The development of new technologies has caused computers one of the most popular electronic products. However, there is always a number of people who intend to take advantages of others through attacking others’ computers. To avoid property damage as much as possible, a precise and efficient detection is essential. This work uses the dataset which was generated by combining heartbeat and threat reports collected by Microsoft’ s endpoint protection solution to find out an effective solution. Since the dataset is large and has many categorical variables, reduction of memory and label encoding are used in data cleaning. Further, to handle the dimension problem and improve training efficiency, Chi-square testing is applied, and the top 42 fields are selected. Then, three algorithms (Logistic Regression, KNN and LightGBM) are chosen to build models and results are got respectively. The results show that LightGBM model achieves the best accuracy that AUC reaches 0.720687, and it is the most time-saving way. To the end, according to the feature importance from LightGBM algorithm, this work pick top-three important variables to analyze the underlying causes in the malware attack. One of the results reveals that the computer which has anti-virus software with bugs or pitfalls will suffer more attacks.

Skeletal Class III malocclusion with maxillary deficiency is a severe maxillofacial disease with unclear pathogenic mechanisms. We recruited a Han Chinese family who was clinically diagnosed with skeletal Class III malocclusion and maxillary deficiency. Using whole exome sequencing, a missense variant in ADAMTS2 (NM_014244: c.3506G>T: p.G1169V) was identified and predicted as deleterious by in silico tools. We also found ADAMTS2 variants associated with deficient maxillary development in a cohort. ADAMTS2 expression in HEK293 cells showed significant decrease due to the variant, which was also consistent in dental pulp stem cells from the proband and a healthy control. In the adamts2-knockdown zebrafish model, the length and width of the ethmoid plate, as well as the length of the palatoquadrate became significantly shorter than the control group (p < 0.001), while there was no significant difference in the length and width of the mandible. The expression of Sox3, which was required in early embryonic craniofacial development, was significantly downregulated in the adamts2-knockdown zebrafish embryos. Bioinformatic and cellular studies showed that the decreased expression of ADAMTS2 may inhibit downstream ErbB signaling pathway transduction and restrain subsequent osteogenesis in human adult mesenchymal stromal cells. Collectively, these data showed that ADAMTS2 (c.3506G>T: p.G1169V) may confer susceptibility to risk of skeletal Class III malocclusion with maxillary deficiency.

Non‐syndromic skeletal Class III malocclusion is a major craniofacial disorder characterized by genetic and environmental factors. Patients with severe skeletal Class III malocclusion require orthognathic surgery to obtain aesthetic facial appearance and functional occlusion. Recent studies have demonstrated that susceptible chromosomal regions and genetic variants of candidate genes play important roles in the etiology of skeletal Class III malocclusion. Here, we provide a comprehensive review of our current understanding of the genetic factors that affect non‐syndromic skeletal Class III malocclusion, including the patterns of inheritance and multiple genetic approaches. We then summarize the functional studies on related loci and genes using cell biology and animal models, which will help to implement individualized therapeutic interventions.