Comparison of the performance of synthetic maize varieties created based on either genetic distance or general combining ability of the parents

Synthetics varieties are grown by farmers and used by breeders to select new inbred lines. In countries unable to market hybrids, use of synthetics leads to yield improvements over landraces. Synthetics are derived from intercrossing inbred lines known to possess high general combining ability (GCA) as measured via crossing with testers and phenotyping for yield in multiple environments. Genetic similarity (GS) between lines measured by molecular markers may efficiently estimate GCA. Although the prediction of specific combining ability (SCA) of lines via GS has not been successful, it may have potential to predict the suitability of lines to form a synthetic variety. As this has not been reported, the objective of this research was to compare the performance of four synthetic maize varieties developed using GS calculated between parents using SSR markers with the performance of synthetics developed using GCA based on yield. Synthetics were phenotyped for yield and other agronomic traits in replicated field trials in several environments. The two synthetics formed based on low GS (0.34 and 0.33) performed better than all other synthetics in yield and most agronomic traits. The synthetics formed based on high GS (0.77 and 0.53), performed worst for nearly all traits. The GCA-based synthetics were generally intermediate for all traits. Response of synthetics to environmental variation and efficiencies gained via use of molecular markers in synthetic formation is discussed

Adrenomedullin as a potential biomarker involved in patients with hereditary hemorrhagic telangiectasia

Background: Adrenomedullin (AM) is a vasoactive peptide mostly secreted by endothelial cells with an important role in preserving endothelial integrity. The relationship between AM and hereditary hemorrhagic telangiectasia (HHT) is unknown. We aimed to compare the serum levels and tissue expression of AM between HHT patients and controls. Methods: Serum AM levels were measured by radioimmunoassay and compared between control and HHT groups. AM levels were also compared among HHT subgroups according to clinical characteristics. The single nucleotide polymorphism (SNP) rs4910118 was assessed by restriction analysis and sequencing. AM immunohistochemistry was performed on biopsies of cutaneous telangiectasia from eight HHT patients and on the healthy skin from five patients in the control group. Results: Forty-five HHT patients and 50 healthy controls were included, mean age (SD) was 50.7 (14.9) years and 46.4 (9.9) years (p = 0.102), respectively. HHT patients were mostly female (60% vs 38%, p = 0.032). Median [Q1-Q3] serum AM levels were 68.3 [58.1-80.6] pg/mL in the HHT group and 47.7 [43.2-53.8] pg/mL in controls (p<0.001), with an optimal AM cut-off according to Youden's J statistic of 55.32 pg/mL (J:0.729). Serum AM levels were similar in the HHT subgroups. No patient with HHT had the SNP rs4910118. AM immunoreactivity was found with high intensity in the abnormal blood vessels of HHT biopsies

Image informatics strategies for deciphering neuronal network connectivity

Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services

The taxonomic name resolution service : an online tool for automated standardization of plant names

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Bioinformatics 14 (2013): 16, doi:10.1186/1471-2105-14-16.The digitization of biodiversity data is leading to the widespread application of taxon names that are superfluous, ambiguous or incorrect, resulting in mismatched records and inflated species numbers. The ultimate consequences of misspelled names and bad taxonomy are erroneous scientific conclusions and faulty policy decisions. The lack of tools for correcting this ‘names problem’ has become a fundamental obstacle to integrating disparate data sources and advancing the progress of biodiversity science. The TNRS, or Taxonomic Name Resolution Service, is an online application for automated and user-supervised standardization of plant scientific names. The TNRS builds upon and extends existing open-source applications for name parsing and fuzzy matching. Names are standardized against multiple reference taxonomies, including the Missouri Botanical Garden's Tropicos database. Capable of processing thousands of names in a single operation, the TNRS parses and corrects misspelled names and authorities, standardizes variant spellings, and converts nomenclatural synonyms to accepted names. Family names can be included to increase match accuracy and resolve many types of homonyms. Partial matching of higher taxa combined with extraction of annotations, accession numbers and morphospecies allows the TNRS to standardize taxonomy across a broad range of active and legacy datasets. We show how the TNRS can resolve many forms of taxonomic semantic heterogeneity, correct spelling errors and eliminate spurious names. As a result, the TNRS can aid the integration of disparate biological datasets. Although the TNRS was developed to aid in standardizing plant names, its underlying algorithms and design can be extended to all organisms and nomenclatural codes. The TNRS is accessible via a web interface at http://tnrs.iplantcollaborative.org/ webcite and as a RESTful web service and application programming interface. Source code is available at https://github.com/iPlantCollaborativeOpenSource/TNRS/ webcite.BJE was supported by NSF grant DBI 0850373 and TR by CSIRO Marine and Atmospheric Research, Australia,. BB and BJE acknowledge early financial support from Conservation International and TEAM who funded the development of early prototypes of taxonomic name resolution. The iPlant Collaborative (http://www.iplantcollaborative.org) is funded by a grant from the National Science Foundation (#DBI-0735191)

Seroepidemiology of Toxoplasma gondii infection in pregnant women in a public hospital in northern Mexico

BACKGROUND: Toxoplasma gondii (T. gondii) infection in pregnant women represents a risk for congenital disease. There is scarce information about the epidemiology of T. gondii infection in pregnant women in Mexico. Therefore, we sought to determine the prevalence of T. gondii infection and associated socio-demographic, clinical and behavioural characteristics in a population of pregnant women of Durango City, Mexico. METHODS: Three hundred and forty three women seeking prenatal care in a public hospital of Durango City in Mexico were examined for T. gondii infection. All women were tested for anti-T. gondii IgM and IgG antibodies by using IMx Toxo IgM and IMx Toxo IgG 2.0 kits (Abbott Laboratories, Abbott Park, IL, USA), respectively. Socio-demographic, clinical and behavioural characteristics from each participant were also obtained. RESULTS: Twenty one out of the 343 (6.1%) women had IgG anti-T. gondii antibodies. None of the 343 women had IgM anti-T. gondii antibodies. Multivariate analysis using logic regression showed that T. gondii infection was associated with living in a house with soil floor (adjusted OR = 7.16; 95% CI: 1.39–36.84), residing outside of Durango State (adjusted OR = 4.25; 95% CI: 1.72–10.49), and turkey meat consumption (adjusted OR = 3.85; 95% CI: 1.30–11.44). Other characteristics as cat contact, gardening, and food preferences did not show any association with T. gondii infection. CONCLUSION: The prevalence of T. gondii infection in pregnant women of Durango City is low as compared with those reported in other regions of Mexico and the majority of other countries. Poor housing conditions as soil floors, residing in other Mexican States, and turkey meat consumption might contribute to acquire T. gondii infection

A global action agenda for turning the tide on fatty liver disease

Background and Aims: Fatty liver disease is a major public health threat due to its very high prevalence and related morbidity and mortality. Focused and dedicated interventions are urgently needed to target disease prevention, treatment, and care. Approach and Results: We developed an aligned, prioritized action agenda for the global fatty liver disease community of practice. Following a Delphi methodology over 2 rounds, a large panel (R1 n = 344, R2 n = 288) reviewed the action priorities using Qualtrics XM, indicating agreement using a 4-point Likert-scale and providing written feedback. Priorities were revised between rounds, and in R2, panelists also ranked the priorities within 6 domains: epidemiology, treatment and care, models of care, education and awareness, patient and community perspectives, and leadership and public health policy. The consensus fatty liver disease action agenda encompasses 29 priorities. In R2, the mean percentage of “agree” responses was 82.4%, with all individual priorities having at least a super-majority of agreement (> 66.7% “agree”). The highest-ranked action priorities included collaboration between liver specialists and primary care doctors on early diagnosis, action to address the needs of people living with multiple morbidities, and the incorporation of fatty liver disease into relevant non-communicable disease strategies and guidance. Conclusions: This consensus-driven multidisciplinary fatty liver disease action agenda developed by care providers, clinical researchers, and public health and policy experts provides a path to reduce the prevalence of fatty liver disease and improve health outcomes. To implement this agenda, concerted efforts will be needed at the global, regional, and national levels