BackgroundDigestive cancers are common malignancies worldwide, however there are few effective prognostic markers available. In this study we comprehensively investigated the prognostic significance of ZEB1 and ZEB2 in digestive cancers.MethodsElectronic databases were searched and studies met the selection criteria were included. Study information was recorded and quality assessment was performed according to the REMARK guideline. Hazard ratios and its corresponding 95% confidence intervals were extracted and pooled. Sensitivity analyses, subgroup analyses, cumulative meta-analyses and secondary analyses were also performed to increase the stability and reliability of our results.Results24 cohort studies were included in the study. High ZEB1 and ZEB2 levels predicted poor overall survival, meanwhile high ZEB2 levels predicted poor disease free survival for digestive cancer patients. From subgroup analyses we observed ZEB1 was found to be significantly associated with poor overall survival for patients with pancreatic cancer, gastric cancer and colorectal cancer, while ZEB2 was found to be significantly associated with poor overall survival for patients with hepatocellular carcinoma and gastric cancer. Furthermore, by conducting secondary analyses we confirmed both ZEB1 and ZEB2 played important roles in gastric cancer prediction. In addition, we found high ZEB1 and ZEB2 expression were significantly associated with depth of invasion, lymph node metastasis and TNM stage in digestive cancer patients.ConclusionsThe present study validated the prognostic value and clinicopathological association of ZEB1 and ZEB2 in digestive cancers, especially in gastric cancer.
The limited energy in wireless sensor network has always been a key topic. Most previous studies usually regulate the network loading by periodically directing the data flow to different sinks in order to extend the overall life-time of network and enhance the network availability or data delivery. However, the time and place that an event occurred can not be estimated, thus regular information flow switching may not be able to balance the actual loading of network. Another, multiple paths to sinks for each node are established in the tolerance area defined by a pre-defined difference between the cost, i.e. hop counts away from sinks, of paths to different sinks such that each node in-between multiple sinks can distribute the forwarding burden among the paths to different sinks. Since sending data to a farther sink consumes much more overall energy of network, the gain of data delivery should be evaluated at the sacrifice of energy consumption. In this paper, a quantized model is proposed to evaluate the tradeoff between energy consumption and data delivery under non-uniformly events triggering in network. The tradeoff between network availability and energy consumption would be analyzed and the corresponding simulation results would be included.
A compact optical pickup head in blue wavelength with a single-axial actuator i.e. focusing, for laser thermal lithography was designed, fabricated, and tested. The numerical aperture of the objective lens was 0.85. The linear range of the focus error signal was 3 μm. A planar spring structure for improving the horizontal stability was designed and incorporated into the actuator. We applied a modified push-pull method together with a static Blu-ray re-writable disc to test the horizontal stability of the pickup head. We found that the in-plane jitter of the pickup head in two orthogonal directions were 0.34 nm and 1.59 nm, respectively. We demonstrated an example of applying the pickup head to write an inorganic photo-resist GeSbSnO film, and well-defined pattern was obtained with ~220 nm spot size.
An Extension Taguchi Method (ETM) is proposed on the optimized allocation of equipment capacity for solar cell power generation, wind power generation, full cells, electrolyzer and hydrogen tanks. The ETM is based on the domain knowledge containing the product specifications and allocation levels provided by suppliers and design factors since most of the renewable energy equipment available in the market comes with a specific capacity. A proper orthogonal array is used to collect 18 sets of simulation responses. The extension theory is introduced to determine the correlation function, and factor effects are used to identify the optimized capacity allocation. The hours of power shortage are simulated using Matlab for all capacity allocations at the lowest establishment cost and the optimized capacity allocation of loss of load probability (LOLP). Finally, the extension theory, extension AHP theory, ETM and Analytic Hierarchy Process (AHP) are used to determine the optimized capacity allocation of the system. Results are compared for the above four optimization simulation methods and verify that the proposed ETM surpasses the others on achieving the optimized capacity allocation.
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