Comprehensive data infrastructure for plant bioinformatics

The iPlant Collaborative is a 5-year, National Science Foundation-funded effort to develop cyberinfrastructure to address a series of grand challenges in plant science. The second of these grand challenges is the Genotype-to- Phenotype project, which seeks to provide tools, in the form of a web-based Discovery Environment, for understanding the developmental process from DNA to a full-grown plant. Addressing this challenge requires the integration of multiple data types that may be stored in multiple formats, with varying levels of standardization. Providing for reproducibility requires that detailed information documenting the experimental provenance of data, and the computational transformations applied to data once it is brought into the iPlant environment. Handling the large quantities of data involved in high-throughput sequencing and other experimental sources of bioinformatics data requires a robust infrastructure for storing and reusing large data objects. We describe the currently planned workflows to be developed for the Genotype-to-Phenotype discovery environment, the data types and formats that must be imported and manipulated within the environment, and we describe the data model that has been developed to express and exchange data within the Discovery Environment, along with the provenance model defined for capturing experimental source and digital transformation descriptions. Capabilities for interaction with reference databases are addressed, focusing not just on the ability to retrieve data from such data sources, but on the ability to use the iPlant Discovery Environment to further populate these important resources. Future activities and the challenges they will present to the data infrastructure of the iPlant Collaborative are also described. © 2010 IEEE

Atrial natriuretic peptide (ANP) gene promoter variant and increased susceptibility to early development of hypertension in humans.

Previous evidence supports a role of atrial natriuretic peptide (ANP) as a candidate gene for hypertension. We characterized an ANP gene promoter variant, which has been associated with lower peptide levels, in a sample of young male subjects from Southern Italy (n=395, mean age=35.2+/-2 years) followed up for 28 years. In this cohort, the ANP gene variant was associated with early blood pressure increase and predisposition to develop hypertension

Characterization of a surface-active protein extracted from a marine strain of penicillium chrysogenum

Marine microorganisms represent a reservoir of new promising secondary metabolites. Surface-active proteins with good emulsification activity can be isolated from fungal species that inhabit the marine environment and can be promising candidates for different biotechnological applications. In this study a novel surface-active protein, named Sap-Pc, was purified from a marine strain of Penicillium chrysogenum. The effect of salt concentration and temperature on protein production was analyzed, and a purification method was set up. The purified protein, identified as Pc13g06930, was annotated as a hypothetical protein. It was able to form emulsions, which were stable for at least one month, with an emulsification index comparable to that of other known surface-active proteins. The surface tension reduction was analyzed as function of protein concentration and a critical micellar concentration of 2 M was determined. At neutral or alkaline pH, secondary structure changes were monitored over time, concurrently with the appearance of protein precipitation. Formation of amyloid-like fibrils of SAP-Pc was demonstrated by spectroscopic and microscopic analyses. Moreover, the effect of protein concentration, a parameter affecting kinetics of fibril formation, was investigated and an on-pathway involvement of micellar aggregates during the fibril formation process was suggested

Ensuring meiotic DNA break formation in the mouse pseudoautosomal region

In mice, the pseudoautosomal region of the sex chromosomes undergoes a dynamic structural rearrangement to promote a high rate of DNA double-strand breaks and to ensure X-Y recombination. Sex chromosomes in males of most eutherian mammals share only a small homologous segment, the pseudoautosomal region (PAR), in which the formation of double-strand breaks (DSBs), pairing and crossing over must occur for correct meiotic segregation(1,2). How cells ensure that recombination occurs in the PAR is unknown. Here we present a dynamic ultrastructure of the PAR and identify controlling cis- and trans-acting factors that make the PAR the hottest segment for DSB formation in the male mouse genome. Before break formation, multiple DSB-promoting factors hyperaccumulate in the PAR, its chromosome axes elongate and the sister chromatids separate. These processes are linked to heterochromatic mo-2 minisatellite arrays, and require MEI4 and ANKRD31 proteins but not the axis components REC8 or HORMAD1. We propose that the repetitive DNA sequence of the PAR confers unique chromatin and higher-order structures that are crucial for recombination. Chromosome synapsis triggers collapse of the elongated PAR structure and, notably, oocytes can be reprogrammed to exhibit spermatocyte-like levels of DSBs in the PAR simply by delaying or preventing synapsis. Thus, the sexually dimorphic behaviour of the PAR is in part a result of kinetic differences between the sexes in a race between the maturation of the PAR structure, formation of DSBs and completion of pairing and synapsis. Our findings establish a mechanistic paradigm for the recombination of sex chromosomes during meiosis.Peer reviewe

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 diagnostic accuracy of high b-value diffusion- and T2-weighted imaging for the detection of prostate cancer: a meta-analysis

Purpose: This study aims to investigate the role of diffusion-weighted imaging (DWI) and T2-weighted imaging (T2WI) in combination for the detection of prostate cancer, specifically assessing the role of high b-values (> 1000 s/mm2), with a systematic review and meta-analysis of the existing published data.  Methods: The electronic databases MEDLINE, EMBASE, and OpenSIGLE were searched between inception and September 1, 2017. Eligible studies were those that reported the sensitivity and specificity of DWI and T2WI for the diagnosis of prostate cancer by visual assessment using a histopathologic reference standard. The QUADAS-2 critical appraisal tool was used to assess the quality of included studies. A meta-analysis with pooling of sensitivity, specificity, likelihood, and diagnostic odds ratios was undertaken, and a summary receiver-operating characteristics (sROC) curve was constructed. Predetermined subgroup analysis was also performed.  Results: Thirty-three studies were included in the final analysis, evaluating 2949 patients. The pooled sensitivity and specificity were 0.69 (95% CI 0.68–0.69) and 0.84 (95% CI 0.83–0.85), respectively, and the sROC AUC was 0.84 (95% CI 0.81–0.87). Subgroup analysis showed significantly better sensitivity with high b-values (> 1000 s/mm2). There was high statistical heterogeneity between studies.  Conclusion: The diagnostic accuracy of combined DWI and T2WI is good with high b-values (> 1000 s/mm2) seeming to improve overall sensitivity while maintaining specificity. However, further large-scale studies specifically looking at b-value choice are required before a categorical recommendation can be made

Reduced brain UCP2 expression mediated by microRNA-503 contributes to increased stroke susceptibility in the high-salt fed stroke-prone spontaneously hypertensive rat

UCP2 maps nearby the lod score peak of STR1-stroke QTL in the SHRSP rat strain. We explored the potential contribution of UCP2 to the high-salt diet (JD)-dependent increased stroke susceptibility of SHRSP. Male SHRSP, SHRSR, two reciprocal SHRSR/SHRSP-STR1/QTL stroke congenic lines received JD for 4 weeks to detect brain UCP2 gene/protein modulation as compared with regular diet (RD). Brains were also analyzed for NF-\u3baB protein expression, oxidative stress level and UCP2-targeted microRNAs expression level. Next, based on knowledge that fenofibrate and Brassica Oleracea (BO) stimulate UCP2 expression through PPAR\u3b1 activation, we monitored stroke occurrence in SHRSP receiving JD plus fenofibrate versus vehicle, JD plus BO juice versus BO juice plus PPAR\u3b1 inhibitor. Brain UCP2 expression was markedly reduced by JD in SHRSP and in the (SHRsr.SHRsp-(D1Rat134-Mt1pa)) congenic line, whereas NF-\u3baB expression and oxidative stress level increased. The opposite phenomenon was observed in the SHRSR and in the (SHRsp.SHRsr-(D1Rat134-Mt1pa)) reciprocal congenic line. Interestingly, the UCP2-targeted rno-microRNA-503 was significantly upregulated in SHRSP and decreased in SHRSR upon JD, with consistent changes in the two reciprocal congenic lines. Both fenofibrate and BO significantly decreased brain microRNA-503 level, upregulated UCP2 expression and protected SHRSP from stroke occurrence. In vitro overexpression of microRNA-503 in endothelial cells suppressed UCP2 expression and led to a significant increase of cell mortality with decreased cell viability. Brain UCP2 downregulation is a determinant of increased stroke predisposition in high-salt-fed SHRSP. In this context, UCP2 can be modulated by both pharmacological and nutraceutical agents. The microRNA-503 significantly contributes to mediate brain UCP2 downregulation in JD-fed SHRSP

METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII

Purpose: To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies. Methods: We conducted an online modified Delphi study with a group of international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members to identify the items to be voted; and Stage#3, four rounds of the modified Delphi exercise by panelists to determine the items eligible for the METRICS and their weights. The consensus threshold was 75%. Based on the median ranks derived from expert panel opinion and their rank-sum based conversion to importance scores, the category and item weights were calculated. Result: In total, 59 panelists from 19 countries participated in selection and ranking of the items and categories. Final METRICS tool included 30 items within 9 categories. According to their weights, the categories were in descending order of importance: study design, imaging data, image processing and feature extraction, metrics and comparison, testing, feature processing, preparation for modeling, segmentation, and open science. A web application and a repository were developed to streamline the calculation of the METRICS score and to collect feedback from the radiomics community. Conclusion: In this work, we developed a scoring tool for assessing the methodological quality of the radiomics research, with a large international panel and a modified Delphi protocol. With its conditional format to cover methodological variations, it provides a well-constructed framework for the key methodological concepts to assess the quality of radiomic research papers. Critical relevance statement: A quality assessment tool, METhodological RadiomICs Score (METRICS), is made available by a large group of international domain experts, with transparent methodology, aiming at evaluating and improving research quality in radiomics and machine learning. Key points: • A methodological scoring tool, METRICS, was developed for assessing the quality of radiomics research, with a large international expert panel and a modified Delphi protocol. • The proposed scoring tool presents expert opinion-based importance weights of categories and items with a transparent methodology for the first time. • METRICS accounts for varying use cases, from handcrafted radiomics to entirely deep learning-based pipelines. • A web application has been developed to help with the calculation of the METRICS score (https://metricsscore.github.io/metrics/METRICS.html) and a repository created to collect feedback from the radiomics community (https://github.com/metricsscore/metrics). Graphical Abstract: [Figure not available: see fulltext.

brainlife.io: A decentralized and open source cloud platform to support neuroscience research

Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering access to FAIR data analysis to portions of the worldwide research community. brainlife.io was developed to reduce these burdens and democratize modern neuroscience research across institutions and career levels. Using community software and hardware infrastructure, the platform provides open-source data standardization, management, visualization, and processing and simplifies the data pipeline. brainlife.io automatically tracks the provenance history of thousands of data objects, supporting simplicity, efficiency, and transparency in neuroscience research. Here brainlife.io's technology and data services are described and evaluated for validity, reliability, reproducibility, replicability, and scientific utility. Using data from 4 modalities and 3,200 participants, we demonstrate that brainlife.io's services produce outputs that adhere to best practices in modern neuroscience research