BACKGROUND The standard treatment for advanced T2 gastric cancer(GC)is laparoscopic or surgical gastrectomy(either partial or total)and D2 lymphadenectomy.A novel combined endoscopic and laparoscopic surgery(NCELS)has...BACKGROUND The standard treatment for advanced T2 gastric cancer(GC)is laparoscopic or surgical gastrectomy(either partial or total)and D2 lymphadenectomy.A novel combined endoscopic and laparoscopic surgery(NCELS)has recently been proposed as a better option for T2 GC.Here we describe two case studies demonstrating the efficacy and safety of NCELS.CASE SUMMARY Two T2 GC cases were both resected by endoscopic submucosal dissection and full-thickness resection and laparoscopic lymph nodes dissection.This method has the advantage of being more precise and minimally invasive compared to current methods.The treatment of these 2 patients was safe and effective with no complications.These cases were followed up for nearly 4 years without recurrence or metastasis.CONCLUSION This novel method provides a minimally invasive treatment option for T2 GC,and its potential indications,effectiveness and safety needs to be further evaluated in controlled studies.展开更多
基于本地化差分隐私多关系表示上的Star-JOIN查询已得到研究者广泛关注.现有基于OLH机制与层次树结构的Star-JOIN查询算法存在根节点泄露隐私风险、τ-截断机制没有给出如何选择合适τ值等问题.针对现有算法存在的不足,提出一种有效且...基于本地化差分隐私多关系表示上的Star-JOIN查询已得到研究者广泛关注.现有基于OLH机制与层次树结构的Star-JOIN查询算法存在根节点泄露隐私风险、τ-截断机制没有给出如何选择合适τ值等问题.针对现有算法存在的不足,提出一种有效且满足本地化差分隐私的Star-JOIN查询算法LPRR-JOIN(longitudinal path random response for join).该算法充分利用层次树的纵向路径结构与GRR机制,设计一种纵向本地扰动算法LPRR,该算法以所有属性纵向路径上的节点组合作为扰动值域.每个用户把自身元组映射到相应节点组合中,再利用GRR机制对映射后的元组进行本地扰动.为了避免事实表上存在的频率攻击,LPRR-JOIN算法允许每个用户利用阈值τ本地截断自身元组个数,大于τ条元组删减、小于τ条元组补充.为了寻找合适的τ值,LPRR-JOIN算法利用τ-截断带来的偏差与扰动方差构造总体误差函数,通过优化误差目标函数获得τ值;其次结合用户分组策略获得τ值的总体分布,再利用中位数获得合适的τ值.LPRR-JOIN算法与现有算法在3种多关系数据集上进行比较,实验结果表明其响应查询算法优于同类算法.展开更多
文摘BACKGROUND The standard treatment for advanced T2 gastric cancer(GC)is laparoscopic or surgical gastrectomy(either partial or total)and D2 lymphadenectomy.A novel combined endoscopic and laparoscopic surgery(NCELS)has recently been proposed as a better option for T2 GC.Here we describe two case studies demonstrating the efficacy and safety of NCELS.CASE SUMMARY Two T2 GC cases were both resected by endoscopic submucosal dissection and full-thickness resection and laparoscopic lymph nodes dissection.This method has the advantage of being more precise and minimally invasive compared to current methods.The treatment of these 2 patients was safe and effective with no complications.These cases were followed up for nearly 4 years without recurrence or metastasis.CONCLUSION This novel method provides a minimally invasive treatment option for T2 GC,and its potential indications,effectiveness and safety needs to be further evaluated in controlled studies.
文摘基于本地化差分隐私多关系表示上的Star-JOIN查询已得到研究者广泛关注.现有基于OLH机制与层次树结构的Star-JOIN查询算法存在根节点泄露隐私风险、τ-截断机制没有给出如何选择合适τ值等问题.针对现有算法存在的不足,提出一种有效且满足本地化差分隐私的Star-JOIN查询算法LPRR-JOIN(longitudinal path random response for join).该算法充分利用层次树的纵向路径结构与GRR机制,设计一种纵向本地扰动算法LPRR,该算法以所有属性纵向路径上的节点组合作为扰动值域.每个用户把自身元组映射到相应节点组合中,再利用GRR机制对映射后的元组进行本地扰动.为了避免事实表上存在的频率攻击,LPRR-JOIN算法允许每个用户利用阈值τ本地截断自身元组个数,大于τ条元组删减、小于τ条元组补充.为了寻找合适的τ值,LPRR-JOIN算法利用τ-截断带来的偏差与扰动方差构造总体误差函数,通过优化误差目标函数获得τ值;其次结合用户分组策略获得τ值的总体分布,再利用中位数获得合适的τ值.LPRR-JOIN算法与现有算法在3种多关系数据集上进行比较,实验结果表明其响应查询算法优于同类算法.
