Given two sets A and B of multidimensional objects, the all-nearest-neighbors (ANN) query retrieves for each object in A its nearest neighbor in B. Although this operation is common in several applications, it has not received much attention in the database literature. In this paper we study alternative methods for processing ANN queries depending on whether A and B are indexed. Our algorithms are evaluated through extensive experimentation using synthetic and real datasets. The performance studies show that they are an order of magnitude faster than a previous approach based on closest-pairs query processing. 1Introduction Let A and B be two spatial datasets and dist(p,q) be a distance metric. Then, the all-nearest-neighbors query is defined as: . In this paper, we propose novel techniques for general ANN query processing. Following the common trend in the literature, we assume that the underlying indexes (whenever available) are R-trees [Gut84, BKSS90]. Although, for simplicity, we deal with points and use Euclidean distance, extensions to other data partition access methods, extended objects and other distance metrics are straightforward. The rest of the paper is organized as follows. Section 2 discusses previous work directly related to the ANN problem. Sections 3 and 4 present algorithms for different cases, based on whether A, B, or both are indexed. Section 5 experimentally evaluates the algorithms, and section 6 concludes the paper with a discussion. 2Related work ANN queries constitute a hybrid of nearest neighbor search and spatial joins; therefore, in sections 2.1 and 2.2 we review related work for these query types focusing more on the processing techniques that are also employed by our algorithms. Section 2.3 describes methods for closest-pair queries, and section 2.4 discusses existing techniques for ANN query processing. 2.1Nearest neighbor queries The goal of nearest neighbor (NN) search is to find the objects in a dataset A that are closest to a query point q. Existing algorithms presume that the dataset is indexed by an R-tree and use various metrics to prune the search space: mindist(q,M) is the minimum distance between q and any point in a minimum bounding rectangle (MBR) M. The algorithm of [RKV95] traverses the tree in a depth-first (DF) manner. Assume that we search for the nearest neighbor NN(q,R) of q in R-tree R. Starting from the root, all entries are sorted according to their mindist from q, and the entry with the smallest mindist is visited first. The process is repeated recursively until the leaf level where a potential nearest neighbor is found. During backtracking to the upper levels, the algorithm only visits entries whose mindist is smaller than the distance of the nearest neighbor found so far. As an example consider the R-tree of Figure 1, where the number in each entry refers to the mindist (for intermediate entries) or the actual distance (for leaf entries, i.e., objects) from q (these numbers are not stored but computed dynamically during query processing). DF would...

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Mildronate has been used as antianginal drug in parts of Europe for many years, but its pharmacokinetic (PK) properties in humans remain unclear. This study was designed to assess and compare the PK properties of mildronate capsules after single escalating oral dose and multiple doses in healthy Chinese volunteers. Volunteers were randomly assigned to receive a single dose of 250, 500, 1000, 1250 or 1500 mg of mildronate capsules. Those who received the 500-mg dose continued on the multiple-dose phase and received 500 mg three times a day for 13 days. Plasma drug concentrations were analysed by ultraperformance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). Tolerability was assessed throughout the study. A total of 40 Chinese volunteers were enrolled in the study. No period or sequence effect was observed. Area under the concentration and C(max) were increased proportionally with the dose levels, whereas t(1/2) and V(d)/f were dependent on the dose. Nonlinear PK properties were found at doses of 250-1500 mg. There was an accumulation after multiple-dose administration. No serious adverse events (AEs) were reported in the PK study. The formulation was well tolerated.

A human plasma sample was subjected to nondenaturing micro 2DE and a gel area (5 mm × 18 mm) that includes high‐density lipoprotein (HDL) was cut into 1 mm × 1 mm squares, then the proteins in the 90 gel pieces were analyzed by quantitative LC‐MS/MS. Grid‐cutting of the gel was employed to; (i) ensure the total analysis of the proteins in the area, (ii) standardize the conditions of analysis by LC‐MS/MS, (iii) reconstruct the protein distribution patterns from the quantity data. Totally 154 proteins were assigned in the 90 gel pieces and the quantity distribution of each was reconstructed as a color density pattern (a native protein map). The map of apolipoprotein (Apo) A‐I showed a wide apparent mass distribution characteristic to HDL and was compared with the maps of the other 153 proteins. Eleven proteins showed maps of wide distribution that overlapped with the map of Apo A‐I, and all have been reported to be the components of HDL. Further, seven minor proteins associated with HDL were detected at the gel positions of high Apo A‐I quantity. These results for the first time visualized the localization of HDL apolipoproteins on a nondenaturing 2DE gel and strongly suggested their interactions.

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