Interleukin 2 transcription factors as molecular targets of cAMP inhibition: delayed inhibition kinetics and combinatorial transcription roles

Elevation of cAMP can cause gene-specific inhibition of interleukin 2 (IL-2) expression. To investigate the mechanism of this effect, we have combined electrophoretic mobility shift assays and in vivo genomic footprinting to assess both the availability of putative IL-2 transcription factors in forskolin-treated cells and the functional capacity of these factors to engage their sites in vivo. All observed effects of forskolin depended upon protein kinase A, for they were blocked by introduction of a dominant negative mutant subunit of protein kinase A. In the EL4.E1 cell line, we report specific inhibitory effects of cAMP elevation both on NF-κB/Rel family factors binding at -200 bp, and on a novel, biochemically distinct "TGGGC" factor binding at -225 bp with respect to the IL-2 transcriptional start site. Neither NF-AT nor AP-1 binding activities are detectably inhibited in gel mobility shift assays. Elevation of cAMP inhibits NF-κB activity with delayed kinetics in association with a delayed inhibition of IL-2 RNA accumulation. Activation of cells in the presence of forskolin prevents the maintenance of stable protein-DNA interactions in vivo, not only at the NF-κB and TGGGC sites of the IL-2 enhancer, but also at the NF-AT, AP-1, and other sites. This result, and similar results in cyclosporin A-treated cells, imply that individual IL-2 transcription factors cannot stably bind their target sequences in vivo without coengagement of all other distinct factors at neighboring sites. It is proposed that nonhierarchical, cooperative enhancement of binding is a structural basis of combinatorial transcription factor action at the IL-2 locus

Automated Generation of Geometric Theorems from Images of Diagrams

We propose an approach to generate geometric theorems from electronic images of diagrams automatically. The approach makes use of techniques of Hough transform to recognize geometric objects and their labels and of numeric verification to mine basic geometric relations. Candidate propositions are generated from the retrieved information by using six strategies and geometric theorems are obtained from the candidates via algebraic computation. Experiments with a preliminary implementation illustrate the effectiveness and efficiency of the proposed approach for generating nontrivial theorems from images of diagrams. This work demonstrates the feasibility of automated discovery of profound geometric knowledge from simple image data and has potential applications in geometric knowledge management and education.Comment: 31 pages. Submitted to Annals of Mathematics and Artificial Intelligence (special issue on Geometric Reasoning