111 research outputs found

    Agrobacterium rhizogenes-Mediated Transformation of the Parasitic Plant Phtheirospermum japonicum

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    Background: Plants within the Orobanchaceae are an agriculturally important group of parasites that attack economically important crops to obtain water and nutrients from their hosts. Despite their agricultural importance, molecular mechanisms of the parasitism are poorly understood. Methodology/Principal Findings: We developed transient and stable transformation systems for Phtheirospermum japonicum, a facultative parasitic plant in the Orobanchaceae. The transformation protocol was established by a combination of sonication and acetosyringone treatments using the hairy-root-inducing bacterium, Agrobacterium rhizogenes and young seedlings. Transgenic hairy roots of P. japonicum were obtained from cotyledons 2 to 3 weeks after A. rhizogenes inoculation. The presence and the expression of transgenes in P. japonicum were verified by genomic PCR, Southern blot and RT-PCR methods. Transgenic roots derived from A. rhizogenes-mediated transformation were able to develop haustoria on rice and maize roots. Transgenic roots also formed apparently competent haustoria in response to 2,6dimethoxy-1,4-benzoquinone (DMBQ), a haustorium-inducing chemical. Using this system, we introduced a reporter gene with a Cyclin B1 promoter into P. japonicum, and visualized cell division during haustorium formation. Conclusions: We provide an easy and efficient method for hairy-root transformation of P. japonicum. Transgenic marker analysis revealed that cell divisions during haustorium development occur 24 h after DMBQ treatment. The protocol

    Cigarette Smoke Affects Keratinocytes SRB1 Expression and Localization via H2O2 Production and HNE Protein Adducts Formation

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    Scavenger Receptor B1 (SR-B1), also known as HDL receptor, is involved in cellular cholesterol uptake. Stratum corneum (SC), the outermost layer of the skin, is composed of more than 25% cholesterol. Several reports support the view that alteration of SC lipid composition may be the cause of impaired barrier function which gives rise to several skin diseases. For this reason the regulation of the genes involved in cholesterol uptake is of extreme significance for skin health. Being the first shield against external insults, the skin is exposed to several noxious substances and among these is cigarette smoke (CS), which has been recently associated with various skin pathologies. In this study we first have shown the presence of SR-B1 in murine and human skin tissue and then by using immunoblotting, immunoprecipitation, RT-PCR, and confocal microscopy we have demonstrated the translocation and the subsequent lost of SR-B1 in human keratinocytes (cell culture model) after CS exposure is driven by hydrogen peroxide (H2O2) that derives not only from the CS gas phase but mainly from the activation of cellular NADPH oxidase (NOX). This effect was reversed when the cells were pretreated with NOX inhibitors or catalase. Furthermore, CS caused the formation of SR-B1-aldheydes adducts (acrolein and 4-hydroxy-2-nonenal) and the increase of its ubiquitination, which could be one of the causes of SR-B1 loss. In conclusion, exposure to CS, through the production of H2O2, induced post-translational modifications of SR-B1 with the consequence lost of the receptor and this may contribute to the skin physiology alteration as a consequence of the variation of cholesterol uptake

    AI is a viable alternative to high throughput screening: a 318-target study

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    : High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

    Coupled electrochemical splitting-off of halogens

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    Mono- and bispropellanes with a [6.2.1] fragment

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