Loss of AMIGO2 causes dramatic damage to cardiac preservation after ischemic injury

Background: Recent studies have identified amphoterin-induced gene and open reading frame (AMIGO2). The role of AMIGO2 in tumour research is well-studied, but its role in ischemic heart diseases is seldom reported. In the present study, the role of AMIGO2 in myocardial infarction (MI) is under investigation for the first time. Methods: For in vitro studies, cardiomyocytes (CMs) and endothelial cells (ECs) were isolated from both AMIGO2 knockout (KO) and WT mice. The apoptosis of CMs was tested after 48 h of ischemic stimulation. A proliferation test was implemented after 7 days of normoxic incubation and tube forma­tion on ECs. For in vivo studies, the MI model was built in mice hearts. Echocardiographic evaluation was performed at 3 days and 28 days post-MI, while the hemodynamics test was performed at 28 days post-MI. The histological results of the apoptosis, proliferation, angiogenesis and infarct zone assess­ments were determined using terminal deoxynucleotidyl transferase-mediated dUTP nick end-labelling (TUNEL) assay, Ki67 staining, a-SMA/CD31 immunostain and the Masson-Trichrome method, respectively. The expression changes of the Akt pathway and related proteins were confirmed using both quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot. Results: The present results demonstrated that AMIGO2 deficiency caused more CMs suffering apop­tosis, lower proliferation and less angiogenesis in vitro and in vivo. Weaker cardiac function and larger scar formation were detected in AMIGO2 KO mice, and increased expression of active-caspase-3 and decreased expression of PDK1, p-Akt, Bcl-2/Bax and VEGF occurred. Conclusions: Herein the findings indicate that AMIGO2 deficiency plays an attenuated cardio-pro­tective role in ischemic heart disease via inactivation of the PDK1/Pten/Akt pathway

Preparation and characterization of presulfidation-free MoNiP/Al2O3 catalyst for thiophene hydrodesulfurization

A new type of MoNiP/Al2O3 catalyst for thiophene hydrodesulfurization was prepared by the co-impregnation method, wherein a suitable amount of citric acid was added in the Mo-Ni-P-O impregnation solution. The catalyst exhibits high activity for thiophene hydrodesulfurization under presulfidation- and calcination-free conditions. The catalyst was characterized by N-2 adsorption, temperature-programmed reduction, X-ray photoelectron spectroscopy, infrared spectroscopy, and elemental analysis methods. The effects of citric acid on the structure and activity of the MoNiP/Al2O3 catalyst were studied. The results show that the addition of citric acid weakens the interaction between the active metal components and support, improves dispersion of active metal components on the support surface, and promotes the reduction and sulfidation of the catalyst by sulfur-containing feedstocks. Therefore, the hydrodesulfurization activity of the catalyst is improved

Effect of dynamic hip screw on the treatment of femoral neck fracture in the elderly

Objective:To discuss the indications, surgical procedures, and curative effect of dynamic hip screw (DHS) in the treatment of femoral neck fracture in the elderly. Methods: A retrospective study was conducted to analyse the clinical data of 42 elderly patients who had been treated for femoral neck fracture with DHS in our department between June 2009 and November 2011. There were 21 males and 21 females with a mean age of 68.5 years (range 60-75 years). According to the Garden Classification, there were 19 cases of type II, 21 cases of type III and 2 cases of type IV fractures. By the Singh Index Classification, there were 3 cases of level 2, 19 cases of level 3 and 20 cases of level 4 fractures. The Harris criterion, complications and function recovery after opera- tion were analysed. Results:The average hospitalization time in 42 patients was 11.2 days (range 7-21 days). All patients were followed up for 12-26 months (mean 18 months). No lung infection, deep venous thrombosis or other complications occurred. Partial backing-out of the screws was found in 2 cases. The internal fixation device was withdrawn after fracture healing. Internal fixation cutting was found in 1 case, and he had a good recovery after total hip arthroplasty. The time for fracture healing ranged from 3-6 months (average 4.5 months). According to Harris criterion, 15 cases were rated as excellent, 24 good, 2 fair and 1 poor. The Harris scale was significantly improved from 30.52±2.71 preoperatively to 86.61±2.53 at 6 months postoperatively (P<0.05). Conclusion: DHS, being minimal invasive, allowing early activity and weight-bearing, is advisable for treatment of elderly patients with femoral neck fracture. In addition, it can avoid complications seen in artificial joint replacement. It is especially suitable for patients with mild osteoporosis

Data Redundancy Mitigation in V2X based Collective Perceptions

Collective perception is a new paradigm to extend the limited horizon of individual vehicles. Incorporating with the recent vehicle-2-x (V2X) technology, connected and autonomous vehicles (CAVs) can periodically share their sensory information, given that traffic management authorities and other road participants can benefit from these information enormously. Apart from the benefits, employing collective perception could result in a certain level of transmission redundancy, because the same object might fall in the visible region of multiple CAVs, hence wasting the already scarce network resources. In this paper, we analytically study the data redundancy issue in highway scenarios, showing that the redundant transmissions could result in heavy loads on the network under medium to dense traffic. We then propose a probabilistic data selection scheme to suppress redundant transmissions. The scheme allows CAVs adaptively adjust the transmission probability of each tracked objects based on the position, vehicular density and road geometry information. Simulation results confirm that our approach can reduce at most 60% communication overhead in the meanwhile maintain the system reliability at desired levels

Learn to Make Decision with Small Data for Autonomous Driving: Deep Gaussian Process and Feedback Control

Autonomous driving is a popular and promising field in artificial intelligence. Rapid decision of the next action according to the latest few actions and status, such as acceleration, brake, and steering angle, is a major concern for autonomous driving. There are some learning methods, such as reinforcement learning which automatically learns the decision. However, it usually requires large volume of samples. In this paper, to reduce the sample size, we exploit the deep Gaussian process, where a regression model is trained on small sample datasets and captures the most significant features correctly. Besides, to realize the real-time and close-loop control, we combine the feedback control into the process. Experimental results on the Torcs simulation engine illustrate smooth driving on virtual road which can be achieved. Compared with the amount of training data in deep reinforcement learning, our method uses only 0.34% of its size and obtains similar simulation results. It may be useful for real road tests in the future

Learn to Make Decision with Small Data for Autonomous Driving : Deep Gaussian Process and Feedback Control

Autonomous driving is a popular and promising field in artificial intelligence. Rapid decision of the next action according to the latest few actions and status, such as acceleration, brake, and steering angle, is a major concern for autonomous driving. There are some learning methods, such as reinforcement learning which automatically learns the decision. However, it usually requires large volume of samples. In this paper, to reduce the sample size, we exploit the deep Gaussian process, where a regression model is trained on small sample datasets and captures the most significant features correctly. Besides, to realize the real-time and close-loop control, we combine the feedback control into the process. Experimental results on the Torcs simulation engine illustrate smooth driving on virtual road which can be achieved. Compared with the amount of training data in deep reinforcement learning, our method uses only 0.34\% of its size and obtains similar simulation results. It may be useful for real road tests in the future

An Aptamer-Array-Based Sample-to-Answer Biosensor for Ochratoxin A Detection via Fluorescence Resonance Energy Transfer

Food toxins are a hidden threat that can cause cancer and tremendously impact human health. Therefore, the detection of food toxins in a timely manner with high sensitivity is of paramount importance for public health and food safety. However, the current detection methods are relatively time-consuming and not practical for field tests. In the present work, we developed a novel aptamer-chip-based sample-to-answer biosensor (ACSB) for ochratoxin A (OTA) detection via fluorescence resonance energy transfer (FRET). In this system, a cyanine 3 (Cy3)-labeled OTA-specific biotinylated aptamer was immobilized on an epoxy-coated chip via streptavidin-biotin binding. A complementary DNA strand to OTA aptamer at the 3′-end was labeled with a black hole quencher 2 (BHQ2) to quench Cy3 fluorescence when in proximity. In the presence of OTA, the Cy3-labeled OTA aptamer bound specifically to OTA and led to the physical separation of Cy3 and BHQ2, which resulted in an increase of fluorescence signal. The limit of detection (LOD) of this ACSB for OTA was 0.005 ng/mL with a linearity range of 0.01–10 ng/mL. The cross-reactivity of ACSB against other mycotoxins, ochratoxin B (OTB), aflatoxin B1 (AFB1), zearalenone (ZEA), or deoxynilvalenol (DON), was less than 0.01%. In addition, this system could accurately detect OTA in rice samples spiked with OTA, and the mean recovery rate of the spiked-in OTA reached 91%, with a coefficient of variation (CV) of 8.57–9.89%. Collectively, the ACSB may represent a rapid, accurate, and easy-to-use platform for OTA detection with high sensitivity and specificity