114 research outputs found

    3-Methyl­quinoxaline-2-carb­oxy­lic acid 4-oxide monohydrate

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    In the crystal structure of the title compound, C10H8N2O3·H2O, mol­ecules are linked via inter­molecular O—H⋯O and O—H⋯N hydrogen bonds into a two-dimensional network

    Characterisation of two quorum sensing systems in the endophytic Serratia plymuthica strain G3: differential control of motility and biofilm formation according to life-style

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    <p>Abstract</p> <p>Background</p> <p><it>N</it>-acylhomoserine lactone (AHL)-based quorum sensing (QS) systems have been described in many plant-associated Gram-negative bacteria to control certain beneficial phenotypic traits, such as production of biocontrol factors and plant growth promotion. However, the role of AHL-mediated signalling in the endophytic strains of plant-associated <it>Serratia </it>is still poorly understood. An endophytic <it>Serratia </it>sp. G3 with biocontrol potential and high levels of AHL signal production was isolated from the stems of wheat and the role of QS in this isolate was determined.</p> <p>Results</p> <p>Strain G3 classified as <it>Serratia plymuthica </it>based on 16S rRNA was subjected to phylogenetic analysis. Using primers to conserved sequences of <it>luxIR </it>homologues from the <it>Serratia </it>genus, <it>splIR </it>and <it>spsIR </it>from the chromosome of strain G3 were cloned and sequenced. AHL profiles from strain G3 and <it>Escherichia coli </it>DH5α expressing <it>splI </it>or <it>spsI </it>from recombinant plasmids were identified by liquid chromatography-tandem mass spectrometry. This revealed that the most abundant AHL signals produced by SplI in <it>E. coli </it>were <it>N</it>-3-oxo-hexanoylhomoserine lactone (3-oxo-C6-HSL), <it>N</it>-3-oxo-heptanoylhomoserine lactone (3-oxo-C7-HSL), <it>N</it>-3-hydroxy-hexanoylhomoserine lactone (3-hydroxy-C6-HSL), <it>N</it>-hexanoylhomoserine lactone (C6-HSL), and <it>N</it>-heptanoyl homoserine lactone (C7-HSL); whereas SpsI was primarily responsible for the synthesis of <it>N</it>-butyrylhomoserine lactone (C4-HSL) and <it>N</it>-pentanoylhomoserine lactone (C5-HSL). Furthermore, a quorum quenching analysis by heterologous expression of the <it>Bacillus </it>A24 AiiA lactonase in strain G3 enabled the identification of the AHL-regulated biocontrol-related traits. Depletion of AHLs with this lactonase resulted in altered adhesion and biofilm formation using a microtiter plate assay and flow cells coupled with confocal laser scanning microscopy respectively. This was different from the closely related <it>S. plymuthica </it>strains HRO-C48 and RVH1, where biofilm formation for both strains is AHL-independent. In addition, QS in G3 positively regulated antifungal activity, production of exoenzymes, but negatively regulated production of indol-3-acetic acid (IAA), which is in agreement with previous reports in strain HRO-C48. However, in contrast to HRO-C48, swimming motility was not controlled by AHL-mediated QS.</p> <p>Conclusions</p> <p>This is the first report of the characterisation of two AHL-based quorum sensing systems in the same isolate of the genus <it>Serratia</it>. Our results show that the QS network is involved in the global regulation of biocontrol-related traits in the endophytic strain G3. However, although free-living and endophytic <it>S. plymuthica </it>share some conservation on QS phenotypic regulation, the control of motility and biofilm formation seems to be strain-specific and possible linked to the life-style of this organism.</p

    Data-driven multi-mode adaptive operation of soft open point with measuring bad data

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    The high penetration of distributed generators (DGs) deteriorates the uncertainty of active distribution networks (ADNs). Soft open points (SOPs) can effectively improve flexibility and deal with operational issues in ADNs. However, the formulation of SOP control strategies depends on the accurate mechanism model. Data-driven method can utilize only measuring data to conduct operation and becomes a promising way. In practical conditions, the measuring data may suffer from bad data and measuring errors, which poses a challenge to meet the diverse operational requirements. This paper proposes a data-driven multi-mode adaptive control method for SOP with measuring bad data. First, considering the inaccurate network parameters and quality of measuring data, a robust data-driven framework for SOP operation is proposed based on robust hierarchical-optimization recursive least squares (HO-RLS). Then, a multi-mode control strategy for SOP is proposed to adapt to the diverse operational requirements. A dynamic triggering mechanism is designed to achieve adaptive mode switching. The case studies on practical distribution networks show that the proposed method can fully explore the benefits of SOP to improve the operational performance of ADNs. The potential limitations are discussed to enhance practicality

    Soil CO2 and N2O emissions and microbial abundances altered by temperature rise and nitrogen addition in active-layer soils of permafrost peatland

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    Changes in soil CO2 and N2O emissions due to climate change and nitrogen input will result in increased levels of atmospheric CO2 and N2O, thereby feeding back into Earth’s climate. Understanding the responses of soil carbon and nitrogen emissions mediated by microbe from permafrost peatland to temperature rising is important for modeling the regional carbon and nitrogen balance. This study conducted a laboratory incubation experiment at 15 and 20°C to observe the impact of increasing temperature on soil CO2 and N2O emissions and soil microbial abundances in permafrost peatland. An NH4NO3 solution was added to soil at a concentration of 50 mg N kg−1 to investigate the effect of nitrogen addition. The results indicated that elevated temperature, available nitrogen, and their combined effects significantly increased CO2 and N2O emissions in permafrost peatland. However, the temperature sensitivities of soil CO2 and N2O emissions were not affected by nitrogen addition. Warming significantly increased the abundances of methanogens, methanotrophs, and nirK-type denitrifiers, and the contents of soil dissolved organic carbon (DOC) and ammonia nitrogen, whereas nirS-type denitrifiers, β-1,4-glucosidase (βG), cellobiohydrolase (CBH), and acid phosphatase (AP) activities significantly decreased. Nitrogen addition significantly increased soil nirS-type denitrifiers abundances, β-1,4-N- acetylglucosaminidase (NAG) activities, and ammonia nitrogen and nitrate nitrogen contents, but significantly reduced bacterial, methanogen abundances, CBH, and AP activities. A rising temperature and nitrogen addition had synergistic effects on soil fungal and methanotroph abundances, NAG activities, and DOC and DON contents. Soil CO2 emissions showed a significantly positive correlation with soil fungal abundances, NAG activities, and ammonia nitrogen and nitrate nitrogen contents. Soil N2O emissions showed positive correlations with soil fungal, methanotroph, and nirK-type denitrifiers abundances, and DOC, ammonia nitrogen, and nitrate contents. These results demonstrate the importance of soil microbes, labile carbon, and nitrogen for regulating soil carbon and nitrogen emissions. The results of this study can assist simulating the effects of global climate change on carbon and nitrogen cycling in permafrost peatlands

    Combination of transbronchial cryobiopsy based clinic-radiologic-pathologic strategy and metagenomic next-generation sequencing for differential diagnosis of rapidly progressive diffuse parenchymal lung diseases

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    BackgroundThe complicated spectrum of rapidly progressive diffused parenchymal lung diseases (RP-DPLD) creates obstacles to the precise diagnosis and treatment. We evaluated the differential diagnostic value of transbronchial cryobiopsy (TBCB) based clinic-radiologic-pathologic (CRP) strategy combined with bronchoalveolar lavage fluid (BALF) metagenomic next-generation sequencing (mNGS) in RP-DPLD patients.MethodsRP-DPLD patients who underwent the diagnostic strategy of TBCB-based CRP combined with BALF mNGS at Shanghai East Hospital from May 2020 to Oct 2022 were retrospectively analyzed. Clinical characteristics were summarized, including demographic data, high-resolution computed tomography (HRCT) findings, histopathology of TBCB and microbiological results. Diagnostic value of the combined strategy, as well as the sensitivity, specificity, and positive detection rates of mNGS were evaluated.ResultsA total of 115 RP-DPLD patients were enrolled, with a mean age of 64.4 years old and a male proportion of 54.8%. The pulmonary imaging findings in most patients were complex and diverse, with all patients showing bilateral lung diffuse lesions in HRCT, and progressively aggravated imaging changes within one month. After combining TBCB-based CRP strategy with mNGS, all participants received a corresponding diagnosis with 100% diagnostic yield. In these patients, 58.3% (67/115) were diagnosed with noninfectious RP-DPLD and 41.7% (48/115) with infection-related RP-DPLD. There were 86.1% of cases with known etiology according to the DPLD classification. BALF mNGS and traditional pathogen detection methods were performed in all patients, the positive detection rates were 50.4% (58/115) and 32.2% (37/115), respectively. Meanwhile, the mNGS showed significantly higher sensitivity and negative predictive value than the traditional pathogen detection methods for the diagnosis of infection-related RP-DPLD (100% vs 60.4% (p&lt;0.001), 100% vs 75.6% (p&lt;0.001), respectively). Among noninfectious RP-DPLD patients, the true negative rate of mNGS was 85.1% (57/67). All patients had their treatment regimen modified and the 30-day mortality was 7.0%.ConclusionThe novel strategy of TBCB-based CRP combined with mNGS provided dependable and sufficient evidence for the diagnosis, meanwhile further improved the accuracy of RP-DPLD treatment, as well as the prognosis of patients. Our results highlight the significant value of combined strategy in determining whether the RP-DPLD patients were infection associated or not

    Circulating Mucosal-Associated Invariant T Cells in a Large Cohort of Healthy Chinese Individuals From Newborn to Elderly

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    Mucosal-associated invariant T (MAIT) cells, which are enriched in human blood and express a semi-invariant TCR chain, play important roles in conditions such as infectious diseases and cancer. The influence of age on levels and functional characteristics of circulating MAIT cells have not been fully addressed. Here we have collected blood samples from a large cohort of healthy Chinese individuals from newborn (cord blood) to the elderly and assessed the levels of circulating MAIT cells as well as their phenotype, activation and apoptosis status, and cytokine expression profiles after in vitro stimulation. We found that the frequencies of circulating MAIT cells gradually increased in blood from newborns as they progressed into adulthood (20–40 years old) but then decreased during further progression toward old age (&gt;60 years old). The lowered numbers of circulating MAIT cells in the elderly was correlated with a gradual increase of apoptosis. A majority of circulating MAIT cells expressed the chemokine receptors CCR5 and CCR6, and most also expressed CD8 and CD45RO. Few expressed CD69 in cord blood, but the frequency increased with age. Upon in vitro activation with PMA plus ionomycin or IL12 plus IL18, fewer MAIT cells isolated from the young adult group expressed IFN-γ, IL17A and Granzyme B then cells from other age groups while the proportion of cells that expressed TNF-α was similar. Taken together, our data provide information for guiding the assessment of normal levels and phenotypes of MAIT cells at different ages in healthy individuals and patients

    Learning long term face aging patterns from partially dense aging databases

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    Studies on face aging are handicapped by lack of long term dense aging sequences for model training. To handle this problem, we propose a new face aging model, which learns long term face aging patterns from partially dense aging databases. The learning strategy is based on two assumptions: (i) short term face aging pattern is relatively simple and is possible to be learned from currently available databases; (ii) long term face aging is a continuous and smooth Markov process. Adopting a compositional face representation, our aging algorithm learns a function-based short term aging model from real aging sequences to infer facial parameters within a short age span. Based on the predefined smoothness criteria between two overlapping short term aging patterns, we concatenate these learned short term aging patterns to build the long term aging patterns. Both the subjective assessment and objective evaluations of synthetic aging sequences validate the effectiveness of the proposed model. 1
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