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Background Intervertebral disc degeneration (IVDD) is a well-known cause of lower back pain, which is induced by multiple factors including increased apoptosis and decreased survival of nucleus pulposus cells. In this study, we evaluate the effect and potential mechanism of miR-660 on the nucleus pulposus cells apoptosis induced by TNF-α. Methods First, we collected tissue of nucleus pulposus from IVDD and healthy controls. General characteristic of the IVDD and healthy control was also collected. And, we also collected nucleus pulposus cells that stimulated by TNF-α or control. miRNA microarray was performed to identify the differentially expressed miRNAs. Apoptosis rate and miR-660 relative expression was measured after stimulated with different concentration of TNF-α to identify the optimal concentration of TNF-α. Second, we successfully constructed antigomiR-660 to block the miR-660 expression in nucleus pulposus cells and then stimulated with TNF-α (100 ng/ml, 12 h). The apoptosis rates and relative protein expression were then measured again. The target association between miR-660 and SAA1 was confirmed by dual-luciferase reporter. Results There was no significant difference between the age (IVDD: 39 ± 10 years, healthy controls: 36 ± 7 years), BMI and sex between IVDD and healthy controls. Microarray analysis found that miR-660 was significantly up-regulated in IVDD and TNF-α treated groups, which was further identified by PCR. We found that the rate of apoptosis and miR-660 expression increased with TNF-α concentration increased. Finally, TNF-a with 100 ng/ml was used for further experiment. Compared with TNF-α group, TNF-α + antigomiR-660 could significantly down-regulated the apoptosis rate and relative protein (c-Caspase3 and c-Caspase7). Dual-luciferase reporter revealed that miR-660 could directly binding to the SAA1 at 80–87 sites. Compared with TNF-α alone group, TNF-α + antigomiR-660 significantly up-regulated the SAA1 expression (P Conclusion These results indicated that knockdown of miR-660 protected the nucleus pulposus from apoptosis that induced TNF-α via up-regulation of SAA1. Further studies should focus on the role of miR-660 in protecting IVDD in vivo.

Background: To investigate the clinical effects of stage I repair of skin and soft tissue defects using lateral femoral perforator free flap in pilon fracture surgery. Methods: Fifteen cases of pilon fractures were selected from our hospital between April 2013 and January 2017. There were 8 cases of 43-C1, 4 cases of 43-C2 and 3 cases of 43-C3 fractures, as defined by the Miller AO classification. In all cases, severe contusion of skin and soft tissue around the fracture, skin darkening and necrosis, and tissue edema during surgery, led to difficult closure of incision. The skin and soft tissue defects were repaired at stage I by ipsilateral lateral femoral perforator free flap. Results: Venous crisis occurred in one case, while the other 14 cases survived. During the 6–18 months of follow-up, the function of ankles was satisfactory and the wearing of shoes was not affected by the abnormal foot. The flap color and texture were normal and the protective sensation of the flap recovered. Only a linear scar remained at the donor site and no muscle adhesion occurred. Conclusions: Stage I repair of skin and soft tissue defects using lateral femoral perforator free flap in pilon fracture surgery apparently decreased postoperative infection and protected the blood supply around the fracture. Hence, it was an effective repair method.

How to detect Botnet has become a very important problem in security network. The existent detection methods based on network traffic and host behaviors cant handle the emergency Botnets. In this paper we present an optimized method to analyze the similarity and time period of Botnets behaviors. In the end, our method gets an effective result. Our method uses the IDS-like architecture, which develops six specific components to detect six important Botnets abnormal behaviors. And it builds correlation rules to calculate match score. Through the experiments described in the paper, we can see that our method can not only detect already known Botnets precisely, but also detect unknown Botnets to some extent. The experiments prove that our method is effective and it has some advantages compared with other methods. At last, the paper proposes the future direction and the points that need to be improved.