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  • 2015-2019  (410)
  • 2000-2004  (2)
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  • 1
    Electronic Resource
    Electronic Resource
    [s.l.] : Macmillian Magazines Ltd.
    Nature 431 (2004), S. 556-559 
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] Late Cenozoic terrestrial fossil records of North America are biased by a predominance of mid-latitude deposits, mostly in the western half of the continent. Consequently, the biological history of eastern North America, including the eastern deciduous forest, remains largely hidden. ...
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1471-4159
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine
    Notes: Abstract: A 20-kDa DNA-binding protein that binds the AT-rich sequences within the promoters of the brain-specific protein kinase C (PKC) γ and neurogranin/RC3 genes has been characterized as chromosomal nonhistone high-mobility-group protein (HMG)-I. This protein is a substrate of PKC α, β, γ, and δ but is poorly phosphorylated by PKC ε and ζ. Two major (Ser44 and Ser64) and four minor phosphorylation sites have been identified. The extents of phosphorylation of Ser44 and Ser64 were 1:1, whereas those of the four minor sites all together were 〈30% of the major one. These PKC phosphorylation sites are distinct from those phosphorylated by cdc2 kinase, which phosphorylates Thr53 and Thr78. Phosphorylation of HMG-I by PKC resulted in a reduction of DNA-binding affinity by 28-fold as compared with 12-fold caused by the phosphorylation with cdc2 kinase. HMG-I could be additively phosphorylated by cdc2 kinase and PKC, and the resulting doubly phosphorylated protein exhibited a 〉 100-fold reduction in binding affinity. The two cdc2 kinase phosphorylation sites of HMG-I are adjacent to the N terminus of two of the three predicted DNA-binding domains. In comparison, one of the major PKC phosphorylation sites, Ser64, is adjacent to the C terminus of the second DNA-binding domain, whereas Ser44 is located within the spanning region between the first and second DNA-binding domains. The current results suggest that phosphorylation of the mammalian HMG-I by PKC alone or in combination with cdc2 kinase provides an effective mechanism for the regulation of HMG-I function.
    Type of Medium: Electronic Resource
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  • 3
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    PANGAEA
    In:  RMIT University, Melbourne | Supplement to: Wang, Xiaoming; Zhang, Kefei; Wu, Suqin; Fan, Shijie; Cheng, Yingyan (2016): Water vapor-weighted mean temperature and its impact on the determination of precipitable water vapor and its linear trend. Journal of Geophysical Research: Atmospheres, 121(2), 833-852, https://doi.org/10.1002/2015JD024181
    Publication Date: 2023-01-13
    Description: Water vapor-weighted mean temperature, Tm, is a vital parameter for retrieving precipitable water vapor (PWV) from the zenith wet delay (ZWD) of Global Navigation Satellite Systems (GNSS) signal propagation. In this study, the Tm at 368 GNSS stations for 2000-2012 were calculated using three methods: (1) temperature and humidity profiles from ERA-Interim, (2) the Bevis Tm-Ts relationship, and (3) the Global Pressure and Temperature 2 wet model. Tm derived from the first method was used as a reference to assess the errors of the other two methods. Comparisons show that the relative errors of the Tm derived from these two methods are in the range of 1-3% across more than 95% of all the stations. The PWVs were calculated using the aforementioned three types of Tm and the GNSS-derived ZWD at 107 stations. Again, the PWVs calculated using Tm from the first method were used as the reference of the other two PWVs. The root-mean-square errors of these two PWVs are both in the range of 0.1-0.7 mm. The second method is recommended in real-time applications, since its performance is slightly better than the third method. In addition, the linear trends of the PWV time series from the first method were also used as the reference to evaluate the trends from the other two methods. Results show that 13% and 23% of the PWV trends from the respective second and third methods have a relative error of larger than 10%. For climate change studies, the first method, if available, is always recommended.
    Type: Dataset
    Format: application/zip, 372 datasets
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  • 4
    Publication Date: 2023-01-13
    Keywords: ADE1; Analysis of precipitable water vapor from GPS measurements; Australia; DATE/TIME; Day of the year; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 32680 data points
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  • 5
    Publication Date: 2023-01-13
    Keywords: ADIS; Analysis of precipitable water vapor from GPS measurements; DATE/TIME; Day of the year; Ethiopia; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 13458 data points
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  • 6
    Publication Date: 2023-01-13
    Keywords: AIRA; Analysis of precipitable water vapor from GPS measurements; DATE/TIME; Day of the year; Japan; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 43728 data points
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  • 7
    Publication Date: 2023-01-13
    Keywords: ALGO; Analysis of precipitable water vapor from GPS measurements; Canada; DATE/TIME; Day of the year; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 57340 data points
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  • 8
    Publication Date: 2023-01-13
    Keywords: ALBH; Analysis of precipitable water vapor from GPS measurements; British Columbia, Canada; DATE/TIME; Day of the year; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 58180 data points
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  • 9
    Publication Date: 2023-01-13
    Keywords: ALIC; Analysis of precipitable water vapor from GPS measurements; Australia; DATE/TIME; Day of the year; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 50798 data points
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  • 10
    Publication Date: 2023-01-13
    Keywords: ALRT; Analysis of precipitable water vapor from GPS measurements; Arctic Ocean; DATE/TIME; Day of the year; Precipitable water vapour; Weather station/meteorological observation; WST
    Type: Dataset
    Format: text/tab-separated-values, 31766 data points
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