Papaya Ringspot Virus Resistance of Transgenic Rainbow and SunUp is Affected by Gene Dosage, Plant Development, and Coat Protein Homology

R1 plants of the transgenic papaya line 55-1, which expresses a single coat protein (CP) gene of the mild strain of the papaya ringspot virus (PRSV) HA from Hawaii, were previously shown to be resistant only to PRSV isolates from Hawaii. Two transgenic papaya cultivars were subsequently derived from line 55-1. UH SunUp (SunUp) is homozygous for the CP gene insertion and UH Rainbow (Rainbow) is hemizygous for the CP gene because it is a F1 hybrid of a cross between SunUp and the nontransgenic papaya cultivar Kapoho. To determine the various parameters that affect the resistance of SunUp and Rainbow, plants at different developmental stages (younger and older) were inoculated with PRSV isolates from Hawaii, Brazil, Jamaica, and Thailand. Hawaiian isolates shared nucleotide sequence identities of 96.7-99.8% to the CP transgene, and the other isolates shared sequence identities of 89.5-92.5%. Resistance was affected by CP gene dosage, plant developmental stage, and CP sequence identity of the challenge isolate. Young and older hemizygous Rainbow plants were resistant to the homologous PRSV HA (99.8% homology to CP transgene), while only older Rainbow plants were resistant to the other Hawaiian isolates (96.7% homology). However, all inoculated Rainbow plants were susceptible to PRSV isolates collected from Jamaica, Brazil, and Thailand. In contrast, SunUp was resistant to all PRSV isolates, except the one from Thailand, regardless of the plant developmental stage. Resistance to the Thailand isolate, which shares 89.5% homology to the transgene, was observed only with SunUp plants inoculated at an older stage. Steady state RNA analysis and nuclear run-on experiments suggested that resistance of the transgenic papaya is RNA-mediated via post-transcriptional gene silencin

Alterations in intracellular potassium concentration by HIV-1 and SIV Nef

<p>Abstract</p> <p>Background</p> <p>HIV-1 mediated perturbation of the plasma membrane can produce an alteration in the transmembrane gradients of cations and other small molecules leading to cell death. Several HIV-1 proteins have been shown to perturb membrane permeability and ion transport. <it>Xenopus laevis </it>oocytes have few functional endogenous ion channels, and have proven useful as a system to examine direct effects of exogenously added proteins on ion transport.</p> <p>Results</p> <p>HIV-1 Nef induces alterations in the intracellular potassium concentration in CD4+ T-lymphoblastoid cells, but not intracellular pH. Two electrode voltage-clamp recording was used to determine that Nef did not form ion channel-like pores in <it>Xenopus </it>oocytes.</p> <p>Conclusion</p> <p>These results suggest that HIV-1 Nef regulates intracellular ion concentrations indirectly, and may interact with membrane proteins such as ion channels to modify their electrical properties.</p

NOVOS INDICADORES PARA A AVALIAÇÃO DE IMPACTOS SÓCIO AMBIENTAIS DA INOVAÇÃO TECNOLÓGICA EM AGROINDÚSTRIAS DE REAPROVEITAMENTO DE RESÍDUOS. APLICAÇÃO NA AGROINDÚSTRIA DE COCO

A predição de impactos das inovações tecnológicas se constitui em elementode essencial importância para a tomada de decisões para sua implantaçãonos marcos do desenvolvimento sustentável. O presente trabalho objetivoudesenvolver novos indicadores que permitam avaliar os impactossocioambientais da implantação de novas tecnologias em agroindústrias denova geração, cuja matéria-prima fundamental são resíduos agroflorestais. Otrabalho coloca em foco inovações tecnológicas ligadas ao aproveitamentode resíduos de coco: na produção de adsorventes naturais de metais, tóxicaem água e na produção de materiais de construção, e objetiva fazer aavaliação (“ex-antes”) dos impactos socioambientais da implantação destasnovas tecnologias. É proposta e utilizada uma ampliação da metodologiaAMBITEC, da EMBRAPA, com a introdução de novos indicadores. Osresultados obtidos dos coeficientes de impacto e o Índice Geral de Impacto,no âmbito ambiental e social nos cenários estudados, indicam a viabilidadeda implementação das novas tecnologias estudadas

oFVSD: a Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data

The complexity and high dimensionality of neuroimaging data pose problems for decoding information with machine learning (ML) models because the number of features is often much larger than the number of observations. Feature selection is one of the crucial steps for determining meaningful target features in decoding; however, optimizing the feature selection from such high-dimensional neuroimaging data has been challenging using conventional ML models. Here, we introduce an efficient and high-performance decoding package incorporating a forward variable selection (FVS) algorithm and hyper-parameter optimization that automatically identifies the best feature pairs for both classification and regression models, where a total of 18 ML models are implemented by default. First, the FVS algorithm evaluates the goodness-of-fit across different models using the k-fold cross-validation step that identifies the best subset of features based on a predefined criterion for each model. Next, the hyperparameters of each ML model are optimized at each forward iteration. Final outputs highlight an optimized number of selected features (brain regions of interest) for each model with its accuracy. Furthermore, the toolbox can be executed in a parallel environment for efficient computation on a typical personal computer. With the optimized forward variable selection decoder (oFVSD) pipeline, we verified the effectiveness of decoding sex classification and age range regression on 1,113 structural magnetic resonance imaging (MRI) datasets. Compared to ML models without the FVS algorithm and with the Boruta algorithm as a variable selection counterpart, we demonstrate that the oFVSD significantly outperformed across all of the ML models over the counterpart models without FVS (approximately 0.20 increase in correlation coefficient, r, with regression models and 8% increase in classification models on average) and with Boruta variable selection algorithm (approximately 0.07 improvement in regression and 4% in classification models). Furthermore, we confirmed the use of parallel computation considerably reduced the computational burden for the high-dimensional MRI data. Altogether, the oFVSD toolbox efficiently and effectively improves the performance of both classification and regression ML models, providing a use case example on MRI datasets. With its flexibility, oFVSD has the potential for many other modalities in neuroimaging. This open-source and freely available Python package makes it a valuable toolbox for research communities seeking improved decoding accuracy

Synbiotic therapy decreases microbial translocation and inflammation and improves immunological status in HIV-infected patients: a double-blind randomized controlled pilot trial

BACKGROUND: HIV-infection results in damage and dysfunction of the gastrointestinal system. HIV enteropathy includes pronounced CD4+ T-cell loss, increased intestinal permeability, and microbial translocation that promotes systemic immune activation, which is implicated in disease progression. A synbiotic is the combination of probiotics and prebiotics that could improve gut barrier function. Our study goal was to determine whether the use of a synbiotic, probiotics or a prebiotic can recover immunological parameters in HIV-infected subjects through of a reduction of microbial translocation and pro-inflammatory cytokine production. METHODS: A randomized, double-blind controlled study was performed; twenty Antiretroviral treatment-naïve HIV-infected subjects were subgrouped and assigned to receive a synbiotic, probiotics, a prebiotic, or a placebo throughout 16 weeks. RESULTS: We had no reports of serious adverse-events. From baseline to week 16, the synbiotic group showed a reduction in bacterial DNA concentrations in plasma (p = 0.048). Moreover, the probiotic and synbiotic groups demonstrated a decrease in total bacterial load in feces (p = 0.05). The probiotic group exhibited a significant increment of beneficial bacteria load (such as Bifidobacterium; p = 0.05) and a decrease in harmful bacteria load (such as Clostridium; p = 0.063). In the synbiotic group, the CD4+ T-cells count increased (median: +102 cells/μL; p = 0.05) and the level of Interleukin 6 cytokine decreased significantly (p = 0.016). CONCLUSIONS: Our study showed a significant increase in CD4+ T lymphocyte levels in the synbiotic group, which could delay the initiation of antiretroviral therapy and decrease costs in countries with limited resources

Oxygen reduction reaction at LaxCa1-xMnO3 nanostructures: interplay between A-site segregation and B-site valency

The mean activity of surface Mn sites at LaxCa1−xMnO3 nanostructures towards the oxygen reduction reaction (ORR) in alkaline solution is assessed as a function of the oxide composition. Highly active oxide nanoparticles were synthesised by an ionic liquid-based route, yielding phase-pure nanoparticles, across the entire range of compositions, with sizes between 20 and 35 nm. The bulk vs. surface composition and structure are investigated by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and X-ray absorption near edge spectroscopy (XANES). These techniques allow quantification of not only changes in the mean oxidation state of Mn as a function of x, but also the extent of A-site surface segregation. Both trends manifest themselves in the electrochemical responses associated with surface Mn sites in 0.1 M KOH solution. The characteristic redox signatures of Mn sites are used to estimate their effective surface number density. This parameter allows comparing, for the first time, the mean electrocatalytic activity of surface Mn sites as a function of the LaxCa1−xMnO3 composition. The ensemble of experimental data provides a consistent picture in which increasing electron density at the Mn sites leads to an increase in the ORR activity. We also demonstrate that normalisation of electrochemical activity by mass or specific surface area may result in inaccurate structure–activity correlations

Landscape-use optimisation with regards to the groundwater resources protection in mountain hardrock areas, LOWRGREP

Synthesis of work performed during the European Project LOWRGREPThis report assesses the degree of interference of human activities with the hydrosphere in mountain-zones, all located in hard-rock areas of different countries in the European Union. Each of the test-regions has a specific degree of protection: from regions with very few inhabitants and very low human impact, to regions submitted to a strong anthropogenic impact. The investigations focused on the changes in water quality and on the simulation of various alternatives leading to optimum landscape-use from the point of view of water-management. The project's own Geographic Information System was used to fulfil the following objective: present all the obtained knowledge and analyse all the data in user-friendly form (maps of water vulnerability) and make this knowledge available for potential users with, for instance, the creation and use of a web site. A simulation tool has been developed which facilitates the assessment of the impact of landscape-use on the water budget of the catchment. In all the areas investigated chloride is present, only in winter and very close to roads. Another result of this work is the decreasing impact on water of sulphur and sulphuric compounds in Germany and in the Czech Republic, while the nitrogen impact is increasing. Recommendations concerning the landscape-use presented for all the regions in particular for good practices in agricultur