirical sampling
<p class="MsoNormal">There is disagreement about the potential for regenerative management practices to sequester sufficient soil organic carbon (SOC) to help mitigate climate change. Measuring change in SOC stocks following practice adoption at the grain of farm fields, within the extent of regional agriculture, could help resolve this disagreement. Yet sampling demands to quantify change are considered infeasible primarily because within-field variation in stock sizes is thought to obscure accurate quantification of management effects on incremental SOC accrual. We evaluate this 'infeasibility assumption' using high-density, within-field, sampling data from 45 cropland fields inventoried for SOC. We explore how within-field sampling density, field numbers, and magnitude of simulated change in SOC stocks impacts the ability to accurately quantify management effects on SOC change. We find that (1) stock change estimates for individual fields are inaccurate and variable, where marked losses and gains in SOC stocks are frequently estimated even when no change has occurred. Higher sampling densities narrow the range of estimated stock changes but inaccuracies remain large. (2) The accuracy of stock change estimates at the project level (i.e., multiple fields) were similarly sensitive to sampling density. In contrast to individual fields, however, higher sampling densities (e.g., 1.2 ha sample<sup>-1</sup>), as well as a greater number of fields (e.g., 30), generated robust and accurate, mean project-level estimates of carbon accrual, with ~80% of the estimates falling within 20% of the simulated stock change. Yet such monitoring designs do not account for dynamic baselines, which necessitates measurement of stock changes in control, non-regenerative fields. We find (3) that higher sampling densities, field numbers, and magnitudes of simulated SOC stock change are then collectively required to make accurate estimates of management effects on stock change at the project level. The simulated effect sizes that could be consistently detected included rates of SOC accrual considered achievable and meaningful for climate mitigation (e.g., 3 Mg C ha<sup>-1</sup> 10 y<sup>-1</sup>), using field numbers and sampling densities that are reasonable given current sampling methods. Our findings reveal the potential to use empirical approaches to accurately quantify, at project scales, SOC stock responses to practice change. We provide recommendations for data that government, farmer and corporate entities should measure and share to build confidence in the effects of regenerative practices, freeing the SOC debate from overreliance on theory and data collected at scales mismatched with agricultural management.</p><p>R code is open-source statistical software and can be converted as a text file. Other file types are text for metadata and csv for data.</p><p>Funding provided by: General Mills (United States)<br>Crossref Funder Registry ID: https://ror.org/03kgyg741<br>Award Number: </p><p>Funding provided by: The Earth Fund*<br>Crossref Funder Registry ID: <br>Award Number: </p><p>Funding provided by: King Philanthropies*<br>Crossref Funder Registry ID: <br>Award Number: </p><p>Funding provided by: Arcadia Fund<br>Crossref Funder Registry ID: https://ror.org/051z6e826<br>Award Number: </p><p>Funding provided by: Yale Center for Natural Carbon Capture*<br>Crossref Funder Registry ID: <br>Award Number: </p>