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Rong-Zheng Ma,1 Ping-Ping Han,1 Xin-Cao Tao,2 Huan Li,1 Ling Wang,1 Zhen-Guo Zhai,2 Li-Ping Fu1 1Department of Nuclear Medicine, China-Japan Friendship Hospital, Beijing, 100029, People’s Republic of China; 2Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital, National Center for Respiratory Medicine, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, National Clinical Research Center for Respiratory Diseases, Beijing, 100029, People’s Republic of ChinaCorrespondence: Li-Ping FuDepartment of Nuclear Medicine, China-Japan Friendship Hospital, No. 2 of Yinghuayuan Road, Chaoyang District, Beijing, 100029, People’s Republic of ChinaTel +86 10 84205389Fax +86 10-84205389Email fulipjh@126.comZhen-Guo ZhaiDepartment of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital, No. 2 of Yinghuayuan Road, Chaoyang District, Beijing, 100029, People’s Republic of ChinaTel +86 10 84206269Fax +86 10 84206269Email zhaizhguo235@outlook.comObjective: The study is designed to evaluate the diagnostic ability of single-photon emission computed tomography (SPECT) pulmonary ventilation/perfusion (V/Q) imaging in patients with chronic thromboembolic pulmonary hypertension (CTEPH) and investigate its feasibility in assessing patient risk.Methods: A total of 83 patients suspected of having CTEPH who received V/Q tomography were retrospectively analyzed. The consistency between SPECT V/Q imaging and pulmonary angiography was compared to investigate the correlation between the percentage of pulmonary perfusion defect score (PPDs%) and the hemodynamic indices. Patients were grouped according to the pulmonary arterial hypertension risk stratification, and the V/Q imaging results were compared between different groups.Results: For the 1494 pulmonary segments of the 83 patients, the sensitivity, specificity, and accuracy of identifying pulmonary segments with defects using V/Q imaging was 87.05%, 82.78% (668/807), and 84.7

Peng Xu,1,2,* Jia Yao,1,* Zhen Li,3,* Meng Wang,2 Linghui Zhou,1,2 Guansheng Zhong,1 Yi Zheng,1,2 Na Li,1,2 Zhen Zhai,1,2 Si Yang,1,2 Ying Wu,1,2 Dai Zhang,2 Zhijun Dai1 1Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, People’s Republic of China; 2Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, People’s Republic of China; 3Department of Student Affairs, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhijun DaiDepartment of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, People’s Republic of ChinaTel +86 571 8723 6852Email dzj0911@126.comIntroduction: Sonodynamic Therapy (SDT) has good targeting and non-invasive advantages in solid cancers, but its antitumor effect is not sufficient to replace traditional treatments. Some studies that combined SDT with chemotherapy or nanoparticles have managed to enhance its efficiency and overcome the side effects of chemotherapy.Materials and Methods: In this study, we synthesized and characterized mesoporous silica nanoparticles (MSN-DOX-Ce6) loaded with doxorubicin (DOX) and sonosensitizer, chlorin e6 (Ce6). Then, we conducted in vitro and in vivo experiments to explore the antitumor effect of MSN-DOX-Ce6 under ultrasound (US) treatment.Results: The characterization tests showed that the nanoparticles are uniformly sized spheres with mesoporous structure, resulting in a high drug-loading efficiency. In the in vitro experiments, MSN-DOX-Ce6 could effectively inhibit cell proliferation under US but not more than other treatment groups. However, the in vivo studies showed that MSN-DOX-Ce6+US has better antitumor effect than DOX+Ce6+US

Peng Xu,1,2,* Jia Yao,1,* Zhen Li,3,* Meng Wang,2 Linghui Zhou,1,2 Guansheng Zhong,1 Yi Zheng,1,2 Na Li,1,2 Zhen Zhai,1,2 Si Yang,1,2 Ying Wu,1,2 Dai Zhang,2 Zhijun Dai1 1Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, People’s Republic of China; 2Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, People’s Republic of China; 3Department of Student Affairs, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhijun DaiDepartment of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, People’s Republic of ChinaTel +86 571 8723 6852Email dzj0911@126.comIntroduction: Sonodynamic Therapy (SDT) has good targeting and non-invasive advantages in solid cancers, but its antitumor effect is not sufficient to replace traditional treatments. Some studies that combined SDT with chemotherapy or nanoparticles have managed to enhance its efficiency and overcome the side effects of chemotherapy.Materials and Methods: In this study, we synthesized and characterized mesoporous silica nanoparticles (MSN-DOX-Ce6) loaded with doxorubicin (DOX) and sonosensitizer, chlorin e6 (Ce6). Then, we conducted in vitro and in vivo experiments to explore the antitumor effect of MSN-DOX-Ce6 under ultrasound (US) treatment.Results: The characterization tests showed that the nanoparticles are uniformly sized spheres with mesoporous structure, resulting in a high drug-loading efficiency. In the in vitro experiments, MSN-DOX-Ce6 could effectively inhibit cell proliferation under US but not more than other treatment groups. However, the in vivo studies showed that MSN-DOX-Ce6+US has better antitumor effect than DOX+Ce6+US

Nearest neighbor search is a basic primitive method used for machine learning and information retrieval. We look at exact nearest neighbor search algorithms using tree structures. The most basic tree structure used for fast nearest neighbor search is k-d trees. This thesis will look at k-d tree’s shortcomings and explore various ways to improve its performance. First, we look at PCA trees, which give good performance but is time-expensive. We then study randomized trees, which are very efficient data structures and are flexible in space complexity. Then we introduce a new randomized tree structure, two-vantage-point tree, which outperforms all other tree structures including PCA trees, r-k-d trees, and RP trees. At last, we look at spillover on trees, which can be used to improve the performance of any tree structures. We then compare randomized trees with spillover and show that spill trees only work well with very small spill factor. If more space is allowed, two-vantage-point trees are preferred over spill trees.

Nearest neighbor search is a basic primitive method used for machine learning and information retrieval. We look at exact nearest neighbor search algorithms using tree structures. The most basic tree structure used for fast nearest neighbor search is k-d trees. This thesis will look at k-d tree’s shortcomings and explore various ways to improve its performance. First, we look at PCA trees, which give good performance but is time-expensive. We then study randomized trees, which are very efficient data structures and are flexible in space complexity. Then we introduce a new randomized tree structure, two-vantage-point tree, which outperforms all other tree structures including PCA trees, r-k-d trees, and RP trees. At last, we look at spillover on trees, which can be used to improve the performance of any tree structures. We then compare randomized trees with spillover and show that spill trees only work well with very small spill factor. If more space is allowed, two-vantage-point trees are preferred over spill trees.

Li Yao,1,* Linghui Zhou,2,3,* Yujiao Deng,2,3,* Yi Zheng,2,3 Pengtao Yang,2 Meng Wang,2 Shanshan Dong,4 Qian Hao,2,3 Peng Xu,2,3 Na Li,2,3 Ying Wu,2,3 Zhen Zhai,2,3 Lijuan Lyu,2,3 Zhijun Dai2,3 1Department of Neurology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, People’s Republic of China; 2Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, People’s Republic of China; 3Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, People’s Republic of China; 4School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhijun DaiDepartment of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, People’s Republic of ChinaEmail dzj0911@126.comBackground: Thymidylate synthase (TYMS) polymorphisms are reported to be related to susceptibility to some cancers. However, no study exists on TYMS polymorphisms and glioma risk. This study aimed to evaluate the relationship between two common TYMS gene variants (rs1059394 C>T, rs2847153 G>A) and glioma susceptibility.Methods: This case-control study included 605 patients and 1300 cancer-free individuals. Genotyping was performed using Sequenom Mass-ARRAY. We determined odds ratios (ORs) and their 95% confidence intervals (CIs) to estimate the correlations.Results: The analysis revealed that rs1059394 TT and CT+TT genotype had significantly low glioma risk (TT to CC: OR = 0.71, 95% CI = 0.52–0.97, P = 0.03; CT+TT to CC: OR = 0.74, 95% CI = 0.55–0.99, P = 0.04). However, no significant difference was found between rs2847153 and glioma risk in any genetic model (Pï¹¥0.05). In high-grade gliomas, th