Prognostic Significance of miR-181b and miR-21 in Gastric Cancer Patients Treated with S-1/Oxaliplatin or Doxifluridine/Oxaliplatin

Background: The goal of this study is to evaluate the effectiveness of S-1/Oxaliplatin vs. Doxifluridine/Oxaliplatin regimen and to identify miRNAs as potential prognostic biomarkers in gastric cancer patients. The expression of candidate miRNAs was quantified from fifty-five late stage gastric cancer FFPE specimens. Experimental Design: Gastric cancer patients with KPS>70 were recruited for the trial. The control group was treated with 400 mg/twice/day Doxifluridine plus i.v. with Oxaliplatin at 130 mg/m 2/first day/4 week cycle. The testing group was treated with S-1 at 40 mg/twice/day/4 week cycle plus i.v. with Oxaliplatin at 130 mg/m 2/first day/4 week cycle. Total RNAs were extracted from normal and gastric tumor specimens. The levels of miRNAs were quantified using real time qRT-PCR expression analysis. Results: The overall objective response rate (CR+PR) of patients treated with S-1/Oxaliplatin was 33.3% (CR+PR) vs. 17.6% (CR+PR) with Doxifluridine/Oxaliplatin for advanced stage gastric cancer patients. The average overall survival for patients treated with S-1/Oxaliplatin was 7.80 month vs. 7.30 month with patients treated with Doxifluridine/Oxaliplatin. The expression of miR-181b (P = 0.022) and miR-21 (P = 0.0029) was significantly overexpressed in gastric tumors compared to normal gastric tissues. Kaplan-Meier survival analysis revealed that low levels of miR-21 expression (Log rank test, hazard ratio: 0.17, CI = 0.06-0.45; P = 0.0004) and miR-181b (Log rank test, hazard ratio: 0.37, CI = 0.16-0.87; P = 0.018) are closely associated with better patient's overall survival for both S-1 and Doxifluridine based regimens. Conclusion: Patients treated with S-1/Oxaliplatin had a better response than those treated with Doxifluridine/Oxaliplatin. miR-21 and miR-181b hold great potential as prognostic biomarkers in late stage gastric cancer. © 2011 Jiang et al

Design of pH-Responsive Polymer Monolith Based on Cyclodextrin Vesicle for Capture and Release of Myoglobin

β-Cyclodextrin vesicles (CDVs) were first introduced into the polymer monolith to prepare a pH-responsive adsorption material and used for capture and release of a cardiac biomarker, myoglobin (Myo). SH-CDV was decorated with adamantane-modified SH-octapeptide to enhance the encapsulation and release rates of Myo. Afterward, SH-CDV was introduced into the polymer monolith via click reaction to produce a pH-responsive monolith. Combining with the mass spectrometry detection, the CDV-based pH-responsive monolith was used for the enrichment of Myo glycopeptides from the mixture of glycopeptides and nonglycoprotein (bovine serum albumin) tryptsin digests reach up to 1:10 000. A limit of detection of 0.1 fmol was obtained for Myo glycopeptides in the blood sample, indicating the high sensitivity of the method. The prepared CDV-based hybrid monolith demonstrated itself to be a promising material for capture of glycoproteins in complex samples, which provides an efficient strategy for the identification and discovery of biomarkers of acute myocardial infarction

Self-Assembling Glutamate-Functionalized Cyclodextrin Molecular Tube for Specific Enrichment of N‑Linked Glycopeptides

Cyclodextrin molecular tube (CDMT), a new comer of cyclodextrin family, possesses large and hydrophilic outer area and stable structure. Its development and applications remain highly desired, especially in the field of separation and enrichment. Herein, we developed a CDMT-based enrichment platform focusing on the specific capture of glycopeptides. To enhance the hydrophilicity of CDMT, it was functionalized with glutamate (glu). The prepared gluCDMT exhibited large hydrophilic surface, high stability, and good acidic/alkalic resistance. A solid monolithic support was employed to immobilize gluCDMT by a host–guest self-assembly synthetic strategy, which did not occupy the surface hydrophilic sites. The gluCDMT-based monolith exhibited high binding capacity (∼50 mg g^–1), good ability to capture glycopeptides (23 HRP glycopeptides and 28 IgG glycopeptides), and high selectivity (horseradish peroxidase/bovine serum albumin = 1:10 000). Moreover, the developed platform was successfully applied to analyze glycopetides in acute myelogenous leukemia cell lysate and human serum samples

UAV Autonomous Tracking and Landing Based on Deep Reinforcement Learning Strategy

Unmanned aerial vehicle (UAV) autonomous tracking and landing is playing an increasingly important role in military and civil applications. In particular, machine learning has been successfully introduced to robotics-related tasks. A novel UAV autonomous tracking and landing approach based on a deep reinforcement learning strategy is presented in this paper, with the aim of dealing with the UAV motion control problem in an unpredictable and harsh environment. Instead of building a prior model and inferring the landing actions based on heuristic rules, a model-free method based on a partially observable Markov decision process (POMDP) is proposed. In the POMDP model, the UAV automatically learns the landing maneuver by an end-to-end neural network, which combines the Deep Deterministic Policy Gradients (DDPG) algorithm and heuristic rules. A Modular Open Robots Simulation Engine (MORSE)-based reinforcement learning framework is designed and validated with a continuous UAV tracking and landing task on a randomly moving platform in high sensor noise and intermittent measurements. The simulation results show that when the moving platform is moving in different trajectories, the average landing success rate of the proposed algorithm is about 10% higher than that of the Proportional-Integral-Derivative (PID) method. As an indirect result, a state-of-the-art deep reinforcement learning-based UAV control method is validated, where the UAV can learn the optimal strategy of a continuously autonomous landing and perform properly in a simulation environment

Flower-like C@SnOX@C hollow nanostructures with enhanced electrochemical properties for lithium storage

Hollow nanostructures have attracted considerable attention owing to their large surface area, tunable cavity, and low density. In this study, a unique flower-like C@SnOX@C hollow nanostructure (denoted as C@SnOX@C-1) was synthesized through a novel one-pot approach. The C@SnOX@C-1 had a hollow carbon core and interlaced petals on the shell. Each petal was a SnO2 nanosheet coated with an ultrathin carbon layer similar to 2 nm thick. The generation of the hollow carbon core, the growth of the SnO2 nanosheets, and the coating of the carbon layers were simultaneously completed via a hydrothermal process using resorcinol-formaldehyde resin-coated SiO2 nanospheres, tin chloride, urea, and glucose as precursors. The resultant architecture with a large surface area exhibited excellent lithium-storage performance, delivering a high reversible capacity of 756.9 mA.h.g(-1) at a current density of 100 mA.g(-1) after 100 cycles

A Method for Detecting Dynamic Mutation of Complex Systems Using Improved Information Entropy

In this study, a nonlinear analysis method called improved information entropy (IIE) is proposed on the basis of constructing a special probability mass function for the normalized analysis of Shannon entropy for a time series. The definition is directly applied to several typical time series, and the characteristic of IIE is analyzed. This method can distinguish different kinds of signals and reflects the complexity of one-dimensional time series of high sensitivity to the changes in signal. Thus, the method is applied to the fault diagnosis of a rolling bearing. Experimental results show that the method can effectively extract the sensitive characteristics of the bearing running state and has fast operation time and minimal parameter requirements

Construction of point-line-plane (0-1-2 dimensional) Fe2O3-SnO2/graphene hybrids as the anodes with excellent lithium storage capability

The assembly of hybrid nanomaterials has opened up a new direction for the construction of high-performance anodes for lithium-ion batteries (LIBs). In this work, we present a straightforward, eco-friendly, one-step hydrothermal protocol for the synthesis of a new type of FeO-SnO/graphene hybrid, in which zero-dimensional (0D) SnO nanoparticles with an average diameter of 8 nm and one-dimensional (1D) FeO nanorods with a length of ~150 nm are homogeneously attached onto two-dimensional (2D) reduced graphene oxide nanosheets, generating a unique point-line-plane (0D-1D-2D) architecture. The achieved FeO-SnO/graphene exhibits a well-defined morphology, a uniform size, and good monodispersity. As anode materials for LIBs, the hybrids exhibit a remarkable reversible capacity of 1,530 mA·g at a current density of 100 mA·g after 200 cycles, as well as a high rate capability of 615 mAh·g at 2,000 mA·g. Detailed characterizations reveal that the superior lithium-storage capacity and good cycle stability of the hybrids arise from their peculiar hybrid nanostructure and conductive graphene matrix, as well as the synergistic interaction among the components. [Figure not available: see fulltext.

Reservoir Overpressure in the Mahu Sag, Northwestern Junggar Basin, China: Characteristics and Controlling Factors

Reservoirs with overpressure are of great importance for petroleum exploration where commercial production can be usually obtained. Studying the distribution characteristics and controlling factors of reservoir overpressure is crucial for further petroleum exploration. In this study, we investigate the vertical and planar distribution of reservoir overpressure in the Mahu sag, northwestern Junggar basin by analyzing measured pressure data from well testing of oil reservoirs. In the Baikouquan-Jiamuhe Formation, reservoir overpressure is widely distributed, and the pressure coefficient increases from the margin to the center of the sag and generally increases with the increasing altitude. Crossplot analysis of density and velocity in the Triassic strata and Permian Fengcheng Formation is conducted to further investigate the influence of undercompaction in the Mahu sag for the first time. The result suggests that undercompaction has little influence on reservoir overpressure, whereas fluid charging may play a vital role in the development of overpressure. Our research further conducted the analyses of distribution of source rocks and oil-source correlation. The results further confirmed that hydrocarbon generates from the Fengcheng Formation and charges into other reservoirs, suggesting that hydrocarbon generation and fluid charging are the main mechanism of reservoir overpressure