On trip planning queries in spatial databases

In this paper we discuss a new type of query in Spatial Databases, called Trip Planning Query (TPQ). Given a set of points P in space, where each point belongs to a category, and given two points s and e, TPQ asks for the best trip that starts at s, passes through exactly one point from each category, and ends at e. An example of a TPQ is when a user wants to visit a set of different places and at the same time minimize the total travelling cost, e.g. what is the shortest travelling plan for me to visit an automobile shop, a CVS pharmacy outlet, and a Best Buy shop along my trip from A to B? The trip planning query is an extension of the well-known TSP problem and therefore is NP-hard. The difficulty of this query lies in the existence of multiple choices for each category. In this paper, we first study fast approximation algorithms for the trip planning query in a metric space, assuming that the data set fits in main memory, and give the theory analysis of their approximation bounds. Then, the trip planning query is examined for data sets that do not fit in main memory and must be stored on disk. For the disk-resident data, we consider two cases. In one case, we assume that the points are located in Euclidean space and indexed with an Rtree. In the other case, we consider the problem of points that lie on the edges of a spatial network (e.g. road network) and the distance between two points is defined using the shortest distance over the network. Finally, we give an experimental evaluation of the proposed algorithms using synthetic data sets generated on real road networks

On trip planning queries in spatial databases

In this paper we discuss a new type of query in Spatial Databases, called Trip Planning Query (TPQ). Given a set of points P in space, where each point belongs to a category, and given two points s and e, TPQ asks for the best trip that starts at s, passes through exactly one point from each category, and ends at e. An example of a TPQ is when a user wants to visit a set of different places and at the same time minimize the total travelling cost, e.g. what is the shortest travelling plan for me to visit an automobile shop, a CVS pharmacy outlet, and a Best Buy shop along my trip from A to B? The trip planning query is an extension of the well-known TSP problem and therefore is NP-hard. The difficulty of this query lies in the existence of multiple choices for each category. In this paper, we first study fast approximation algorithms for the trip planning query in a metric space, assuming that the data set fits in main memory, and give the theory analysis of their approximation bounds. Then, the trip planning query is examined for data sets that do not fit in main memory and must be stored on disk. For the disk-resident data, we consider two cases. In one case, we assume that the points are located in Euclidean space and indexed with an Rtree. In the other case, we consider the problem of points that lie on the edges of a spatial network (e.g. road network) and the distance between two points is defined using the shortest distance over the network. Finally, we give an experimental evaluation of the proposed algorithms using synthetic data sets generated on real road networks

Pro-inflammatory of PRDM1/SIRT2/NLRP3 Axis in Monosodium Urate-Induced Acute Gouty Arthritis

PR domain containing 1 with zinc finger domain (PRDM1) has been reported as a promoter of inflammation, which is a critical process involved in the pathogenesis of acute gouty arthritis. Herein, we sought to ascertain the function of PRDM1 in the development of acute gouty arthritis and related mechanisms. At first, peripheral blood-derived monocytes from patients with acute gouty arthritis and healthy individuals were collected as experimental samples. Then, macrophages were induced from monocytes using phorbol myristate acetate (PMA). The expression patterns of PRDM1, sirtuin 2 (SIRT2), and NLR family, pyrin domain-containing 3 (NLRP3) were characterized by RT-qPCR and Western blot assay. PMA-induced macrophages were stimulated by monosodium urate (MSU) for in vitro experimentation. Meanwhile, a murine model of MSU-induced acute gouty arthritis was established for in vivo validation. PRDM1 was highly expressed while SIRT2 poorly expressed in patients with acute gouty arthritis. Loss of PRDM1 could reduced NLRP3 inflammasome and mature IL-1β levels and down-regulate inflammatory cytokines in macrophages, which contributed to protection against acute gouty arthritis. Furthermore, results showed that PRDM1 could inhibit SIRT2 expression via binding to the deacetylase SIRT2 promoter. Finally, the in vivo experiments demonstrated that PRDM1 increased NLRP3 inflammasome and mature IL-1β through transcriptional inhibition of SIRT2, whereby aggravating MSU-induced acute gouty arthritis. To sum up, PRDM1 increased NLRP3 inflammasome through inhibiting SIRT2, consequently aggravating MSU-induced acute gouty arthritis