A case of infantile acute monocytic leukemia (AMoL), which was probably transmitted from a pregnant woman with leukemia to her unborn infant, is presented. A woman had AMoL when her third infant was born. This infant, who was a boy, also suffered from AMoL when he was 20 months of age. The infant's leukemic cells had the same cytochemical and immunophenotypic patterns as the mother's leukemic cells. By cytogenetic analysis, the majority of the infant's leukemic marrow cells had the 46,XX karyotype and showed no Y body by quinacrine staining. Moreover, the phenotype for human major histocompatibility system, HLA-A, HLA-B, and HLA-DR of the infant's leukemic cells was consistent with that of the mother's lymphocytes. Thus, the infant's leukemic clone was found to be identical to the mother's leukemic clone. His lymphocytes could not react with the mother's leukemic cells or his own leukemic cells in mixed lymphocyte culture, suggesting that the HLA homozygosity of the mother may have played a role in inducing immunologic tolerance to the immigrated leukemic cells in the infant. This is the first report of an infantile leukemia transmitted from a mother with leukemia, supposedly through the placenta.
Hybrid human-mouse T-cell clones reactive with Tp40 antibody, which detects cluster of differentiation (CD)7 antigen on human T lymphocytes, were established. Karyotype analysis showed that human chromosome 17 was essential for the expression of CD7 antigen. The presence of this chromosome was confirmed by enzyme analysis of galactokinase, which is coded by a gene on human chromosome 17.
Present paper describes the use of a stochastic search procedure that is the bases of genetic algorithm8 ( GAs ) , in developing near − optimal topologies of load . bearing truss structures . Many works have been already pubhshed until today on the structural optimization of truss topology using the genetic algorithms . In most cases these works express the truss topology as a combina − tion of members , and existence of each member is directly connected to the genetic code . These methods , however, have a fatal weak point . Namely when the topology is made along these methods , they might include needless members or those which lies on the other members . IIl addition to these problems , generated structures are not always stable . These problems become more remarkable when the freedom of the problem becomes large . We have already proposed a new method that resolves 止 ose problems by expressing the truss topology as a combination of triangles that are joined with each ot 血 eL However , the length of chromosome tends to become long, This paper proposes brand − new implements for effective optimization , Detail of t匠e pro − posed methodology is presented as well as the results of numerical examples that clearly show effectiveness and e 伍 ciency of the present method . Key wonis : Genetic Algorithm , Topology Optimization , Structural Optimization
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