Evaluation of a PACAP Peptide Analogue Labeled with (68)Ga Using Two Different Chelating Agents.

OBJECTIVE: The authors have conjugated chelating agents (DOTA and NODAGA) with a peptide (pituitary adenylate cyclase-activating peptide [PACAP] analogue) that has a high affinity for VPAC1 receptors expressed on cancer cells. To determine a suitable chelating agent for labeling with (68)Ga, they have compared the labeling kinetics and stability of these peptide conjugates. METHODS: For labeling, (68)GaCl3 was eluted in 0.1 M HCl from a [(68)Ge-(68)Ga] generator. The influences of peptide concentration, pH, and temperature on the radiolabeling efficiency were studied. The stability was evaluated in saline, human serum, DTPA, transferrin, and metallic ions (FeCl3, CaCl2, and ZnCl2). Cell binding assay was performed using human breast cancer cells (T47D). Tissue biodistribution was studied in normal athymic nude mice. RESULTS: Optimal radiolabeling (\u3e95.0%) of the DOTA-peptide conjugates required a higher (50°C-90°C) temperature and 10 minutes of incubation at pH 2-5. The NODAGA-peptide conjugate needed incubation only at 25°C for 10 minutes. Both radiocomplexes were stable in saline, serum, as well as against transchelation and transmetallation. Cell binding at 37°C for 15 minutes of incubation with (68)Ga-NODAGA-peptide was 34.0% compared to 24.5% for (68)Ga-DOTA-peptide. Tissue biodistribution at 1 hour postinjection of both (68)Ga-labeled peptide conjugates showed clearance through the kidneys. CONCLUSIONS: NODAGA-peptide showed more convenient radiolabeling features than that of DOTA-peptide

RSSI-Based Self-Localization with Perturbed Anchor Positions

We consider the problem of self-localization by a resource-constrained mobile node given perturbed anchor position information and distance estimates from the anchor nodes. We consider normally-distributed noise in anchor position information. The distance estimates are based on the log-normal shadowing path-loss model for the RSSI measurements. The available solutions to this problem are based on complex and iterative optimization techniques such as semidefinite programming or second-order cone programming, which are not suitable for resource-constrained environments. In this paper, we propose a closed-form weighted least-squares solution. We calculate the weights by taking into account the statistical properties of the perturbations in both RSSI and anchor position information. We also estimate the bias of the proposed solution and subtract it from the proposed solution. We evaluate the performance of the proposed algorithm considering a set of arbitrary network topologies in comparison to an existing algorithm that is based on a similar approach but only accounts for perturbations in the RSSI measurements. We also compare the results with the corresponding Cramer-Rao lower bound. Our experimental evaluation shows that the proposed algorithm can substantially improve the localization performance in terms of both root mean square error and bias.Comment: Accepted for publication in 28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (IEEE PIMRC 2017

Multi-mode Tracking of a Group of Mobile Agents

We consider the problem of tracking a group of mobile nodes with limited available computational and energy resources given noisy RSSI measurements and position estimates from group members. The multilateration solutions are known for energy efficiency. However, these solutions are not directly applicable to dynamic grouping scenarios where neighbourhoods and resource availability may frequently change. Existing algorithms such as cluster-based GPS duty-cycling, individual-based tracking, and multilateration-based tracking can only partially deal with the challenges of dynamic grouping scenarios. To cope with these challenges in an effective manner, we propose a new group-based multi-mode tracking algorithm. The proposed algorithm takes the topological structure of the group as well as the availability of the resources into consideration and decides the best solution at any particular time instance. We consider a clustering approach where a cluster head coordinates the usage of resources among the cluster members. We evaluate the energy-accuracy trade-off of the proposed algorithm for various fixed sampling intervals. The evaluation is based on the 2D position tracks of 40 nodes generated using Reynolds' flocking model. For a given energy budget, the proposed algorithm reduces the mean tracking error by up to $20\%$ in comparison to the existing energy-efficient cooperative algorithms. Moreover, the proposed algorithm is as accurate as the individual-based tracking while using almost half the energy.Comment: Accepted for publication in the 20th international symposium on wireless personal multimedia communications (WPMC-2017

Characterizing infection in anti-neutrophil cytoplasmic antibody-associated vasculitis:results from a longitudinal, matched-cohort data linkage study

Objectives: Infection exerts a major burden in ANCA-associated vasculitis (AAV), however, its precise extent and nature remains unclear. In this national study we aimed to longitudinally quantify, characterize and contextualize infection risk in AAV. Methods: We conducted a multicentre matched cohort study of AAV. Complementary data on infections were retrieved via data linkage with the population-based Scottish microbiological laboratory, hospitalization and primary care prescribing registries. Results: A total of 379 AAV patients and 1859 controls were followed up for a median of 3.5 years (interquartile range 1.9-5.7). During follow-up, the proportions of AAV patients with at least one laboratory-confirmed infection, severe infection and primary care antibiotic prescription were 55.4%, 35.6% and 74.6%, respectively. The risk of infection was higher in AAV than in matched controls {laboratory-confirmed infections: incidence rate ratio [IRR] 7.3 [95% confidence interval (CI) 5.6, 9.6]; severe infections: IRR 4.4 [95% CI 3.3, 5.7]; antibiotic prescriptions: IRR 2.2 [95% CI 1.9, 2.6]}. Temporal trend analysis showed that AAV patients remained at a higher risk of infections throughout the follow-up period, especially year 1. Although the Escherichia genus was the most commonly identified pathogen (16.6% of AAV, 5.5% of controls; P &lt; 0.0001), AAV patients had the highest risk for Herpes [IRR 12.5 (95% CI 3.7, 42.6)] and Candida [IRR 11.4 (95% CI 2.4, 55.4)]. Conclusion: AAV patients have up to seven times higher risk of infection than the general population and the overall risk remains significant after 8 years of follow-up. The testing of enhanced short- to medium-term prophylactic antibiotic regimes should be considered.</p