Axonal transport of neurotrophins by visceral afferent and efferent neurons of the vagus nerve of the rat.

The receptor-mediated axonal transport of [125I]-labeled neurotrophins by afferent and efferent neurons of the vagus nerve was determined to predict the responsiveness of these neurons to neurotrophins in vivo. [125I]-labeled neurotrophins were administered to the proximal stump of the transected cervical vagus nerve of adult rats. Vagal afferent neurons retrogradely transported [125I]neurotrophin-3 (NT-3), [125I]nerve growth factor (NGF), and [125I]neurotrophin-4 (NT-4) to perikarya in the ipsilateral nodose ganglion, and transganglionically transported [125I]NT-3, [125I]NGF, and [125I]NT-4 to the central terminal field, the nucleus tractus solitarius (NTS). Vagal afferent neurons showed minimal accumulation of [125I]brain-derived neurotrophic factor (BDNF). In contrast, efferent (parasympathetic and motor) neurons located in the dorsal motor nucleus of the vagus and nucleus ambiguus retrogradely transported [125I]BDNF, [125I]NT-3, and [125I]NT-4, but not [125I]NGF. The receptor specificity of neurotrophin transport was examined by applying [125I]-labeled neurotrophins with an excess of unlabeled neurotrophins. The retrograde transport of [125I]NT-3 to the nodose ganglion was reduced by NT-3 and by NGF, and the transport of [125I]NGF was reduced only by NGF, whereas the transport of [125I]NT-4 was significantly reduced by each of the neurotrophins. The competition profiles for the transport of NT-3 and NGF are consistent with the presence of TrkA and TrkC and the absence of TrkB in the nodose ganglion, whereas the profile for NT-4 suggests a p75 receptor-mediated transport mechanism. The transport profiles of neurotrophins by efferent vagal neurons in the dorsal motor nucleus of the vagus and nucleus ambiguus are consistent with the presence of TrkB and TrkC, but not TrkA, in these nuclei. These observations describe the unique receptor-mediated axonal transport of neurotrophins in adult vagal afferent and efferent neurons and thus serve as a template to discern the role of specific neurotrophins in the functions of these visceral sensory and motor neurons in vivo.

A Zipfian model of an automatic bibliographic system: an application to MEDLINE.

A Zipfian model of an automatic bibliographic system is developed using parameters describing the contents of it database and its inverted file. The underlying structure of the Zipf distribution is derived, with particular emphasis on its application to work frequencies, especially with regard to the inverted flies of an automatic bibliographic system. Andrew Booth developed a form of Zipf's law which estimates the number of words of a particular frequency for a given author and text. His formulation has been adopted as the basis of a model of term dispersion in an inverted file system. The model is also distinctive in its consideration of the proliferation of spelling errors in free text, and the inclusion of all searchable elements from the system's inverted file. This model is applied to the National Library of Medicine's MEDLINE. The model carries implications for the determination of database storage requirements, search response time, and search exhaustiveness.

Automated DRG systems: unanswered questions.

Health care facilities seeking to prepare for a DRG-based or a similar case mix system may consider a range of options: microcomputers, shared computer services, a generalized data base management system.

Data base design for infectious disease control.

This paper presents an overview of a problem requiring the design of a decision support system (DSS) to be used for infectious disease control at a Veterans Administration hospital. An overview of the DSS selected for this application is presented. The major design question addressed is that of determining the data base schema. An automated network data base design technique is presented along with a description of its use in actually designing a data base required for monitoring infectious disease control. This technique can generate data bases containing large numbers of data items and set relationships, while maintaining several useful properties within the data structure.