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  • Online Resource  (4)
  • MDPI AG  (4)
  • Zhang, Li  (4)
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  • Online Resource  (4)
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  • MDPI AG  (4)
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  • 1
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 15, No. 1 ( 2014-01-08), p. 725-742
    Abstract: Methicillin-resistant Staphylococcus aureus (MRSA) has become an important nosocomial pathogen, causing considerable morbidity and mortality. During the last 20 years, a variety of genotyping methods have been introduced for screening the prevalence of MRSA. In this study, we developed and evaluated an improved approach capillary gel electrophoresis based multilocus variable-number tandem-repeat fingerprinting (CGE/MLVF) for rapid MRSA typing. A total of 42 well-characterized strains and 116 non-repetitive clinical MRSA isolates collected from six hospitals in northeast China between 2009 and 2010 were tested. The results obtained by CGE/MLVF against clinical isolates were compared with traditional MLVF, spa typing, Multilocus sequence typing/ staphylococcal cassette chromosome mec (MLST/SCCmec) and pulse field gel electrophoresis (PFGE). The discriminatory power estimated by Simpson’s index of diversity was 0.855 (28 types), 0.855 (28 patterns), 0.623 (11 types), 0.517 (8 types) and 0.854 (28 patterns) for CGE/MLVF, traditional MLVF, spa typing, MLST/SCCmec and PFGE, respectively. All methods tested showed a satisfied concordance in clonal complex level calculated by adjusted Rand’s coefficient. CGE/MLVF showed better reproducibility and accuracy than traditional MLVF and PFGE methods. In addition, the CGE/MLVF has potential to produce portable results. In conclusion, CGE/MLVF is a rapid and easy to use MRSA typing method with lower cost, good reproducibility and high discriminatory power for monitoring the outbreak and clonal spread of MRSA isolates.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    Language: English
    Publisher: MDPI AG
    Publication Date: 2014
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 2
    In: Remote Sensing, MDPI AG, Vol. 12, No. 18 ( 2020-09-21), p. 3086-
    Abstract: Global rapid expansion of the coastal aquaculture industry has made great contributions to enhance food security, but has also caused a series of ecological and environmental issues. Sustainable management of coastal areas requires the explicit and efficient mapping of the spatial distribution of aquaculture ponds. In this study, a Google Earth Engine (GEE) application was developed for mapping coastal aquaculture ponds at a national scale with a novel classification scheme using Sentinel-1 time series data. Relevant indices used in the classification mainly include the water index, texture, and geometric metrics derived from radar backscatter, which were then used to segment and classify aquaculture ponds. Using this approach, we classified aquaculture ponds for the full extent of the coastal area in Vietnam with an overall accuracy of 90.16% (based on independent sample evaluation). The approach, enabling wall-to-wall mapping and area estimation, is essential to the efficient monitoring and management of aquaculture ponds. The classification results showed that aquaculture ponds are widely distributed in Vietnam’s coastal area and are concentrated in the Mekong River Delta and Red River delta (85.14% of the total area), which are facing the increasing collective risk of climate change (e.g., sea level rise and salinity intrusion). Further investigation of the classification results also provides significant insights into the stability and deliverability of the approach. The water index derived from annual median radar backscatter intensity was determined to be efficient at mapping water bodies, likely due to its strong response to water bodies regardless of weather. The geometric metrics considering the spatial variation of radar backscatter patterns were effective at distinguishing aquaculture ponds from other water bodies. The primary use of GEE in this approach makes it replicable and transferable by other users. Our approach lays a solid foundation for intelligent monitoring and management of coastal ecosystems.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2513863-7
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  • 3
    In: Molecules, MDPI AG, Vol. 18, No. 10 ( 2013-10-17), p. 12987-13002
    Abstract: Suppressor of cytokine signaling 3 (SOCS3) is a cytokine-induced negative feedback-loop regulator of cytokine signaling. More and more evidence has proved it to be an inhibitor of signal transducers and activators of transcription 5 (STAT5). Here, we used dairy cow mammary epithelial cells (DCMECs) to analyze the function of SOCS3 and the interaction between SOCS3 and STAT5a. The expression of SOCS3 was found in cytoplasm and nucleus of DCMECs by fluorescent immunostaining. Overexpression and inhibition of SOCS3 brought a remarkable milk protein synthesis change through the regulation of JAK2/STAT5a pathway activity, and SOCS3 expression also decreased SREBP-1c expression and fatty acid synthesis. Inhibited STAT5a activation correlated with reduced SOCS3 expression, which indicated that SOCS3 gene might be one of the targets of STAT5a activation, DCMECs treated with L-methionine (Met) resulted in a decrease of SOCS3 expression. SOCS3 could also decrease cell proliferation and viability by CASY-TT detection. Together, our findings indicate that SOCS3 acts as an inhibitor of JAK2/STAT5a pathway and disturbs fatty acid synthesis by decreasing SREBP-1c expression, which validates its involvement in both milk protein synthesis and fat synthesis. In aggregate, these results reveal that low SOCS3 expression is required for milk synthesis and proliferation of DCMECs in vitro.
    Type of Medium: Online Resource
    ISSN: 1420-3049
    Language: English
    Publisher: MDPI AG
    Publication Date: 2013
    detail.hit.zdb_id: 2008644-1
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  • 4
    In: Remote Sensing, MDPI AG, Vol. 12, No. 11 ( 2020-06-09), p. 1866-
    Abstract: Pen aquaculture is the main form of aquaculture in some shallow lakes in eastern China. It is valuable to map the spatiotemporal changes of pen aquaculture in eutrophic lakes to assess its effect on water quality, thereby helping the relevant decision-making agencies to manage the water quality (WQ) of lakes. In this study, an automatic approach for extracting the pen aquaculture area was developed based on Landsat data. The approach integrates five algorithms, including grey transformation, discrete wavelet transform, fast Fourier transform, singular value decomposition and k-nearest neighbor classification. It was successfully applied in the automatic mapping of the pen aquaculture areas in Lake Yangcheng from 1990 to 2016. The overall accuracies were greater than 92%. The result indicted that the practice of pen aquaculture experienced five stages, with the general area increasing in the beginning and decreasing by the end of the last stage. Meanwhile, the changes of nine WQ parameters observed from 2000 to 2016, such as ammonia (NH3-N), pH, total nitrogen (TN), total phosphorus (TP), chlorophyll a, biochemical oxygen demand (BOD), chemiluminescence detection of permanganate index (CODMn), Secchi disk depth (SDD) and dissolved oxygen (DO), were analyzed in the lake sectors of Lake Yangcheng, and then their relationships were explored with the percentage of pen aquaculture area. The result suggested that the percentage of pen aquaculture area exhibits significantly positive correlations with NH3-N, TN, TP, chlorophyll a, BOD and CODMn, but significantly negative correlations with SDD and DO. The experimental results may offer an important implication for managing similar shallow lakes with pen aquaculture expansion and water pollution problems.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2513863-7
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