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After intratesticular injection of a chromium hematoxylin and fluorescent nanoparticle solution, we found a novel flow path in the abdominal cavity consisting of primo-vessels and primo-nodes. This flow path formed a network that crossed over the surfaces of abdominal organs, and generally linked to the greater omentum and adjacent visceral peritoneum. Some of these structures terminated at organs such as the small intestine and the urinary bladder; occasionally, the network entered the parenchyma of organs. The semitransparent primo-vessels and nodes were wholly or partially stained dark-blue by chromium hematoxylin. Injected nanoparticles were also observed in primo-vessels and nodes as well as the parenchyma of organs which were the site of primo-vessel termination. Transmission electron microscopy showed that the primo-vessels consist of many sinuses (4-6 mum), surrounded by collagen fibers, specific granules, cellular remnants, immune cells, extracellular matrices, and hematopoietic cells. These histological features are completely different from blood and lymph vessels indicating that primo-vessels are novel structures that allow the flow of dye.

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A wireless sensor network is a collection of sensor nodes distributed over a geographic area to monitor physical conditions, such as temperature, light, humidity, or pressure. Since a sensor node has limited energy supply, running multiple continuous monitoring queries may impose significant overhead on the sensor network. In this paper, we propose an energy-efficient multiple query optimization method to reduce the number of monitoring queries that are running in the sensor network. When a new monitoring query is submitted to the base station, the proposed method checks whether the new query can be evaluated using results of currently running queries. If so, the proposed method rewrites the new query using currently running queries and then evaluates the rewritten query at the base station without injecting it into the sensor network. Consequently, the amount of data transmitted from sensor nodes to the base station is reduced, resulting in lower energy consumption. Through experiments, we show the effectiveness of the proposed method.