Chemical composition of n-BuOH extract of Potentilla anserina L. and its protective effect of EAhy926 endothelial cells under hypoxia

The protective role of n-BuOH extract of Potentilla anserina roots was measured by MTT method and colorimetric method on human umbilical vein endothelial cells (EAhy926) under hypoxia injury. The extract tested (3 mg/mL, 1.5 mg/mL) remarkably increased cell viability, the activity of superoxide dismutase (SOD) and the concentration of nitrogen monoxidum (NO), and at same time reduced the release of lactate dehydrogenase (LDH) and endothelin (ET-1) in cells during hypoxia injury. From this extraction, five compounds were isolated and determined as adenosine (1), daidzin (2), puerarin (3), 3'- methoxypuerarin (4) and daidzein 8-C-apiosyl glucoside (5) on the basis of physico-chemical properties and spectroscopic analysis, including 1D- and 2D-NMR spectral data. Compound 2-5 were isolated from genus Potentilla for the first time. Compound 1 was first isolated from the title plant.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Exploring the pathogenesis of colorectal carcinoma complicated with hepatocellular carcinoma via microarray data analysis

Background: Despite the increasing number of research endeavors dedicated to investigating the relationship between colorectal carcinoma (CRC) and hepatocellular carcinoma (HCC), the underlying pathogenic mechanism remains largely elusive. The aim of this study is to shed light on the molecular mechanism involved in the development of this comorbidity.Methods: The gene expression profiles of CRC (GSE90627) and HCC (GSE45267) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) of psoriasis and atherosclerosis, three kinds of analyses were performed, namely, functional annotation, protein‐protein interaction (PPI) network and module construction, and hub gene identification, survival analysis and co-expression analysis.Results: A total of 150 common downregulated differentially expressed genes and 148 upregulated differentially expressed genes were selected for subsequent analyses. The significance of chemokines and cytokines in the pathogenesis of these two ailments is underscored by functional analysis. Seven gene modules that were closely connected were identified. Moreover, the lipopolysaccharide-mediated signaling pathway is intricately linked to the development of both diseases. Finally, 10 important hub genes were identified using cytoHubba, including CDK1, KIF11, CDC20, CCNA2, TOP2A, CCNB1, NUSAP1, BUB1B, ASPM, and MAD2L1.Conclusion: Our study reveals the common pathogenesis of colorectal carcinoma and hepatocellular carcinoma. These common pathways and hub genes may provide new ideas for further mechanism research

Microbial biotechnology approaches for conversion of pineapple waste in to emerging source of healthy food for sustainable environment

One of the most significant and difficult jobs in food sustainability, is to make use of waste in the vegetable and fruit processing sectors. The discarded fruits along with their waste materials, is anticipated to have potential use for further industrial purposes via extraction of functional ingredients, extraction of bioactive components, fermentation. As a result of its abundant availability, simplicity and safe handling, and biodegradability, pineapple waste is now the subject of extensive research. It is regarded as a resource for economic development. This vast agro-industrial waste is being investigated as a low-cost raw material to produce a variety of high-value-added goods. Researchers have concentrated on the exploitation of pineapple waste, particularly for the extraction of prebiotic oligosaccharides as well as bromelain enzyme, and as a low-cost source of fibre, biogas, organic acids, phenolic antioxidants, and ethanol. Thus, this review emphasizes on pineapple waste valorisation approaches, extraction of bioactive and functional ingredients together with the advantages of pineapple waste to be used in many areas. From the socioeconomic perspective, pineapple waste can be a new raw material source to the industries and may potentially replace the current expensive and non-renewable sources. This review summarizes various approaches used for pineapple waste processing along with several important value-added products gained which could contribute towards healthy food and a sustainable environment

Improved Prediction Model of the Friction Error of CNC Machine Tools Based on the Long Short Term Memory Method

Friction is one of important factors that cause contouring errors, and the friction error is difficult to predict because of its nonlinearity. In this paper, a prediction model of the friction error of a servo system is proposed based on the Long Short-Term Memory method (LSTM). Firstly, the transfer function is used to predict the position of the servo system, and then the prediction error of the transfer function is obtained. Secondly, the nonlinear friction error is extracted and predicted by a LSTM network. Finally, the accurate tracking error can be predicted by the proposed combined model. The experimental results show that the proposed model can improve the prediction accuracy of tracking errors dramatically

Improved Prediction Model of the Friction Error of CNC Machine Tools Based on the Long Short Term Memory Method

Friction is one of important factors that cause contouring errors, and the friction error is difficult to predict because of its nonlinearity. In this paper, a prediction model of the friction error of a servo system is proposed based on the Long Short-Term Memory method (LSTM). Firstly, the transfer function is used to predict the position of the servo system, and then the prediction error of the transfer function is obtained. Secondly, the nonlinear friction error is extracted and predicted by a LSTM network. Finally, the accurate tracking error can be predicted by the proposed combined model. The experimental results show that the proposed model can improve the prediction accuracy of tracking errors dramatically

Development and Application of a Tandem Force Sensor

In robot teaching for contact tasks, it is necessary to not only accurately perceive the traction force exerted by hands, but also to perceive the contact force at the robot end. This paper develops a tandem force sensor to detect traction and contact forces. As a component of the tandem force sensor, a cylindrical traction force sensor is developed to detect the traction force applied by hands. Its structure is designed to be suitable for humans to operate, and the mechanical model of its cylinder-shaped elastic structural body has been analyzed. After calibration, the cylindrical traction force sensor is proven to be able to detect forces/moments with small errors. Then, a tandem force sensor is developed based on the developed cylindrical traction force sensor and a wrist force sensor. The robot teaching experiment of drawer switches were made and the results confirm that the developed traction force sensor is simple to operate and the tandem force sensor can achieve the perception of the traction and contact forces

A New Fusion Fault Diagnosis Method for Fiber Optic Gyroscopes

The fiber optic gyroscope (FOG) is a high precision inertial navigation device, and it is necessary to ensure its reliability for effective use. However, the extracted fault features are easily distorted due to the interference of vibrations when the FOG is in operation. In order to minimize the influence of vibrations to the greatest extent, a fusion diagnosis method was proposed in this paper. It extracted features from fault data with Fast Fourier Transform (FFT) and wavelet packet decomposition (WPD), and built a strong diagnostic classifier with a sparse auto encoder (SAE) and a neural network (NN). Then, a fusion neural network model was established based on the diagnostic output probabilities of the two primary classifiers, which improved the diagnostic accuracy and the anti-vibration capability. Then, five fault types of the FOG under random vibration conditions were established. Fault data sets were collected and generated for experimental comparison with other methods. The results showed that the proposed fusion fault diagnosis method could perform effective and robust fault diagnosis for the FOG under vibration conditions with a high diagnostic accuracy

A New Fusion Fault Diagnosis Method for Fiber Optic Gyroscopes

The fiber optic gyroscope (FOG) is a high precision inertial navigation device, and it is necessary to ensure its reliability for effective use. However, the extracted fault features are easily distorted due to the interference of vibrations when the FOG is in operation. In order to minimize the influence of vibrations to the greatest extent, a fusion diagnosis method was proposed in this paper. It extracted features from fault data with Fast Fourier Transform (FFT) and wavelet packet decomposition (WPD), and built a strong diagnostic classifier with a sparse auto encoder (SAE) and a neural network (NN). Then, a fusion neural network model was established based on the diagnostic output probabilities of the two primary classifiers, which improved the diagnostic accuracy and the anti-vibration capability. Then, five fault types of the FOG under random vibration conditions were established. Fault data sets were collected and generated for experimental comparison with other methods. The results showed that the proposed fusion fault diagnosis method could perform effective and robust fault diagnosis for the FOG under vibration conditions with a high diagnostic accuracy