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4. 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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8. Development and validation of a new risk assessment model for immunomodulatory drug-associated venous thrombosis among Chinese patients with multiple myeloma

Author

Li, Xiaozhe, Sun, Xiuli, Fang, Baijun, Leng, Yun, Sun, Fangfang, Wang, Yaomei, Wang, Qing, Jin, Jie, Yang, Min, Xu, Bing, Fang, Zhihong, Chen, Lijuan, Chen, Zhi, Yang, Qimei, Zhang, Kejie, Ye, Yinhai, Geng, Hui, Sun, Zhiqiang, Hao, Dan, Huang, Hongming, Wang, Xiaotao, Jing, Hongmei, Ma, Lan, Pan, Xueyi, Chen, Wenming, and Li, Juan

Published
2023
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24. Predicting the Risk of Fundus Lesions in Systemic Lupus Erythematosus: A Nomogram Model.

Author

Xie, Huan, Sun, Fangfang, Yang, Huimin, Li, Jin, and Raza, Faisal

Abstract

Objectives. This study aimed to use laboratory and clinical data of systemic lupus erythematosus (SLE) patients to construct prediction models for fundus complications in SLE. Methods. Routine blood test data and clinical information of 277 SLE patients were collected retrospectively. Based on their fundus examination, they were divided into two groups, with or without fundus lesions, defined as retinopathy and choroidopathy in this study. The data of the two groups were compared, and the prediction model was established using binary logistic regression analysis. Results. There were 85 patients in the fundus lesions' group and 192 patients in the control group. Between the two groups, age, SLEDAI, serositis, hypertension, diabetes, anticardiolipin antibody (ACA), anti‐Sm antibody, C‐reactive protein (CRP), hemoglobin (Hb), platelet count (PLT), albumin (Alb), serum creatinine(Scr), urea, uric acid(UA), and immunoglobulin G(IgG) were significantly different (p < 0.05). Besides, age, SLEDAI, serositis, hypertension, diabetes, anti‐SSB, CRP, Hb, PLT, FIB, Alb, Scr, urea, UA, GLU, and IgG were significantly correlated with SLE‐related fundus lesions. PLT, fibrinogen (FIB), IgG, and urea were independent risk factors of SLE‐related fundus lesions. The area under the curve (AUC) was 0.830 (p < 0.001; 95% CI = 0.762–0.898), and the nomogram was established with great evaluation efficiency demonstrated by the calibration curve and the Hosmer–Lemeshow test. The result of k‐fold cross‐validation also showed high prediction accuracy. Conclusions. We have found the independent risk factors of SLE‐related fundus lesions and developed a model to improve the prediction of fundus lesions in SLE. [ABSTRACT FROM AUTHOR]

Published
2024
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25. General method to digitalize multi-layer woven structure.

Author

Sun, Fangfang, Zhou, Haili, Gu, Lijun, Han, Chenchen, Huang, Jian, Li, Chao, Zhang, Liquan, and Zhao, Qian

Abstract

As an advanced composite reinforcement, multi-layer woven fabrics are widely used in industries. However, for most nonprofessional engineers and researchers, the complexity of the spatial architecture of multi-layer woven structure (MLWS) makes it difficult to understand and apply. In order to fully utilize the advantage of the designability of MLWS, a digitalization expression is used to define the design variable of MLWS by 8 parameters. This expression has wide universality and practicability, which can parametrize all kinds of MLWSs, and characterize full-scale complex preforms. Based on this expression, a general method and process for constructing novel and complex MLWS architectures are also proposed and developed. Furthermore, a method to generate the preform jacquard pattern for the electronic jacquard system is also developed to demonstrate the application in manufacturing. This digitalization expression can be considered as the key point to connect the material design and automatic manufacturing, which can improve the design technology of multi-layer woven composite material. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Effects of concentrated sulfuric acid etching durations on the shear bond strength between polyether-ketone-ketone and dentin

Author

WANG Chenwei, SUN Fangfang, YANG Chuncheng, DING Ling, CHEN Xi, ZHANG Jiaqi, and WU Guofeng

Subjects
polyether-ketone-ketone, surface treatment, dentin, bonding, primer, relyxtm ultimate, shear bond strength, scanning electron microscope, Medicine
Abstract

Objective To study the effects of different concentrated sulfuric acid etching durations on the shear bond strength between polyether-ketone-ketone (PEKK) and dentin, providing a scientific basis for the clinical bonding procedures of PEKK prosthesis. Methods Forty-four PEKK specimens were prepared and randomly divided into four groups: group A was the control group, which was only polished with abrasive papers, group B, group C and group D were experimental groups, which were etched by 98% concentrated sulfuric acid for 5 s, 30 s and 60 s, respectively. In addition, one sample was randomly selected from each group, and the profile was prepared by a slow cutting machine. The surface morphology of the profile was observed under SEM. After the four groups of specimens and dentin were bonded by resin, they were soaked in distilled water at 37 ℃ for 24 h. After the shear bonding strengths were measured, the fracture interfaces of the specimens were examined by the scanning electron microscopy and stereomicroscopy, and failure models of bonding were analyzed. Results After acid etching treatments, the cross-sectional images in group B presented uniform spongy shapes, while the cross-sectional images in group C and group D showed destructive pore structures. The shear bond strengths of group B (16.84 ± 1.84) MPa, group C (12.33 ± 1.22) MPa and group D (6.44 ± 1.18) MPa were higher than that of group A (3.99 ± 1.06) MPa (P < 0.05). The highest shear bond strength was observed in group B (16.84 ± 1.84) MPa. Conclusion The surface treatment of 98% sulfuric acid etching for 5 s manifested the best bond strength between PEKK and dentin.

Published
2021
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32. Green and efficient method for the realization of full-component recovery of LiFePO4 black powder.

Author

Gao, Mai, Sun, Fangfang, Peng, Wenxiu, Dai, Wenbin, Zhang, Zaiwu, Zhang, Lei, Zhang, Hongzhou, Ma, Yue, Zhang, Lianqi, and Song, Dawei

Subjects
*WASTE recycling, *LIQUID waste, *POLLUTION, *WASTE gases, *POWDERS, *GEOLOGICAL carbon sequestration
Abstract

With regard to retired LiFePO4 batteries, resource treatment has become a matter of public concern. The currently used wet recycling process causes secondary environmental pollution and has the difficulty of full-component recovery. Therefore, a green and efficient recovery process for the realization of full-component recovery of LiFePO4 black powder is proposed in this work. In this closed-loop process with liquid flow circulation, no waste liquid and gas emission is generated, and the purity of recycled Li2CO3 can reach up to 99.4%. Moreover, battery-grade FePO4 can be obtained after simple treatment, solving the problem of lithium tailings and slag in the traditional wet recycling process. The performances of recycled Li2CO3 and FePO4 are similar to commercialization products according to electrochemical tests. More importantly, the resynthesized LiFePO4 cathode displays high-capacity retention of 97.5% after 200 cycles at 0.5 C, indicating the superiority of our strategy. Furthermore, the pouch cell with 5.2 A h presents outstanding performance, and high-capacity retentions of 96% and 95.2% can be observed after 500 cycles at 0.5 C and 1 C, respectively. The aforementioned results indicate the attractive prospects of this green and efficient lithium extraction and full-component recovery process. [ABSTRACT FROM AUTHOR]

Published
2024
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33. Exploration of the Effects of Cadmium Stress on Photosynthesis in Oenanthe javanica (Blume) DC.

Author

Zhou, Ronghua, Xu, Jun, Li, Liangjun, Yin, Yulai, Xue, Bowen, Li, Jingjing, and Sun, Fangfang

Subjects
ELECTRON transport, PHOTOSYNTHESIS, AQUATIC plants, POLLUTANTS, CHLOROPHYLL spectra
Abstract

Cadmium ion (Cd2+) stress is a major abiotic stressor affecting plant photosynthesis. However, the impact of sustained high-concentration Cd stress on the photosynthetic electron transport chain of aquatic plants is currently unclear. Here, prompt fluorescence (PF), delayed fluorescence (DF), and P700 signals were simultaneously measured to investigate the effect of Cd stress on photosynthesis in water dropwort [Oenanthe javanica (Blume) DC.]. We aimed to elucidate how Cd stress continuously affects the electron transport chain in this species. The PF analysis showed that with prolonged Cd stress, the FJ, FI and FP steadily decreased, accompanied by a positive shift in the K-band and L-band. Moreover, JIP-test parameters, including TRO/ABS, ABS/CSO, TRO/CSO and PIABS, were significantly reduced. The P700 signals showed that exposure to Cd stress hindered both the fast decrease and slow increase phases of the MR transient, ultimately resulting in a gradual reduction in both VPSI and VPSII−PSI. The DF analysis showed a gradual decrease in the I1 and I2 values as the duration of stress from Cd increased. The above results suggested that Cd stress affected the photosynthetic electron transport in water dropwort by influencing the amount of active PSII and PSI, primarily affecting PSII RCs in the early to mid-stages and PSI reductive activity in the later stage. [ABSTRACT FROM AUTHOR]

Published
2024
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34. Spatiotemporal Controllable Sono‐Nanovaccines Driven by Free‐Field Based Whole‐Body Ultrasound for Personalized Cancer Therapy.

Author

Wang, Yang, Li, Guangzhe, Su, Jianlong, Liu, Yiming, Zhang, Xiaomai, Zhang, Guanyi, Wu, Zhihao, Li, Jinrong, Zhang, Yuxuan, Wang, Xu, Yang, Zejia, Wang, Ruimin, Wang, Chengdong, Wang, Liu, Sun, Fangfang, Zhao, Weijie, Wang, Xuejian, Peng, Xiaojun, and Shao, Kun

Subjects
CANCER treatment, TUMOR antigens, CANCER vaccines, ULTRASONIC imaging, CARCINOMA in situ
Abstract

Therapeutic cancer vaccines fail to produce satisfactory outcomes against solid tumors since vaccine‐induced anti‐tumor immunity is significantly hampered by immunosuppression. Generating an in situ cancer vaccine targeting immunological cold tumor microenvironment (TME) appears attractive. Here, a type of free‐field based whole‐body ultrasound (US)‐driven nanovaccines are constructed, named G5‐CHC‐R, by conjugating the sonosensitizer, Chenghai chlorin (CHC) and the immunomodulator, resiquimod (R848) on top of a super small‐sized dendrimeric nanoscaffold. Once entering tumors, R848 can be cleaved from a hypoxia‐sensitive linker, thus modifying the TME via converting macrophage phenotypes. The animals bearing orthotopic pancreatic cancer with intestinal metastasis and breast cancer with lung metastasis are treated with G5‐CHC‐R under a free‐field based whole‐body US system. Benefit from the deep penetration capacity and highly spatiotemporal selectiveness, G5‐CHC‐R triggered by US represented a superior alternative for noninvasive irradiation of deep‐seated tumors and magnification of local immune responses via driving mass release of tumor antigens and "cold‐warm‐hot" three‐state transformation of TME. In addition to irradiating primary tumors, a robust adaptive anti‐tumor immunity is potentiated, leading to successful induction of systemic tumor suppression. The sono‐nanovaccines with good biocompatibility posed wide applicability to a broad spectrum of tumors, revealing immeasurable potential for translational research in oncology. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Meta-Learning Enhanced Trade Forecasting: A Neural Framework Leveraging Efficient Multicommodity STL Decomposition.

Author

Ma, Bohan, Xue, Yushan, Chen, Jing, and Sun, Fangfang

Abstract

In the dynamic global trade environment, accurately predicting trade values of diverse commodities is challenged by unpredictable economic and political changes. This study introduces the Meta-TFSTL framework, an innovative neural model that integrates Meta-Learning Enhanced Trade Forecasting with efficient multicommodity STL decomposition to adeptly navigate the complexities of forecasting. Our approach begins with STL decomposition to partition trade value sequences into seasonal, trend, and residual elements, identifying a potential 10-month economic cycle through the Ljung–Box test. The model employs a dual-channel spatiotemporal encoder for processing these components, ensuring a comprehensive grasp of temporal correlations. By constructing spatial and temporal graphs leveraging correlation matrices and graph embeddings and introducing fused attention and multitasking strategies at the decoding phase, Meta-TFSTL surpasses benchmark models in performance. Additionally, integrating meta-learning and fine-tuning techniques enhances shared knowledge across import and export trade predictions. Ultimately, our research significantly advances the precision and efficiency of trade forecasting in a volatile global economic scenario. [ABSTRACT FROM AUTHOR]

Published
2024
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36. Controlled Reflected McKean–Vlasov SDEs and Neumann Problem for Backward SPDEs.

Author

Ma, Li, Sun, Fangfang, and Han, Xinfang

Subjects
*NEUMANN problem, *STOCHASTIC partial differential equations, *STOCHASTIC differential equations, *NEUMANN boundary conditions, *STOCHASTIC control theory
Abstract

This paper is concerned with the stochastic optimal control problem of a 1-dimensional McKean–Vlasov stochastic differential equation (SDE) with reflection, of which the drift coefficient and diffusion coefficient can be both dependent on the state of the solution process along with its law and control. One backward stochastic partial differential equation (BSPDE) with the Neumann boundary condition can represent the value function of this control problem. Existence and uniqueness of the solution to the above equation are obtained. Finally, the optimal feedback control can be constructed by the BSPDE. [ABSTRACT FROM AUTHOR]

Published
2024
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44. Mn Cluster-Embedded N/F Co-Doped Carbon toward Mild Aqueous Supercapacitors.

Author

Zheng, Chen, Han, Xu, Sun, Fangfang, Zhang, Yue, Huang, Zihang, and Ma, Tianyi

Subjects
SUPERCAPACITORS, SUPERCAPACITOR electrodes, ENERGY storage equipment, DOPING agents (Chemistry), CARBON-based materials, ENERGY density, TRANSITION metals, MANGANESE, FULLERENES
Abstract

Aqueous supercapacitors have occupied a significant position among various types of stationary energy storage equipment, while their widespread application is hindered by the relatively low energy density. Herein, N/F co-doped carbon materials activated by manganese clusters (NCM) are constructed by the straightforward experimental routine. Benefiting from the elevated conductivity structure at the microscopic level, the optimized NCM-0.5 electrodes exhibited a remarkable specific capacitance of 653 F g−1 at 0.4 A g−1 and exceptional cycling stability (97.39% capacity retention even after 40,000 cycles at the scanning rate of 100 mV s−1) in a neutral 5 M LiCl electrolyte. Moreover, we assembled an asymmetric device pairing with a VOx anode (NCM-0.5//VOx), which delivered a durable life span of 95% capacity retention over 30,000 cycles and an impressive energy density of 77.9 Wh kg−1. This study provides inspiration for transition metal element doping engineering in high-energy storage equipment. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Global burden of diabetes mellitus from 1990 to 2019 attributable to dietary factors: An analysis of the Global Burden of Disease Study 2019.

Author

Hong, Ting, Sun, Fangfang, Wang, Qiwei, Chen, Xufeng, and Han, Kun

Subjects
*GLOBAL burden of disease, *MEAT, *FACTOR analysis, *DIABETES
Abstract

Aims: To analyse spatial and temporal changes in the global burden of diabetes mellitus (DM) attributable to dietary factors from 1990 to 2019. Materials and Methods: The burden of DM was analysed in terms of age‐standardized disability‐adjusted life‐year (DALY) rates and age‐standardized death rates (ASDRs), which were obtained from the Global Burden of Disease Study 2019, and their corresponding estimated annual percentage changes (EAPCs). Results: The ASDR exhibited a decreasing trend (EAPC = −0.02), while the age‐standardized DALY rate exhibited an increasing trend (EAPC = 0.65). Forty‐four percent of the burden of DM was attributable to dietary factors, with the three largest contributors being high intake of red meat, high intake of processed meat, and low intake of fruit. Residence in a region with a high sociodemographic index (SDI) was associated with a diet low in whole grains and high in red meat and processed meat, while residence in a low‐SDI region was associated with a diet low in whole grains and fruits, and high in red meat. Conclusions: The age‐standardized DALYs of DM attributable to dietary factors increased between 1990 and 2019 but differed among areas. The three largest dietary contributors to the burden of DM were high intake of red meat, high intake of processed meat, and low intake of fruit. [ABSTRACT FROM AUTHOR]

Published
2024
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