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1. Revisiting the 3{\alpha} reaction rates in helium burning stars

Author

Depastas, Theodoros, Sun, Shuting, Heb, Hongbin, Zheng, Hua, and Bonasera, Aldo

Subjects
Nuclear Theory
Abstract

Helium burning is one of the most fundamental steps of stellar nucleosynthesis, as it describes the formation of life-determining element of carbon, while it plays a key role in the evolution of Red Giant, accreting White Dwarfs and Neutron Stars. In this work we develop a generalized statistical theory for the 3{\alpha} reaction, which is based on the use of the Imaginary Time Method, along with the semi-classical Hybrid {\alpha}-Clustering (H{\alpha}C) and Neck Model (NM) frameworks. The results compared to the methodology and data of the NACRE collaboration, following in several orders of magnitude discrepancies, especially at low temperatures. This may be crucial for the early dynamics of helium burning stars., Comment: 5 pages, 3 figures

Published
2024

4. Conceptualisation of Family and Language Practice in Family Language Policy Research on Migrants: A Systematic Review

Author

Bose, Priyanka, Gao, Xuesong, Starfield, Sue, Sun, Shuting, and Ramdani, Junjun Muhamad

Abstract

Family language policy (FLP) is increasingly recognised as a distinct domain of language policy concerned with the family as an arena of language policy formulation and implementation. While FLP is a relatively new research area, its conceptualisation of family and language practice requires re-examination due to social changes and technological developments, including the expansion of digital communication within families and the rise of globally dispersed families a product of global migration and transnationalism. In this systematic review of migrant FLP research, we investigate how the notions of family and language practice are conceptualised in research. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we identified a total of 163 articles for analysis. Our analysis reveals that the majority of studies were conducted in nuclear families, i.e., those consisting of a father, a mother, and one or more children. Studies also tend to conceptualise the family as fixed and physically located in one place. Paradoxically, around half of the studies acknowledge the presence of geographically dispersed family relations, but this does not necessarily affect their conceptualisation of what comprises a family. Language practice was conceptualised as physical and face-to-face communication in 51% of instances, with only 11% incorporating an analysis of digital communications. Based on our review, we recommend that FLP researchers researching migrant families reconceptualise the family as geographically dispersed and language practice as digital and multimodal when necessary. Such a reconceptualisation will help researchers understand the hitherto underexamined contributions of dispersed family members and multimodal digital communications in migrant FLP.

Published
2023
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5. Weight-based Channel-model Matrix Framework provides a reasonable solution for EEG-based cross-dataset emotion recognition

Author

Chen, Huayu, He, Huanhuan, Zhu, Jing, Sun, Shuting, Li, Jianxiu, Shao, Xuexiao, Li, Junxiang, Li, Xiaowei, and Hu, Bin

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Cross-dataset emotion recognition as an extremely challenging task in the field of EEG-based affective computing is influenced by many factors, which makes the universal models yield unsatisfactory results. Facing the situation that lacks EEG information decoding research, we first analyzed the impact of different EEG information(individual, session, emotion and trial) for emotion recognition by sample space visualization, sample aggregation phenomena quantification, and energy pattern analysis on five public datasets. Based on these phenomena and patterns, we provided the processing methods and interpretable work of various EEG differences. Through the analysis of emotional feature distribution patterns, the Individual Emotional Feature Distribution Difference(IEFDD) was found, which was also considered as the main factor of the stability for emotion recognition. After analyzing the limitations of traditional modeling approach suffering from IEFDD, the Weight-based Channel-model Matrix Framework(WCMF) was proposed. To reasonably characterize emotional feature distribution patterns, four weight extraction methods were designed, and the optimal was the correction T-test(CT) weight extraction method. Finally, the performance of WCMF was validated on cross-dataset tasks in two kinds of experiments that simulated different practical scenarios, and the results showed that WCMF had more stable and better emotion recognition ability., Comment: 18 pages, 12 figures, 8 tables

Published
2022

6. Student Voice in Assessment and Feedback (2011-2022): A Systematic Review

Author

Sun, Shuting, Gao, Xuesong, Rahmani, Bita Dwi, Bose, Priyanka, and Davison, Chris

Abstract

In recent years, there has been a growing body of research on student voice in the context of higher education, generating significant insights for pedagogical improvement. This systematic literature review aims to examine studies on student voice from 2011 to 2022, specifically those concerned with assessment and feedback in higher education. The review draws on 38 empirical studies and identifies the increasing use of mixed-methods designs in student voice research related to assessment and feedback. The analysis of these studies highlights that student voice research can improve students' experiences, change teachers' practices and inform university support concerning assessment and feedback. The review finds, however, that most studies were conducted in, or on students from, developed countries. It is necessary for researchers to engage students from different backgrounds to investigate their experiences of assessment and feedback. The results of the review also suggest that more longitudinal, mixed-methods studies should be conducted to generate further critical insights. Future research should regard students as partners in effective assessment and feedback practices, and a focus should be placed on students developing assessment and feedback literacy.

Published
2023
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7. Mechanism of bisphosphonate-related osteonecrosis of the jaw (BRONJ) revealed by targeted removal of legacy bisphosphonate from jawbone using competing inert hydroxymethylene diphosphonate.

Author

Okawa, Hiroko, Kondo, Takeru, Hokugo, Akishige, Cherian, Philip, Campagna, Jesus J, Lentini, Nicholas A, Sung, Eric C, Chiang, Samantha, Lin, Yi-Ling, Ebetino, Frank H, John, Varghese, Sun, Shuting, McKenna, Charles E, and Nishimura, Ichiro

Subjects
Animals, Humans, Mice, Nitrogen, Diphosphonates, Liposomes, Bisphosphonate-Associated Osteonecrosis of the Jaw, Zoledronic Acid, biochemistry, bisphosphonate, chemical biology, immunology, inflammation, mouse, oral barrier inflammation, osteonecrosis of the jaw, therapeutic, Clinical Research, Dental/Oral and Craniofacial Disease, Aetiology, 2.1 Biological and endogenous factors, Mouse, Biochemistry and Cell Biology
Abstract

Bisphosphonate-related osteonecrosis of the jaw (BRONJ) presents as a morbid jawbone lesion in patients exposed to a nitrogen-containing bisphosphonate (N-BP). Although it is rare, BRONJ has caused apprehension among patients and healthcare providers and decreased acceptance of this antiresorptive drug class to treat osteoporosis and metastatic osteolysis. We report here a novel method to elucidate the pathological mechanism of BRONJ by the selective removal of legacy N-BP from the jawbone using an intra-oral application of hydroxymethylene diphosphonate (HMDP) formulated in liposome-based deformable nanoscale vesicles (DNV). After maxillary tooth extraction, zoledronate-treated mice developed delayed gingival wound closure, delayed tooth extraction socket healing and increased jawbone osteonecrosis consistent with human BRONJ lesions. Single cell RNA sequencing of mouse gingival cells revealed oral barrier immune dysregulation and unresolved proinflammatory reaction. HMDP-DNV topical applications to nascent mouse BRONJ lesions resulted in accelerated gingival wound closure and bone socket healing as well as attenuation of osteonecrosis development. The gingival single cell RNA sequencing demonstrated resolution of chronic inflammation by increased anti-inflammatory signature gene expression of lymphocytes and myeloid-derived suppressor cells. This study suggests that BRONJ pathology is related to N-BP levels in jawbones and demonstrates the potential of HMDP-DNV as an effective BRONJ therapy.

Published
2022

8. Lowering systolic blood pressure to less than 120 mm Hg versus less than 140 mm Hg in patients with high cardiovascular risk with and without diabetes or previous stroke: an open-label, blinded-outcome, randomised trial

Author

Ai, Xinyue, An, Chun, An, Yuhong, Bai, Shiru, Bai, Xueke, Bi, Jingao, Bin, Xiaoling, Bu, Miaomiao, Bu, Peili, Bu, Wei, Cai, Lvping, Cai, Nana, Cai, Shuhui, Cai, Ting, Cai, Wenjing, Cao, Bin, Cao, Bingbing, Cao, Huaping, Cao, Libo, Cao, Xiancun, Chai, Hui, Chai, Yonggui, Chai, Zhiyong, Chang, Chunduo, Chang, Jianbao, Chang, Shuyue, Chang, Yunling, Chao, Huanhuan, Che, Hang, Che, Qianqiu, Chen, Danlin, Chen, Dongsheng, Chen, Faxiu, Chen, Guang, Chen, Hairong, Chen, Hao, Chen, Huahua, Chen, Huijun, Chen, Jiafu, Chen, Jian, Chen, Jiasen, Chen, Jing, Chen, Jinzi, Chen, Junrong, Chen, lichun, Chen, Lijuan, Chen, Liyuan, Chen, Qun, Chen, Run, Chen, Shaoxing, Chen, Song, Chen, Tieshuang, Chen, Xianghong, Chen, Xiaowu, Chen, Xudong, Chen, Xue, Chen, Xunchun, Chen, Yao, Chen, Yongli, Chen, Yuanyue, Chen, Yuhong, Chen, Yuyi, Chen, Zhangying, Chen, Zhidong, Chen, Zuyi, Cheng, Caiming, Cheng, Jianbin, Cheng, Xiaoxia, Chu, Junjie, Cui, Ruifeng, Cui, Xiaolin, Cui, Xuechen, Cui, Yang, Cui, Zhonghua, Dai, Wanhong, Dai, Xing, Ding, Chunxia, Ding, Huihong, Ding, Qiuhong, Ding, Yaozong, Ding, Yingjie, Dong, Jiajia, Dong, Lei, Dong, Qi, Dong, Yumei, Du, Bing, Du, Hong, Du, Jie, Du, Laijing, Du, Meiling, Du, Qiong, Du, Tianmin, Du, Xue, Duan, Ru, Duan, Xiaojing, Duan, Xiaoting, Fan, Dandan, Fan, Xiaohong, Fan, Xin, Fang, Fang, Fang, Jing, Fang, Xibo, Fang, Yang, Feng, Erke, Feng, Hejin, Feng, Ling, Feng, Rui, Feng, Zhaohui, Fu, Hongmei, Fu, Qiuai, Gao, Haofei, Gao, Li, Gao, Lina, Gao, Liwei, Gao, Lu, Gao, Min, Gao, Qian, Gao, Yan, Gao, Yuan, Ge, Jinzhuo, Geng, Hongxu, Geng, Hui, Geng, Leijun, Geng, Lianqing, Gou, Hongyan, Gu, Qin, Guan, Lili, Guan, Shuo, Guan, Wenchi, Guan, Zheng, Guang, Bin, Guo, Anran, Guo, Changhong, Guo, Gaofeng, Guo, Lizhi, Guo, Qing, Guo, Qiue, Guo, Ying, Guo, Zhihua, Han, Aihong, Han, Meihong, Han, Suhui, Han, Xinru, Han, Yajun, Hao, Feng, Hao, Jingmin, Hao, Shiguo, He, Chuanhui, He, Dejian, He, Mengyuan, He, Miaomiao, He, Shaojuan, He, Wenkai, He, Xiaoyu, He, Yuxiang, Hong, Jige, Hou, Chuanxing, Hou, Jing, Hu, Danli, Hu, Jian, Hu, Jun, Hu, Lingai, Hu, Mengying, Hu, Zhiyuan, Huang, Anhui, Huang, Chunxia, Huang, Haolin, Huang, Jianlan, Huang, Sha, Huang, Siqi, Huang, Weijun, Huang, Wenxiu, Huang, Xinghe, Huang, Xinsheng, Huang, Xinxin, Hui, Jiliang, Hui, Lijun, Hui, Zhongsheng, Huo, Fangjie, Ji, Runqing, Jia, Guojiong, Jia, Hao, Jia, Jingjing, Jia, Jingmei, Jia, Xiaoling, Jiang, Hua, Jiang, Jingcheng, Jiang, Qian, Jiang, Xianyan, Jiang, Xiaoyuan, Jiang, Yanxiang, Jiao, Yunhong, Jie, Liying, Jin, Binbin, Jin, Lingjiao, Jin, Renshu, Jin, Rong, Jin, Xiang, Jin, Xianping, Jin, Yongfan, Jin, Zepu, Jin, Zhenan, Jing, Chengrong, Jing, Jiajie, Jing, Ruiling, Kang, Liping, Kang, Yu, Kong, Jianqiong, Kou, Shijie, Kou, Xianli, Kulaxihan, Lai, Jijia, Lei, Lubi, Li, Baoxiang, Li, Bin, Li, Bing, Li, Chaohui, Li, Cheng, Li, Chunmei, Li, Chunyan, Li, Daqing, Li, Deen, Li, Di, Li, Feng, Li, Guanyi, Li, Haiyang, Li, Hongwei, Li, Jia, Li, Jialin, Li, Jianan, Li, Jianguang, Li, Jiaying, Li, Jing, Li, Jinmei, Li, Lala, Li, Li, Li, Lijun, Li, Liping, Li, Lize, Li, Mingju, Li, Minglan, Li, Mingyan, Li, Na, Li, Nan, Li, Nana, Li, Qiang, Li, Qianru, Li, Rui, Li, Ruihong, Li, Shanshan, Li, Shilin, Li, Si, Li, Suwen, Li, Tongshe, Li, Tongying, Li, Wanke, Li, Wei, Li, Wenbo, Li, Wenjuan, Li, Xi, Li, Xiangxia, Li, Xiao, Li, Xiaohui, Li, Xingyan, Li, Xiujuan, Li, Yan, Li, Yanfang, Li, Yang, Li, Yanxia, Li, Yaona, Li, Yichong, Li, Ying, Li, Yuqing, Li, Zheng, Li, Zhengye, Liang, Chuanliang, Liang, Jihua, Liang, Jin, Liang, Ke, Liang, Linju, Liang, Tingchen, Liang, Xia, Liang, Xianfeng, Liang, Yanli, Liang, Zhenye, Lie, Zhenbang, Lin, Qingfei, Lin, Ruifang, Lin, Xiao, Lin, Zhiqiang, Liu, Aijun, Liu, Chao, Liu, Chunxia, Liu, Cong, Liu, Fang, Liu, Guaiyan, Liu, Hongjun, Liu, Jiamin, Liu, Jiangling, Liu, Jianqi, Liu, Jieyun, Liu, Jihong, Liu, Jing, Liu, Jinsha, Liu, Juan, Liu, Junfang, Liu, Liming, Liu, Lin, Liu, Ling, Liu, Lu, Liu, Qiang, Liu, Qiaoling, Liu, Qiaoxia, Liu, Qiuxia, Liu, Shaobo, Liu, Xiaobao, Liu, Xiaocheng, Liu, Xiaoyuan, Liu, Xinbo, Liu, Xu, Liu, Yang, Liu, Yanhu, Liu, Yanming, Liu, Yaqin, Liu, Yong, Liu, Zhihong, Long, Jing, Lu, Futang, Lu, Huamei, Lu, Jiapeng, Lu, Junhong, Lu, Weibin, Lu, Yanrong, Lu, Yuchun, Luan, Tianwei, Luo, Qingwei, Luo, Qun, Luo, Tian, Luo, Xia, Luo, Yongmei, Lv, Jing, Lv, Jinhai, Lv, Lei, Lv, Lili, Lv, Meng, Ma, Aiqing, Ma, Huaimin, Ma, Huihuang, Ma, Jie, Ma, Jinbao, Ma, Li, Ma, Lingzhen, Ma, Nan, Ma, Qiaojuan, Ma, Shumei, Ma, Tengfei, Ma, Xiange, Ma, Xiaowen, Ma, Yuehua, Mai, Lanxian, Mei, Xiao, Meng, Gen, Miao, Ruichao, Miao, Xue, Miao, Xuyan, Min, Tingting, Mo, Shubing, Morigentu, Nan, Tingyan, Ni, Jinyang, Ni, Shuguo, Nie, Yu, Ning, Benxing, Ning, Xiaowei, Niu, Manman, Niu, Qingying, Niu, Wentang, Niu, Xiaoxia, Ou, Fang, Pan, Biyun, Pan, Chengjie, Pan, Congming, Pan, Jieli, Pan, Xiaowen, Pan, Ziying, Pei, Guangzhong, Pei, Lingyu, Pei, Min, Pei, Yanzhen, Peng, Yinyu, Peng, Yuming, Pu, Zhaokun, Qi, Fengjun, Qi, Liwei, Qi, Meiqiong, Qi, Yan, Qian, Jun, Qin, Lei, Qin, Zhonghua, Qing, Lan, Qiu, Lixia, Qiu, Weiyu, Qiu, Xiaoling, Qu, Yueli, Quan, Minghua, Ren, Dingping, Ren, Hong, Ren, Lingzhi, Ren, Tingting, Ren, Wei, Ren, Yihui, Rong, Yufang, Ruan, Jiahui, Shang, Peiqin, Shao, Minyan, Shao, Xuefeng, Shao, Yuling, Shen, Junrong, Shen, Rui, Sheng, Lin, Shi, Jiangjie, Shi, Xun, Shi, Yanhong, Shi, Yeju, Shi, Yujiao, Shu, Bo, Song, Bingchun, Song, Dan, Song, Jinhui, Song, Jinwang, Song, Jinxian, Song, Wei, Song, Xiaoping, Song, Yawen, Su, He, Su, Qinfeng, Su, Shuhong, Su, Xiaozhou, Sun, Chengxiang, Sun, Fangfang, Sun, Gongping, Sun, Jiangnan, Sun, Mengmeng, Sun, Rongrong, Sun, Shuting, Sun, Songtao, Sun, Ying, Sun, Yongmiao, Sun, Yunhong, Sun, Zhiqiang, Suo, Mengying, Tan, Binghu, Tang, Chunyan, Tang, Zhongli, Tao, Yu, Tian, Changming, Tian, Hongmei, Tian, Jian, Tian, Xiaomin, Wan, Huaibin, Wan, Qin, Wan, Rongjun, Wang, Bobin, Wang, Chao, Wang, Chaoqun, Wang, Chengliang, Wang, Di, Wang, Enfang, Wang, Feng, Wang, Gang, Wang, Guangqiang, Wang, Guixiang, Wang, Haifeng, Wang, Haijun, Wang, Haiyang, Wang, Jianfang, Wang, Jianfeng, Wang, Jing, Wang, Junping, Wang, Junying, Wang, Kang, Wang, Lei, Wang, Lin, Wang, Lize, Wang, Meng, Wang, Pan, Wang, Qi, Wang, Qiong, Wang, Qiuli, Wang, Qiuxue, Wang, Ran, Wang, Shaojin, Wang, Shuai, Wang, Tao, Wang, Tiantian, Wang, Tinghui, Wang, Tongyan, Wang, Wanhong, Wang, Wenjuan, Wang, Wenyan, Wang, Wenying, Wang, Wenzhuan, Wang, Xiaofei, Wang, Xiaoyan, Wang, Xitong, Wang, Xu, Wang, Yan, Wang, Yanfang, Wang, Yang, Wang, Yanping, Wang, Yanying, Wang, Yaoxin, Wang, Yingli, Wang, Yiting, Wang, Yue, Wang, Yumei, Wang, Yuzhuo, Wang, Zhenhua, Wang, Zhifang, Wang, Zhimin, Wei, Chunli, Wei, Lixia, Wei, Pei, Wei, Shuying, Wei, Xiqing, Wen, Hong, Wen, Yun, Wu, Chaoqun, Wu, Hairong, Wu, Lihua, Wu, Lingxiang, Wu, Qi, Wu, Shaorong, Wu, Wenting, Wu, Xueyi, Wu, Yongshuan, Wu, Zhihao, Wu, Zhuying, Wu, Zongyin, Wuhanbilige, Xia, Jun, Xia, Yang, Xiang, Jing, Xiao, Heliu, Xiao, Yaying, Xie, Meiling, Xie, Yinyan, Xin, Huiling, Xing, Jing, Xiu, Guoquan, Xu, Baohua, Xu, Chuangze, Xu, En, Xu, Jian, Xu, Shuli, Xu, Wei, Xu, Wen, Xue, Na, Xue, Tingting, Xue, Wei, Yan, Haiyan, Yan, Xiaofang, Yan, Yanqing, Yang, Bo, Yang, Hui, Yang, Huiyu, Yang, Jinhua, Yang, Kun, Yang, Man, Yang, Mengya, Yang, Ning, Yang, Ping, Yang, Xiajiao, Yang, Xiaomo, Yang, Xin, Yang, Xiujuan, Yang, Xuemei, Yang, Xuming, Yang, Yan, Yang, Yanhua, Yang, Yi, Yang, Yuanyuan, Yang, Zhimei, Yang, Zhiming, Yao, Hui, Yao, Lu, Ye, Jinling, Ye, Wenhua, Yi, Mingjiao, Yi, Shaowei, Yi, Wenyi, Yi, Zhimin, Yin, Guangxia, Yin, Guoyuan, Yu, Guibin, Yu, Hairong, Yu, Huaitao, Yu, Lijie, Yu, Lijun, Yu, Nana, Yu, Qin, Yu, Xinli, Yu, Yi, Yuan, Biao, Zeng, Chunmei, Zhai, Na, Zhai, Xiaojuan, Zhan, Hongju, Zhang, Aizhen, Zhang, Baohua, Zhang, Bin, Zhang, Caizhu, Zhang, Chaoying, Zhang, Chengbo, Zhang, Chunlai, Zhang, Churuo, Zhang, Fan, Zhang, Feiqin, Zhang, Ge, Zhang, Haibo, Zhang, Hailin, Zhang, Hanxue, Zhang, Huaixing, Zhang, Hui, Zhang, Huijuan, Zhang, Jinguo, Zhang, Jingyu, Zhang, Jinyun, Zhang, Jisheng, Zhang, Jun, Zhang, Lei, Zhang, Li, Zhang, Liang, Zhang, Lifeng, Zhang, Lina, Zhang, Liping, Zhang, Min, Zhang, Ping, Zhang, Qiang, Zhang, Rufang, Zhang, Ruifen, Zhang, Shengde, Zhang, Siqi, Zhang, Sufang, Zhang, Tingting, Zhang, Wanyue, Zhang, Weiliang, Zhang, Xiaohan, Zhang, Xiaohong, Zhang, Xiaojuan, Zhang, Xin, Zhang, Xue, Zhang, Xuewei, Zhang, Yachen, Zhang, Yang, Zhang, Yanyan, Zhang, Yaojie, Zhang, Yingyu, Zhang, Yuan, Zhang, Yun, Zhang, Yunfeng, Zhang, Zaozhang, Zhang, Zhichao, Zhao, Baihui, Zhao, Dan, Zhao, Fuxian, Zhao, Guizeng, Zhao, Haijie, Zhao, Honglei, Zhao, Huizhen, Zhao, Jindong, Zhao, Juan, Zhao, Liming, Zhao, Ling, Zhao, Lingshan, Zhao, Qingxia, Zhao, Qiuping, Zhao, Wanchen, Zhao, Wangxiu, Zhao, Weiyi, Zhao, Xiaodi, Zhao, Xiaojing, Zhao, Xiaoli, Zhao, Xiaoyan, Zhao, Xiling, Zhao, Yannan, Zhao, Yiyuan, Zheng, Shuzhen, Zheng, Xin, Zhi, Lixia, Zhong, Hui, Zhong, Qing, Zhong, Xin, Zhong, Yunzhi, Zhou, Jianfeng, Zhou, Jihu, Zhou, Ke, Zhou, Liangliang, Zhou, Ling, Zhou, Na, Zhou, Shengcheng, Zhou, Suyun, Zhou, Tao, Zhou, Wanren, Zhou, Weifeng, Zhou, Weijuan, Zhou, Xiaohong, Zhou, Yunke, Zhou, Yuquan, Zhou, Zhaohai, Zhou, Zhiming, Zhu, Bingpo, Zhu, Jifa, Zhu, Jing, Zhu, Mengnan, Zhu, Youcun, Zong, Dafei, Zuo, Hongbo, and Zuo, Zhaokai

Published
2024
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13. Evidence of bisphosphonate-conjugated sitafloxacin eradication of established methicillin-resistant S. aureus infection with osseointegration in murine models of implant-associated osteomyelitis

Author

Ren, Youliang, Weeks, Jason, Xue, Thomas, Rainbolt, Joshua, de Mesy Bentley, Karen L., Shu, Ye, Liu, Yuting, Masters, Elysia, Cherian, Philip, McKenna, Charles E., Neighbors, Jeffrey, Ebetino, Frank H., Schwarz, Edward M., Sun, Shuting, and Xie, Chao

Published
2023
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14. A study of resting-state EEG biomarkers for depression recognition

Author

Sun, Shuting, Li, Jianxiu, Chen, Huayu, Gong, Tao, Li, Xiaowei, and Hu, Bin

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Background: Depression has become a major health burden worldwide, and effective detection depression is a great public-health challenge. This Electroencephalography (EEG)-based research is to explore the effective biomarkers for depression recognition. Methods: Resting state EEG data was collected from 24 major depressive patients (MDD) and 29 normal controls using 128 channel HydroCel Geodesic Sensor Net (HCGSN). To better identify depression, we extracted different types of EEG features including linear features, nonlinear features and functional connectivity features phase lagging index (PLI) to comprehensively analyze the EEG signals in patients with MDD. And using different feature selection methods and classifiers to evaluate the optimal feature sets. Results: Functional connectivity feature PLI is superior to the linear features and nonlinear features. And when combining all the types of features to classify MDD patients, we can obtain the highest classification accuracy 82.31% using ReliefF feature selection method and logistic regression (LR) classifier. Analyzing the distribution of optimal feature set, it was found that intrahemispheric connection edges of PLI were much more than the interhemispheric connection edges, and the intrahemispheric connection edges had a significant differences between two groups. Conclusion: Functional connectivity feature PLI plays an important role in depression recognition. Especially, intrahemispheric connection edges of PLI might be an effective biomarker to identify depression. And statistic results suggested that MDD patients might exist functional dysfunction in left hemisphere.

Published
2020

15. MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

Author

Cai, Hanshu, Gao, Yiwen, Sun, Shuting, Li, Na, Tian, Fuze, Xiao, Han, Li, Jianxiu, Yang, Zhengwu, Li, Xiaowei, Zhao, Qinglin, Liu, Zhenyu, Yao, Zhijun, Yang, Minqiang, Peng, Hong, Zhu, Jing, Zhang, Xiaowei, Gao, Guoping, Zheng, Fang, Li, Rui, Guo, Zhihua, Ma, Rong, Yang, Jing, Zhang, Lan, Hu, Xiping, Li, Yumin, and Hu, Bin

Subjects
Computer Science - Digital Libraries, Computer Science - Machine Learning, Quantitative Biology - Neurons and Cognition
Abstract

According to the World Health Organization, the number of mental disorder patients, especially depression patients, has grown rapidly and become a leading contributor to the global burden of disease. However, the present common practice of depression diagnosis is based on interviews and clinical scales carried out by doctors, which is not only labor-consuming but also time-consuming. One important reason is due to the lack of physiological indicators for mental disorders. With the rising of tools such as data mining and artificial intelligence, using physiological data to explore new possible physiological indicators of mental disorder and creating new applications for mental disorder diagnosis has become a new research hot topic. However, good quality physiological data for mental disorder patients are hard to acquire. We present a multi-modal open dataset for mental-disorder analysis. The dataset includes EEG and audio data from clinically depressed patients and matching normal controls. All our patients were carefully diagnosed and selected by professional psychiatrists in hospitals. The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications. The 128-electrodes EEG signals of 53 subjects were recorded as both in resting state and under stimulation; the 3-electrode EEG signals of 55 subjects were recorded in resting state; the audio data of 52 subjects were recorded during interviewing, reading, and picture description. We encourage other researchers in the field to use it for testing their methods of mental-disorder analysis.

Published
2020
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17. Rescue bisphosphonate treatment of alveolar bone improves extraction socket healing and reduces osteonecrosis in zoledronate-treated mice

Author

Hokugo, Akishige, Kanayama, Keiichi, Sun, Shuting, Morinaga, Kenzo, Sun, Yujie, Wu, QingQing, Sasaki, Hodaka, Okawa, Hiroko, Evans, Courtney, Ebetino, Frank H, Lundy, Mark W, Sadrerafi, Keivan, McKenna, Charles E, and Nishimura, Ichiro

Subjects
Biomedical and Clinical Sciences, Dentistry, Dental/Oral and Craniofacial Disease, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, Musculoskeletal, Administration, Intravenous, Animals, Bone Density Conservation Agents, Diphosphonates, Female, Mice, Mice, Inbred C57BL, Osteonecrosis, Wound Healing, Zoledronic Acid, Bisphosphonates, Osteonecrosis of the jaw, BRONJ, MRONJ, Drug displacement, Prophylaxis, Biological Sciences, Engineering, Medical and Health Sciences, Endocrinology & Metabolism, Clinical sciences
Abstract

Bisphosphonate (BP)-related osteonecrosis of the jaw, previously known as BRONJ, now referred to more broadly as medication-related osteonecrosis of the jaw (MRONJ), is a morbid condition that represents a significant risk for oncology patients who have received high dose intravenous (IV) infusion of a potent nitrogen containing BP (N-BP) drug. At present, no clinical procedure is available to prevent or effectively treat MRONJ. Although the pathophysiological basis is not yet fully understood, legacy adsorbed N-BP in jawbone has been proposed to be associated with BRONJ by one or more mechanisms. We hypothesized that removal of the pre-adsorbed N-BP drug common to these pathological mechanisms from alveolar bone could be an effective preventative/therapeutic strategy. This study demonstrates that fluorescently labeled BP pre-adsorbed on the surface of murine maxillo-cranial bone in vivo can be displaced by subsequent application of other BPs. We previously described rodent BRONJ models involving the combination of N-BP treatment such as zoledronate (ZOL) and dental initiating factors such as tooth extraction. We further refined our mouse model by using gel food during the first 7 days of the tooth extraction wound healing period, which decreased confounding food pellet impaction problems in the open boney socket. This refined mouse model does not manifest BRONJ-like severe jawbone exposure, but development of osteonecrosis around the extraction socket and chronic gingival inflammation are clearly exhibited. In this study, we examined the effect of benign BP displacement of legacy N-BP on tooth extraction wound healing in the in vivo model. Systemic IV administration of a low potency BP (lpBP: defined as inactive at 100 μM in a standard protein anti-prenylation assay) did not significantly attenuate jawbone osteonecrosis. We then developed an intra-oral formulation of lpBP, which when injected into the gingiva adjacent to the tooth prior to extraction, dramatically reduced the osteocyte necrosis area. Furthermore, the tooth extraction wound healing pattern was normalized, as evidenced by timely closure of oral soft tissue without epithelial hyperplasia, significantly reduced gingival inflammation and increased new bone filling in the extraction socket. Our results are consistent with the hypothesis that local application of a rescue BP prior to dental surgery can decrease the amount of a legacy N-BP drug in proximate jawbone surfaces below the threshold that promotes osteocyte necrosis. This observation should provide a conceptual basis for a novel strategy to improve socket healing in patients treated with BPs while preserving therapeutic benefit from anti-resorptive N-BP drug in vertebral and appendicular bones.

Published
2019

19. A multi-modal open dataset for mental-disorder analysis

Author

Cai, Hanshu, Yuan, Zhenqin, Gao, Yiwen, Sun, Shuting, Li, Na, Tian, Fuze, Xiao, Han, Li, Jianxiu, Yang, Zhengwu, Li, Xiaowei, Zhao, Qinglin, Liu, Zhenyu, Yao, Zhijun, Yang, Minqiang, Peng, Hong, Zhu, Jing, Zhang, Xiaowei, Gao, Guoping, Zheng, Fang, Li, Rui, Guo, Zhihua, Ma, Rong, Yang, Jing, Zhang, Lan, Hu, Xiping, Li, Yumin, and Hu, Bin

Published
2022
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21. A Light-Weight Deployment Methodology for DNN Re-training in Resource-Constraint Scenarios

Author

Sun, Shuting, Guo, Songtao, Xiao, Chunhua, Liao, Zilan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Liu, Zhe, editor, Wu, Fan, editor, and Das, Sajal K., editor

Published
2021
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29. Lowering systolic blood pressure to less than 120 mm Hg versus less than 140 mm Hg in patients with high cardiovascular risk with and without diabetes or previous stroke: an open-label, blinded-outcome, randomised trial

Author

Liu, Jiamin, Li, Yan, Ge, Jinzhuo, Yan, Xiaofang, Zhang, Haibo, Zheng, Xin, Lu, Jiapeng, Li, Xi, Gao, Yan, Lei, Lubi, Liu, Jing, Li, Jing, Ai, Xinyue, An, Chun, An, Yuhong, Bai, Shiru, Bai, Xueke, Bi, Jingao, Bin, Xiaoling, Bu, Miaomiao, Bu, Peili, Bu, Wei, Cai, Lvping, Cai, Nana, Cai, Shuhui, Cai, Ting, Cai, Wenjing, Cao, Bin, Cao, Bingbing, Cao, Huaping, Cao, Libo, Cao, Xiancun, Chai, Hui, Chai, Yonggui, Chai, Zhiyong, Chang, Chunduo, Chang, Jianbao, Chang, Shuyue, Chang, Yunling, Chao, Huanhuan, Che, Hang, Che, Qianqiu, Chen, Danlin, Chen, Dongsheng, Chen, Faxiu, Chen, Guang, Chen, Hairong, Chen, Hao, Chen, Huahua, Chen, Huijun, Chen, Jiafu, Chen, Jian, Chen, Jian, Chen, Jiasen, Chen, Jing, Chen, Jinzi, Chen, Junrong, Chen, lichun, Chen, Lijuan, Chen, Liyuan, Chen, Qun, Chen, Run, Chen, Shaoxing, Chen, Song, Chen, Tieshuang, Chen, Xianghong, Chen, Xiaowu, Chen, Xudong, Chen, Xue, Chen, Xunchun, Chen, Yao, Chen, Yongli, Chen, Yuanyue, Chen, Yuhong, Chen, Yuyi, Chen, Zhangying, Chen, Zhidong, Chen, Zuyi, Cheng, Caiming, Cheng, Jianbin, Cheng, Xiaoxia, Chu, Junjie, Cui, Ruifeng, Cui, Xiaolin, Cui, Xuechen, Cui, Yang, Cui, Zhonghua, Dai, Wanhong, Dai, Xing, Ding, Chunxia, Ding, Huihong, Ding, Qiuhong, Ding, Yaozong, Ding, Yingjie, Dong, Jiajia, Dong, Lei, Dong, Qi, Dong, Yumei, Du, Bing, Du, Hong, Du, Jie, Du, Laijing, Du, Meiling, Du, Qiong, Du, Tianmin, Du, Xue, Duan, Ru, Duan, Xiaojing, Duan, Xiaoting, Fan, Dandan, Fan, Xiaohong, Fan, Xin, Fang, Fang, Fang, Jing, Fang, Xibo, Fang, Yang, Feng, Erke, Feng, Hejin, Feng, Ling, Feng, Rui, Feng, Zhaohui, Fu, Hongmei, Fu, Qiuai, Gao, Haofei, Gao, Li, Gao, Lina, Gao, Liwei, Gao, Lu, Gao, Min, Gao, Min, Gao, Qian, Gao, Yan, Gao, Yuan, Ge, Jinzhuo, Geng, Hongxu, Geng, Hui, Geng, Leijun, Geng, Lianqing, Gou, Hongyan, Gu, Qin, Guan, Lili, Guan, Shuo, Guan, Wenchi, Guan, Zheng, Guang, Bin, Guo, Anran, Guo, Changhong, Guo, Gaofeng, Guo, Lizhi, Guo, Qing, Guo, Qiue, Guo, Ying, Guo, Zhihua, Han, Aihong, Han, Meihong, Han, Suhui, Han, Xinru, Han, Yajun, Hao, Feng, Hao, Jingmin, Hao, Shiguo, He, Chuanhui, He, Dejian, He, Mengyuan, He, Miaomiao, He, Shaojuan, He, Wenkai, He, Xiaoyu, He, Yuxiang, Hong, Jige, Hou, Chuanxing, Hou, Jing, Hu, Danli, Hu, Jian, Hu, Jun, Hu, Lingai, Hu, Mengying, Hu, Zhiyuan, Huang, Anhui, Huang, Chunxia, Huang, Haolin, Huang, Jianlan, Huang, Sha, Huang, Siqi, Huang, Weijun, Huang, Wenxiu, Huang, Xinghe, Huang, Xinsheng, Huang, Xinxin, Hui, Jiliang, Hui, Lijun, Hui, Zhongsheng, Huo, Fangjie, Ji, Runqing, Ji, Runqing, Jia, Guojiong, Jia, Hao, Jia, Jingjing, Jia, Jingmei, Jia, Xiaoling, Jiang, Hua, Jiang, Jingcheng, Jiang, Qian, Jiang, Xianyan, Jiang, Xiaoyuan, Jiang, Yanxiang, Jiao, Yunhong, Jie, Liying, Jin, Binbin, Jin, Lingjiao, Jin, Renshu, Jin, Rong, Jin, Xiang, Jin, Xianping, Jin, Yongfan, Jin, Zepu, Jin, Zhenan, Jing, Chengrong, Jing, Jiajie, Jing, Ruiling, Kang, Liping, Kang, Yu, Kong, Jianqiong, Kou, Shijie, Kou, Xianli, Kulaxihan, Lai, Jijia, Lei, Lubi, Li, Baoxiang, Li, Bin, Li, Bing, Li, Chaohui, Li, Cheng, Li, Chunmei, Li, Chunyan, Li, Daqing, Li, Deen, Li, Di, Li, Feng, Li, Guanyi, Li, Haiyang, Li, Hongwei, Li, Jia, Li, Jialin, Li, Jianan, Li, Jianguang, Li, Jiaying, Li, Jing, Li, Jing, Li, Jinmei, Li, Lala, Li, Li, Li, Lijun, Li, Liping, Li, Lize, Li, Mingju, Li, Minglan, Li, Mingyan, Li, Na, Li, Na, Li, Nan, Li, Nana, Li, Qiang, Li, Qianru, Li, Rui, Li, Ruihong, Li, Shanshan, Li, Shilin, Li, Si, Li, Suwen, Li, Tongshe, Li, Tongying, Li, Wanke, Li, Wei, Li, Wenbo, Li, Wenjuan, Li, Xi, Li, Xiangxia, Li, Xiao, Li, Xiaohui, Li, Xingyan, Li, Xiujuan, Li, Yan, Li, Yanfang, Li, Yang, Li, Yanxia, Li, Yaona, Li, Yichong, Li, Ying, Li, Yuqing, Li, Zheng, Li, Zhengye, Liang, Chuanliang, Liang, Jihua, Liang, Jin, Liang, Ke, Liang, Linju, Liang, Tingchen, Liang, Xia, Liang, Xianfeng, Liang, Yanli, Liang, Zhenye, Lie, Zhenbang, Lin, Qingfei, Lin, Ruifang, Lin, Xiao, Lin, Zhiqiang, Liu, Aijun, Liu, Chao, Liu, Chunxia, Liu, Cong, Liu, Fang, Liu, Fang, Liu, Guaiyan, Liu, Hongjun, Liu, Jiamin, Liu, Jiangling, Liu, Jianqi, Liu, Jieyun, Liu, Jihong, Liu, Jing, Liu, Jinsha, Liu, Juan, Liu, Junfang, Liu, Liming, Liu, Lin, Liu, Lin, Liu, Lin, Liu, Ling, Liu, Lu, Liu, Qiang, Liu, Qiaoling, Liu, Qiaoxia, Liu, Qiuxia, Liu, Shaobo, Liu, Xiaobao, Liu, Xiaocheng, Liu, Xiaoyuan, Liu, Xinbo, Liu, Xu, Liu, Yang, Liu, Yanhu, Liu, Yanming, Liu, Yaqin, Liu, Yong, Liu, Zhihong, Long, Jing, Lu, Futang, Lu, Huamei, Lu, Jiapeng, Lu, Junhong, Lu, Weibin, Lu, Yanrong, Lu, Yuchun, Luan, Tianwei, Luo, Qingwei, Luo, Qun, Luo, Tian, Luo, Xia, Luo, Yongmei, Lv, Jing, Lv, Jinhai, Lv, Lei, Lv, Lili, Lv, Meng, Ma, Aiqing, Ma, Huaimin, Ma, Huihuang, Ma, Jie, Ma, Jinbao, Ma, Li, Ma, Lingzhen, Ma, Nan, Ma, Qiaojuan, Ma, Shumei, Ma, Tengfei, Ma, Xiange, Ma, Xiaowen, Ma, Yuehua, Mai, Lanxian, Mei, Xiao, Meng, Gen, Miao, Ruichao, Miao, Xue, Miao, Xuyan, Min, Tingting, Mo, Shubing, Morigentu, Nan, Tingyan, Ni, Jinyang, Ni, Shuguo, Nie, Yu, Ning, Benxing, Ning, Xiaowei, Niu, Manman, Niu, Qingying, Niu, Wentang, Niu, Xiaoxia, Ou, Fang, Pan, Biyun, Pan, Chengjie, Pan, Congming, Pan, Jieli, Pan, Xiaowen, Pan, Ziying, Pei, Guangzhong, Pei, Lingyu, Pei, Min, Pei, Yanzhen, Peng, Yinyu, Peng, Yuming, Pu, Zhaokun, Qi, Fengjun, Qi, Liwei, Qi, Meiqiong, Qi, Yan, Qian, Jun, Qin, Lei, Qin, Zhonghua, Qing, Lan, Qiu, Lixia, Qiu, Weiyu, Qiu, Xiaoling, Qu, Yueli, Quan, Minghua, Ren, Dingping, Ren, Hong, Ren, Lingzhi, Ren, Tingting, Ren, Wei, Ren, Yihui, Rong, Yufang, Ruan, Jiahui, Shang, Peiqin, Shao, Minyan, Shao, Xuefeng, Shao, Yuling, Shen, Junrong, Shen, Rui, Sheng, Lin, Shi, Jiangjie, Shi, Xun, Shi, Yanhong, Shi, Yeju, Shi, Yujiao, Shu, Bo, Song, Bingchun, Song, Dan, Song, Jinhui, Song, Jinwang, Song, Jinxian, Song, Wei, Song, Xiaoping, Song, Yawen, Su, He, Su, Qinfeng, Su, Shuhong, Su, Xiaozhou, Sun, Chengxiang, Sun, Fangfang, Sun, Gongping, Sun, Jiangnan, Sun, Mengmeng, Sun, Rongrong, Sun, Shuting, Sun, Songtao, Sun, Ying, Sun, Yongmiao, Sun, Yunhong, Sun, Zhiqiang, Suo, Mengying, Tan, Binghu, Tang, Chunyan, Tang, Zhongli, Tao, Yu, Tian, Changming, Tian, Hongmei, Tian, Jian, Tian, Xiaomin, Wan, Huaibin, Wan, Qin, Wan, Rongjun, Wang, Bobin, Wang, Chao, Wang, Chaoqun, Wang, Chengliang, Wang, Di, Wang, Enfang, Wang, Feng, Wang, Gang, Wang, Guangqiang, Wang, Guixiang, Wang, Haifeng, Wang, Haijun, Wang, Haiyang, Wang, Jianfang, Wang, Jianfeng, Wang, Jing, Wang, Junping, Wang, Junying, Wang, Kang, Wang, Lei, Wang, Lei, Wang, Lin, Wang, Lize, Wang, Meng, Wang, Pan, Wang, Qi, Wang, Qiong, Wang, Qiuli, Wang, Qiuxue, Wang, Ran, Wang, Shaojin, Wang, Shuai, Wang, Tao, Wang, Tiantian, Wang, Tinghui, Wang, Tongyan, Wang, Wanhong, Wang, Wenjuan, Wang, Wenyan, Wang, Wenying, Wang, Wenzhuan, Wang, Xiaofei, Wang, Xiaoyan, Wang, Xitong, Wang, Xu, Wang, Yan, Wang, Yan, Wang, Yan, Wang, Yanfang, Wang, Yang, Wang, Yang, Wang, Yanping, Wang, Yanying, Wang, Yaoxin, Wang, Yingli, Wang, Yiting, Wang, Yue, Wang, Yumei, Wang, Yuzhuo, Wang, Zhenhua, Wang, Zhifang, Wang, Zhimin, Wei, Chunli, Wei, Lixia, Wei, Pei, Wei, Shuying, Wei, Xiqing, Wen, Hong, Wen, Yun, Wu, Chaoqun, Wu, Hairong, Wu, Lihua, Wu, Lingxiang, Wu, Qi, Wu, Shaorong, Wu, Wenting, Wu, Xueyi, Wu, Yongshuan, Wu, Zhihao, Wu, Zhuying, Wu, Zongyin, Wuhanbilige, Xia, Jun, Xia, Yang, Xiang, Jing, Xiao, Heliu, Xiao, Yaying, Xie, Meiling, Xie, Yinyan, Xin, Huiling, Xing, Jing, Xiu, Guoquan, Xu, Baohua, Xu, Chuangze, Xu, En, Xu, Jian, Xu, Shuli, Xu, Wei, Xu, Wen, Xue, Na, Xue, Tingting, Xue, Wei, Yan, Haiyan, Yan, Xiaofang, Yan, Yanqing, Yang, Bo, Yang, Hui, Yang, Huiyu, Yang, Jinhua, Yang, Kun, Yang, Man, Yang, Mengya, Yang, Ning, Yang, Ping, Yang, Xiajiao, Yang, Xiaomo, Yang, Xin, Yang, Xiujuan, Yang, Xuemei, Yang, Xuming, Yang, Yan, Yang, Yanhua, Yang, Yi, Yang, Yuanyuan, Yang, Zhimei, Yang, Zhiming, Yao, Hui, Yao, Lu, Ye, Jinling, Ye, Wenhua, Yi, Mingjiao, Yi, Shaowei, Yi, Wenyi, Yi, Zhimin, Yin, Guangxia, Yin, Guoyuan, Yu, Guibin, Yu, Hairong, Yu, Huaitao, Yu, Lijie, Yu, Lijun, Yu, Nana, Yu, Qin, Yu, Xinli, Yu, Yi, Yuan, Biao, Zeng, Chunmei, Zhai, Na, Zhai, Xiaojuan, Zhan, Hongju, Zhang, Aizhen, Zhang, Baohua, Zhang, Bin, Zhang, Caizhu, Zhang, Chaoying, Zhang, Chengbo, Zhang, Chunlai, Zhang, Churuo, Zhang, Fan, Zhang, Feiqin, Zhang, Ge, Zhang, Haibo, Zhang, Hailin, Zhang, Hanxue, Zhang, Huaixing, Zhang, Hui, Zhang, Huijuan, Zhang, Jinguo, Zhang, Jingyu, Zhang, Jinyun, Zhang, Jisheng, Zhang, Jun, Zhang, Lei, Zhang, Li, Zhang, Li, Zhang, Liang, Zhang, Lifeng, Zhang, Lina, Zhang, Liping, Zhang, Liping, Zhang, Min, Zhang, Ping, Zhang, Qiang, Zhang, Rufang, Zhang, Ruifen, Zhang, Shengde, Zhang, Siqi, Zhang, Sufang, Zhang, Tingting, Zhang, Wanyue, Zhang, Weiliang, Zhang, Xiaohan, Zhang, Xiaohong, Zhang, Xiaojuan, Zhang, Xin, Zhang, Xin, Zhang, Xue, Zhang, Xuewei, Zhang, Yachen, Zhang, Yang, Zhang, Yanyan, Zhang, Yaojie, Zhang, Yingyu, Zhang, Yuan, Zhang, Yun, Zhang, Yunfeng, Zhang, Zaozhang, Zhang, Zhichao, Zhao, Baihui, Zhao, Dan, Zhao, Fuxian, Zhao, Guizeng, Zhao, Haijie, Zhao, Honglei, Zhao, Huizhen, Zhao, Jindong, Zhao, Juan, Zhao, Liming, Zhao, Ling, Zhao, Lingshan, Zhao, Qingxia, Zhao, Qiuping, Zhao, Wanchen, Zhao, Wangxiu, Zhao, Weiyi, Zhao, Xiaodi, Zhao, Xiaojing, Zhao, Xiaoli, Zhao, Xiaoyan, Zhao, Xiling, Zhao, Yannan, Zhao, Yiyuan, Zheng, Shuzhen, Zheng, Xin, Zhi, Lixia, Zhong, Hui, Zhong, Qing, Zhong, Xin, Zhong, Yunzhi, Zhou, Jianfeng, Zhou, Jihu, Zhou, Ke, Zhou, Liangliang, Zhou, Ling, Zhou, Na, Zhou, Shengcheng, Zhou, Suyun, Zhou, Tao, Zhou, Wanren, Zhou, Weifeng, Zhou, Weijuan, Zhou, Xiaohong, Zhou, Yunke, Zhou, Yuquan, Zhou, Zhaohai, Zhou, Zhiming, Zhu, Bingpo, Zhu, Jifa, Zhu, Jing, Zhu, Mengnan, Zhu, Youcun, Zong, Dafei, Zuo, Hongbo, and Zuo, Zhaokai

Abstract

Uncertainty exists about whether lowering systolic blood pressure to less than 120 mm Hg is superior to that of less than 140 mm Hg, particularly in patients with diabetes and patients with previous stroke.

Published
2024
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36. Bisphosphonate-induced differential modulation of immune cell function in gingiva and bone marrow in vivo : Role in osteoclast-mediated NK cell activation

Author

Tseng, Han-Ching, Kanayama, Keiichi, Kaur, Kawaljit, Park, So-Hyun, Park, Sil, Kozlowska, Anna, Sun, Shuting, McKenna, Charles E, Nishimura, Ichiro, and Jewett, Anahid

Subjects
Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Alendronate, Animals, Apoptosis, Bone Marrow, Cell Communication, Cell Differentiation, Diphosphonates, Female, Gingiva, Humans, Imidazoles, Killer Cells, Natural, Macrophages, Mice, Mice, Inbred C57BL, Monocytes, Osteoclasts, Zoledronic Acid, Immunology Section, osteoclasts, bisphosphonate, NK cell, zoledronate, etidronate, Immune response, Immunity, Immunology and Microbiology Section, Oncology and Carcinogenesis
Abstract

The aim of this study is to establish osteoclasts as key immune effectors capable of activating the function of Natural Killer (NK) cells, and expanding their numbers, and to determine in vivo and in vitro effect of bisphosphonates (BPs) during NK cell interaction with osteoclasts and on systemic and local immune function. The profiles of 27 cytokines, chemokines and growth factors released from osteoclasts were found to be different from dendritic cells and M1 macrophages but resembling to untreated monocytes and M2 macrophages. Nitrogen-containing BPs Zoledronate (ZOL) and Alendronate (ALN), but not non-nitrogen-containing BPs Etidronate (ETI), triggered increased release of pro-inflammatory mediators from osteoclasts while all three BPs decreased pit formation by osteoclasts. ZOL and ALN mediated significant release of IL-6, TNF-` and IL-1β, whereas they inhibited IL-10 secretion by osteoclasts. Treatment of osteoclasts with ZOL inhibited NK cell mediated cytotoxicity whereas it induced significant secretion of cytokines and chemokines. NK cells lysed osteoclasts much more than their precursor cells monocytes, and this correlated with the decreased expression of MHC class I expression on osteoclasts. Intravenous injection of ZOL in mice induced pro-inflammatory microenvironment in bone marrow and demonstrated significant immune activation. By contrast, tooth extraction wound of gingival tissues exhibited profound immune suppressive microenvironment associated with dysregulated wound healing to the effect of ZOL which could potentially be responsible for the pathogenesis of Osteonecrosis of the Jaw (ONJ). Finally, based on the data obtained in this paper we demonstrate that osteoclasts can be used as targets for the expansion of NK cells with superior function for immunotherapy of cancer.

Published
2015

37. Resting State EEG Based Depression Recognition Research Using Deep Learning Method

Author

Mao, Wandeng, Zhu, Jing, Li, Xiaowei, Zhang, Xin, Sun, Shuting, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Wang, Shouyi, editor, Yamamoto, Vicky, editor, Su, Jianzhong, editor, Yang, Yang, editor, Jones, Erick, editor, Iasemidis, Leon, editor, and Mitchell, Tom, editor

Published
2018
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38. Bisphosphonate Uptake in Areas of Tooth Extraction or Periapical Disease

Author

Cheong, Simon, Sun, Shuting, Kang, Benjamin, Bezouglaia, Olga, Elashoff, David, McKenna, Charles E, Aghaloo, Tara L, and Tetradis, Sotirios

Subjects
Dental/Oral and Craniofacial Disease, Oral and gastrointestinal, Musculoskeletal, Animals, Diphosphonates, Fluorescein, Imidazoles, Male, Mice, Mice, Inbred C57BL, Periapical Diseases, Tooth Extraction, Zoledronic Acid
Abstract

PurposeBisphosphonates (BPs) are widely used for the management of bone diseases such as osteoporosis and bone malignancy. However, osteonecrosis of the jaws (ONJ) is a serious complication of BP treatment. ONJ lesions mainly occur after extraction of teeth deemed unrestorable or around teeth with active periodontal or periapical disease. Because socket healing or dental disease shows higher bone turnover, the authors hypothesized that preferentially high BP accumulation would be observed in these areas.Materials and methodsThe authors tested the uptake of fluorescein-labeled zoledronic acid (5-FAM-ZOL) in sites of tooth extraction or experimental periapical disease in mice. Maxillary molars were extracted or the crowns of mandibular molars were drilled to induce pulp exposure. Animals were injected with 5-FAM-ZOL 200 μg/kg at various times after intervention and fluorescence was measured at healthy versus intervention sites. Fluorescein injections were used as controls. Data were analyzed by t test and mixed effects linear models were constructed because the animals had repeated measurements over time and at the 2 sites.ResultsA statistically significant (P≤.001 to .002) time-dependent uptake of 5-FAM-ZOL was detected in the areas of extraction socket and in the alveolar ridge around teeth with periapical disease compared with the healthy contralateral sites of the same animals. For the 2 conditions, the uptake reached a maximum 3 days after experimental intervention and decreased thereafter.ConclusionsThese data suggest that sites with increased bone turnover, such as extraction sites or areas of periapical inflammation, are exposed to higher BP doses than the remaining alveolar ridge and could explain, at least in part, the susceptibility of such areas to ONJ.

Published
2014

48. Evidence of Bisphosphonate-Conjugated Sitafloxacin Eradication of Established Methicillin-Resistant S. aureus Infection with Osseointegration in Murine Models of Implant-Associated Osteomyelitis

Author

Xie, Chao, primary, Ren, Youliang, additional, Weeks, Jason, additional, Xue, Thomas, additional, Rainbolt, Joshua, additional, Bentley, Karen de Mesy, additional, Shu, Ye, additional, Liu, Yuting, additional, Masters, Elysia, additional, Cherian, Philip, additional, McKenna, Charles, additional, Neighbors, Jeffrey, additional, Ebetino, Frank, additional, Schwarz, Edward, additional, and Sun, Shuting, additional

Published
2023
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49. Data from Real-Time Intravital Imaging Establishes Tumor-Associated Macrophages as the Extraskeletal Target of Bisphosphonate Action in Cancer

Author

Junankar, Simon, primary, Shay, Gemma, primary, Jurczyluk, Julie, primary, Ali, Naveid, primary, Down, Jenny, primary, Pocock, Nicholas, primary, Parker, Andrew, primary, Nguyen, Akira, primary, Sun, Shuting, primary, Kashemirov, Boris, primary, McKenna, Charles E., primary, Croucher, Peter I., primary, Swarbrick, Alexander, primary, Weilbaecher, Katherine, primary, Phan, Tri Giang, primary, and Rogers, Michael J., primary

Published
2023
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50. Supplementary Movie 1 from Real-Time Intravital Imaging Establishes Tumor-Associated Macrophages as the Extraskeletal Target of Bisphosphonate Action in Cancer

Author

Junankar, Simon, primary, Shay, Gemma, primary, Jurczyluk, Julie, primary, Ali, Naveid, primary, Down, Jenny, primary, Pocock, Nicholas, primary, Parker, Andrew, primary, Nguyen, Akira, primary, Sun, Shuting, primary, Kashemirov, Boris, primary, McKenna, Charles E., primary, Croucher, Peter I., primary, Swarbrick, Alexander, primary, Weilbaecher, Katherine, primary, Phan, Tri Giang, primary, and Rogers, Michael J., primary

Published
2023
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