1,135 research outputs found

    Chromosomal DNA deletion confers phage resistance to Pseudomonas aeruginosa.

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    Bacteria develop a broad range of phage resistance mechanisms, such as prevention of phage adsorption and CRISPR/Cas system, to survive phage predation. In this study, Pseudomonas aeruginosa PA1 strain was infected with lytic phage PaP1, and phage-resistant mutants were selected. A high percentage (~30%) of these mutants displayed red pigmentation phenotype (Red mutant). Through comparative genomic analysis, one Red mutant PA1r was found to have a 219.6 kb genomic fragment deletion, which contains two key genes hmgA and galU related to the observed phenotypes. Deletion of hmgA resulted in the accumulation of a red compound homogentisic acid; while A galU mutant is devoid of O-antigen, which is required for phage adsorption. Intriguingly, while the loss of galU conferred phage resistance, it significantly attenuated PA1r in a mouse infection experiment. Our study revealed a novel phage resistance mechanism via chromosomal DNA deletion in P. aeruginosa

    A Q-Learning Based Hybrid Meta-Heuristic for Integrated Scheduling of Disassembly and Reprocessing Processes Considering Product Structures and Stochasticity

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    Remanufacturing is regarded as a sustainable manufacturing paradigm of energy conservation and environment protection. To improve the efficiency of the remanufacturing process, this work investigates an integrated scheduling problem for disassembly and reprocessing in a remanufacturing process, where product structures and uncertainty are taken into account. First, a stochastic programming model is developed to minimize the maximum completion time (makespan). Second, a Q-learning based hybrid meta-heuristic (Q-HMH) is specially devised. In each iteration, a Q-learning method is employed to adaptively choose a premium algorithm from four candidate ones, including genetic algorithm (GA), artificial bee colony (ABC), shuffled frog-leaping algorithm (SFLA), and simulated annealing (SA) methods. At last, simulation experiments are carried out by using sixteen instances with different scales, and three state-of-the-art algorithms in literature and an exact solver CPLEX are chosen for comparisons. By analyzing the results with the average relative percentage deviation (RPD) metric, we find that Q-HMH outperforms its rivals by 9.79%−26.76%. The results and comparisons verify the excellent competitiveness of Q-HMH for solving the concerned problems.</p

    All-in-one aerial image enhancement network for forest scenes

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    Drone monitoring plays an irreplaceable and significant role in forest firefighting due to its characteristics of wide-range observation and real-time messaging. However, aerial images are often susceptible to different degradation problems before performing high-level visual tasks including but not limited to smoke detection, fire classification, and regional localization. Recently, the majority of image enhancement methods are centered around particular types of degradation, necessitating the memory unit to accommodate different models for distinct scenarios in practical applications. Furthermore, such a paradigm requires wasted computational and storage resources to determine the type of degradation, making it difficult to meet the real-time and lightweight requirements of real-world scenarios. In this paper, we propose an All-in-one Image Enhancement Network (AIENet) that can restore various degraded images in one network. Specifically, we design a new multi-scale receptive field image enhancement block, which can better reconstruct high-resolution details of target regions of different sizes. In particular, this plug-and-play module enables it to be embedded in any learning-based model. And it has better flexibility and generalization in practical applications. This paper takes three challenging image enhancement tasks encountered in drone monitoring as examples, whereby we conduct task-specific and all-in-one image enhancement experiments on a synthetic forest dataset. The results show that the proposed AIENet outperforms the state-of-the-art image enhancement algorithms quantitatively and qualitatively. Furthermore, extra experiments on high-level vision detection also show the promising performance of our method compared with some recent baselines.Award-winningPostprint (published version

    Nomograms predicting survival of cervical cancer patients treated with concurrent chemoradiotherapy based on the 2018 FIGO staging system

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    Background: In 2018, a revised staging system was released for cervical cancer, which defined pelvic and paraaortic lymph node metastasis as stages IIIC1 and IIIC2, respectively. In this study, we constructed and validated nomograms to predict the 3- and 5-year survival of patients with cervical cancer based on the revised International Federation of Gynecology and Obstetrics (FIGO) staging system. Methods: We retrospectively examined patients with 2009 FIGO stage IB–IVA cervical cancer who were treated at our institute between 2011 and 2015. Patients were randomized into the model development and validation cohorts (2:1). Univariate and multivariate analyses were conducted for the model development cohort to identify prognostic factors. In the multivariate analysis, nomograms were built to predict overall survival (OS) and disease-free survival (DFS) using significant variables. The nomograms were assessed based on the discrimination and calibration in both cohorts. Discrimination was assessed using the concordance index. Calibration was performed by comparing the mean nomogram estimated survival and the mean observed survival. Results: We included 1,192 patients, with 795 and 397 patients in the model development and validation cohorts, respectively. In the model development cohort, the median follow-up period was 49.2 months. After multivariate analysis, age, histology, 2018 FIGO stage, and pelvic lymph node number were independent factors for OS. Histology, 2018 FIGO stage, squamous cell carcinoma antigen, and pelvic lymph node number were significant predictors of DFS. The nomograms constructed to predict OS and DFS were based on these factors. In both model cohorts, the concordance index for the nomogram-predicted OS and DFS was 0.78 and 0.75 and 0.74 and 0.67, respectively. The calibration curve revealed good agreement between the nomogram predictions and actual values. Conclusion: We constructed robust nomograms to predict the OS and DFS of patients with cervical cancer undergoing treatment with concurrent chemoradiotherapy based on the 2018 FIGO staging system

    Clustered DNA damage induced by protons radiation in plasmid DNA

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    Molecular Characterization of Cultivated Bromeliad Accessions with Inter-Simple Sequence Repeat (ISSR) Markers

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    Bromeliads are of great economic importance in flower production; however little information is available with respect to genetic characterization of cultivated bromeliads thus far. In the present study, a selection of cultivated bromeliads was characterized via inter-simple sequence repeat (ISSR) markers with an emphasis on genetic diversity and population structure. Twelve ISSR primers produced 342 bands, of which 287 (~84%) were polymorphic, with polymorphic bands per primer ranging from 17 to 34. The Jaccard’s similarity ranged from 0.08 to 0.89 and averaged ~0.30 for the investigated bromeliads. The Bayesian-based approach, together with the un-weighted paired group method with arithmetic average (UPGMA)-based clustering and the principal coordinate analysis (PCoA), distinctly grouped the bromeliads from Neoregelia, Guzmania, and Vriesea into three separately clusters, well corresponding with their botanical classifications; whereas the bromeliads of Aechmea other than the recently selected hybrids were not well assigned to a cluster. Additionally, ISSR marker was proven efficient for the identification of hybrids and bud sports of cultivated bromeliads. The findings achieved herein will further our knowledge about the genetic variability within cultivated bromeliads and therefore facilitate breeding for new varieties of cultivated bromeliads in future as well

    Unlocking the mystery of the hard-to-sequence phage genome: PaP1 methylome and bacterial immunity

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    BACKGROUND: Whole-genome sequencing is an important method to understand the genetic information, gene function, biological characteristics and survival mechanisms of organisms. Sequencing large genomes is very simple at present. However, we encountered a hard-to-sequence genome of Pseudomonas aeruginosa phage PaP1. Shotgun sequencing method failed to complete the sequence of this genome. RESULTS: After persevering for 10 years and going over three generations of sequencing techniques, we successfully completed the sequence of the PaP1 genome with a length of 91,715 bp. Single-molecule real-time sequencing results revealed that this genome contains 51 N-6-methyladenines and 152 N-4-methylcytosines. Three significant modified sequence motifs were predicted, but not all of the sites found in the genome were methylated in these motifs. Further investigations revealed a novel immune mechanism of bacteria, in which host bacteria can recognise and repel modified bases containing inserts in a large scale. This mechanism could be accounted for the failure of the shotgun method in PaP1 genome sequencing. This problem was resolved using the nfi(-) mutant of Escherichia coli DH5α as a host bacterium to construct a shotgun library. CONCLUSIONS: This work provided insights into the hard-to-sequence phage PaP1 genome and discovered a new mechanism of bacterial immunity. The methylome of phage PaP1 is responsible for the failure of shotgun sequencing and for bacterial immunity mediated by enzyme Endo V activity; this methylome also provides a valuable resource for future studies on PaP1 genome replication and modification, as well as on gene regulation and host interaction. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-803) contains supplementary material, which is available to authorized users

    STC3141 improves acute lung injury through neutralizing circulating histone in rat with experimentally-induced acute respiratory distress syndrome

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    Background: Acute respiratory distress syndrome (ARDS) remains a challenge because of its high morbidity and mortality. Circulation histones levels in ARDS patients were correlated to disease severity and mortality. This study examined the impact of histone neutralization in a rat model of acute lung injury (ALI) induced by a lipopolysaccharide (LPS) double-hit.Methods: Sixty-eight male Sprague-Dawley rats were randomized to sham (N = 8, received saline only) or LPS (N = 60). The LPS double-hit consisted of a 0.8 mg/kg intraperitoneal injection followed after 16 h by 5 mg/kg intra-tracheal nebulized LPS. The LPS group was then randomized into five groups: LPS only; LPS +5, 25, or 100 mg/kg intravenous STC3141 every 8 h (LPS + L, LPS + M, LPS + H, respectively); or LPS + intraperitoneal dexamethasone 2.5 mg/kg every 24 h for 56 h (LPS + D). The animals were observed for 72 h.Results: LPS animals developed ALI as suggested by lower oxygenation, lung edema formation, and histological changes compared to the sham animals. Compared to the LPS group, LPS + H and +D groups had significantly lower circulating histone levels and lung wet-to-dry ratio, and the LPS + D group also had lower BALF histone concentrations; the blood neutrophils and platelets counts in LPS + D group did not change, meanwhile, the LPS + L, +M and +H groups had significantly lower neutrophil counts and higher platelet counts in the blood; the total number of BALF WBC, platelet counts, MPO and H3 were significantly lower in the LPS + L, +M, +H and +D groups than in the LPS only group; and the degree of inflammation was significantly less in the LPS + L, +M, +H and +D groups, moreover, inflammation in the LPS + L, +M and +H animals showed a dose-dependent response; finally, the LPS + L, +M, +H and +D groups had improved oxygenation compared to the LPS group, and there were no statistical differences in PCO2 or pH among groups. All animals survived.Conclusion: Neutralization of histone using STC3141, especially at high dose, had similar therapeutic effects to dexamethasone in this LPS double-hit rat ALI model, with significantly decreased circulating histone concentration, improved acute lung injury and oxygenation
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