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Cytokines can initiate and perpetuate human diseases, and are among the best-validated of therapeutic targets. Cytokines can be blocked by the use of soluble receptors; however, the use of this approach for cytokines such as interleukin (IL)-1, IL-4, IL-6 and IL-13 that use multi-component receptor systems is limited because monomeric soluble receptors generally exhibit low affinity or function as agonists. We describe here a generally applicable method to create very high-affinity blockers called 'cytokine traps' consisting of fusions between the constant region of IgG and the extracellular domains of two distinct cytokine receptor components involved in binding the cytokine. Traps potently block cytokines in vitro and in vivo and represent a substantial advance in creating novel therapeutic candidates for cytokine-driven diseases., Author(s): Aris N. Economides [1, 8]; Laura Rocco Carpenter [1, 8]; John S. Rudge [1]; Vivien Wong [2]; Ellen M. Koehler-Stec [2]; Christopher Hartnett [3]; Erica A. Pyles [3]; Xiaobing [...]

This article presents an approach to using cognitive models of narrative discourse comprehension to define an explicit computational model of a reader's comprehension process during reading, predicting aspects of narrative focus and inferencing with precision. This computational model is employed in a narrative discourse generation system to select and sequence content from a partial plan representing story world facts, objects, and events, creating discourses that satisfy comprehension criteria. Cognitive theories of narrative discourse comprehension define explicit models of a reader's mental state during reading. These cognitive models are created to test hypotheses and explain empirical results about reader comprehension, but do not often contain sufficient precision for implementation on a computer. Therefore, they have not previously been suitable for computational narrative generation. The results of three experiments are presented and discussed, exhibiting empirical support for the approach presented. This work makes a number of contributions that advance the state-of-the-art in narrative discourse generation: a formal model of narrative focus, a formal model of online inferencing in narrative, a method of selecting narrative discourse content to satisfy comprehension criteria, and both implementation and evaluation of these models. [ABSTRACT FROM AUTHOR]