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  • Articles  (2)
  • Blackwell Science Ltd  (1)
  • SpringerOpen  (1)
  • 2015-2019
  • 2010-2014  (1)
  • 2000-2004  (1)
  • 1
    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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  • 2
    Publication Date: 2014-10-22
    Description: In this paper, we extend the deterministic single-group MSIRS epidemic model to a multi-group model, and we also extend the deterministic multi-group framework to a stochastic one and formulate it as a stochastic differential equation. In the deterministic multi-group model, the basic reproduction number R0 is a threshold that completely determines the persistence or extinction of the disease. By using Lyapunov function techniques, we show that if R0〉1, then the disease will prevail, the infective condition persists and the endemic state is asymptotically stable in a feasible region. If R0⩽1, then the infective condition disappears and the disease dies out. For the stochastic version, we perform a detailed analysis on the asymptotic behavior of the stochastic model, which also depends on the value of R0, when R0〉1, we determine the asymptotic stability of the endemic equilibrium by measuring the difference between the solution and the endemic equilibrium of the deterministic model in time-averaged data. Numerical methods are used to illustrate the dynamic behavior of the model and to solve the systems.
    Print ISSN: 1687-1839
    Electronic ISSN: 1687-1847
    Topics: Mathematics
    Published by SpringerOpen
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