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Weterman, M. A. J., Wilbrink, M. J. M., Janssen, I. M., Janssen, H. A. P., Berg, E. v. d., Fisher, S. E., Craig, I., & Geurts van Kessel, A. H. M. (1996). Molecular cloning of the papillary renal cell carcinoma-associated translocation (X;1)(p11;q21) breakpoint. Cytogenetic and genome research, 75(1), 2-6. doi:10.1159/000134444.
Abstract
A combination of Southern blot analysis on a panel of tumor-derived somatic cell hybrids and fluorescence in situ hybridization techniques was used to map YACs, cosmids and DNA markers from the Xp11.2 region relative to the X chromosome breakpoint of the renal cell carcinoma-associated t(X;1)(p11;q21). The position of the breakpoint could be determined as follows: Xcen-OATL2-DXS146-DXS255-SYP-t(X;1)-TFE 3-OATL1-Xpter. Fluorescence in situ hybridization experiments using TFE3-containing YACs and cosmids revealed split signals indicating that the corresponding DNA inserts span the breakpoint region. Subsequent Southern blot analysis showed that a 2.3-kb EcoRI fragment which is present in all TFE3 cosmids identified, hybridizes to aberrant restriction fragments in three independent t(X;1)-positive renal cell carcinoma DNAs. The breakpoints in these tumors are not the same, but map within a region of approximately 6.5 kb. Through preparative gel electrophoresis an (X;1) chimaeric 4.4-kb EcoRI fragment could be isolated which encompasses the breakpoint region present on der(X). Preliminary characterization of this fragment revealed the presence of a 150-bp region with a strong homology to the 5' end of the mouse TFE3 cDNA in the X-chromosome part, and a 48-bp segment in the chromosome 1-derived part identical to the 5' end of a known EST (accession number R93849). These observations suggest that a fusion gene is formed between the two corresponding genes in t(X;1)(p11;q21)-positive papillary renal cell carcinomas. -
Wittenburg, P., van Kuijk, D., & Dijkstra, T. (1996). Modeling human word recognition with sequences of artificial neurons. In C. von der Malsburg, W. von Seelen, J. C. Vorbrüggen, & B. Sendhoff (
Eds. ), Artificial Neural Networks — ICANN 96. 1996 International Conference Bochum, Germany, July 16–19, 1996 Proceedings (pp. 347-352). Berlin: Springer.Abstract
A new psycholinguistically motivated and neural network based model of human word recognition is presented. In contrast to earlier models it uses real speech as input. At the word layer acoustical and temporal information is stored by sequences of connected sensory neurons which pass on sensor potentials to a word neuron. In experiments with a small lexicon which includes groups of very similar word forms, the model meets high standards with respect to word recognition and simulates a number of wellknown psycholinguistical effects.
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