Objective: The partial inferior turbinectomy and septoplasty was applied to treat the allergic perennial rhinitis (APR), and to observe the ultrastructure changes of the nasal mucosa before and after the operations. M...Objective: The partial inferior turbinectomy and septoplasty was applied to treat the allergic perennial rhinitis (APR), and to observe the ultrastructure changes of the nasal mucosa before and after the operations. Methods: For 36 cases of research objects diagnosed with APR, the partial inferior turbinectomy and septoplasty was administered. For 6 APR cases among them, the pre- and postoperative observation of anterior nasal mucosa of the inferior turbinate on the same side under the electron microscope was conducted for one year respectively. In addition, their pathological alterations of tissues were also conducted. Results: In the pre-operative observation under the electron microscope, it was found that the nasal mucosae epithelium cells were nude without cilia. The lamina propria had edema, and mesenchyme presented the infiltration of substantial eosinophilic granulocytes, basophilic granulocytes, plasmacytes and mast cells. Additionally, abundant degranulation and vacuolation of cytoplasts were observed. The plentiful glands, duct ectasia, edema and structural changes were also found. Some gland cells had degenerated. After the operation, it was found that the epithelium nudity still existed and the deficiency of cilia was not improved. Only a very small amount of microvilli existed. The edema of lamina propria was improved and eosinophilic granulocytes were rarely observed in mesenchyme. However, the infiltration of basophilic granulocytes, plasmocytes and mast cells was still observed. The particle structure was generally stable and the central crystal was clear without degranulation. Meanwhile, the amount of glands was reduced and the tissue structure tended to be recovered. Overall, the nasal mucosa showed changes as chronic inflammation. Conclusions: For the treatment of APR with the methods presented by our research institution, in one year before and after the operation, ultrastructural changes of inferior turbinate mucosa tissues were observed from the preoperatively pathological changes of typical APR to the chronic inflammation with the primary infiltration of neutrophilic granulocyte and mast cells.展开更多
Diabetes have been shown to cause progressive neuronal injury with pain and numbness via advanced glycation end-products(AGEs)-induced neuronal cell apoptosis;however, the valuable drug targets for diabetic neuropathy...Diabetes have been shown to cause progressive neuronal injury with pain and numbness via advanced glycation end-products(AGEs)-induced neuronal cell apoptosis;however, the valuable drug targets for diabetic neuropathy have been poorly reported so far. In this study, we discovered a natural small-molecule schisandrol A(SolA) with significant protective effect against AGEs-induced neuronal cell apoptosis. ATP6V0D1, a major subunit of vacuolar-type ATPase(V-ATPase) in lysosome was identified as a crucial cellular target of SolA. Moreover, SolA allosterically mediated ATP6V0D1 conformation via targeting a unique cysteine 335 residue to activate V-ATPase-dependent lysosomal acidification.Interestingly, SolA-induced lysosome pH downregulation resulted in a mitochondrial-lysosomal crosstalk by selectively promoting mitochondrial BH3-only protein BIM degradation, thereby preserving mitochondrial homeostasis and neuronal cells survival. Collectively, our findings reveal ATP6V0D1 is a valuable pharmacological target for diabetes-associated neuronal injury via controlling lysosomal acidification, and also provide the first small-molecule template allosterically activating V-ATPase for preventing diabetic neuropathy.展开更多
This paper proposes an anomalous behavior detection model based on cloud computing. Virtual Machines （VMs） are one of the key components of cloud Infrastructure as a Service （laaS）. The security of such VMs is cri...This paper proposes an anomalous behavior detection model based on cloud computing. Virtual Machines （VMs） are one of the key components of cloud Infrastructure as a Service （laaS）. The security of such VMs is critical to laaS security. Many studies have been done on cloud computing security issues, but research into VM security issues, especially regarding VM network traffic anomalous behavior detection, remains inadequate. More and more studies show that communication among internal nodes exhibits complex patterns. Communication among VMs in cloud computing is invisible. Researchers find such issues challenging, and few solutions have been proposed--leaving cloud computing vulnerable to network attacks. This paper proposes a model that uses Software-Defined Networks （SDN） to implement traffic redirection. Our model can capture inter-VM traffic, detect known and unknown anomalous network behaviors, adopt hybrid techniques to analyze VM network behaviors, and control network systems. The experimental results indicate that the effectiveness of our approach is greater than 90%, and prove the feasibility of the model.展开更多
Extracting and analyzing network traffic feature is fundamental in the design and implementation of network behavior anomaly detection methods. The traditional network traffic feature method focuses on the statistical...Extracting and analyzing network traffic feature is fundamental in the design and implementation of network behavior anomaly detection methods. The traditional network traffic feature method focuses on the statistical features of traffic volume. However, this approach is not sufficient to reflect the communication pattern features. A different approach is required to detect anomalous behaviors that do not exhibit traffic volume changes, such as low-intensity anomalous behaviors caused by Denial of Service/Distributed Denial of Service （DoS/DDoS） attacks, Internet worms and scanning, and BotNets. We propose an efficient traffic feature extraction architecture based on our proposed approach, which combines the benefit of traffic volume features and network communication pattern features. This method can detect low-intensity anomalous network behaviors and conventional traffic volume anomalies. We implemented our approach on Spark Streaming and validated our feature set using labelled real-world dataset collected from the Sichuan University campus network. Our results demonstrate that the traffic feature extraction approach is efficient in detecting both traffic variations and communication structure changes. Based on our evaluation of the MIT-DRAPA dataset, the same detection approach utilizes traffic volume features with detection precision of 82.3% and communication pattern features with detection precision of 89.9%. Our proposed feature set improves precision by 94%.展开更多
文摘Objective: The partial inferior turbinectomy and septoplasty was applied to treat the allergic perennial rhinitis (APR), and to observe the ultrastructure changes of the nasal mucosa before and after the operations. Methods: For 36 cases of research objects diagnosed with APR, the partial inferior turbinectomy and septoplasty was administered. For 6 APR cases among them, the pre- and postoperative observation of anterior nasal mucosa of the inferior turbinate on the same side under the electron microscope was conducted for one year respectively. In addition, their pathological alterations of tissues were also conducted. Results: In the pre-operative observation under the electron microscope, it was found that the nasal mucosae epithelium cells were nude without cilia. The lamina propria had edema, and mesenchyme presented the infiltration of substantial eosinophilic granulocytes, basophilic granulocytes, plasmacytes and mast cells. Additionally, abundant degranulation and vacuolation of cytoplasts were observed. The plentiful glands, duct ectasia, edema and structural changes were also found. Some gland cells had degenerated. After the operation, it was found that the epithelium nudity still existed and the deficiency of cilia was not improved. Only a very small amount of microvilli existed. The edema of lamina propria was improved and eosinophilic granulocytes were rarely observed in mesenchyme. However, the infiltration of basophilic granulocytes, plasmocytes and mast cells was still observed. The particle structure was generally stable and the central crystal was clear without degranulation. Meanwhile, the amount of glands was reduced and the tissue structure tended to be recovered. Overall, the nasal mucosa showed changes as chronic inflammation. Conclusions: For the treatment of APR with the methods presented by our research institution, in one year before and after the operation, ultrastructural changes of inferior turbinate mucosa tissues were observed from the preoperatively pathological changes of typical APR to the chronic inflammation with the primary infiltration of neutrophilic granulocyte and mast cells.
基金supported by National Key Research and Development Program of China(Nos.2019YFC1708902 and 2019YFC1711000)National Natural Science Foundation of China(Nos.81973505,81773932 and 82104621).
文摘Diabetes have been shown to cause progressive neuronal injury with pain and numbness via advanced glycation end-products(AGEs)-induced neuronal cell apoptosis;however, the valuable drug targets for diabetic neuropathy have been poorly reported so far. In this study, we discovered a natural small-molecule schisandrol A(SolA) with significant protective effect against AGEs-induced neuronal cell apoptosis. ATP6V0D1, a major subunit of vacuolar-type ATPase(V-ATPase) in lysosome was identified as a crucial cellular target of SolA. Moreover, SolA allosterically mediated ATP6V0D1 conformation via targeting a unique cysteine 335 residue to activate V-ATPase-dependent lysosomal acidification.Interestingly, SolA-induced lysosome pH downregulation resulted in a mitochondrial-lysosomal crosstalk by selectively promoting mitochondrial BH3-only protein BIM degradation, thereby preserving mitochondrial homeostasis and neuronal cells survival. Collectively, our findings reveal ATP6V0D1 is a valuable pharmacological target for diabetes-associated neuronal injury via controlling lysosomal acidification, and also provide the first small-molecule template allosterically activating V-ATPase for preventing diabetic neuropathy.
基金supported by the National Natural Science Foundation of China (No.61272447)the National Key Technologies Research and Development Program of China (No.2012BAH18B05)
文摘This paper proposes an anomalous behavior detection model based on cloud computing. Virtual Machines （VMs） are one of the key components of cloud Infrastructure as a Service （laaS）. The security of such VMs is critical to laaS security. Many studies have been done on cloud computing security issues, but research into VM security issues, especially regarding VM network traffic anomalous behavior detection, remains inadequate. More and more studies show that communication among internal nodes exhibits complex patterns. Communication among VMs in cloud computing is invisible. Researchers find such issues challenging, and few solutions have been proposed--leaving cloud computing vulnerable to network attacks. This paper proposes a model that uses Software-Defined Networks （SDN） to implement traffic redirection. Our model can capture inter-VM traffic, detect known and unknown anomalous network behaviors, adopt hybrid techniques to analyze VM network behaviors, and control network systems. The experimental results indicate that the effectiveness of our approach is greater than 90%, and prove the feasibility of the model.
基金supported by the National Natural Science Foundation of China (No. 61272447)Sichuan Province Science and Technology Planning (Nos. 2016GZ0042, 16ZHSF0483, and 2017GZ0168)+1 种基金Key Research Project of Sichuan Provincial Department of Education (Nos. 17ZA0238 and 17ZA0200)Scientific Research Staring Foundation for Young Teachers of Sichuan University (No. 2015SCU11079)
文摘Extracting and analyzing network traffic feature is fundamental in the design and implementation of network behavior anomaly detection methods. The traditional network traffic feature method focuses on the statistical features of traffic volume. However, this approach is not sufficient to reflect the communication pattern features. A different approach is required to detect anomalous behaviors that do not exhibit traffic volume changes, such as low-intensity anomalous behaviors caused by Denial of Service/Distributed Denial of Service （DoS/DDoS） attacks, Internet worms and scanning, and BotNets. We propose an efficient traffic feature extraction architecture based on our proposed approach, which combines the benefit of traffic volume features and network communication pattern features. This method can detect low-intensity anomalous network behaviors and conventional traffic volume anomalies. We implemented our approach on Spark Streaming and validated our feature set using labelled real-world dataset collected from the Sichuan University campus network. Our results demonstrate that the traffic feature extraction approach is efficient in detecting both traffic variations and communication structure changes. Based on our evaluation of the MIT-DRAPA dataset, the same detection approach utilizes traffic volume features with detection precision of 82.3% and communication pattern features with detection precision of 89.9%. Our proposed feature set improves precision by 94%.
