HSP70: a promising target for laryngeal carcinoma radiaotherapy by inhibiting cleavage and degradation of nucleolin

Previous studies have shown that heat shock proteins (HSPs) were upregulated in various types of tumors and were associated with histological grade, recurrence and metastasis of malignant tumors. In this study, we investigated whether heat shock protein 70 kDa (HSP70) was associated with histological grade of laryngeal squamous cell carcinomas (LSCC). We also determine the role of HSP70 in LSCC radiation resistance using a laryngeal carcinoma xenograft model by antisense HSP70 RNA technique. Immunohistochemistry data showed that HSP70 was detected in 96% of LSCC tissues (48 out of 50). The expression level of HSP70 was significantly lower in early stage of LSCC than that in late stage (P = 0.015). Radiation treatment result showed that the volumes and weights of implantation tumors in the group injected with antisense HSP70 oligos were significantly reduced comparing to the group injected with random oligos(p < 0.05). In addition, cleavage and degradation of tumor nucleolin in antisense HSP70 oligos injection group was significantly higher than that in random oligos injection group. Our result suggested that HSP70 may play a role in LSCC radiotherapy resistance by inhibiting cleavage and degradation of nucleolin

The Ninth Visual Object Tracking VOT2021 Challenge Results

acceptedVersionPeer reviewe

Application of PCA-K-means++ combination model to construction of light vehicle driving conditions in intelligent traffic

The construction of typical driving condition of vehicles in line with the actual road traffic conditions in China requires the selection of the same vehicle for two months to collect driving data and the obtention of 496000 driving condition data of light vehicles. The sample data are preprocessed by using multivariate statistical theory and MATLAB. After the elimination of abnormal data, the effective data are extracted before being divided into 3020 kinematic segments. Then, it takes a principal component analysis to reduce the dimension of the characteristic parameter matrix. Through K-means++ clustering algorithm, the six principal components obtained by principal component analysis are clustered into two categories. Then the typical kinematic segments are selected from various fragment libraries by using correlation coefficient method, so as to construct a typical driving condition of the vehicles in a certain city. With the application of PCA-K-means and PCA-K-means++ clustering algorithm, a driving condition curve with a duration of 1200s is constructed before its effectiveness and accuracy being compared and analyzed. The results show that the error rate of driving condition between sample data and driving condition constructed by PCA-K-mean++ clustering algorithm is less than 6 % and the error rate of average speed and acceleration standard deviation is less than 1 %. The correlation degree between working condition curve constructed by PCA-K-means ++ clustering algorithm and sample data is increased by 4.08 %. The proportion of deceleration time and idle time in vehicle driving state is obviously different, which indicates that PCA-K-means++ is a better way to solve the problem and the clustering algorithm can effectively construct the driving condition curve of light vehicles suitable for local cities

Textual generalization method of accident risk factors in oil & gas storage and transportation enterprises based on CW-AGNES

The textual generalization of accident risk factors is an important step to establish the knowledge graph of accident risk factors of the oil & gas storage and transportation enterprises. In order to solve the problem of semantic representation limitations and word segmentation errors for the textual generalization of risk factors accumulated in the production process of oil & gas storage and transportation enterprises by existing event text generalization methods, a textual generalization method of accident risk factors based on the Char-Word feature based AGNES (CW-AGNES) was put forward according to the complicated and changeable text expression of safety management. Definitely, the character feature and binary word feature vectors of the oil & gas storage and transportation enterprises were obtained by Word2vec method. The text of accident risk factors is vectorized according to the pre-trained word vector model. Then, the char-word features of the text are added with the agglomerative nesting method, and the error caused by word segmentation can be reduced on the basis of retaining the semantic information of the words, so as to realize the generalization of the risk factor text. Specifically, the CW-AGNES method was applied to the actual safety management texts of the oil & gas storage and transportation enterprises. Meanwhile, comparison was made with other generalization methods. The results show that: The CW-AGNES method has a better generalization effect with 2.44%–5.74% improvement in quantitative evaluation indicators such as AMI, ARI, V-Measure and FMI. Therefore, the proposed method could provide support for the construction of accident risk knowledge graph in the field of oil & gas storage and transportation

Homo-oxidized HSPB1 protects H9c2 cells against oxidative stress via activation of KEAP1/NRF2 signaling pathway

Summary: Several heat shock proteins are implicated in the endogenous cardioprotective mechanisms, but little is known about the role of heat shock protein beta-1 (HSPB1). This study aims to investigate the oxidation state and role of HSPB1 in cardiomyocytes undergoing oxidative stress and underlying mechanisms. Here, we demonstrate that hydrogen peroxide (H2O2) promotes the homo-oxidation of HSPB1. Cys137 residue of HSPB1 is not only required for it to protect cardiomyocytes against oxidative injury but also modulates its oxidation, phosphorylation at Ser15, and distribution to insoluble cell components after H2O2 treatment. Moreover, Cys137 residue is indispensable for HSPB1 to interact with KEAP1, thus regulating its oxidation and intracellular distribution, subsequently promoting the nuclear translocation of NRF2, and increasing the transcription of GLCM, HMOX1, and TXNRD1. Altogether, these findings provide evidence that Cys137 residue is indispensable for HSPB1 to maintain its redox state and antioxidant activity via activating KEAP1/NRF2 signaling cascade in cardiomyocytes

Manipulation of Si Doping Concentration for Modification of the Electric Field and Carrier Injection for AlGaN-Based Deep-Ultraviolet Light-Emitting Diodes

Electron overflow is one of the key factors that limit the quantum efficiency for AlGaN-based deep-ultraviolet light-emitting diodes. In this work, we report a numerical study to improve the electron injection efficiency by manipulating the electric field profiles via doping the n-Al0.60Ga0.40N electron source layer with different concentrations and reveal the physical mechanism of the Si doping effect on the electron and the hole injection. By utilizing the appropriate doping concentration, the electric field will reduce the electron drift velocity and, thus, the mean free path. Therefore, a higher electron capture efficiency by the multiple quantum wells (MQWs) and an increase of the hole concentration in the active region can be realized, resulting in an improved radiative recombination rate and an optical output power