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Additional file 4. The sequence variations of positive selection haplotype in clones of high sucrose content (HS) and low sucrose content (LS).

Additional file 1. The amplification of SPSB gene for 18 germplasms, M: markers, the size is 5000bp, 3000bp, 2000bp, 1500bp, 1000bp, 750bp, 500bp, 250bp, 100bp;1: Badila, 2: India1, 3: Guangze bamboo cane, 4: katha, 5: YZ02-588, 6: Dezhe93-88, 7: YZ14-401, 8: YZ14-405, 9: YT00-236, 10: YZ14-407, 11: GT12, 12: YZ94-343, 13: YZ14-402, 14: YZ14-403, 15: YZ14-404, 16: YZ14-406, 17: YZ14-408, 18: ROC22.

Category: Ankle Introduction/Purpose: Fixation of syndesmosis disruption with metal screws remains a frequent and efficacious treatment modality. Screw breakage remains a complication seen in many patients following metal fixation. Overtime physiologic rotation or the tibia and fibula can lead to bone erosion and pain in patients with screw breakage. The purpose of this study is to compare patients with syndesmosis screw breakage and patients with intact screws based surgically controlled variables. Methods: A retrospective analysis of patients who underwent syndesmotic screw fixation from 2008 - 2020 was performed. Ninety-seven patients were found to have syndesmosis screw breakage, of which 88 met inclusion criteria. A control group of patients without syndesmosis screw breakage was selected at random and analyzed until 88 patients met inclusion criteria. The number of screws used, width, length, fracture type and number of cortices were all collected. Further analysis included radiographic measurement syndesmosis screw angle and height of placement above the tibial plafond. A regression analysis was performed to compare to the two groups, including a separate analysis comparing unbroken screws within syndesmosis screw breakage cohort versus their broken screws, as this provided an absolute control group. A stratified analysis of screw placement and angle was also performed based on standard deviation. Results: The average screw width in the breakage group was 3.67 (SD =.38) and 4.06 (SD =0.04) in the intact group (P = 20mm above the tibial plafond, compared to 64.0% in the control group. Most screws were placed at angle > 82 degrees relative to the tibial plafond; 76% (n =92) of broken screws and 81.2% (n=211) of intact screws). Decreased screw width (P = 20mm above the tibial plafond (P =Conclusion: Metal screw fixation remains an efficacious treatment method of syndesmotic disruption. Despite extensive research the cause of syndesmosis screw breakage and the necessity of screw removal remains without consensus. The is study aims to analyze surgical variables in attempt to find correlation with screw breakage. An increased BMI was seen to predispose to screw breakage. Placement of the syndesmosis screw

Category: Ankle Introduction/Purpose: Metal screw fixation remains a common and effective way to repair syndesmotic injuries. They are inexpensive, familiar, and provide superior torsional resistance to sagittal translation compared to other fixation modalities. Symptomatic screw breakage is one of the most common complications of metal screw fixation. Routine removal remains unsupported by literature. Consequently, many patients retain broken screws and are at risk for pain; particularly when the breakage occurs within the tibia or the fibula. The purpose of this study is to analyze outcomes of patients with intact syndesmosis screws and those with syndesmosis screw breakage. Methods: A total of 176 patients (260 screws) with syndesmotic disruption treated with syndesmosis screw fixation were included in the study. Half of the patients had broken syndesmosis screws while the other half had intact syndesmosis screws. Basic patient demographic data was collected including BMI, age, and gender. Further collection of patient comorbidities was compiled using two comorbidity indices (Charlson, Elixhauser). Outcome analysis included revision rate, removal secondary to pain, complication rate, range of motion deficits, and patient pain scores. In patients who had their screws removed, further analysis was conducted to compare strength, range of motion deficits, complication rates, pain scores and revision rates between the intact and breakage group. Results: BMI averages of 33.64 (SD=8.77) and 30.64 (SD=6.76) were seen in breakage and intact group, respectively. A complication rate of 24.0% was seen the breakage group versus 36.1% in the control group. Revision rates of 12.4% and 20.10% were seen in the breakage and control group, respectively. Range of motion deficits were seen in 50.2% in the intact group and 39.7% in the breakage group (P = 0.2253). Removal secondary to pain occurred in 60.30% (n = 73) in the broken group compared to 24.5% (n = 34) in the control group. Decreased complication rate (P =.002), increased BMI (P = Conclusion: Metal screw fixation remains a popular treatment of syndesmotic disruption. Many patients retain broken screws and intact screws which can be associated with future complications. Patients with syndesmosis screw breakage are a high comorbid population. Syndesmosis screw breakage is associated with decreased complication rates, increased BMI, and increased risk of eventual removal secondary to pain. Range of motion deficits were seen more commonly when in patients with intact syndesmosis screws. Additionally, revisions rates were higher in the intact group compared to the breakage group. Following screw removal, the intact group had a non-statistically significant increase in complication rate and range.

The popularity of encryption method brings a great challenge to malware traffic identification. Traditional classes defined by expert experience are usually classified based on the host behaviors of malware, such as banking malware or ransomware, which are often irrelevant to its communication traffic behaviors. It leads to the fact that the boundaries of traffic feature dataset of different malware classes are fuzzy and make these traditional classes unhelpful for classification based on traffic features. Meanwhile, traditional machine learning-based encrypted malware traffic identification methods, such as using the multi-classification supervised learning model, are inefficient both in model training and detection, and its detection accuracy cannot meet the demand. In this paper, we propose a distance-based method, which utilizes unsupervised learning algorithm Gaussian mixture model (GMM) and ordering points to identify the clustering structure (OPTICS) to calculate the Distance between malwares and make use of the Distance to define the new malware class called FClass. Then, a set of models are trained by XGBoost algorithm to build an identification framework based on the FClass. The performance of the proposed method has been evaluated by comparing it with the other four methods. The results show that the proposed distance-based method is more efficient and accurate.