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AJCC TNM stage and WHO grade (G) are two widely used staging systems to guide clinical management for pancreatic neuroendocrine neoplasms (panNENs), based on clinical staging and pathological grading information, respectively. We proposed to integrate TNM stage and G grade into one staging system (TNMG) and to evaluate its clinical application as a prognostic indicator for panNENs. Accordingly, 5254 patients diagnosed with panNENs were used to evaluate and to validate the applicability of TNMG to panNENs. The predictive accuracy of TNMG system was compared with that of each separate staging/grading system. We found that TNM stage and G grade were independent risk factors for survival in both the Surveillance, Epidemiology, and End Result (SEER) and multicenter series. The interaction effect between TNM stage and G grade was significant. Twelve subgroups combining the TNM stage and G grade were proposed in the TNMG stage, which were classified into five stages TNMG. According to the TNMG staging classification in the SEER series, the estimated median survival for stages I, II, III, IV, and V were 203, 174, 112, 61, and 8 months, respectively. The predictive accuracy of TNMG stage was higher than that of TNM stage and G grade used independently. The TNMG stage classification was more accurate in predicting panNEN patient's prognosis than either the TNM stage or G grade.

Poetry composition is an ecologically valid approach for investigating creative processes. However, little is known about how the brain creates poetry and about the role of knowledge during poetry composition. Here, we identified patterns of task-based functional connectivity during poetry composition by experts and novices under two experimental conditions (familiar vs unfamiliar themes) and one control condition. Poetry composition was related to large-scale network connectivity between the language network (LN) and the right executive control network (RECN), precuneus, and higher visual network. Under familiar themes, poetry composition recruited more functional connections between the RECN and default mode network, whereas using unfamiliar themes elicited more functional connections between sensorimotor and visual networks. Moreover, the strength of LN-RECN is positively correlated with originality in the familiar condition, while negatively correlated with originality in the unfamiliar condition. These results reveal the brain connectivity patterns and highlight the importance of knowledge underlying poetry composition.

Epidermal growth factor receptor (EGFR) is an essential target for cancer treatment. However, EGFR inhibitor erlotinib showed limited clinical benefit in pancreatic cancer therapy. Here, we showed the underlying mechanism of tumor microenvironment suppressing the sensitivity of EGFR inhibitor through the pancreatic stellate cell (PSC).The expression of alpha-smooth muscle actin (α-SMA) and hypoxia marker in human pancreatic cancer tissues were detected by immunohistochemistry, and their correlation with overall survival was evaluated. Human immortalized PSC was constructed and used to investigate the potential effect on pancreatic cancer cell lines in hypoxia and normoxia. Luciferase reporter assay and Chromatin immunoprecipitation were performed to explore the potential mechanisms in vitro. The combined inhibition of EGFR and Met was evaluated in an orthotopic xenograft mouse model of pancreatic cancer.We found that high expression levels of α-SMA and hypoxia markers are associated with poor prognosis of pancreatic cancer patients. Mechanistically, we demonstrated that hypoxia induced the expression and secretion of HGF in PSC via transcription factor HIF-1α. PSC-derived HGF activates Met, the HGF receptor, suppressing the sensitivity of pancreatic cancer cells to EGFR inhibitor in a KRAS-independent manner by activating the PI3K-AKT pathway. Furthermore, we found that the combination of EGFR inhibitor and Met inhibitor significantly suppressed tumor growth in an orthotopic xenograft mouse model.Our study revealed a previously uncharacterized HIF1α-HGF-Met-PI3K-AKT signaling axis between PSC and cancer cells and indicated that EGFR inhibition plus Met inhibition might be a promising strategy for pancreatic cancer treatment.This study was supported by The National Natural Science Foundation of China.

In contrast to the steady increase in survival observed for most cancer types, advances have been slow for pancreatic cancers. Current chemotherapy has limited benefits for patients with pancreatic cancer. Therefore, there is an urgent need for effective pancreatic cancer treatment strategies. At present, targeting the autophagic pathway is regarded as a promising new strategy for cancer treatment. Danthron (1,8-dihydroxyanthrquinone), a component from Rheum palmatum L. (polygonaceae), has several biological activities. However, the inhibition of autophagy by danthron has never been recognized, previously.Here we find that danthron may prevent autophagy, inhibit proliferation and induce apoptosis in pancreatic cancer cells in vitro. Autophagy induced by doxorubicin plays a protective role in pancreatic cancer cells and inhibition of autophagy by chloroquine or silencing autophagy protein 5 (Atg5) may chemosensitize pancreatic cancer cell lines to doxorubicin. Similarly, inhibition of autophagy by danthron also enhances toxicity of doxorubicin to pancreatic cancer cells. These results indicate that danthron has an anticancer effect and can sensitize the chemotherapeutic effect of doxorubicin on pancreatic cancer cells. These findings also suggest that inhibition of autophagy may be an effective way to promote the chemotherapy of pancreatic cancer.

The lysosome is emerging as a central regulator of the autophagic process, which plays a critical role in tumor growth and chemoresistance. Alantolactone, which is a natural compound produced by Inula helenium, has been shown to induce apoptosis in numerous cancer types. However, the mechanism by which alantolactone regulates apoptosis is still poorly understood. In this work, we observed that alantolactone caused the accumulation of autophagosomes due to impaired autophagic degradation and substantially inhibited the activity and expression of CTSB/CTSD proteins that when depleted caused lysosomal dysfunction. Furthermore, we found that alantolactone inhibited the proliferation of pancreatic cancer cells in vitro and in vivo and enhanced the chemosensitivity of pancreatic cancer cells to oxaliplatin. In addition, a reduction in TFEB levels was a critical event in the apoptosis and cell death caused by alantolactone. Our data demonstrated that alantolactone, which impaired autophagic degradation, was a pharmacological inhibitor of autophagy in pancreatic cancer cells and markedly enhanced the chemosensitivity of pancreatic cancer cells to oxaliplatin.

In order to improve the penetration performance of hypersonic glide vehicles, a lateral pendulum maneuvering strategy is proposed. A single radar trajectory tracking model is established and EKF is used to estimate the entire trajectory parameters. Based on the analysis of the composition of the defense system and the intercepting mechanism, the pendulum maneuvering trajectory is designed, and the influencing factors of the gliding penetration performance are analyzed. Then, an integrated index of penetration performance consists of the hit point prediction error, intercepting velocity, overload and the energy consumption caused by maneuver is constructed. Furthermore, a maneuvering strategy is proposed that the first maneuver is performed to enlarge prediction error of hitting point when the vehicle entrances the radar coverage, and the second one is carried out in the intercept zone to increase the maneuvering overload. The two maneuvers are the combat of the glider to the early warning system and the intercept system respectively, which can effectively enhance the penetration performance with less energy consumption.

As modular multilevel converter(MMC) requires a large number of sensors to measure capacitor voltages, reducing the number of sensors for MMC has become an emerging topic. One of the technical challenges for reduced-voltage-sensor-based MMC operated with NLM is to eliminate the overvoltage that occurred on submodules. In order to solve this problem, a capacitor overvoltage elimination strategy for reduced-voltage-sensor-based MMC is proposed in this paper. The overvoltage elimination is consists of pre-measurement and in-process measurement of capacitor voltage, which is to obtain the actual value of submodule capacitor voltage so that to sort submodule capacitor voltages in the correct sequence. In this way, the submodules with excessively high voltage or with overvoltage trends can be selected for discharging until their voltages reach the normal level. Therefore, the overvoltage that occurred on submodules can be eliminated. A 31-level single-phase MMC simulation model is performed in MATLAB/SIMULINK, and a 9-level one is constructed in an experimental laboratory. Both the simulation and experimental results verify the effectiveness of the proposal even in the situation of capacitance parameter deviation.

A rapid entry trajectory planning algorithm for hypersonic glide vehicles is presented in this paper, and the avoidance of no-fly zones with large cross-range is achieved. The highly-constrained entry trajectory generation mission is accomplished using an adjustable angle of attack and bank, instead of a nominal angle of attack and reversal logic of bank angle. In this way, the maneuvering capability of the vehicle is greatly improved. Moreover, as no reversal of bank angle exists in the whole flight, the control command is easier to follow. Firstly, longitudinal entry corridor with an adjustable angle of attack is built up. The drag acceleration profile is represented as five piecewise affine functions of the energy, which are adjusted to meet the requirements of the trajectory length and lateral maneuvering capability. Secondly, based on the quasi-equilibrium glide condition (QEGC), the maximum and minimum boundary of the lateral lift-to-drag corridor corresponding to the current drag acceleration profile is approximated, and the lateral profile is represented as an interpolation result of the boundaries. Finally, the parameters of longitudinal and lateral profile are found by the Newton iteration scheme with the help of a reduced order system. A combined proportional integral derivative (PID) tracker is also designed to follow the drag and heading angle profile. The approach is tested using the Common Aero Vehicle model. Simulation results demonstrate that the generated entry trajectories can avoid no-fly zone with a large cross-range and achieve the terminal conditions while satisfying all the complex path constraints.

An entry trajectory planning algorithm that generates flyable trajectories satisfying multiple no-fly zones and other path and terminal constraints is presented. The algorithm divides the entry trajectory into initial and glide phases. In the initial phase, the maximum value of heating rate is controlled accurately as the altitude of the quasi-equilibrium glide condition (QEGC) transition point is adjusted with a nominal angle of attack and a parameterized bank angle. In the glide phase, a geometry based planning algorithm that relies on the center positions and radius of the multiple no-fly zones, is proposed to calculate the waypoints of the virtual flight path. The magnitude and reversal point of the bank angle in each sub-phase are searched based on a reduced-order lateral system with the predictor-corrector method. The altitude is designed as an analytical function of energy, and the QEGC is employed to analytically solve the remaining state variables. Finally, a linear quadratic regulator is used to test the realization of the 3D trajectory. The algorithm is tested using the common aero vehicle-H model. The results demonstrate that the algorithm can rapidly generate the entry trajectory with multiple no-fly zone constraints and achieve complex flight missions satisfying all flight constraints.

Sequential convex programming method is one of the potential approaches to make trajectory generation onboard. However, the contradiction between the solution accuracy and the computational efficiency restricts its application. To overcome the difficulty, a novel sequential convex programming method based on customized adaptive mesh refinement is proposed in this paper. The main contribution includes two aspects. Firstly, a customized adaptive mesh refinement method is developed. The mesh points are adjusted adaptively based on the linearization error after each iteration, and thus the number of mesh points is changed. Secondly, an unconventional convergence condition is proposed, which can make the sequential convex programming method converges to a feasible solution of the original problem with fewer iterations. Taking the entry trajectory planning problem as an example, the simulation results show that the proposed method can decrease the number of mesh points while ensuring the feasibility of converged solution. Due to the fewer iterations, the computational time to solve the original problem is decreased. As a result, a good balance between solution accuracy and computational efficiency is achieved.

In the tire industry, the Payne effect and hysteresis loss of carbon black (CB) filled rubber under cyclic loading are two kinds of most concerned issues. In this paper, effects of temperature ranging from -30 °C to 50 °C on the Payne effect and hysteresis loss of the CB filled natural rubber are investigated. Experimental results show that the amplitudes of the Payne effect are improved with the decreasing of temperature, especially, at -30 °C, an enhanced Payne effect is observed. The hysteresis loss of the material shows a decreasing tendency with the increasing of temperature. Moreover, the logarithmic storage modulus and loss modulus vs. logarithmic strain amplitude curves at different temperatures can be shifted vertically along the ordinate to get a single smooth one, and the temperature shift factor satisfies the Williams-Landel-Ferry (WLF) equation. This can provide an accelerated method to evaluate the Payne effect at any temperature based on just fewer test data. According to the Kraus model and Payne effect test data, a method to predict the hysteresis loss of the material under different temperatures is developed and validated. The method proposed in the paper can provide an accelerated method to evaluate the Payne effect at arbitrary temperature based on fewer test data, and then accurate estimation of the hysteresis loss of CB filled rubber under cyclic loadings with various temperatures.