Prognostic significance of inflammatory markers LMR, PLR, MPV, FIB in intermediate-and high-risk papillary thyroid carcinoma.

Background: Lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio (PLR), mean platelet volume (MPV) and fibrinogen (FIB) have been identified as predictive biomarkers in several malignancies. The aim of this study was to explore the association between inflammatory index with clinicopathologic features as well as recurrence risk in intermediate-to high-risk papillary thyroid carcinoma (PTC). Methods: Retrospective evaluation of 212 patients diagnosed with intermediate-to high-risk PTC who underwent surgery at China-Japan Union Hospital between 2015 and 2016. Logistic regression and receiver operating curves (ROC) were used to explore possible risk factors. Results: LMR was predictive of capsular invasion (AUC=0.595, P=0.017), FIB was predictive of lymph node metastasis (LN) (AUC=0.714, P=0.002), MPV was predictive of largest LN size ≥1cm (AUC=0.639, P=0.002), PLR and MPV were predictive of recurrence (AUC=0.616, P=0.032; AUC=0.626, P=0.020). In addition, FIB ≤ 2.6 (OR=6.440, 95%CI:1.777-23.336, P=0.005) and capsular invasion (OR=3.773, 95%CI:1.171-12.159, P=0.026) were identified as independent risk factors for lymph node metastasis by multivariate analysis. In addition, LN metastasis (P=0.048), largest LN size ≥ 1 cm (P=0.032), MPV > 9.4 (P=0.046), and PLR ≤ 128.1 (P=0.032) were significantly related with recurrence. Further multivariate regression analysis revealed that PLR ≤ 128.1 was a potentially independent risk factor for recurrence. Specifically, the risk of recurrence was 2.951 times higher in patients with a PLR ≤ 128.1 compared with patients with a PLR > 128.1 (OR=2.951, 95% CI:1.238-7.037, P=0.015). Conclusion: In intermediate-to high-risk PTC, LMR, PLR, MPV, and FIB could predict clinicopathologic features and recurrence, with lower PLR being the potential risk factors for recurrence.

On a Blockchain-Based Security Scheme for Defense against Malicious Nodes in Vehicular Ad-Hoc Networks.

Vehicular ad-hoc networks (VANETs) aim to provide a comfortable driving experience. Sharing messages in VANETs can help with traffic management, congestion mitigation, and driving safety. However, forged or false messages may undermine the efficiency of VANETs. In this paper, we propose a security scheme based on blockchain technology, where two types of blockchain are constructed based on roadside units (RSUs) and Certificate Authorities (CAs), respectively. The proposed security scheme has multifold goals to identify malicious nodes and detect forged messages based on multiple factors, such as reputation of sender nodes, and time and distance effectiveness of messages. In addition, an incentive mechanism is introduced on the RSU blockchain to encourage RSUs to adopt active behaviors. Extensive simulations show that the proposed scheme exhibits superior performances to existing methods in detecting forged messages and identifying malicious nodes. Meanwhile, it provides privacy protection and improves the efficiency of vehicular networks.

A Hybrid Multi-Target Path Planning Algorithm for Unmanned Cruise Ship in an Unknown Obstacle Environment.

To solve the problem of traversal multi-target path planning for an unmanned cruise ship in an unknown obstacle environment of lakes, this study proposed a hybrid multi-target path planning algorithm. The proposed algorithm can be divided into two parts. First, the multi-target path planning problem was transformed into a traveling salesman problem, and an improved Grey Wolf Optimization (GWO) algorithm was used to calculate the multi-target cruise sequence. The improved GWO algorithm optimized the convergence factor by introducing the Beta function, which can improve the convergence speed of the traditional GWO algorithm. Second, based on the planned target sequence, an improved D* Lite algorithm was used to implement the path planning between every two target points in an unknown obstacle environment. The heuristic function in the D* Lite algorithm was improved to reduce the number of expanded nodes, so the search speed was improved, and the planning path was smoothed. The proposed algorithm was verified by experiments and compared with the other four algorithms in both ordinary and complex environments. The experimental results demonstrated the strong applicability and high effectiveness of the proposed method.

Development and Validation of a Prognostic Nomogram Based on Residual Tumor in Patients With Nondisseminated Nasopharyngeal Carcinoma.

OBJECTIVES: To investigate the prognostic value of residual tumor based on Magnetic resonance imaging(MRI) and establish an effective prognostic nomogram model referring to clinical,pathological and other related factors for predicting prognosis in nasopharyngeal carcinoma. METHODS: Overall, 538 patients with non-metastatic, histologically-confirmed nasopharyngeal carcinoma were retrospectively examined. Data from 397 patients were used for the construction and validation of a nomogram based on the presence of residual tumor. A concordance index (C-index) was employed to assess the predictive accuracy and discriminative ability of the nomogram. RESULTS: The 3-year survival rates in the non-residual and residual tumor cohorts were as follows: progression-free survival, 73.4% vs. 61.0%, P = 0.009; locoregional recurrence-free survival, 81.9% vs. 72.0%, P = 0.02; and distant metastasis-free survival, 80.7% vs. 73.5%, P = 0.11. Nine significant factors were included in the nomogram model. The calibration curve for the probability of progression-free survival showed that the nomogram-based predictive values had good concordance with the actual observations. CONCLUSION: The results showed that the patients in the residual tumor cohorts had a worse prognosis.The proposed nomogram may predict the prognosis and guide clinical decision-making concerning local residual tumors in nasopharyngeal carcinoma patients. Patients with a high risk of progression require more timely and aggressive treatment.

Intermediate honeycomb ordering to trigger oxygen redox chemistry in layered battery electrode.

Sodium-ion batteries are attractive energy storage media owing to the abundance of sodium, but the low capacities of available cathode materials make them impractical. Sodium-excess metal oxides Na2MO3 (M: transition metal) are appealing cathode materials that may realize large capacities through additional oxygen redox reaction. However, the general strategies for enhancing the capacity of Na2MO3 are poorly established. Here using two polymorphs of Na2RuO3, we demonstrate the critical role of honeycomb-type cation ordering in Na2MO3. Ordered Na2RuO3 with honeycomb-ordered [Na(1/3)Ru(2/3)]O2 slabs delivers a capacity of 180 mAh g(-1) (1.3-electron reaction), whereas disordered Na2RuO3 only delivers 135 mAh g(-1) (1.0-electron reaction). We clarify that the large extra capacity of ordered Na2RuO3 is enabled by a spontaneously ordered intermediate Na1RuO3 phase with ilmenite O1 structure, which induces frontier orbital reorganization to trigger the oxygen redox reaction, unveiling a general requisite for the stable oxygen redox reaction in high-capacity Na2MO3 cathodes.