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BackgroundCarbapenemase-producing Klebsiella pneumoniae (CP-Kp) poses distinct clinical challenges due to extensively drug resistant (XDR) phenotype, and sequence type (ST) 11 is the most dominant blaKPC-2-bearing CP-Kp clone in China. The purpose of this current retrospective study was to explore the genetic factors associated with the success of XDR CP-Kp ST11 strains circulated in the intensive care unit (ICU) of a Chinese tertiary hospital.MethodsSix ST11 XDR CP-Kp strains were identified between May and December 2014 and validated by minimum inhibitory concentration examination, polymerase chain reaction, and pyrosequencing. The six ST11 XDR CP-Kp, as well as three multi-drug resistant (MDR) and four susceptible strains, were sequenced using single-molecule real-time method. Comprehensively structural and functional analysis based on comparative genomics was performed to identify genomic characteristics of the XDR ST11 CP-Kp strains.ResultsWe found that ST11 XDR blaKPC-2-bearing CP-Kp strains isolated from inpatients spread in the ICU of the hospital. Functionally, genes associated with information storage and processing of the ST11 XDR CP-Kp strains were more abundant than those of MDR and susceptible strains, especially genes correlative with mobile genetic elements (MGEs) such as transposons and prophages. Structurally, eleven large-scale genetic regions taken for the unique genome in these ST11 XDR CP-Kp strains were identified as MGEs including transposons, integrons, prophages, genomic islands, and integrative and conjugative elements. Three of them were located on plasmids and eight on chromosomes; five of them were with antimicrobial resistance genes and eight with adaptation associated genes. Notably, a new blaKPC-2-bearing ΔΔTn1721-blaKPC-2 transposon, probably transposed and truncated from ΔTn1721-blaKPC-2 by IS903D and ISKpn8, was identified in all six ST11 XDR CP-Kp strains.ConclusionOur findings suggested that together with clonal spread, MGEs identified uniquely in the ST11 XDR CP-Kp strains might contribute to their formidable adaptability, which facilitated their widespread dissemination in hospital.

Understanding the ecological impacts of large-scale hydraulic projects is critical for maintaining ecosystem health while meeting human water needs. It is, however, currently hindered by a lack of direct evidence on ecological impacts associated with this type of project particularly on water quality and fish communities. Here, we characterized patterns and variations of fish communities and water quality in five impounded lakes of the Chinese South-to-North Water Diversion Project (SNWDP), with the aim of better understanding potential ecological impacts of inter-basin water transfers. We found that 1) the impacts of water transfer on water quality in the impounded lakes was generally characterized by hydrological parameters (e.g. total suspended solids, turbidity, transparency, chlorophyll a, dissolved oxygen, conductivity and total hardness) in an upstream-downstream direction; 2) increased hydrological connectivity may have favored biological invasion (e.g. Tridentiger bifasciatus) and promoted a potential biotic homogenization among the impounded lakes: and 3) there was a pattern of decreased fish abundance and biomass from the upstream to downstream lakes with fish communities strongly driven by changing water quality patterns across the impounded lakes. These findings improve our understanding of ecological impacts of large-scale hydraulic projects and provide a significant basis for water agencies with similar water transfer systems to optimize their water transfer management in order to minimize ecological impacts.

37th European Photovoltaic Solar Energy Conference and Exhibition; 1388-1391, Operation and maintenance (O&M) is critical for running successful PV projects as the reliable renewable resource for energy transition. We have utilized artificial intelligence (AI) system to optimize O&M task for 120 projects up to 39.2MW more than 2 years. The average daily energy yield of 3.9% (0.13 kWh/kWp) is increased for the projects with AI system, and the O&M transportation cost is 41% reduced. The power prediction algorithm of the fingerprint-like model for each inverter-MPPT is upgraded by simulated POA irradiance instead of that measured by only one pyranometer in multiple-orientation power plants. According to the one-year experiment result for 74 the projects (26.3MW) with 4,792 MPPTs, the Mean Absolute Percentage Error (MAPE) of power prediction decreases from 17.1% to 7.0%. The overall fault detection precision reaches 98.6%, while the precision of failure mode diagnosis improves from 92.3% to 94.0%. The accurate failure mode diagnosis practically enhances operation efficiency and reduces the maintenance expense in the cost structure by low carbon footprint O&M solution.