Notes

An energetic risk-based method of owning a outbreak.
Mining activities are known to generate a large amount of mine tailings and acid mine drainage which contain varieties of heavy metals. Heavy metals play an important role in co-selection for bacterial antibiotic resistance. However, the characteristics of antibiotic resistance genes (ARGs) in mining-affected water environments are still unclear. Here we investigated the pollution of metals, profiles of ARGs, mobile genetic elements (MGEs) and microbial community in mining-affected surface water and groundwater. The results showed that in the tested water samples, the concentrations of Zn and Mn were the highest, and Ni was the lowest. Higher abundances of ARGs with great proportion of sulfonamides, chloramphenicols and tetracyclines resistance genes were found in mining-affected water when compared with those without mining activities. Additionally, there were positive correlations between heavy metals (especially Ni, Zn and Mn) and these ARGs. Linear regression analysis suggested that MGEs were positively correlated with ARGs. In addition, total phosphorus was correlated with ARGs (p less then 0.05). The microbial community was different between the mining-affected water and the reference (p less then 0.05). Proteobacteria, Bacteroidetes and Actinobacteria were dominant phyla in the surface water and groundwater. Network analysis showed that many ARGs were significantly associated with these dominant bacteria, which suggested they might be potential hosts for these ARGs. These findings provide a clear evidence that the mining activities in the study area had a significant impact on surface water and groundwater to different degrees.Phosphate plays an important role in a wide range of chemical and biological processes, so the development of a new phosphate optical sensor with high sensitivity, specificity and visual recognition function has important practical significance. Herein, a ratiometric fluorescent (RF) probe and a smartphone-integrated colorimetric test paper sensing platform for assay phosphate was fabricated using hybrid fluorescent UiO-66-NH2 and Eu3+@MOF-808 metal-organic frameworks. After continuous addition of phosphate, the blue fluorescence emission of UiO-66-NH2 and the red emission of Eu3+@MOF-808 were regularly enhanced and quenched respectively, and the fluorescence response of the detection platform to phosphate exhibited a clear color change process (red → pink → blue). More importantly, the probe solution and test paper of the integrated smartphone are converted to digital values through RGB channels and successfully used to visualize semi-quantitative recognition of phosphate. In addition, an RF probe and a smartphone integrated fluorescent test paper were developed separately to devise logic gate devices for detecting phosphate. The multifunctional ratio sensing platform integrated by the smartphone furnishes a new strategy and broad prospects for the intelligent online identification of important targets in biological samples and environmental samples.Humans are increasingly dependent on engineered landscapes to minimize negative health impacts of water consumption. Managed aquifer recharge (MAR) systems, such as river and lake bank filtration, surface spreading or direct injection into the aquifer have been used for decades for water treatment and storage. Microbial and sorptive processes in these systems are effective for the attenuation of many emerging contaminants including trace organic chemicals such as pharmaceuticals and personal care products. Recent studies showed a superior efficiency of trace organic chemical biotransformation by incumbent communities of microorganisms under oxic and carbon-limited (oligotrophic) conditions. This study sought to identify features of bacterial genomes that are predictive of trophic strategy in this water management context. Samples from a pilot scale managed aquifer recharge system with regions of high and low carbon concentration, were used to generate a culture collection from which oligotrophic and copiotrophic bacteria were categorized. Genomic markers linked to either trophic strategy were used to develop a Bayesian network model that can infer prevailing carbon conditions in MAR systems from metagenomic data.Haloketones (HKs) is one class of disinfection by-products (DBPs) which is genetically toxic and mutagenic. selleck Monitoring HKs in drinking water is important for drinking water safety, yet it is a time-consuming and laborious job. Developing predictive models of HKs to estimate their occurrence in drinking water is a good alternative, but to date no study was available for HKs modeling. This study was to explore the feasibility of linear, log linear regression models, back propagation (BP) as well as radial basis function (RBF) artificial neural networks (ANNs) for predicting HKs occurrence (including dichloropropanone, trichloropropanone and total HKs) in real water supply systems. Results showed that the overall prediction ability of RBF and BP ANNs was better than linear/log linear models. Though the BP ANN showed excellent prediction performance in internal validation (N25 = 98-100%, R2 = 0.99-1.00), it could not well predict HKs occurrence in external validation (N25 = 62-69%, R2 = 0.202-0.848). Prediction ability of RBF ANN in external validation (N25 = 85%, R2 = 0.692-0.909) was quite good, which was comparable to that in internal validation (N25 = 74-88%, R2 = 0.799-0.870). These results demonstrated RBF ANN could well recognized the complex nonlinear relationship between HKs occurrence and the related water quality, and paved a new way for HKs prediction and monitoring in practice.Effective biomonitoring requires an understanding of the factors driving concentrations of the substances or compounds of interest in the tissues of studied organisms. Biomonitoring of trace elements, and heavy metals in particular, has been the focus of much research; however, the complex roles many trace elements play in animal and plant tissues can make it difficult to disentangle environmental signals from physiology. This study examined the concentrations of 15 trace elements in the teeth of 122 Pacific walruses (Odobenus rosmarus divergens) to investigate the potential for walrus teeth as biomonitors of trace elements in Arctic ecosystems. Elemental concentrations were measured across cementum growth layer groups (GLGs), thereby reconstructing a lifetime history of element concentrations for each walrus. The locations of GLGs were used to divide trace element time series into individual years, allowing each GLG to be associated with an animal age and a calendar year. The elements studied exhibited a great deal of complexity, reflecting the numerous factors responsible for generating tooth trace element concentrations.
My Website: https://www.selleckchem.com/products/Mubritinib-TAK-165.html