The Global Navigation Satellite System (GNSS) cannot achieve accurate positioning and navigation in the indoor environment. Therefore, efficient indoor positioning technology has become a very active research topic. Bluetooth beacon positioning is one of the most widely used technologies. Because of the time-varying characteristics of the Bluetooth received signal strength indication (RSSI), traditional positioning algorithms have large ranging errors because they use fixed path loss models. In this paper, we propose an RSSI real-time correction method based on Bluetooth gateway which is used to detect the RSSI fluctuations of surrounding Bluetooth nodes and upload them to the cloud server. The terminal to be located collects the RSSIs of surrounding Bluetooth nodes, and then adjusts them by the RSSI fluctuation information stored on the server in real-time. The adjusted RSSIs can be used for calculation and achieve smaller positioning error. Moreover, it is difficult to accurately fit the RSSI distance model with the logarithmic distance loss model due to the complex electromagnetic environment in the room. Therefore, the back propagation neural network optimized by particle swarm optimization (PSO-BPNN) is used to train the RSSI distance model to reduce the positioning error. The experiment shows that the proposed method has better positioning accuracy than the traditional method.

The NGR-containing peptides have been shown to bind specifically to CD13/aminopeptidase N (APN) receptor, one of the attractive tumor vasculature biomarkers. In this study, we evaluated (64)Cu-labeled monomeric and dimeric NGR peptides for microPET imaging of CD13 receptor expression in vivo. Western blot analysis and immunofluorescence staining were performed to identify CD13-positive and CD13-negative cell lines. NGR-containing peptides were conjugated with 1,4,7,10-tetraazadodecane-N,N',N″,N‴-tetraacetic acid (DOTA) and labeled with (64)Cu (t(1/2) = 12.7 h) in ammonium acetate buffer. The resulting monomeric ((64)Cu-DOTA-NGR1) and dimeric ((64)Cu-DOTA-NGR2) peptides were then subjected to in vitro stability, cell uptake and efflux, small animal micorPET, and biodistribution studies. In vitro studies demonstrated that CD13 receptors are overexpressed in human fibrosarcoma HT-1080 cells and negative in human colon adenocarcinoma HT-29 cells. The binding affinity of (64)Cu-DOTA-NGR2 to HT-1080 cells was measured to be within low nanomolar range and about 2-fold higher than that of (64)Cu-DOTA-NGR1. For small animal microPET studies, (64)Cu-DOTA-NGR2 displayed more favorable in vivo performance in terms of higher tumor uptake and slower tumor washout in CD13-positive HT-1080 tumor xenografts as compared to (64)Cu-DOTA-NGR1. As expected, significantly lower tumor uptake and poorer tumor/normal organ contrast were observed for both (64)Cu-DOTA-NGR1 and (64)Cu-DOTA-NGR2 in CD13-negative HT-29 tumor xenografts in comparison with those in the HT-1080 tumor xenografts. The CD13-specific tumor activity accumulation of both (64)Cu-DOTA-NGR1 and (64)Cu-DOTA-NGR2 was further demonstrated by significant reduction of tumor uptake in HT-1080 tumor xenografts with a coinjected blocking dose of cyclic NGR peptide [c(CNGRC)]. The biodistribution results were consistent with the quantitative analysis of microPET imaging. We concluded that both (64)Cu-DOTA-NGR1 and (64)Cu-DOTA-NGR2 have good and specific tumor uptake in CD13-positive HT-1080 tumor xenografts. (64)Cu-DOTA-NGR2 showed higher tumor uptake and better tumor retention than (64)Cu-DOTA-NGR1, presumably due to bivalency effect and increase in apparent molecular size. (64)Cu-DOTA-NGR2 is a promising PET probe for noninvasive detection of CD13 receptor expression in vivo.