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  • Candida albicans  (1)
  • mathematical programming
  • Springer  (2)
  • American Geophysical Union (AGU)
  • 2000-2004
  • 1975-1979  (2)
  • 1976  (2)
Collection
Publisher
  • Springer  (2)
  • American Geophysical Union (AGU)
Years
  • 2000-2004
  • 1975-1979  (2)
Year
  • 1
    ISSN: 1573-0832
    Keywords: Candida albicans ; caffeine ; mutagens
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Medicine
    Notes: Abstract Ultraviolet radiation is more effective than either ethyl methanesulfonate or nitrous acid in inducing reverse mutation from auxotrophy to prototrophy in C. albicans. The killing effect of each of the mutagens is greater for cells grown at 37 C than at 25 C after treatment; mutation frequencies are unaffected by post-treatment growth temperatures. Though caffeine depresses survival of mutagen treated cells at both 25 C or 37 C, its effect is more pronounced at 37 C. Caffeine has no effect on mutagenesis by nitrous acid or ethyl methanesulfonate; it depresses UV mutagenesis, but only at 37 C and at high UV dosages. These findings indicate that UV mutagenesis in C. albicans is mediated by a caffeine-sensitive, recombinational system for DNA repair analogous to those known to occur in other species of yeasts. The repair system of C. albicans is unique in being susceptible to caffeine only at high temperature and when the number of DNA lesions to be repaired is large. The caffeine-sensitive steps in repair critical to UV mutagenesis are not involved in fixing mutations induced by the chemical mutagens tested.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of optimization theory and applications 18 (1976), S. 469-483 
    ISSN: 1573-2878
    Keywords: Nonlinear least-square problems ; parameter optimization ; penalty function methods ; mathematical programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract An algorithm for solving the general nonlinear least-square problem is developed. An estimate for the Hessian matrix is constructed as the sum of two matrices. The first matrix is the usual first-order estimate used by the Gauss method, while the second matrix is generated recursively using a rank-one formula. Test results indicate that the method is superior to the standard Gauss method and compares favorably with other methods, especially for problems with nonzero residuals at the solution.
    Type of Medium: Electronic Resource
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