100 research outputs found

    Characterization of Isolates of Sclerotium Rolfsii and Evaluation of Peanut for Reaction to Southern Blight

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    Plant Patholog

    ADESSO : Scientific software development environment

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    This paper presents the Adesso, a computational environment for the development of scientific software. The Adesso environment leverages the reusable software component programming model to support the development and integration of components to several scientific programming platforms. The Adesso system is based on an XML component database and a set of XML document transformation tools for the automatic generation of component code, documentation and packaging. An authoring tool, built with the help of the Adesso transformation system itself, is provided to assist the user in the creation of components. The Adesso system has been used for the development of several image processing toolboxes and applications. Some of them are presented briefly in this paper.Facultad de Informátic

    Causes of variation in BCG vaccine efficacy: examining evidence from the BCG REVAC cluster randomized trial to explore the masking and the blocking hypotheses.

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    BCG protection varies and in some places (nearest the equator) is low or absent. Understanding this variation can inform the efforts to develop new vaccines against tuberculosis. Two main hypotheses are used to explain this variation: under masking, new vaccines are unlikely to increase protection; under blocking new vaccines have a greater potential to be effective when BCG is not. We conducted a cluster randomized trial to explored the masking and blocking hypotheses by studying BCG vaccine efficacy of neonatal vaccination and when administered for the first or a second (revaccination) time at school age in two sites (Manaus close and Salvador further south from the equator). Seven hundred and sixty three state schools were matched on socio economic characteristics of the neighborhood and 239,934 children were randomized to vaccine (BCG vaccination at school age) or control group. Protection by first BCG vaccination at school age was high in Salvador (34%, 95% CI 7-53%, p=0.017) but low in Manaus (8%, 95% CI t0 39-40%, p=0.686). For revaccination at school age, protection was modest in Salvador (19%, 95% CI 3-33%, p=0.022) and absent in Manaus (1%, 95% CI to 27-23%, p=0.932). Vaccine efficacy for neonatal vaccination was similar in Salvador (40%, 95% CI 22-54%, p<0.001) and Manaus (36%, 95% CI 11-53%, p=0.008). Variation in BCG efficacy was marked when vaccine was given at school age but absent at birth, which points towards blocking as the dominant mechanism. New tuberculosis vaccines that overcome or by pass this blocking effect could confer protection in situations where BCG is not protective

    Identification of Dmrt2a downstream genes during zebrafish early development using a timely controlled approach

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    This research was supported by FCT (Portugal) grant (PTDC/SAU-BID/119627/2010) given to L.S. L.S. was supported by an IF contract from FCT (Portugal). R.A.P. was supported by a PhD fellowship (SFRH/BD/87607/2012) from FCT (Portugal). Publication was sponsored by LISBOA-01-0145-FEDER-007391, project co-funded by FEDER through POR Lisboa 2020 - Programa Operacional Regional de Lisboa, PORTUGAL 2020 and by Fundacao para a Ciencia e a Tecnologia.BACKGROUND: Dmrt2a is a zinc finger like transcription factor with several roles during zebrafish early development: left-right asymmetry, synchronisation of the somite clock genes and fast muscle differentiation. Despite the described functions, Dmrt2a mechanism of action is unknown. Therefore, with this work, we propose to identify Dmrt2a downstream genes during zebrafish early development. RESULTS: We generated and validated a heat-shock inducible transgenic line, to timely control dmrt2a overexpression, and dmrt2a mutant lines. We characterised dmrt2a overexpression phenotype and verified that it was very similar to the one described after knockdown of this gene, with left-right asymmetry defects and desynchronisation of somite clock genes. Additionally, we identified a new phenotype of somite border malformation. We generated several dmrt2a mutant lines, but we only detected a weak to negligible phenotype. As dmrt2a has a paralog gene, dmrt2b, with similar functions and expression pattern, we evaluated the possibility of redundancy. We found that dmrt2b does not seem to compensate the lack of dmrt2a. Furthermore, we took advantage of one of our mutant lines to confirm dmrt2a morpholino specificity, which was previously shown to be a robust knockdown tool in two independent studies. Using the described genetic tools to perform and validate a microarray, we were able to identify six genes downstream of Dmrt2a: foxj1b, pxdc1b, cxcl12b, etv2, foxc1b and cyp1a. CONCLUSIONS: In this work, we generated and validated several genetic tools for dmrt2a and identified six genes downstream of this transcription factor. The identified genes will be crucial to the future understanding of Dmrt2a mechanism of action in zebrafish.publishersversionpublishe

    Characterisation of Human Embryonic Stem Cells Conditioning Media by 1H-Nuclear Magnetic Resonance Spectroscopy

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    BACKGROUND: Cell culture media conditioned by human foreskin fibroblasts (HFFs) provide a complex supplement of protein and metabolic factors that support in vitro proliferation of human embryonic stem cells (hESCs). However, the conditioning process is variable with different media batches often exhibiting differing capacities to maintain hESCs in culture. While recent studies have examined the protein complement of conditioned culture media, detailed information regarding the metabolic component of this media is lacking. METHODOLOGY/PRINCIPAL FINDINGS: Using a (1)H-Nuclear Magnetic Resonance ((1)H-NMR) metabonomics approach, 32 metabolites and small compounds were identified and quantified in media conditioned by passage 11 HFFs (CMp11). A number of metabolites were secreted by HFFs with significantly higher concentration of lactate, alanine, and formate detected in CMp11 compared to non-conditioned media. In contrast, levels of tryptophan, folate and niacinamide were depleted in CMp11 indicating the utilisation of these metabolites by HFFs. Multivariate statistical analysis of the (1)H-NMR data revealed marked age-related differences in the metabolic profile of CMp11 collected from HFFs every 24 h over 72 h. Additionally, the metabolic profile of CMp11 was altered following freezing at -20°C for 2 weeks. CM derived from passage 18 HFFs (CMp18) was found to be ineffective at supporting hESCs in an undifferentiated state beyond 5 days culture. Multivariate statistical comparison of CMp11 and CMp18 metabolic profiles enabled rapid and clear discrimination between the two media with CMp18 containing lower concentrations of lactate and alanine as well as higher concentrations of glucose and glutamine. CONCLUSIONS/SIGNIFICANCE: (1)H-NMR-based metabonomics offers a rapid and accurate method of characterising hESC conditioning media and is a valuable tool for monitoring, controlling and optimising hESC culture media preparation

    Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study)

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    Diabetic kidney disease (DKD) is a devastating complication that affects an estimated third of patients with type 1 diabetes mellitus (DM). There is no cure once the disease is diagnosed, but early treatment at a sub-clinical stage can prevent or at least halt the progression. DKD is clinically diagnosed as abnormally high urinary albumin excretion rate (AER). We hypothesize that subtle changes in the urine metabolome precede the clinically significant rise in AER. To test this, 52 type 1 diabetic patients were recruited by the FinnDiane study that had normal AER (normoalbuminuric). After an average of 5.5 years of follow-up half of the subjects (26) progressed from normal AER to microalbuminuria or DKD (macroalbuminuria), the other half remained normoalbuminuric. The objective of this study is to discover urinary biomarkers that differentiate the progressive form of albuminuria from non-progressive form of albuminuria in humans. Metabolite profiles of baseline 24 h urine samples were obtained by gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–MS) to detect potential early indicators of pathological changes. Multivariate logistic regression modeling of the metabolomics data resulted in a profile of metabolites that separated those patients that progressed from normoalbuminuric AER to microalbuminuric AER from those patients that maintained normoalbuminuric AER with an accuracy of 75% and a precision of 73%. As this data and samples are from an actual patient population and as such, gathered within a less controlled environment it is striking to see that within this profile a number of metabolites (identified as early indicators) have been associated with DKD already in literature, but also that new candidate biomarkers were found. The discriminating metabolites included acyl-carnitines, acyl-glycines and metabolites related to tryptophan metabolism. We found candidate biomarkers that were univariately significant different. This study demonstrates the potential of multivariate data analysis and metabolomics in the field of diabetic complications, and suggests several metabolic pathways relevant for further biological studies

    Pharmacogenetics Meets Metabolomics: Discovery of Tryptophan as a New Endogenous OCT2 Substrate Related to Metformin Disposition

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    Genetic polymorphisms of the organic cation transporter 2 (OCT2), encoded by SLC22A2, have been investigated in association with metformin disposition. A functional decrease in transport function has been shown to be associated with the OCT2 variants. Using metabolomics, our study aims at a comprehensive monitoring of primary metabolite changes in order to understand biochemical alteration associated with OCT2 polymorphisms and discovery of potential endogenous metabolites related to the genetic variation of OCT2. Using GC-TOF MS based metabolite profiling, clear clustering of samples was observed in Partial Least Square Discriminant Analysis, showing that metabolic profiles were linked to the genetic variants of OCT2. Tryptophan and uridine presented the most significant alteration in SLC22A2-808TT homozygous and the SLC22A2-808G>T heterozygous variants relative to the reference. Particularly tryptophan showed gene-dose effects of transporter activity according to OCT2 genotypes and the greatest linear association with the pharmacokinetic parameters (Clrenal, Clsec, Cl/F/kg, and Vd/F/kg) of metformin. An inhibition assay demonstrated the inhibitory effect of tryptophan on the uptake of 1-methyl-4-phenyl pyrinidium in a concentration dependent manner and subsequent uptake experiment revealed differential tryptophan-uptake rate in the oocytes expressing OCT2 reference and variant (808G>T). Our results collectively indicate tryptophan can serve as one of the endogenous substrate for the OCT2 as well as a biomarker candidate indicating the variability of the transport activity of OCT2

    Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research

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    Mass spectrometry (MS) techniques, because of their sensitivity and selectivity, have become methods of choice to characterize the human metabolome and MS-based metabolomics is increasingly used to characterize the complex metabolic effects of nutrients or foods. However progress is still hampered by many unsolved problems and most notably the lack of well established and standardized methods or procedures, and the difficulties still met in the identification of the metabolites influenced by a given nutritional intervention. The purpose of this paper is to review the main obstacles limiting progress and to make recommendations to overcome them. Propositions are made to improve the mode of collection and preparation of biological samples, the coverage and quality of mass spectrometry analyses, the extraction and exploitation of the raw data, the identification of the metabolites and the biological interpretation of the results
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