CD51/CD61+ Endothelial Microparticles Decrease in Diabetes Patients with Hypertension

Backgrounds: Type 2 Diabetes Mellitus (T2DM) and hypertension are commonly co-occurred and both diseases are related to endothelial dysfunction. Endothelial microparticles (EMPs) are shed from endothelial cells and can be found in condition of endothelial dysfunction. This study aimed to evaluate the circulating endothelial MPs (CD51/CD61+) levels in T2DM patients with or without hypertension and the correlation between endothelial MPs and clinical parameters. Methods and Results: 20 healthy control, 16 T2DM patients without hypertension and 11 T2DM patients with hypertension were recruited. CD51/CD61+ EMPs from all subjects were analyzed by flow cytometry. We found that, in the group of T2DM patients with hypertension, the absolute median number of CD51/CD61+EMPs was significantly decreased, compared with that in the healthy control and T2DM without hypertension groups. Furthermore, we conducted receiver operating characteristics (ROC) analysis to examine the accuracy of CD51/CD61+EMPs in the discrimination  between T2DM patients with hypertension and healthy control, showing the accuracy was 76.4%. In addition, we also found that the accuracy of CD51/CD61+EMPs was 83.5% in the discrimination between T2DM patients with hypertension or without hypertension Conclusion: These findings identify CD51/CD61+EMPs as a potential biomarker to monitor endothelial dysfunction in T2DM patients with hypertension

R-bUCRP: A Novel Reputation-Based Uneven Clustering Routing Protocol for Cognitive Wireless Sensor Networks

Energy of nodes is an important factor that affects the performance of Wireless Sensor Networks (WSNs), especially in the case of existing selfish nodes, which attracted many researchers’ attention recently. In this paper, we present a reputation-based uneven clustering routing protocol (R-bUCRP) considering both energy saving and reputation assessment. In the cluster establishment phase, we adopt an uneven clustering mechanism which controls the competitive scope of cluster head candidates to save the energy of WSNs. In the cluster heads election phase, the residual energy and reputation value are used as the indexes to select the optimal cluster head, where the reputation mechanism is introduced to support reputation assessment. Simulation results show that the proposed R-bUCRP can save node energy consumption, balance network energy distribution, and prolong network lifetime

Efficient Strong Privacy-Preserving Conjunctive Keyword Search Over Encrypted Cloud Data

Searchable symmetric encryption (SSE) supports keyword search over outsourced symmetrically encrypted data. Dynamic searchable symmetric encryption (DSSE), a variant of SSE, further enables data updating. Most DSSE works with conjunctive keyword search primarily consider forward and backward privacy. Ideally, the server should only learn the result sets involving all keywords in the conjunction. However, existing schemes suffer from keyword pair result pattern (KPRP) leakage, revealing the partial result sets containing two of query keywords. We propose the first DSSE scheme to address aforementioned concerns that achieves strong privacy-preserving conjunctive keyword search. Specifically, our scheme can maintain forward and backward privacy and eliminate KPRP leakage, offering a higher level of security. The search complexity scales with the number of documents stored in the database in several existing schemes. However, the complexity of our scheme scales with the update frequency of the least frequent keyword in the conjunction, which is much smaller than the size of the entire database. Besides, we devise a least frequent keyword acquisition protocol to reduce frequent interactions between clients. Finally, we analyze the security of our scheme and evaluate its performance theoretically and experimentally. The results show that our scheme has strong privacy preservation and efficiency

P-bRS: A Physarum-Based Routing Scheme for Wireless Sensor Networks

Routing in wireless sensor networks (WSNs) is an extremely challenging issue due to the features of WSNs. Inspired by the large and single-celled amoeboid organism, slime mold Physarum polycephalum, we establish a novel selecting next hop model (SNH). Based on this model, we present a novel Physarum-based routing scheme (P-bRS) for WSNs to balance routing efficiency and energy equilibrium. In P-bRS, a sensor node can choose the proper next hop by using SNH which comprehensively considers the distance, energy residue, and location of the next hop. The simulation results show how P-bRS can achieve the effective trade-off between routing efficiency and energy equilibrium compared to two famous algorithms