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107. Knowledge of Child Health and Affecting Factors Among Preschool Teachers: A Cross-Sectional Study in Chongqing, China

Author

Hu H, Wu T, Fan L, Zuo K, Chen L, Zhang J, and Zhao X

Subjects
preschool teachers, preschool children, health knowledge, supportive measures, Public aspects of medicine, RA1-1270
Abstract

Hongmei Hu,1– 4,* Tingting Wu,3,* Luying Fan,5 Keying Zuo,5 Ling Chen,5 Jiaqiong Zhang,1,3 Xin Zhao2 1College of Pre-School Education, Chongqing University of Education, Chongqing 400067, People’s Republic of China; 2Children’s Research Institute, Chongqing University of Education, Chongqing 400067, People’s Republic of China; 3Chongqing Collaborative Innovation Center for Functional Food, Chongqing University of Education, Chongqing 400067, People’s Republic of China; 4Family Education Guidance Center for 0– 6 Years Old, Chongqing University of Education, Chongqing 400067, People’s Republic of China; 5School of Public Health and Management, Chongqing Medical University, Chongqing 400016, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jiaqiong Zhang; Xin Zhao Tel +86-23-6163-8842; +86-23-6265-3650Email cque@foxmail.com; zhaoxin@cque.edu.cnAim: This research aims to explore the health knowledge mastery of preschool teachers in Chongqing.Methods: A cross-sectional questionnaire survey of preschool teachers in Chongqing was conducted by random sampling. A total of 399 preschool teachers were included in this research. Multiple linear regression analysis was conducted to explore the influencing factors on preschool teachers’ mastery of preschool child health knowledge.Results: This research found that the average score of preschool teacher’s knowledge of preschool children was only 34.01± 0.78, and the accuracy of the knowledge points of continuous short-distance eye use time was the lowest, at less than 5%. The conducting of eye exercises by the kindergarten and the scores of preschool teachers were negatively correlated (β=− 0.257, p< 0.001); the score of health knowledge of preschool teachers of the kindergarten whose screen time met the standard was lower (β=− 0.113, p=0.017); whether the time and frequency for outdoor activities of the kindergarten met the standards and the health knowledge score of preschool teachers was positively correlated (β=0.130, p< 0.001 vs β=0.163, p< 0.001). Male preschool teachers and teachers overweight according to BMI had higher scores for preschool health knowledge (β=− 0.114, p=0.016 vs β=0.099, p=0.034).Conclusion: Preschool teachers in Chongqing had a poor grasp of knowledge regarding preschool children’s health, and in particular, knowledge of children’s exercise and eye use. Educational background and work experience may no longer indicate preparedness for teaching these topics, and suggests that supportive measures can also be directly provided at the kindergarten level in the future to increase the health knowledge of preschool teachers.Keywords: preschool teachers, preschool children, health knowledge, supportive measures

Published
2020

108. Blood Flow Index and Skin Temperature Measured by Laser Speckle Contrast Imaging and Infrared Thermography After Specific Ultrasound-Guided Blocking of the C6, C7 Nerve Root: A Case Report

Author

Zhang S, Fan L, and Mei W

Subjects
selective nerve root block, laser speckle contrast imaging, infrared thermography, ultrasound guidance, Medicine (General), R5-920
Abstract

Shuang Zhang, Longchang Fan, Wei Mei Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province 430030, People’s Republic of ChinaCorrespondence: Longchang FanDepartment of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Ave 1095, Wuhan, Hubei Province 430030, People’s Republic of ChinaEmail flc5200@tjh.tjmu.edu.cnWei MeiDepartment of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Ave 1095, Wuhan, Hubei Province 430030, People’s Republic of ChinaTel + 86- 130 0616 2508Email wmei@hust.edu.cnAbstract: Ultrasound-guided cervical nerve root block is the technique of injecting local anesthetic or steroid into the intertubercular groove outside of the cervical foramen under real-time ultrasound guidance. It has established diagnostic and therapeutic employment for patients suffering symptoms caused by cervical disc disorders and foraminal stenosis. Measures of selective nerve root blockade would have vital clinical utility, especially in multilevel disease or combined with atypical symptoms, where subjective assessment is difficult. This case reported a 47-year-old male patient who suffered from severe radicular pain confined to the index and middle fingers, with weakness of the right upper extremity. He was successfully treated with selective C6, C7 nerve root under ultrasound guidance. For confirmation of the proper analgesia range, laser speckle contrast imaging (LSCI) and infrared thermography (IT) were both constructed over the dorsum of the hands and forearms during the procedure. The results of the off-line analysis suggested LSCI and IT might be considered as alternative measurements for the selective cervical nerve root.Keywords: selective nerve root block, laser speckle contrast imaging, infrared thermography, ultrasound guidance

Published
2020

109. Structural Insight into the Mechanism of 4-Aminoquinolines Selectivity for the alpha2A-Adrenoceptor

Author

Li Z, Li J, Liu L, Deng W, Liu Q, Liu R, Zhang W, He Z, Fan L, Yang Y, Duan Y, Hou H, Wang X, Yang Z, Chen S, Wang Y, Huang N, and Chen J

Subjects
alpha2-adrenoceptor, selectivity, linker length, allosteric modulation, Therapeutics. Pharmacology, RM1-950
Abstract

Zaibing Li,1,2,* Jingyu Li,1,* Liyan Liu,1 Wenyi Deng,3 Qingrong Liu,4 Ruofan Liu,4 Wen Zhang,3 Zaiqing He,5 Lei Fan,6 Yingzhuo Yang,7 Yun Duan,7 Huifang Hou,1 Xinyuan Wang,1 Zhimei Yang,1 Xiaoying Wang,1 Shanze Chen,1 Yi Wang,1 Ning Huang,1 Junli Chen1 1Department of Pathophysiology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, People’s Republic of China; 2Department of Pathophysiology, School of Basic Medical Science, Southwest Medical University, Luzhou, Sichuan 646000, People’s Republic of China; 3West China Medical School, Sichuan University, Chengdu 610041, People’s Republic of China; 4West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu 610041, People’s Republic of China; 5Department of Pathology, Nuclear of Industry 416 Hospital, Chengdu, Sichuan 610051, People’s Republic of China; 6Department of Occupational Medicine, Nuclear of Industry 416 Hospital, Chengdu, Sichuan 610051, People’s Republic of China; 7Department of Nuclear Medicine, Sichuan Cancer Hospital, Chengdu 610041, People’s Republic of China*These authors contributed equally to this workCorrespondence: Junli Chen; Ning Huang Email chenjunlinsf@163.com; ninghuangcjl@163.comBackground: α2A-adrenoceptor (AR) is a potential target for the treatment of degenerative diseases of the central nervous system, and α2A-AR agonists are effective drugs for this condition. However, the lack of high selectivity for α2A-AR subtype of traditional drugs greatly limits their clinic usage.Methods: A series of homobivalent 4-aminoquinolines conjugated by two 4-aminoquinoline moieties via varying alkane linker length (C2-C12) were characterized for their affinities for each α2-AR subtype. Subsequently, docking, molecular dynamics and mutagenesis were applied to uncover the molecular mechanism.Results: Most 4-aminoquinolines (4-aminoquinoline monomer, C2-C6, C8-C10) were selective for α2A-AR over α2B- and α2C-ARs. Besides, the affinities are of similar linker length-dependence for each α2-AR subtype. Among all the compounds tested, C10 has the highest affinity for α2A-AR (pKi=− 7.45± 0.62), which is 12-fold and 60-fold selective over α2B-AR and α2C-AR, respectively. Docking and molecular dynamics suggest that C10 simultaneously interacts with orthosteric and “allosteric” sites of the α2A-AR. The mutation of F205 decreases the affinity by 2-fold. The potential allosteric residues include S90, N93, E94 and W99.Conclusion: The specificity of C10 for the α2A-AR and the potential orthosteric and allosteric binding sites proposed in this study provide valuable guidance for the development of novel α2A-AR subtype selective compounds.Keywords: alpha2-adrenoceptor, selectivity, linker length, allosteric modulation

Published
2020

110. Predicting Stage of Exercise Among Patients with Type 2 Diabetes: A Test of the Extended Theory of Planned Behavior

Author

Gao M, Chen X, Sun X, Wang F, and Fan L

Subjects
theory of planned behavior, stage of change, exercise, descriptive norm, self-identity, Medicine (General), R5-920
Abstract

Min Gao,1,2 Xueying Chen,1 Xin Sun,1 Fengbin Wang,1 Lishi Fan,1 Xinying Sun1 1School of Public Health, Peking University Health Science Center, Beijing, People’s Republic of China; 2Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UKCorrespondence: Xinying SunSchool of Public Health, Peking University Health Science Center, 38, Xueyuan Road, Haidian District, Beijing 100191, People’s Republic of ChinaTel +86 136 9121 2050Email xysun@bjmu.edu.cnPurpose: This study aimed to predict stage of exercise among Chinese patients with type 2 diabetes by using an extended theory of planned behavior model (TPB) incorporating descriptive norm and self-identity.Patients and Methods: Participants (N=791) were included in a cross-sectional study. Structural equation modeling was used to explain how the extended TPB could predict the stage of exercise.Results: The model accounted for 41% of the variance in stage of exercise and 81.1% of the variance in intention. Intention (β=0.359, P< 0.01) and self-identity (β=0.236, P< 0.001) had a direct effect on stage of exercise. Self-identity (β=0.261, P< 0.001), descriptive norm (β=0.035, P< 0.05) and PBC (β=0.683, P< 0.001) were strong predicators of intention. The effects of self-identity and PBC on behavior were significantly mediated via intention. Age, BMI and stage of diet behavior were found to be significantly related to intention and behavior.Conclusion: This study has tested the usefulness of the extended TPB for explaining exercise in Chinese diabetic patients. To promote patients to start or continue exercising, interventions should target self-identity and controllability for physical activity.Keywords: theory of planned behavior, stage of change, exercise, descriptive norm, self-identity

Published
2020

111. RGFP966 Suppresses Tumor Growth and Migration Through Inhibition of EGFR Expression in Hepatocellular Carcinoma Cells in vitro

Author

Yu X, Yang F, Jiang H, and Fan L

Subjects
rgfp966, hepatocellular carcinoma, hdac3, egfr, Therapeutics. Pharmacology, RM1-950
Abstract

Xinying Yu, 1 Fan Yang, 2 Hong Jiang, 3 Ling Fan 1 1Second Pediatric Intensive Care Unit, Shengjing Hospital of China Medical University, Shenyang City, Liaoning Province, People’s Republic of China; 2Third Neonatal Ward, Shengjing Hospital of China Medical University, Shenyang City, Liaoning Province, People’s Republic of China; 3Second Neonatal Ward, Shengjing Hospital of China Medical University, Shenyang City, Liaoning Province, People’s Republic of ChinaCorrespondence: Xinying Yu; Ling FanShengjing Hospital of China Medical University, Shenyang City, Liaoning Province 110004, People’s Republic of ChinaTel/Fax +86 24-31939077Email fanl@sj-hospital.org; yuxinying0707@126.comPurpose: Histone deacetylase 3 (HDAC3) has been suggested to play a role in hepatocellular carcinoma (HCC). In the present report, we aimed to identify the effects of RGFP966, a specific HDAC3 inhibitor, on the cell proliferation and migration of HCC cell lines.Methods: Human HCC cell lines, which were identified using short tandem repeat (STR) DNA profiling analysis, were used in this report. Cell proliferation assay was used to identify the growth viability of cells. Wound healing and transwell assay were used to identify the migration ability of cells. Further, a human phospho-receptor tyrosine kinases array kit was used to screen out RGFP966 effects on key receptor tyrosine kinases. Then, the mRNA expression was quantified by real-time PCR, and protein expression was identified by Western blot immunoassay.Results: We found that RGFP966 inhibited both proliferation and migration of HCC cells. Further, RGFP966 represses the expression and phosphorylation levels of epidermal growth factor receptor (EGFR) in HCC cells. Moreover, HDAC3 is involved in the inhibition of EGFR by RGFP966. Overall, we elucidated an inhibitive function of RGFP966 in HCC progression.Conclusion: RGFP966 inhibits EGFR signaling pathway and suppresses proliferation and migration of HCC cells.Keywords: RGFP966, hepatocellular carcinoma, HDAC3, EGFR

Published
2020

114. JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo

Author

Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, Alexandros, T, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de Andre, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Bergnoli, A, Birkenfeld, T, Blin, S, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callegari, R, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Chan, C, Chang, J, Chang, Y, Chen, G, Chen, P, Chen, S, Chen, X, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chetverikov, A, Chiesa, D, Chimenti, P, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Di Lorenzo, S, Corti, D, Corso, F, Dalager, O, De La Taille, C, Deng, Z, Depnering, W, Diaz, M, Ding, X, Ding, Y, Dirgantara, B, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dusini, S, Dvorak, M, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, D, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Ford, R, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Gottel, A, Grassi, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, J, Guo, W, Guo, X, Guo, Y, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Ioannisian, A, Isocrate, R, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Joutsenvaara, J, Kalousis, L, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kutovskiy, N, Kuusiniemi, P, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Lippi, I, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martellini, C, Martin-Chassard, G, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meinusch, A, Meng, Y, Meregaglia, A, Meroni, E, Meyhofer, D, Mezzetto, M, Miller, J, Miramonti, L, Molla, M, Montini, P, Montuschi, M, Muller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, R, Paoloni, A, Parmeggiano, S, Pei, Y, Pelicci, L, Pelliccia, N, Peng, A, Peng, H, Peng, Y, Peng, Z, Perrot, F, Petitjean, P, Petrucci, F, Pilarczyk, O, Rico, L, Popov, A, Poussot, P, Previtali, E, Qi, F, Qi, M, Qian, S, Qian, X, Qian, Z, Qiao, H, Qin, Z, Qiu, S, Ranucci, G, Raper, N, Rasheed, R, Re, A, Rebber, H, Rebii, A, Redchuk, M, Ren, B, Ren, J, Ricci, B, Rifai, M, Roche, M, Rodphai, N, Romani, A, Roskovec, B, Ruan, X, Rybnikov, A, Sadovsky, A, Saggese, P, Sanfilippo, S, Sangka, A, Sawangwit, U, Sawatzki, J, Schever, M, Schwab, C, Schweizer, K, Selyunin, A, Serafini, A, Settanta, G, Settimo, M, Shao, Z, Sharov, V, Shaydurova, A, Shi, J, Shi, Y, Shutov, V, Sidorenkov, A, Simkovic, F, Sirignano, C, Siripak, J, Sisti, M, Slupecki, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Sokolov, S, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Sramek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Stefanik, D, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Su, J, Sun, S, Sun, X, Sun, Y, Sun, Z, Suwonjandee, N, Szelezniak, M, Tang, J, Tang, Q, Tang, X, Hariharan, V, Theisen, E, Tietzsch, A, Tkachev, I, Tmej, T, Torri, M, Treskov, K, Triossi, A, Troni, G, Trzaska, W, Tuve, C, Ushakov, N, Vedin, V, Verde, G, Vialkov, M, Viaud, B, Vollbrecht, C, Volpe, C, Sturm, K, Vorobel, V, Voronin, D, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, Wang, L, Wang, M, Wang, R, Wang, S, Wang, W, Wang, X, Wang, Y, Weng, Y, Wang, Z, Watcharangkool, A, Wei, W, Wei, Y, Wen, K, Wen, L, Weng, J, Wiebusch, C, Wong, S, Wonsak, B, Wu, D, Wu, Q, Wu, Z, Wurm, M, Wurtz, J, Wysotzki, C, Xi, Y, Xia, D, Xiao, X, Xie, X, Xie, Y, Xie, Z, Xin, Z, Xing, Z, Xu, B, Xu, C, Xu, D, Xu, F, Xu, H, Xu, J, Xu, M, Xu, Y, Yan, B, Yan, Q, Yan, T, Yan, W, Yan, X, Yan, Y, Yang, C, Yang, H, Yang, J, Yang, L, Yang, X, Yang, Y, Yeng, Y, Yao, H, Ye, J, Ye, M, Ye, Z, Yermia, F, You, Z, Yu, B, Yu, C, Yu, H, Yu, M, Yu, X, Yu, Z, Yuan, C, Yuan, Y, Yuan, Z, Yue, B, Zafar, N, Zavadskyi, V, Zeng, S, Zeng, T, Zeng, Y, Zhan, L, Zhang, A, Zhang, B, Zhang, F, Zhang, G, Zhang, H, Zhang, J, Zhang, M, Zhang, P, Zhang, Q, Zhang, S, Zhang, T, Zhang, X, Zhang, Y, Zhang, Z, Zhao, F, Zhao, J, Zhao, R, Zhao, S, Zheng, D, Zheng, H, Zheng, Y, Zhong, W, Zhou, J, Zhou, L, Zhou, N, Zhou, S, Zhou, T, Zhou, X, Zhu, J, Zhu, K, Zhu, Z, Zhuang, B, Zhuang, H, Zong, L, Zou, J, Zwickel, S, Abusleme A., Adam T., Ahmad S., Ahmed R., Aiello S., Akram M., Aleem A., Alexandros T., An F., An Q., Andronico G., Anfimov N., Antonelli V., Antoshkina T., Asavapibhop B., de Andre J. P. A. M., Auguste D., Bai W., Balashov N., Baldini W., Barresi A., Basilico D., Baussan E., Bellato M., Bergnoli A., Birkenfeld T., Blin S., Blum D., Blyth S., Bolshakova A., Bongrand M., Bordereau C., Breton D., Brigatti A., Brugnera R., Bruno R., Budano A., Busto J., Cabrera A., Caccianiga B., Cai H., Cai X., Cai Y., Cai Z., Callegari R., Cammi A., Campeny A., Cao C., Cao G., Cao J., Caruso R., Cerna C., Chan C., Chang J., Chang Y., Chen G., Chen P., Chen P. -A., Chen S., Chen X., Chen Y., Chen Z., Cheng J., Cheng Y., Cheng Y. C., Chetverikov A., Chiesa D., Chimenti P., Chu Z., Chukanov A., Claverie G., Clementi C., Clerbaux B., Di Lorenzo S. C., Corti D., Corso F. D., Dalager O., De La Taille C., Deng Z., Depnering W., Diaz M., Ding X., Ding Y., Dirgantara B., Dmitrievsky S., Dohnal T., Dolzhikov D., Donchenko G., Dong J., Doroshkevich E., Dou W., Dracos M., Druillole F., Du R., Du S., Dusini S., Dvorak M., Eck J., Enqvist T., Fabbri A., Fahrendholz U., Fan D., Fan L., Fang J., Fang W., Fargetta M., Fedoseev D., Fei Z., Feng L. -C., Feng Q., Ferraro F., Ford R., Fournier A., Gan H., Gao F., Garfagnini A., Gavrikov A., Giammarchi M., Giudice N., Gonchar M., Gong G., Gong H., Gornushkin Y., Gottel A., Grassi M., Gromov V., Gu M., Gu X., Gu Y., Guan M., Guan Y., Guardone N., Guo C., Guo J., Guo W., Guo X., Guo Y., Hagner C., Han R., Han Y., He M., He W., Heinz T., Hellmuth P., Heng Y., Herrera R., Hor Y., Hou S., Hsiung Y., Hu B. -Z., Hu H., Hu J., Hu S., Hu T., Hu Y., Hu Z., Huang G., Huang H., Huang K., Huang W., Huang X., Huang Y., Hui J., Huo L., Huo W., Huss C., Hussain S., Ioannisian A., Isocrate R., Jelmini B., Jeria I., Ji X., Jia H., Jia J., Jian S., Jiang D., Jiang W., Jiang X., Jing X., Jollet C., Joutsenvaara J., Kalousis L., Kampmann P., Kang L., Karaparambil R., Kazarian N., Khatun A., Khosonthongkee K., Korablev D., Kouzakov K., Krasnoperov A., Kutovskiy N., Kuusiniemi P., Lachenmaier T., Landini C., Leblanc S., Lebrin V., Lefevre F., Lei R., Leitner R., Leung J., Li D., Li F., Li G., Li H., Li M., Li N., Li Q., Li R., Li S., Li T., Li W., Li X., Li Y., Li Z., Liang H., Liao J., Limphirat A., Lin G. -L., Lin S., Lin T., Ling J., Lippi I., Liu F., Liu H., Liu J., Liu M., Liu Q., Liu R., Liu S., Liu X., Liu Y., Lokhov A., Lombardi P., Lombardo C., Loo K., Lu C., Lu H., Lu J., Lu P., Lu S., Lubsandorzhiev B., Lubsandorzhiev S., Ludhova L., Lukanov A., Luo D., Luo F., Luo G., Luo S., Luo W., Luo X., Lyashuk V., Ma B., Ma Q., Ma S., Ma X., Maalmi J., Magoni M., Mai J., Malyshkin Y., Mandujano R. C., Mantovani F., Mao X., Mao Y., Mari S. M., Marini F., Martellini C., Martin-Chassard G., Martini A., Mayer M., Mayilyan D., Mednieks I., Meinusch A., Meng Y., Meregaglia A., Meroni E., Meyhofer D., Mezzetto M., Miller J., Miramonti L., Molla M. C., Montini P., Montuschi M., Muller A., Nastasi M., Naumov D. V., Naumova E., Navas-Nicolas D., Nemchenok I., Thi M. T. N., Ning F., Ning Z., Nunokawa H., Oberauer L., Ochoa-Ricoux J. P., Olshevskiy A., Orestano D., Ortica F., Othegraven R., Paoloni A., Parmeggiano S., Pei Y., Pelicci L., Pelliccia N., Peng A., Peng H., Peng Y., Peng Z., Perrot F., Petitjean P. -A., Petrucci F., Pilarczyk O., Rico L. F. P., Popov A., Poussot P., Previtali E., Qi F., Qi M., Qian S., Qian X., Qian Z., Qiao H., Qin Z., Qiu S., Ranucci G., Raper N., Rasheed R., Re A., Rebber H., Rebii A., Redchuk M., Ren B., Ren J., Ricci B., Rifai M., Roche M., Rodphai N., Romani A., Roskovec B., Ruan X., Rybnikov A., Sadovsky A., Saggese P., Sanfilippo S., Sangka A., Sawangwit U., Sawatzki J., Schever M., Schwab C., Schweizer K., Selyunin A., Serafini A., Settanta G., Settimo M., Shao Z., Sharov V., Shaydurova A., Shi J., Shi Y., Shutov V., Sidorenkov A., Simkovic F., Sirignano C., Siripak J., Sisti M., Slupecki M., Smirnov M., Smirnov O., Sogo-Bezerra T., Sokolov S., Songwadhana J., Soonthornthum B., Sotnikov A., Sramek O., Sreethawong W., Stahl A., Stanco L., Stankevich K., Stefanik D., Steiger H., Steinmann J., Sterr T., Stock M. R., Strati V., Studenikin A., Su J., Sun S., Sun X., Sun Y., Sun Z., Suwonjandee N., Szelezniak M., Tang J., Tang Q., Tang X., Hariharan V. T., Theisen E., Tietzsch A., Tkachev I., Tmej T., Torri M. D. C., Treskov K., Triossi A., Troni G., Trzaska W., Tuve C., Ushakov N., Vedin V., Verde G., Vialkov M., Viaud B., Vollbrecht C. M., Volpe C., Sturm K. V., Vorobel V., Voronin D., Votano L., Walker P., Wang C., Wang C. -H., Wang E., Wang G., Wang J., Wang L., Wang M., Wang R., Wang S., Wang W., Wang X., Wang Y., Weng Y., Wang Z., Watcharangkool A., Wei W., Wei Y., Wen K., Wen L., Weng J., Wiebusch C., Wong S. C. -F., Wonsak B., Wu D., Wu Q., Wu Z., Wurm M., Wurtz J., Wysotzki C., Xi Y., Xia D., Xiao X., Xie X., Xie Y., Xie Z., Xin Z., Xing Z., Xu B., Xu C., Xu D., Xu F., Xu H., Xu J., Xu M., Xu Y., Yan B., Yan Q., Yan T., Yan W., Yan X., Yan Y., Yang C., Yang H., Yang J., Yang L., Yang X., Yang Y., Yeng Y., Yao H., Ye J., Ye M., Ye Z., Yermia F., You Z., Yu B., Yu C., Yu H., Yu M., Yu X., Yu Z., Yuan C., Yuan Y., Yuan Z., Yue B., Zafar N., Zavadskyi V., Zeng S., Zeng T., Zeng Y., Zhan L., Zhang A., Zhang B., Zhang F., Zhang G., Zhang H., Zhang J., Zhang M., Zhang P., Zhang Q., Zhang S., Zhang T., Zhang X., Zhang Y., Zhang Z., Zhao F., Zhao J., Zhao R., Zhao S., Zheng D., Zheng H., Zheng Y., Zhong W., Zhou J., Zhou L., Zhou N., Zhou S., Zhou T., Zhou X., Zhu J., Zhu K., Zhu Z., Zhuang B., Zhuang H., Zong L., Zou J., Zwickel S., Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, Alexandros, T, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de Andre, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Bergnoli, A, Birkenfeld, T, Blin, S, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callegari, R, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Chan, C, Chang, J, Chang, Y, Chen, G, Chen, P, Chen, S, Chen, X, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chetverikov, A, Chiesa, D, Chimenti, P, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Di Lorenzo, S, Corti, D, Corso, F, Dalager, O, De La Taille, C, Deng, Z, Depnering, W, Diaz, M, Ding, X, Ding, Y, Dirgantara, B, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dusini, S, Dvorak, M, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, D, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Ford, R, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Gottel, A, Grassi, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, J, Guo, W, Guo, X, Guo, Y, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Ioannisian, A, Isocrate, R, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Joutsenvaara, J, Kalousis, L, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kutovskiy, N, Kuusiniemi, P, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Lippi, I, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martellini, C, Martin-Chassard, G, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meinusch, A, Meng, Y, Meregaglia, A, Meroni, E, Meyhofer, D, Mezzetto, M, Miller, J, Miramonti, L, Molla, M, Montini, P, Montuschi, M, Muller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, R, Paoloni, A, Parmeggiano, S, Pei, Y, Pelicci, L, Pelliccia, N, Peng, A, Peng, H, Peng, Y, Peng, Z, Perrot, F, Petitjean, P, Petrucci, F, Pilarczyk, O, Rico, L, Popov, A, Poussot, P, Previtali, E, Qi, F, Qi, M, Qian, S, Qian, X, Qian, Z, Qiao, H, Qin, Z, Qiu, S, Ranucci, G, Raper, N, Rasheed, R, Re, A, Rebber, H, Rebii, A, Redchuk, M, Ren, B, Ren, J, Ricci, B, Rifai, M, Roche, M, Rodphai, N, Romani, A, Roskovec, B, Ruan, X, Rybnikov, A, Sadovsky, A, Saggese, P, Sanfilippo, S, Sangka, A, Sawangwit, U, Sawatzki, J, Schever, M, Schwab, C, Schweizer, K, Selyunin, A, Serafini, A, Settanta, G, Settimo, M, Shao, Z, Sharov, V, Shaydurova, A, Shi, J, Shi, Y, Shutov, V, Sidorenkov, A, Simkovic, F, Sirignano, C, Siripak, J, Sisti, M, Slupecki, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Sokolov, S, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Sramek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Stefanik, D, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Su, J, Sun, S, Sun, X, Sun, Y, Sun, Z, Suwonjandee, N, Szelezniak, M, Tang, J, Tang, Q, Tang, X, Hariharan, V, Theisen, E, Tietzsch, A, Tkachev, I, Tmej, T, Torri, M, Treskov, K, Triossi, A, Troni, G, Trzaska, W, Tuve, C, Ushakov, N, Vedin, V, Verde, G, Vialkov, M, Viaud, B, Vollbrecht, C, Volpe, C, Sturm, K, Vorobel, V, Voronin, D, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, Wang, L, Wang, M, Wang, R, Wang, S, Wang, W, Wang, X, Wang, Y, Weng, Y, Wang, Z, Watcharangkool, A, Wei, W, Wei, Y, Wen, K, Wen, L, Weng, J, Wiebusch, C, Wong, S, Wonsak, B, Wu, D, Wu, Q, Wu, Z, Wurm, M, Wurtz, J, Wysotzki, C, Xi, Y, Xia, D, Xiao, X, Xie, X, Xie, Y, Xie, Z, Xin, Z, Xing, Z, Xu, B, Xu, C, Xu, D, Xu, F, Xu, H, Xu, J, Xu, M, Xu, Y, Yan, B, Yan, Q, Yan, T, Yan, W, Yan, X, Yan, Y, Yang, C, Yang, H, Yang, J, Yang, L, Yang, X, Yang, Y, Yeng, Y, Yao, H, Ye, J, Ye, M, Ye, Z, Yermia, F, You, Z, Yu, B, Yu, C, Yu, H, Yu, M, Yu, X, Yu, Z, Yuan, C, Yuan, Y, Yuan, Z, Yue, B, Zafar, N, Zavadskyi, V, 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P. A. M., Auguste D., Bai W., Balashov N., Baldini W., Barresi A., Basilico D., Baussan E., Bellato M., Bergnoli A., Birkenfeld T., Blin S., Blum D., Blyth S., Bolshakova A., Bongrand M., Bordereau C., Breton D., Brigatti A., Brugnera R., Bruno R., Budano A., Busto J., Cabrera A., Caccianiga B., Cai H., Cai X., Cai Y., Cai Z., Callegari R., Cammi A., Campeny A., Cao C., Cao G., Cao J., Caruso R., Cerna C., Chan C., Chang J., Chang Y., Chen G., Chen P., Chen P. -A., Chen S., Chen X., Chen Y., Chen Z., Cheng J., Cheng Y., Cheng Y. C., Chetverikov A., Chiesa D., Chimenti P., Chu Z., Chukanov A., Claverie G., Clementi C., Clerbaux B., Di Lorenzo S. C., Corti D., Corso F. D., Dalager O., De La Taille C., Deng Z., Depnering W., Diaz M., Ding X., Ding Y., Dirgantara B., Dmitrievsky S., Dohnal T., Dolzhikov D., Donchenko G., Dong J., Doroshkevich E., Dou W., Dracos M., Druillole F., Du R., Du S., Dusini S., Dvorak M., Eck J., Enqvist T., Fabbri A., Fahrendholz U., Fan D., Fan L., Fang J., Fang W., Fargetta M., Fedoseev D., Fei Z., Feng L. -C., Feng Q., Ferraro F., Ford R., Fournier A., Gan H., Gao F., Garfagnini A., Gavrikov A., Giammarchi M., Giudice N., Gonchar M., Gong G., Gong H., Gornushkin Y., Gottel A., Grassi M., Gromov V., Gu M., Gu X., Gu Y., Guan M., Guan Y., Guardone N., Guo C., Guo J., Guo W., Guo X., Guo Y., Hagner C., Han R., Han Y., He M., He W., Heinz T., Hellmuth P., Heng Y., Herrera R., Hor Y., Hou S., Hsiung Y., Hu B. -Z., Hu H., Hu J., Hu S., Hu T., Hu Y., Hu Z., Huang G., Huang H., Huang K., Huang W., Huang X., Huang Y., Hui J., Huo L., Huo W., Huss C., Hussain S., Ioannisian A., Isocrate R., Jelmini B., Jeria I., Ji X., Jia H., Jia J., Jian S., Jiang D., Jiang W., Jiang X., Jing X., Jollet C., Joutsenvaara J., Kalousis L., Kampmann P., Kang L., Karaparambil R., Kazarian N., Khatun A., Khosonthongkee K., Korablev D., Kouzakov K., Krasnoperov A., Kutovskiy N., Kuusiniemi P., Lachenmaier T., Landini C., Leblanc S., Lebrin V., Lefevre F., Lei R., Leitner R., Leung J., Li D., Li F., Li G., Li H., Li M., Li N., Li Q., Li R., Li S., Li T., Li W., Li X., Li Y., Li Z., Liang H., Liao J., Limphirat A., Lin G. -L., Lin S., Lin T., Ling J., Lippi I., Liu F., Liu H., Liu J., Liu M., Liu Q., Liu R., Liu S., Liu X., Liu Y., Lokhov A., Lombardi P., Lombardo C., Loo K., Lu C., Lu H., Lu J., Lu P., Lu S., Lubsandorzhiev B., Lubsandorzhiev S., Ludhova L., Lukanov A., Luo D., Luo F., Luo G., Luo S., Luo W., Luo X., Lyashuk V., Ma B., Ma Q., Ma S., Ma X., Maalmi J., Magoni M., Mai J., Malyshkin Y., Mandujano R. C., Mantovani F., Mao X., Mao Y., Mari S. M., Marini F., Martellini C., Martin-Chassard G., Martini A., Mayer M., Mayilyan D., Mednieks I., Meinusch A., Meng Y., Meregaglia A., Meroni E., Meyhofer D., Mezzetto M., Miller J., Miramonti L., Molla M. C., Montini P., Montuschi M., Muller A., Nastasi M., Naumov D. V., Naumova E., Navas-Nicolas D., Nemchenok I., Thi M. T. N., Ning F., Ning Z., Nunokawa H., Oberauer L., Ochoa-Ricoux J. P., Olshevskiy A., Orestano D., Ortica F., Othegraven R., Paoloni A., Parmeggiano S., Pei Y., Pelicci L., Pelliccia N., Peng A., Peng H., Peng Y., Peng Z., Perrot F., Petitjean P. -A., Petrucci F., Pilarczyk O., Rico L. F. 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C. -F., Wonsak B., Wu D., Wu Q., Wu Z., Wurm M., Wurtz J., Wysotzki C., Xi Y., Xia D., Xiao X., Xie X., Xie Y., Xie Z., Xin Z., Xing Z., Xu B., Xu C., Xu D., Xu F., Xu H., Xu J., Xu M., Xu Y., Yan B., Yan Q., Yan T., Yan W., Yan X., Yan Y., Yang C., Yang H., Yang J., Yang L., Yang X., Yang Y., Yeng Y., Yao H., Ye J., Ye M., Ye Z., Yermia F., You Z., Yu B., Yu C., Yu H., Yu M., Yu X., Yu Z., Yuan C., Yuan Y., Yuan Z., Yue B., Zafar N., Zavadskyi V., Zeng S., Zeng T., Zeng Y., Zhan L., Zhang A., Zhang B., Zhang F., Zhang G., Zhang H., Zhang J., Zhang M., Zhang P., Zhang Q., Zhang S., Zhang T., Zhang X., Zhang Y., Zhang Z., Zhao F., Zhao J., Zhao R., Zhao S., Zheng D., Zheng H., Zheng Y., Zhong W., Zhou J., Zhou L., Zhou N., Zhou S., Zhou T., Zhou X., Zhu J., Zhu K., Zhu Z., Zhuang B., Zhuang H., Zong L., Zou J., and Zwickel S.

Abstract

We discuss JUNO sensitivity to the annihilation of MeV dark matter in the galactic halo via detecting inverse beta decay reactions of electron anti-neutrinos resulting from the annihilation. We study possible backgrounds to the signature, including the reactor neutrinos, diffuse supernova neutrino background, charged- and neutral-current interactions of atmospheric neutrinos, backgrounds from muon-induced fast neutrons and cosmogenic isotopes. A fiducial volume cut, as well as the pulse shape discrimination and the muon veto are applied to suppress the above backgrounds. It is shown that JUNO sensitivity to the thermally averaged dark matter annihilation rate in 10 years of exposure would be significantly better than the present-day best limit set by Super-Kamiokande and would be comparable to that expected by Hyper-Kamiokande.

Published
2023

115. JUNO sensitivity to 7Be, pep, and CNO solar neutrinos

Author

Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, Alexandros, T, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de Andre, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Beretta, M, Bergnoli, A, Bick, D, Bieger, L, Biktemerova, S, Birkenfeld, T, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callier, S, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Cerrone, V, Chan, C, Chang, J, Chang, Y, Chen, C, Chen, G, Chen, P, Chen, S, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chepurnov, A, Chetverikov, A, Chiesa, D, Chimenti, P, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Molla, M, Di Lorenzo, S, Coppi, A, Corti, D, Csakli, S, Dal Corso, F, Dalager, O, Datta, J, De La Taille, C, Deng, Z, Depnering, W, Ding, X, Ding, Y, Dirgantara, B, Dittrich, C, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dugas, K, Dusini, S, Duyang, H, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Gottel, A, Grassi, M, Gromov, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, W, Guo, X, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, J, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Imbert, L, Ioannisian, A, Isocrate, R, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, C, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khan, A, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kuleshov, S, Kutovskiy, N, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, J, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Ling, X, Lippi, I, Liu, C, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Liu, Z, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, J, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meng, Y, Meraviglia, A, Meregaglia, A, Meroni, E, Meyhofer, D, Miramonti, L, Mohan, N, Montini, P, Montuschi, M, Muller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Nikolaev, A, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, R, Paoloni, A, Parmeggiano, S, Pei, Y, Pelicci, L, Peng, A, Peng, H, Peng, Y, Peng, Z, Perrot, F, Petitjean, P, Petrucci, F, Pilarczyk, O, Rico, L, Popov, A, Poussot, P, Previtali, E, Qi, F, Qi, M, Qi, X, Qian, S, Qian, X, Qian, Z, Qiao, H, Qin, Z, Qiu, S, Ranucci, G, Rasheed, R, Re, A, Rebii, A, Redchuk, M, Ren, B, Ren, J, Ricci, B, Rifai, M, Roche, M, Rodphai, N, Romani, A, Roskovec, B, Ruan, X, Rybnikov, A, Sadovsky, A, Saggese, P, Sandanayake, D, Sanfilippo, S, Sangka, A, Sawangwit, U, Schever, M, Schwab, C, Schweizer, K, Selyunin, A, Serafini, A, Settimo, M, Sharov, V, Shaydurova, A, Shi, J, Shi, Y, Shutov, V, Sidorenkov, A, Simkovic, F, Singhal, A, Sirignano, C, Siripak, J, Sisti, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Sokolov, S, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Sramek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Su, J, Sun, S, Sun, X, Sun, Y, Sun, Z, Suwonjandee, N, Szelezniak, M, Takenaka, A, Tang, J, Tang, Q, Tang, X, Hariharan, V, Theisen, E, Tietzsch, A, Tkachev, I, Tmej, T, Torri, M, Tortorici, F, Treskov, K, Triossi, A, Triozzi, R, Trzaska, W, Tung, Y, Tuve, C, Ushakov, N, Vedin, V, Verde, G, Vialkov, M, Viaud, B, Vollbrecht, C, von Sturm, K, Vorobel, V, Voronin, D, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, Wang, L, Wang, M, Wang, R, Wang, S, Wang, W, Wang, X, Wang, Y, Wang, Z, Watcharangkool, A, Wei, W, Wei, Y, Wen, K, Wen, L, Weng, J, Wiebusch, C, Wirth, R, Wonsak, B, Wu, D, Wu, Q, Wu, Y, Wu, Z, Wurm, M, Wurtz, J, Wysotzki, C, Xi, Y, Xia, D, Xiao, X, Xie, X, Xie, Y, Xie, Z, Xin, Z, Xing, Z, Xu, B, Xu, C, Xu, D, Xu, F, Xu, H, Xu, J, Xu, M, Xu, Y, Yan, B, Yan, Q, Yan, T, Yan, X, Yan, Y, Yang, C, Yang, J, Yang, L, Yang, X, Yang, Y, Yao, H, Ye, J, Ye, M, Ye, Z, Yermia, F, You, Z, Yu, B, Yu, C, Yu, G, Yu, H, Yu, M, Yu, X, Yu, Z, Yuan, C, Yuan, Y, Yuan, Z, Yue, B, Zafar, N, Zavadskyi, V, Zeng, S, Zeng, T, Zeng, Y, Zhan, L, Zhang, A, Zhang, B, Zhang, F, Zhang, H, Zhang, J, Zhang, M, Zhang, P, Zhang, Q, Zhang, S, Zhang, T, Zhang, X, Zhang, Y, Zhang, Z, Zhao, J, Zhao, R, Zhao, S, Zheng, D, Zheng, H, Zheng, Y, Zhong, W, Zhou, J, Zhou, L, Zhou, N, Zhou, S, Zhou, T, Zhou, X, Zhu, J, Zhu, K, Zhu, Z, Zhuang, B, Zhuang, H, Zong, L, Zou, J, Zufle, J, Zwickel, S, Abusleme A., Adam T., Ahmad S., Ahmed R., Aiello S., Akram M., Aleem A., Alexandros T., An F., An Q., Andronico G., Anfimov N., Antonelli V., Antoshkina T., Asavapibhop B., de Andre J. P. A. M., Auguste D., Bai W., Balashov N., Baldini W., Barresi A., Basilico D., Baussan E., Bellato M., Beretta M., Bergnoli A., Bick D., Bieger L., Biktemerova S., Birkenfeld T., Blum D., Blyth S., Bolshakova A., Bongrand M., Bordereau C., Breton D., Brigatti A., Brugnera R., Bruno R., Budano A., Busto J., Cabrera A., Caccianiga B., Cai H., Cai X., Cai Y., Cai Z., Callier S., Cammi A., Campeny A., Cao C., Cao G., Cao J., Caruso R., Cerna C., Cerrone V., Chan C., Chang J., Chang Y., Chen C., Chen G., Chen P., Chen S., Chen Y., Chen Z., Cheng J., Cheng Y., Cheng Y. C., Chepurnov A., Chetverikov A., Chiesa D., Chimenti P., Chu Z., Chukanov A., Claverie G., Clementi C., Clerbaux B., Molla M. C., Di Lorenzo S. C., Coppi A., Corti D., Csakli S., Dal Corso F., Dalager O., Datta J., De La Taille C., Deng Z., Depnering W., Ding X., Ding Y., Dirgantara B., Dittrich C., Dmitrievsky S., Dohnal T., Dolzhikov D., Donchenko G., Dong J., Doroshkevich E., Dou W., Dracos M., Druillole F., Du R., Du S., Dugas K., Dusini S., Duyang H., Eck J., Enqvist T., Fabbri A., Fahrendholz U., Fan L., Fang J., Fang W., Fargetta M., Fedoseev D., Fei Z., Feng L. -C., Feng Q., Ferraro F., Fournier A., Gan H., Gao F., Garfagnini A., Gavrikov A., Giammarchi M., Giudice N., Gonchar M., Gong G., Gong H., Gornushkin Y., Gottel A., Grassi M., Gromov M., Gromov V., Gu M., Gu X., Gu Y., Guan M., Guan Y., Guardone N., Guo C., Guo W., Guo X., Hagner C., Han R., Han Y., He M., He W., Heinz T., Hellmuth P., Heng Y., Herrera R., Hor Y., Hou S., Hsiung Y., Hu B. -Z., Hu H., Hu J., Hu S., Hu T., Hu Y., Hu Z., Huang G., Huang H., Huang J., Huang K., Huang W., Huang X., Huang Y., Hui J., Huo L., Huo W., Huss C., Hussain S., Imbert L., Ioannisian A., Isocrate R., Jelmini B., Jeria I., Ji X., Jia H., Jia J., Jian S., Jiang C., Jiang D., Jiang W., Jiang X., Jing X., Jollet C., Kampmann P., Kang L., Karaparambil R., Kazarian N., Khan A., Khatun A., Khosonthongkee K., Korablev D., Kouzakov K., Krasnoperov A., Kuleshov S., Kutovskiy N., Lachenmaier T., Landini C., Leblanc S., Lebrin V., Lefevre F., Lei R., Leitner R., Leung J., Li D., Li F., Li G., Li H., Li J., Li M., Li N., Li Q., Li R., Li S., Li T., Li W., Li X., Li Y., Li Z., Liang H., Liao J., Limphirat A., Lin G. -L., Lin S., Lin T., Ling J., Ling X., Lippi I., Liu C., Liu F., Liu H., Liu J., Liu M., Liu Q., Liu R., Liu S., Liu X., Liu Y., Liu Z., Lokhov A., Lombardi P., Lombardo C., Loo K., Lu C., Lu H., Lu J., Lu P., Lu S., Lubsandorzhiev B., Lubsandorzhiev S., Ludhova L., Lukanov A., Luo D., Luo F., Luo G., Luo J., Luo S., Luo W., Luo X., Lyashuk V., Ma B., Ma Q., Ma S., Ma X., Maalmi J., Magoni M., Mai J., Malyshkin Y., Mandujano R. C., Mantovani F., Mao X., Mao Y., Mari S. M., Marini F., Martini A., Mayer M., Mayilyan D., Mednieks I., Meng Y., Meraviglia A., Meregaglia A., Meroni E., Meyhofer D., Miramonti L., Mohan N., Montini P., Montuschi M., Muller A., Nastasi M., Naumov D. V., Naumova E., Navas-Nicolas D., Nemchenok I., Thi M. T. N., Nikolaev A., Ning F., Ning Z., Nunokawa H., Oberauer L., Ochoa-Ricoux J. P., Olshevskiy A., Orestano D., Ortica F., Othegraven R., Paoloni A., Parmeggiano S., Pei Y., Pelicci L., Peng A., Peng H., Peng Y., Peng Z., Perrot F., Petitjean P. -A., Petrucci F., Pilarczyk O., Rico L. F. P., Popov A., Poussot P., Previtali E., Qi F., Qi M., Qi X., Qian S., Qian X., Qian Z., Qiao H., Qin Z., Qiu S., Ranucci G., Rasheed R., Re A., Rebii A., Redchuk M., Ren B., Ren J., Ricci B., Rifai M., Roche M., Rodphai N., Romani A., Roskovec B., Ruan X., Rybnikov A., Sadovsky A., Saggese P., Sandanayake D., Sanfilippo S., Sangka A., Sawangwit U., Schever M., Schwab C., Schweizer K., Selyunin A., Serafini A., Settimo M., Sharov V., Shaydurova A., Shi J., Shi Y., Shutov V., Sidorenkov A., Simkovic F., Singhal A., Sirignano C., Siripak J., Sisti M., Smirnov M., Smirnov O., Sogo-Bezerra T., Sokolov S., Songwadhana J., Soonthornthum B., Sotnikov A., Sramek O., Sreethawong W., Stahl A., Stanco L., Stankevich K., Steiger H., Steinmann J., Sterr T., Stock M. R., Strati V., Studenikin A., Su J., Sun S., Sun X., Sun Y., Sun Z., Suwonjandee N., Szelezniak M., Takenaka A., Tang J., Tang Q., Tang X., Hariharan V. T., Theisen E., Tietzsch A., Tkachev I., Tmej T., Torri M. D. C., Tortorici F., Treskov K., Triossi A., Triozzi R., Trzaska W., Tung Y. -C., Tuve C., Ushakov N., Vedin V., Verde G., Vialkov M., Viaud B., Vollbrecht C. M., von Sturm K., Vorobel V., Voronin D., Votano L., Walker P., Wang C., Wang C. -H., Wang E., Wang G., Wang J., Wang L., Wang M., Wang R., Wang S., Wang W., Wang X., Wang Y., Wang Z., Watcharangkool A., Wei W., Wei Y., Wen K., Wen L., Weng J., Wiebusch C., Wirth R., Wonsak B., Wu D., Wu Q., Wu Y., Wu Z., Wurm M., Wurtz J., Wysotzki C., Xi Y., Xia D., Xiao X., Xie X., Xie Y., Xie Z., Xin Z., Xing Z., Xu B., Xu C., Xu D., Xu F., Xu H., Xu J., Xu M., Xu Y., Yan B., Yan Q., Yan T., Yan X., Yan Y., Yang C., Yang J., Yang L., Yang X., Yang Y., Yao H., Ye J., Ye M., Ye Z., Yermia F., You Z., Yu B., Yu C., Yu G., Yu H., Yu M., Yu X., Yu Z., Yuan C., Yuan Y., Yuan Z., Yue B., Zafar N., Zavadskyi V., Zeng S., Zeng T., Zeng Y., Zhan L., Zhang A., Zhang B., Zhang F., Zhang H., Zhang J., Zhang M., Zhang P., Zhang Q., Zhang S., Zhang T., Zhang X., Zhang Y., Zhang Z., Zhao J., Zhao R., Zhao S., Zheng D., Zheng H., Zheng Y., Zhong W., Zhou J., Zhou L., Zhou N., Zhou S., Zhou T., Zhou X., Zhu J., Zhu K., Zhu Z., Zhuang B., Zhuang H., Zong L., Zou J., Zufle J., Zwickel S., Abusleme, A, Adam, T, Ahmad, S, Ahmed, R, Aiello, S, Akram, M, Aleem, A, Alexandros, T, An, F, An, Q, Andronico, G, Anfimov, N, Antonelli, V, Antoshkina, T, Asavapibhop, B, de Andre, J, Auguste, D, Bai, W, Balashov, N, Baldini, W, Barresi, A, Basilico, D, Baussan, E, Bellato, M, Beretta, M, Bergnoli, A, Bick, D, Bieger, L, Biktemerova, S, Birkenfeld, T, Blum, D, Blyth, S, Bolshakova, A, Bongrand, M, Bordereau, C, Breton, D, Brigatti, A, Brugnera, R, Bruno, R, Budano, A, Busto, J, Cabrera, A, Caccianiga, B, Cai, H, Cai, X, Cai, Y, Cai, Z, Callier, S, Cammi, A, Campeny, A, Cao, C, Cao, G, Cao, J, Caruso, R, Cerna, C, Cerrone, V, Chan, C, Chang, J, Chang, Y, Chen, C, Chen, G, Chen, P, Chen, S, Chen, Y, Chen, Z, Cheng, J, Cheng, Y, Chepurnov, A, Chetverikov, A, Chiesa, D, Chimenti, P, Chu, Z, Chukanov, A, Claverie, G, Clementi, C, Clerbaux, B, Molla, M, Di Lorenzo, S, Coppi, A, Corti, D, Csakli, S, Dal Corso, F, Dalager, O, Datta, J, De La Taille, C, Deng, Z, Depnering, W, Ding, X, Ding, Y, Dirgantara, B, Dittrich, C, Dmitrievsky, S, Dohnal, T, Dolzhikov, D, Donchenko, G, Dong, J, Doroshkevich, E, Dou, W, Dracos, M, Druillole, F, Du, R, Du, S, Dugas, K, Dusini, S, Duyang, H, Eck, J, Enqvist, T, Fabbri, A, Fahrendholz, U, Fan, L, Fang, J, Fang, W, Fargetta, M, Fedoseev, D, Fei, Z, Feng, L, Feng, Q, Ferraro, F, Fournier, A, Gan, H, Gao, F, Garfagnini, A, Gavrikov, A, Giammarchi, M, Giudice, N, Gonchar, M, Gong, G, Gong, H, Gornushkin, Y, Gottel, A, Grassi, M, Gromov, M, Gromov, V, Gu, M, Gu, X, Gu, Y, Guan, M, Guan, Y, Guardone, N, Guo, C, Guo, W, Guo, X, Hagner, C, Han, R, Han, Y, He, M, He, W, Heinz, T, Hellmuth, P, Heng, Y, Herrera, R, Hor, Y, Hou, S, Hsiung, Y, Hu, B, Hu, H, Hu, J, Hu, S, Hu, T, Hu, Y, Hu, Z, Huang, G, Huang, H, Huang, J, Huang, K, Huang, W, Huang, X, Huang, Y, Hui, J, Huo, L, Huo, W, Huss, C, Hussain, S, Imbert, L, Ioannisian, A, Isocrate, R, Jelmini, B, Jeria, I, Ji, X, Jia, H, Jia, J, Jian, S, Jiang, C, Jiang, D, Jiang, W, Jiang, X, Jing, X, Jollet, C, Kampmann, P, Kang, L, Karaparambil, R, Kazarian, N, Khan, A, Khatun, A, Khosonthongkee, K, Korablev, D, Kouzakov, K, Krasnoperov, A, Kuleshov, S, Kutovskiy, N, Lachenmaier, T, Landini, C, Leblanc, S, Lebrin, V, Lefevre, F, Lei, R, Leitner, R, Leung, J, Li, D, Li, F, Li, G, Li, H, Li, J, Li, M, Li, N, Li, Q, Li, R, Li, S, Li, T, Li, W, Li, X, Li, Y, Li, Z, Liang, H, Liao, J, Limphirat, A, Lin, G, Lin, S, Lin, T, Ling, J, Ling, X, Lippi, I, Liu, C, Liu, F, Liu, H, Liu, J, Liu, M, Liu, Q, Liu, R, Liu, S, Liu, X, Liu, Y, Liu, Z, Lokhov, A, Lombardi, P, Lombardo, C, Loo, K, Lu, C, Lu, H, Lu, J, Lu, P, Lu, S, Lubsandorzhiev, B, Lubsandorzhiev, S, Ludhova, L, Lukanov, A, Luo, D, Luo, F, Luo, G, Luo, J, Luo, S, Luo, W, Luo, X, Lyashuk, V, Ma, B, Ma, Q, Ma, S, Ma, X, Maalmi, J, Magoni, M, Mai, J, Malyshkin, Y, Mandujano, R, Mantovani, F, Mao, X, Mao, Y, Mari, S, Marini, F, Martini, A, Mayer, M, Mayilyan, D, Mednieks, I, Meng, Y, Meraviglia, A, Meregaglia, A, Meroni, E, Meyhofer, D, Miramonti, L, Mohan, N, Montini, P, Montuschi, M, Muller, A, Nastasi, M, Naumov, D, Naumova, E, Navas-Nicolas, D, Nemchenok, I, Thi, M, Nikolaev, A, Ning, F, Ning, Z, Nunokawa, H, Oberauer, L, Ochoa-Ricoux, J, Olshevskiy, A, Orestano, D, Ortica, F, Othegraven, R, Paoloni, A, Parmeggiano, S, Pei, Y, Pelicci, L, Peng, A, Peng, H, Peng, Y, Peng, Z, Perrot, F, Petitjean, P, Petrucci, F, Pilarczyk, O, Rico, L, Popov, A, Poussot, P, Previtali, E, Qi, F, Qi, M, Qi, X, Qian, S, Qian, X, Qian, Z, Qiao, H, Qin, Z, Qiu, S, Ranucci, G, Rasheed, R, Re, A, Rebii, A, Redchuk, M, Ren, B, Ren, J, Ricci, B, Rifai, M, Roche, M, Rodphai, N, Romani, A, Roskovec, B, Ruan, X, Rybnikov, A, Sadovsky, A, Saggese, P, Sandanayake, D, Sanfilippo, S, Sangka, A, Sawangwit, U, Schever, M, Schwab, C, Schweizer, K, Selyunin, A, Serafini, A, Settimo, M, Sharov, V, Shaydurova, A, Shi, J, Shi, Y, Shutov, V, Sidorenkov, A, Simkovic, F, Singhal, A, Sirignano, C, Siripak, J, Sisti, M, Smirnov, M, Smirnov, O, Sogo-Bezerra, T, Sokolov, S, Songwadhana, J, Soonthornthum, B, Sotnikov, A, Sramek, O, Sreethawong, W, Stahl, A, Stanco, L, Stankevich, K, Steiger, H, Steinmann, J, Sterr, T, Stock, M, Strati, V, Studenikin, A, Su, J, Sun, S, Sun, X, Sun, Y, Sun, Z, Suwonjandee, N, Szelezniak, M, Takenaka, A, Tang, J, Tang, Q, Tang, X, Hariharan, V, Theisen, E, Tietzsch, A, Tkachev, I, Tmej, T, Torri, M, Tortorici, F, Treskov, K, Triossi, A, Triozzi, R, Trzaska, W, Tung, Y, Tuve, C, Ushakov, N, Vedin, V, Verde, G, Vialkov, M, Viaud, B, Vollbrecht, C, von Sturm, K, Vorobel, V, Voronin, D, Votano, L, Walker, P, Wang, C, Wang, E, Wang, G, Wang, J, Wang, L, Wang, M, Wang, R, Wang, S, Wang, W, Wang, X, Wang, Y, Wang, Z, Watcharangkool, A, Wei, W, Wei, Y, Wen, K, Wen, L, Weng, J, Wiebusch, C, Wirth, R, Wonsak, B, Wu, D, Wu, Q, Wu, Y, Wu, Z, Wurm, M, Wurtz, J, Wysotzki, C, Xi, Y, Xia, D, Xiao, X, Xie, X, Xie, Y, Xie, Z, Xin, Z, Xing, Z, Xu, B, Xu, C, Xu, D, Xu, F, Xu, H, Xu, J, Xu, M, Xu, Y, Yan, B, Yan, Q, Yan, T, Yan, X, Yan, Y, Yang, C, Yang, J, Yang, L, Yang, X, Yang, Y, Yao, H, Ye, J, Ye, M, Ye, Z, Yermia, F, You, Z, Yu, B, Yu, C, Yu, G, Yu, H, Yu, M, Yu, X, Yu, Z, Yuan, C, Yuan, Y, Yuan, Z, Yue, B, Zafar, N, Zavadskyi, V, Zeng, S, Zeng, T, Zeng, Y, Zhan, L, Zhang, A, Zhang, B, Zhang, F, Zhang, H, Zhang, J, Zhang, M, Zhang, P, Zhang, Q, Zhang, S, Zhang, T, Zhang, X, Zhang, Y, Zhang, Z, Zhao, J, Zhao, R, Zhao, S, Zheng, D, Zheng, H, Zheng, Y, Zhong, W, Zhou, J, Zhou, L, Zhou, N, Zhou, S, Zhou, T, Zhou, X, Zhu, J, Zhu, K, Zhu, Z, Zhuang, B, Zhuang, H, Zong, L, Zou, J, Zufle, J, Zwickel, S, Abusleme A., Adam T., Ahmad S., Ahmed R., Aiello S., Akram M., Aleem A., Alexandros T., An F., An Q., Andronico G., Anfimov N., Antonelli V., Antoshkina T., Asavapibhop B., de Andre J. P. A. M., Auguste D., Bai W., Balashov N., Baldini W., Barresi A., Basilico D., Baussan E., Bellato M., Beretta M., Bergnoli A., Bick D., Bieger L., Biktemerova S., Birkenfeld T., Blum D., Blyth S., Bolshakova A., Bongrand M., Bordereau C., Breton D., Brigatti A., Brugnera R., Bruno R., Budano A., Busto J., Cabrera A., Caccianiga B., Cai H., Cai X., Cai Y., Cai Z., Callier S., Cammi A., Campeny A., Cao C., Cao G., Cao J., Caruso R., Cerna C., Cerrone V., Chan C., Chang J., Chang Y., Chen C., Chen G., Chen P., Chen S., Chen Y., Chen Z., Cheng J., Cheng Y., Cheng Y. C., Chepurnov A., Chetverikov A., Chiesa D., Chimenti P., Chu Z., Chukanov A., Claverie G., Clementi C., Clerbaux B., Molla M. C., Di Lorenzo S. C., Coppi A., Corti D., Csakli S., Dal Corso F., Dalager O., Datta J., De La Taille C., Deng Z., Depnering W., Ding X., Ding Y., Dirgantara B., Dittrich C., Dmitrievsky S., Dohnal T., Dolzhikov D., Donchenko G., Dong J., Doroshkevich E., Dou W., Dracos M., Druillole F., Du R., Du S., Dugas K., Dusini S., Duyang H., Eck J., Enqvist T., Fabbri A., Fahrendholz U., Fan L., Fang J., Fang W., Fargetta M., Fedoseev D., Fei Z., Feng L. -C., Feng Q., Ferraro F., Fournier A., Gan H., Gao F., Garfagnini A., Gavrikov A., Giammarchi M., Giudice N., Gonchar M., Gong G., Gong H., Gornushkin Y., Gottel A., Grassi M., Gromov M., Gromov V., Gu M., Gu X., Gu Y., Guan M., Guan Y., Guardone N., Guo C., Guo W., Guo X., Hagner C., Han R., Han Y., He M., He W., Heinz T., Hellmuth P., Heng Y., Herrera R., Hor Y., Hou S., Hsiung Y., Hu B. -Z., Hu H., Hu J., Hu S., Hu T., Hu Y., Hu Z., Huang G., Huang H., Huang J., Huang K., Huang W., Huang X., Huang Y., Hui J., Huo L., Huo W., Huss C., Hussain S., Imbert L., Ioannisian A., Isocrate R., Jelmini B., Jeria I., Ji X., Jia H., Jia J., Jian S., Jiang C., Jiang D., Jiang W., Jiang X., Jing X., Jollet C., Kampmann P., Kang L., Karaparambil R., Kazarian N., Khan A., Khatun A., Khosonthongkee K., Korablev D., Kouzakov K., Krasnoperov A., Kuleshov S., Kutovskiy N., Lachenmaier T., Landini C., Leblanc S., Lebrin V., Lefevre F., Lei R., Leitner R., Leung J., Li D., Li F., Li G., Li H., Li J., Li M., Li N., Li Q., Li R., Li S., Li T., Li W., Li X., Li Y., Li Z., Liang H., Liao J., Limphirat A., Lin G. -L., Lin S., Lin T., Ling J., Ling X., Lippi I., Liu C., Liu F., Liu H., Liu J., Liu M., Liu Q., Liu R., Liu S., Liu X., Liu Y., Liu Z., Lokhov A., Lombardi P., Lombardo C., Loo K., Lu C., Lu H., Lu J., Lu P., Lu S., Lubsandorzhiev B., Lubsandorzhiev S., Ludhova L., Lukanov A., Luo D., Luo F., Luo G., Luo J., Luo S., Luo W., Luo X., Lyashuk V., Ma B., Ma Q., Ma S., Ma X., Maalmi J., Magoni M., Mai J., Malyshkin Y., Mandujano R. C., Mantovani F., Mao X., Mao Y., Mari S. M., Marini F., Martini A., Mayer M., Mayilyan D., Mednieks I., Meng Y., Meraviglia A., Meregaglia A., Meroni E., Meyhofer D., Miramonti L., Mohan N., Montini P., Montuschi M., Muller A., Nastasi M., Naumov D. V., Naumova E., Navas-Nicolas D., Nemchenok I., Thi M. T. N., Nikolaev A., Ning F., Ning Z., Nunokawa H., Oberauer L., Ochoa-Ricoux J. P., Olshevskiy A., Orestano D., Ortica F., Othegraven R., Paoloni A., Parmeggiano S., Pei Y., Pelicci L., Peng A., Peng H., Peng Y., Peng Z., Perrot F., Petitjean P. -A., Petrucci F., Pilarczyk O., Rico L. F. P., Popov A., Poussot P., Previtali E., Qi F., Qi M., Qi X., Qian S., Qian X., Qian Z., Qiao H., Qin Z., Qiu S., Ranucci G., Rasheed R., Re A., Rebii A., Redchuk M., Ren B., Ren J., Ricci B., Rifai M., Roche M., Rodphai N., Romani A., Roskovec B., Ruan X., Rybnikov A., Sadovsky A., Saggese P., Sandanayake D., Sanfilippo S., Sangka A., Sawangwit U., Schever M., Schwab C., Schweizer K., Selyunin A., Serafini A., Settimo M., Sharov V., Shaydurova A., Shi J., Shi Y., Shutov V., Sidorenkov A., Simkovic F., Singhal A., Sirignano C., Siripak J., Sisti M., Smirnov M., Smirnov O., Sogo-Bezerra T., Sokolov S., Songwadhana J., Soonthornthum B., Sotnikov A., Sramek O., Sreethawong W., Stahl A., Stanco L., Stankevich K., Steiger H., Steinmann J., Sterr T., Stock M. R., Strati V., Studenikin A., Su J., Sun S., Sun X., Sun Y., Sun Z., Suwonjandee N., Szelezniak M., Takenaka A., Tang J., Tang Q., Tang X., Hariharan V. T., Theisen E., Tietzsch A., Tkachev I., Tmej T., Torri M. D. C., Tortorici F., Treskov K., Triossi A., Triozzi R., Trzaska W., Tung Y. -C., Tuve C., Ushakov N., Vedin V., Verde G., Vialkov M., Viaud B., Vollbrecht C. M., von Sturm K., Vorobel V., Voronin D., Votano L., Walker P., Wang C., Wang C. -H., Wang E., Wang G., Wang J., Wang L., Wang M., Wang R., Wang S., Wang W., Wang X., Wang Y., Wang Z., Watcharangkool A., Wei W., Wei Y., Wen K., Wen L., Weng J., Wiebusch C., Wirth R., Wonsak B., Wu D., Wu Q., Wu Y., Wu Z., Wurm M., Wurtz J., Wysotzki C., Xi Y., Xia D., Xiao X., Xie X., Xie Y., Xie Z., Xin Z., Xing Z., Xu B., Xu C., Xu D., Xu F., Xu H., Xu J., Xu M., Xu Y., Yan B., Yan Q., Yan T., Yan X., Yan Y., Yang C., Yang J., Yang L., Yang X., Yang Y., Yao H., Ye J., Ye M., Ye Z., Yermia F., You Z., Yu B., Yu C., Yu G., Yu H., Yu M., Yu X., Yu Z., Yuan C., Yuan Y., Yuan Z., Yue B., Zafar N., Zavadskyi V., Zeng S., Zeng T., Zeng Y., Zhan L., Zhang A., Zhang B., Zhang F., Zhang H., Zhang J., Zhang M., Zhang P., Zhang Q., Zhang S., Zhang T., Zhang X., Zhang Y., Zhang Z., Zhao J., Zhao R., Zhao S., Zheng D., Zheng H., Zheng Y., Zhong W., Zhou J., Zhou L., Zhou N., Zhou S., Zhou T., Zhou X., Zhu J., Zhu K., Zhu Z., Zhuang B., Zhuang H., Zong L., Zou J., Zufle J., and Zwickel S.

Abstract

The Jiangmen Underground Neutrino Observatory (JUNO), the first multi-kton liquid scintillator detector, which is under construction in China, will have a unique potential to perform a real-time measurement of solar neutrinos well below the few MeV threshold typical of Water Cherenkov detectors. JUNO’s large target mass and excellent energy resolution are prerequisites for reaching unprecedented levels of precision. In this paper, we provide estimation of the JUNO sensitivity to 7Be, pep, and CNO solar neutrinos that can be obtained via a spectral analysis above the 0.45 MeV threshold. This study is performed assuming different scenarios of the liquid scintillator radiopurity, ranging from the most optimistic one corresponding to the radiopurity levels obtained by the Borexino experiment, up to the minimum requirements needed to perform the neutrino mass ordering determination with reactor antineutrinos — the main goal of JUNO. Our study shows that in most scenarios, JUNO will be able to improve the current best measurements on 7Be, pep, and CNO solar neutrino fluxes. We also perform a study on the JUNO capability to detect periodical time variations in the solar neutrino flux, such as the day-night modulation induced by neutrino flavor regeneration in Earth, and the modulations induced by temperature changes driven by helioseismic waves.

Published
2023

122. Herschel-ATLAS: towards a sample of ~1000 strongly-lensed galaxies

Author

González-Nuevo, J., Lapi, A., Fleuren, S., Bressan, S., Danese, L., De Zotti, G., Negrello, M., Cai, Z. -Y., Fan, L., Sutherland, W., Baes, M., Baker, A. J., Clements, D. L., Cooray, A., Dannerbauer, H., Dunne, L., Dye, S., Eales, S., Frayer, D. T., Harris, A. I., Ivison, R., Jarvis, M. J., Michałowski, M. J., López-Caniego, M., Rodighiero, G., Rowlands, K., Serjeant, S., Scott, D., van der Werf, P., Auld, R., Buttiglione, S., Cava, A., Dariush, A., Fritz, J., Hopwood, R., Ibar, E., Maddox, S., Pascale, E., Pohlen, M., Rigby, E., Smith, D., and Temi, P.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

While the selection of strongly lensed galaxies with 500{\mu}m flux density S_500>100 mJy has proven to be rather straightforward (Negrello et al. 2010), for many applications it is important to analyze samples larger than the ones obtained when confining ourselves to such a bright limit. Moreover, only by probing to fainter flux densities is possible to exploit strong lensing to investigate the bulk of the high-z star-forming galaxy population. We describe HALOS (the Herschel-ATLAS Lensed Objects Selection), a method for efficiently selecting fainter candidate strongly lensed galaxies, reaching a surface density of ~1.5-2 deg^-2, i.e. a factor of about 4 to 6 higher than that at the 100 mJy flux limit. HALOS will allow the selection of up to ~1000 candidate strongly lensed galaxies (with amplifications \mu>2) over the full H-ATLAS survey area. Applying HALOS to the H-ATLAS Science Demonstration Phase field (~14.4 deg^2) we find 31 candidate strongly lensed galaxies, whose candidate lenses are identified in the VIKING near-infrared catalog. Using the available information on candidate sources and candidate lenses we tentatively estimate a ~72% purity of the sample. The redshift distribution of the candidate lensed sources is close to that reported for most previous surveys for lensed galaxies, while that of candidate lenses extends to substantially higher redshifts than found in the other surveys. The counts of candidate strongly lensed galaxies are also in good agreement with model predictions (Lapi et al. 2011). Even though a key ingredient of the method is the deep near-infrared VIKING photometry, we show that H-ATLAS data alone allow the selection of a similarly deep sample of candidate strongly lensed galaxies with an efficiency close to 50%; a slightly lower surface density (~1.45 deg^-2) can be reached with a ~70% efficiency., Comment: 36 pages, 12 figures, 1 table. Accepted by ApJ

Published
2012
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123. Herschel-ATLAS Galaxy Counts and High Redshift Luminosity Functions: The Formation of Massive Early Type Galaxies

Author

Lapi, A., Gonzalez-Nuevo, J., Fan, L., Bressan, A., De Zotti, G., Danese, L., Negrello, M., Dunne, L., Eales, S., Maddox, S., Auld, R., Baes, M., Bonfield, D. G., Buttiglione, S., Cava, A., Clements, D. L., Cooray, A., Dariush, A., Dye, S., Fritz, J., Herranz, D., Hopwood, R., Ibar, E., Ivison, R., Jarvis, M. J., Kaviraj, S., Lopez-Caniego, M., Massardi, M., Michalowski, M. J., Pascale, E., Pohlen, M., Rigby, E., Rodighiero, G., Serjeant, S., Smith, D. J. B., Temi, P., Wardlow, J., and van der Werf, P.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Exploiting the Herschel-ATLAS Science Demonstration Phase (SDP) survey data, we have determined the luminosity functions (LFs) at rest-frame wavelengths of 100 and 250 micron and at several redshifts z>1, for bright sub-mm galaxies with star formation rates (SFR) >100 M_sun/yr. We find that the evolution of the comoving LF is strong up to z~2.5, and slows down at higher redshifts. From the LFs and the information on halo masses inferred from clustering analysis, we derived an average relation between SFR and halo mass (and its scatter). We also infer that the timescale of the main episode of dust-enshrouded star formation in massive halos (M_H>3*10^12 M_sun) amounts to ~7*10^8 yr. Given the SFRs, which are in the range 10^2-10^3 M_sun/yr, this timescale implies final stellar masses of order of 10^11-10^12 M_sun. The corresponding stellar mass function matches the observed mass function of passively evolving galaxies at z>1. The comparison of the statistics for sub-mm and UV selected galaxies suggests that the dust-free, UV bright phase, is >10^2 times shorter than the sub-mm bright phase, implying that the dust must form soon after the onset of star formation. Using a single reference Spectral Energy Distribution (SED; the one of the z~2.3 galaxy SMM J2135-0102), our simple physical model is able to reproduce not only the LFs at different redshifts > 1 but also the counts at wavelengths ranging from 250 micron to ~1 mm. Owing to the steepness of the counts and their relatively broad frequency range, this result suggests that the dispersion of sub-mm SEDs of z>1 galaxies around the reference one is rather small., Comment: 33 pages, 19 figures, 2 tables. Accepted by ApJ

Published
2011
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124. Cosmic Evolution of Size and Velocity Dispersion for Early Type Galaxies

Author

Fan, L., Lapi, A., Bressan, A., Bernardi, M., De Zotti, G., and Danese, L.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

[abridged] Massive, passively evolving galaxies at redshifts z>1 exhibit on the average physical sizes smaller by factors ~3 than local early type galaxies (ETGs) endowed with the same stellar mass. Small sizes are in fact expected on theoretical grounds, if dissipative collapse occurs. Recent results show that the size evolution at z<1 is limited to less than 40%, while most of the evolution occurs at z>1, where both compact and already extended galaxies are observed and the scatter in size is remarkably larger than locally. The presence at high z of a significant number of ETGs with the same size as their local counterparts as well as of ETGs with quite small size, points to a timescale to reach the new, expanded equilibrium configuration of less than the Hubble time. We demonstrate that the projected mass of compact, high-z galaxies and that of local ETGs within the *same physical radius*, the nominal half-luminosity radius of high-z ETGs, differ substantially, in that the high-z ETGs are on the average significantly denser. We propose that quasar activity, which peaks at z~2, can remove large amounts of gas from central galaxy regions on a timescale shorter than of the dynamical one, triggering a puffing up of the stellar component at constant stellar mass; in this case the size increase goes together with a decrease of the central mass. The size evolution is expected to parallel that of the quasars and the inverse hierarchy, or downsizing, seen in the quasar evolution is mirrored in the size evolution., Comment: 18 pages, 6 figures, uses RevTeX4 + emulateapj.cls and apjfonts.sty. Accepted by ApJ

Published
2010
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125. Herschel-ATLAS: blazars in the SDP field

Author

González-Nuevo, J., De Zotti, G., Andreani, P., Barton, E. J., Bertoldi, F., Birkinshaw, M., Bonavera, L., Buttiglione, S., Cooke, J., Cooray, A., Danese, G., Dunne, L., Eales, S., Fan, L., Jarvis, M. J., Klöckner, H-R., Hatziminaoglou, E., Herranz, D., Hughes, D. H., Lapi, A., Lawrence, A., Leeuw, L., López-Caniego, M., Massardi, M., Mauch, T., Michalowski, M. J., Negrello, M., Rawlings, S., Rodighiero, G., Samui, S., Serjeant, S., Vieira, J. D., White, G., Amblard, A., Auld, R., Baes, M., Bonfield, D. G., Burgarella, D., Cava, A., Clements, D. L., Dariush, A., Dye, S., Frayer, D., Fritz, J., Ibar, E., Ivison, R. J., Lagache, G., Maddox, S., Pascale, E., Pohlen, M., Rigby, E., Sibthorpe, B., Smith, D. J. B., Temi, P., Thompson, M., Valtchanov, I., and Verma, A.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

To investigate the poorly constrained sub-mm counts and spectral properties of blazars we searched for these in the Herschel-ATLAS (H-ATLAS) science demostration phase (SDP) survey catalog. We cross-matched 500$\mu$m sources brighter than 50 mJy with the FIRST radio catalogue. We found two blazars, both previously known. Our study is among the first blind blazar searches at sub-mm wavelengths, i.e., in the spectral regime where little is still known about the blazar SEDs, but where the synchrotron peak of the most luminous blazars is expected to occur. Our early results are consistent with educated extrapolations of lower frequency counts and question indications of substantial spectral curvature downwards and of spectral upturns at mm wavelengths. One of the two blazars is identified with a Fermi/LAT $\gamma$-ray source and a WMAP source. The physical parameters of the two blazars are briefly discussed.These observations demonstrate that the H-ATLAS survey will provide key information about the physics of blazars and their contribution to sub-mm counts., Comment: 5 pages, 2 figures, accepted for publication in A&A (Herschel special issue)

Published
2010
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126. The Herschel ATLAS

Author

Eales, S., Dunne, L., Clements, D., Cooray, A., De Zotti, G., Dye, S., Ivison, R., Jarvis, M., Lagache, G., Maddox, S., Negrello, M., Serjeant, S., Thompson, M. A., Van Kampen, E., Amblard, A., Andreani, P., Baes, M., Beelen, A., Bendo, G. J., Benford, D., Bertoldi, F., Bock, J., Bonfield, D., Boselli, A., Bridge, C., Buat, V., Burgarella, D., Carlberg, R., Cava, A., Chanial, P., Charlot, S., Christopher, N., Coles, P., Cortese, L., Dariush, A., Da Cunha, E., Dalton, G., Danese, L., Dannerbauer, H., Driver, S., Dunlop, J., Fan, L., Farrah, D., Frayer, D., Frenk, C., Geach, J., Gardner, J., Gomez, H., Gonzalez-Nuevo, J., Gonzalez-Solares, E., Griffin, M., Hardcastle, M., Hatziminaoglou, E., Herranz, D., Hughes, D., Ibar, E., Jeong, Woong-Seob, Lacey, C., Lapi, A., Lee, M., Leeuw, L., Liske, J., Lopez-Caniego, M., Muller, T., Nandra, K., Panuzzo, P., Papageorgiou, A., Patanchon, G., Peacock, J., Pearson, C., Phillipps, S., Pohlen, M., Popescu, C., Rawlings, S., Rigby, E., Rigopoulou, M., Rodighiero, G., Sansom, A., Schulz, B., Scott, D., Smith, D. J. B., Sibthorpe, B., Smail, I., Stevens, J., Sutherland, W., Takeuchi, T., Tedds, J., Temi, P., Tuffs, R., Trichas, M., Vaccari, M., Valtchanov, I., Van der Werf, P., Verma, A., Vieria, J., Vlahakis, C., and White, Glenn J.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The Herschel ATLAS is the largest open-time key project that will be carried out on the Herschel Space Observatory. It will survey 510 square degrees of the extragalactic sky, four times larger than all the other Herschel surveys combined, in five far-infrared and submillimetre bands. We describe the survey, the complementary multi-wavelength datasets that will be combined with the Herschel data, and the six major science programmes we are undertaking. Using new models based on a previous submillimetre survey of galaxies, we present predictions of the properties of the ATLAS sources in other wavebands., Comment: submitted to PASP

Published
2009
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129. MA06.03 KontRASt-01: Preliminary Safety and Efficacy of JDQ443 + TNO155 in Patients with Advanced, KRAS G12C-Mutated Solid Tumors

Author

Negrao, M.V., primary, Cassier, P.A., additional, Solomon, B., additional, Schuler, M., additional, Rohrberg, K., additional, Cresta, S., additional, Dooms, C., additional, Tan, D.S.W., additional, Loong, H.H-f., additional, Amatu, A., additional, Assmann, K. Krueger, additional, Fairchild, L., additional, Sansregret, L., additional, Fan, L., additional, Farago, A.F., additional, and Cho, B.C., additional

Published
2023
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131. Berberine induces apoptosis in non-small-cell lung cancer cells by upregulating miR-19a targeting tissue factor

Author

Chen Q, Shi J, Ding Z, Xia Q, Zheng T, Ren Y, Li M, and Fan L

Subjects
non-small-cell lung carcinoma (NSCLC), berberine, miR-19a, tissue factor (TF), MAPK., Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Qian-qian Chen,1–3 Jia-min Shi,1,2 Zhou Ding,1,2 Qing Xia,1,2 Tian-sheng Zheng,1,2 Yan-bei Ren,1,2 Ming Li,1,2 Li-hong Fan1,2 1Department of Respiratory Medicine, Shanghai 10th People’s Hospital, Tongji University, Shanghai 200072, People’s Republic of China; 2Institute of Energy Metabolism and Health, Tongji University School of Medicine, Shanghai 200072, People’s Republic of China; 3Medical School of Nantong University, Nantong, Jiangsu 22601, People’s Republic of ChinaCorrespondence: Li-hong Fan; Ming LiDepartment of Respiratory Medicine, Shanghai 10th People’s Hospital, Tongji University, #301 Mid Yianchang Road, Shanghai 200072, People’s Republic of ChinaTel/fax +86 1 800 176 3288; +86 1 339 135 8760Email 18260626371@163.com; mlid163@163.comBackground: Berberine (BBR) from the widely used Chinese herbal medicine Huanglian has an array of pharmacological and biochemical properties, including anti-neoplastic activity. However, the specific mechanisms underlying these properties are unknown. The aim of this study was to explore the anti-tumor mechanisms of BBR in non-small cell lung cancer (NSCLC).Methods: The effects of BBR on NSCLC tumor development and programmed cell death were investigated both in vivo and in vitro. Luciferase reporter assays were used to determine whether tissue factor (TF) was a target of miR-19a.Results: BBR suppressed NSCLC growth and promoted apoptosis in NSCLC cells by modulating miR-19a and TF expression. Luciferase assays showed that TF was a direct inhibitory target of miR-19a in NSCLC cells. BBR induced apoptosis through the miR-19a/TF/MAPK axis.Conclusion: The results suggest that BBR induces apoptosis of NSCLC cells via the miR-19a/TF/MAPK signaling pathway.Keywords: non-small-cell lung carcinoma, NSCLC, berberine, miR-19a, tissue factor, TF, MAPK

Published
2019

132. The dramatic size evolution of elliptical galaxies and the quasar feedback

Author

Fan, L., Lapi, A., De Zotti, G., and Danese, L.

Subjects
Astrophysics
Abstract

Observations have evidenced that passively evolving massive galaxies at high redshift are much more compact than local galaxies with the same stellar mass. We argue that the observed strong evolution in size is directly related to the quasar feedback, which removes huge amounts of cold gas from the central regions in a Salpeter time, inducing an expansion of the stellar distribution. The new equilibrium configuration, with a size increased by a factor >~ 3, is attained after ~ 40 dynamical times, corresponding to ~ 2 Gyr. This means that massive galaxies observed at z >~ 1 will settle on the Fundamental Plane by z ~ 0.8-1. In less massive galaxies (M_star <~ 2 10^10 M_sun), the nuclear feedback is subdominant, and the mass loss is mainly due to stellar winds. In this case, the mass loss timescale is longer than the dynamical time and results in adiabatic expansion that may increase the effective radius by a factor of up to ~ 2 in 10 Gyr, although a growth by a factor of ~ 1.6 occurs within the first 0.5 Gyr. Since observations are focused on relatively old galaxies, with ages >~ 1 Gyr, the evolution for smaller galaxies is more difficult to perceive. Significant evolution of velocity dispersion is predicted for both small and large galaxies., Comment: 4 pages, 2 figures, uses REVTeX4 + emulateapj.cls and apjfonts.sty. Accepted by ApJL

Published
2008
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133. Inhibition of tumor metastasis by targeted daunorubicin and dioscin codelivery liposomes modified with PFV for the treatment of non-small-cell lung cancer

Author

Wang Y, Fu M, Liu J, Yang Y, Yu Y, Li J, Pan W, Fan L, Li G, Li X, and Wang X

Subjects
daunorubicin, dioscin, liposomes, cell penetrating peptides, tumor metastasis, non-small-cell lung cancer, Medicine (General), R5-920
Abstract

Yuanyuan Wang,1 Min Fu,2 Jingjing Liu,2 Yining Yang,1 Yibin Yu,1 Jinyu Li,1 Weisan Pan,1 Lei Fan,3 Guiru Li,4 Xuetao Li,2 Xiaobo Wang1,31Department of Pharmaceutics, Shenyang Pharmaceutical University, Shenyang, Liaoning, People’s Republic of China; 2School of Pharmacy, Liaoning University of Traditional Chinese Medicine, Dalian, Liaoning, People’s Republic of China; 3Department of Pharmacy, 210th Hospital of People’s Liberation Army, Dalian, Liaoning, People’s Republic of China; 4Department of Pharmacy, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, People’s Republic of ChinaBackground: Chemotherapy for non-small-cell lung cancer (NSCLC) still leads to unsatisfactory clinical prognosis because of poor active targeting and tumor metastasis.Purpose: The objective of this study was to construct a kind of PFV peptide modified targeted daunorubicin and dioscin codelivery liposomes, which could enhance tumor targeting and inhibit tumor cell metastasis.Methods and results: Targeted daunorubicin and dioscin codelivery liposomes were prepared by film dispersion and the ammonium sulfate gradient method. With the ideal physicochemical properties, targeted daunorubicin and dioscin codelivery liposomes exhibited enhanced cellular uptake and showed strong cytotoxicity to tumor cells. The encapsulation of dioscin increased the inhibitory effects of daunorubicin on A549 cells, vasculogenic mimicry (VM) channels and tumor metastasis. The enhanced antimetastatic mechanism of the targeted liposomes was attributed to the downregulation of matrix metalloproteinase-2 (MMP-2), vascular endothelial cadherin (VE-Cad), transforming growth factor-β1 (TGF-β1) and hypoxia inducible factor-1α (HIF-1α). Meanwhile, the targeted daunorubicin and dioscin codelivery liposomes exhibited significant antitumor effects in tumor-bearing mice. H&E staining, immunohistochemistry with Ki-67 and TUNEL assay also showed the promoted antitumor activity of the targeted liposomes.Conclusion: Targeted daunorubicin and dioscin codelivery liposomes may provide an effective strategy for the treatment of NSCLC.Keywords: daunorubicin, dioscin, liposomes, cell penetrating peptides, tumor metastasis, non-small-cell lung cancer

Published
2019

134. Diabetes mellitus predicts inferior survival in diffuse large B-cell lymphoma: a propensity score-matched analysis

Author

Gao R, Liang JH, Man TS, Wang L, Zhu HY, Wu W, Fan L, Li JY, Yang T, and Xu W

Subjects
diffuse large B cell lymphoma, diabetes mellitus, progression-free survival, cancer-specific survival, propensity score-matched analysis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Rui Gao,1 Jin-Hua Liang,2 Tian-Shuo Man,2 Li Wang,2 Hua-Yuan Zhu,2 Wei Wu,2 Lei Fan,2 Jian-Yong Li,2 Tao Yang,1,* Wei Xu2,*1Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing 210029, People’s Republic of China; 2Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing 210029, People’s Republic of China*These authors contributed equally to this workPurpose: Diabetes mellitus (DM) is associated with elevated cancer risk and poor survival. The objective of this study was to assess the prognostic value of DM in diffuse large B-cell lymphoma (DLBCL).Methods: Five hundred and fifty-three newly diagnosed DLBCL patients whose treatments included rituximab were recruited. Propensity score-matched method was performed to balance baseline characteristics and eliminate possible bias. Multivariate Cox regression analyses screened the prognostic risk factors in relation to progression-free survival (PFS) and cancer-specific survival (CSS). Receiver-operator characteristic curves and the corresponding areas under the curve (AUC) assessed the predictive accuracy of international prognostic index (IPI) together with DM.Results: One hundred and nine patients (19.71%) had pre-existing DM. In the propensity-matched cohort, DM was associated with unfavorable PFS and CSS in rituximab era, and it was an independent risk factor for both inferior PFS and CSS, especially in patients with age ≤60 years, IPI 0−2, B symptoms and lactate dehydrogenase ≤upper limit of normal. Prediabetics also demonstrated inferior prognostic outcomes compared to patients with no diabetic tendency. DM as one additional point to IPI had larger AUC compared with IPI alone in CSS prediction and could improve the prognostic capacity of IPI.Conclusion: The results indicate that preexisting DM is an important risk factor for survival. It could help predict life expectancy and build refined prognostication models for DLBCL.Keywords: diffuse large B-cell lymphoma, diabetes mellitus, progression-free survival, cancer-specific survival, propensity score-matched analysis

Published
2019

135. Does experimentally induced pain affect attention? A meta-analytical review

Author

Gong W, Fan L, and Luo F

Subjects
experimental pain, attention, meta-analysis, Medicine (General), R5-920
Abstract

Wenxiao Gong,1,2 Lu Fan,1,2 Fei Luo1,2 1CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, People’s Republic of China; 2Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China Background: Recent studies have found that clinical pain is related to cognitive impairment. However, there remains a scarcity of systematic reviews on the influence of acute pain on attention. Laboratory-induced pain is often used to simulate acute pain. The current systematic meta-analysis aimed to evaluate the effect of induced-pain on three components of attention (orienting, alerting, and executive attention) in healthy subjects. Methods: A systematic search of three databases was performed. Only data from studies that administered laboratory-induced pain and that also included a control group were selected. The effects of experimental pain on orienting attention, alerting attention, and executive attention were analyzed. Two reviewers assessed the studies and extracted relevant data according to the Cochrane Collaboration and Preferred Reporting Items for Systematic Reviews and Meta-Analysis Guidelines. Results: Eight studies were included in the meta-analysis. Orienting attention was marginally interrupted by pain under the invalid cue and marginally facilitated by pain under the valid cue condition. Performance on alerting attention was decreased by pain. Executive attention was not significantly affected by pain.Conclusion: There was moderate evidence that experimentally induced pain can produce effects on orienting and alerting attention but not on executive attention. This meta-analysis suggests that experimentally induced pain influences some aspects of attention. Keywords: experimental pain, attention, meta-analysis

Published
2019

138. Investigating on the nuclear obscuration in two types of Seyfert 2 galaxies

Author

Shu, X. W., Wang, J. X., Jiang, P., Fan, L. L., and Wang, T. G.

Subjects
Astrophysics
Abstract

We build a large sample of Seyfert 2 galaxies (Sy2s) with both optical spectropolarimetric and X-ray data available, in which 29 Sy2s with the detection of polarized broad emission line (PBL) and 25 without. We find that for luminous Sy2s with L_[OIII] > 10^41 erg/s, sources with PBL have smaller X-ray absorption column density comparing with those without PBL (at 92.3% confidence level): most of the Sy2s with N_H<10^23.8 cm^-2 show PBL (86%, 12 out 14), while the fraction is much smaller for sources with heavier obscuration (54%, 15 out 28). The confidence level of the difference in absorption bounces up to 99.1% while using the "T" ratio (F_2-10keV/F_[O III]) as an indicator. We rule out observation or selection bias as the origin for the difference. Our results, for the first time with high statistical confidence, show that, in additional to the nuclei activity, the nuclear obscuration also plays an important role in the visibility of PBL in Sy2s. These results can be interpreted in the framework of the unified model. We can reach these results in the unified model if: a) the absorption column density is higher at large inclinations and b) the scattering region is obscured at large inclinations., Comment: 28 pages, including 7 figures and 3 tables, ApJ accepted

Published
2006
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140. Two dimensional scaling of resistance in flux flow region in $Tl_2Ba_2CaCu_2O_8$ thin films

Author

Lu, X. F., Wang, Z., Gao, H., Shan, L., Zhang, Y. Z., Lu, R. T., Fan, L., Yan, S. L., Wang, Z. D., and Wen, H. H.

Subjects
Condensed Matter - Superconductivity
Abstract

The resistance of $Tl_2Ba_2CaCu_2O_8$ thin films has been measured when the angle between the applied fields and $ab$-plane of the film is changed continuously at various temperatures. Under various magnetic fields, the resistance can be well scaled in terms of the c-axis component of the applied fields at the same temperature in the whole angle range. Meanwhile, we show that the measurement of resistance in this way is a complementary method to determine the growth orientation of the anisotropic high-$T_c$ superconductors., Comment: 11 pages, 8 figures. Have been published in Physica C

Published
2004
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141. A Toy Model for Cooperative Phenomena in Molecular Biology and the Utilization of Biochemical Applications of PNS in Genetic Applications

Author

Bumble, S., Friedler, F., and Fan, L. T.

Subjects
Condensed Matter, Physics - Biological Physics, Quantitative Biology
Abstract

Qualitative attributes of the region between order and disorder are examined to explore models of genetic and protein networks. Results show how the connectivity of vertices and the strength of their connections are related and how their stability is related to their geometry. It has been possible to relate the interaction energies and chemical potentials of general lattices with the coordination numbers of such lattice models. The results seem to agree with some of those obtained by means of other methods, e.g., those of Barabasi, Strognatz, Dorogovtsev, and Kauffman (BSDK). This can yield new perspectives to the cause, treatment and remedies of disease other than the present mode of drug discovery prevalent: the docking of a single ligand on to a target molecule. In order to utilize such results more efficiently, the pathway of biological processes need be elucidated. A method is available for determining biochemical-reaction or metabolic pathways through its systematic synthesis. It is based on a rigorous graph-theoretic method for identifying pathways of catalytic reactions. It synthesizes networks of metabolic pathways using a highly exacting combinatorial method. It generates not only all feasible, independent reaction networks but also those combinations of independent pathways. This method can determine the mechanisms of complex chemical reactions and is applicable to biochemical reactions. It is important to combine this result with the mechanisms existent in gene regulatory networks. Training Genetic Regulatory Networks for feasible biochemical reaction networks or pathways and incorporating such knowledge into DNA would be a superb technique for vanquishing complex diseases., Comment: 13 pages, 7 figures

Published
2003

145. Characteristics of Molecular-biological Systems and Process-network Synthesis

Author

Papp, L., Bumble, S., Friedler, F., and Fan, L. T.

Subjects
Physics - Biological Physics, Quantitative Biology
Abstract

Graph Theoretic Process Network Synthesis is described as an introduction to biological networks. Genetic, protein and metabolic systems are considered. The theoretical work of Kauffman is discussed and amplified by critical property excursions. The scaling apparent in biological systems is shown. Applications to evolution and reverse engineering are construed. The use of several programs, such as the Synprops, Design of molecules, Therm and Knapsack are suggested as instruments to study biological process network synthesis. The properties of robust self-assembly and Self-Organizing synthesis are important contributors to the discussion. The bar code of life and intelligent design is reviewed. The need for better data in biological systems is emphasized., Comment: 25 pages

Published
2002

146. α-hemihydrate calcium sulfate/octacalcium phosphate combined with sodium hyaluronate promotes bone marrow-derived mesenchymal stem cell osteogenesis in vitro and in vivo

Author

Chen C, Zhu C, Hu X, Yu Q, Zheng Q, Tao S, and Fan L

Subjects
Sodium hyaluronate, Characterization, BMSCs, Biocompatibility, Osteogenic differentiation, Therapeutics. Pharmacology, RM1-950
Abstract

Changshun Chen,1 Chen Zhu,2 Xiang Hu,1 Qiuli Yu,3 Qianjin Zheng,1 Shengxiang Tao,1 Lihong Fan2 1Department of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China; 2School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan, Hubei, China; 3School of Health Sciences, Wuhan University, Wuhan, Hubei, China Purpose: The aims of this research were to combine a-hemihydrate calcium sulfate/octacalcium phosphate (α-CSH/OCP) with sodium hyaluronate (SH) or SH sulfate (SHS) to determine whether these composites can be used as a new type of bone repair material. This study may provide a theoretical basis and new ideas for the construction of active bone repair materials and their clinical application.Methods: In this study, we combined α-CSH/OCP with SH or SHS. Scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), thermogravimetric analysis (TGA), and the wettability test were performed, and porosity, setting time, in vitro degradation, and the mechanical properties of these composite materials were analyzed to evaluate the ultrastructural and physicochemical properties. We evaluated the histocompatibility of these composites by MTT assay, hemolysis, acute toxicity, and pyrogenic and intracutaneous stimulation tests. In addition, the osteogenic differentiation ability of these materials was detected in vitro using Western blot analysis and in vivo using an animal model of bone defect.Results: The α-CSH/OCP/SH composite had a compressive strength of 13.72 MPa, a porous rate of 27.45%, and the 28-day degradation rate of 64%. The MTT assay results showed that the relative proliferation rates of the α-CSH/OCP/SH group were greater than 90%. The results of the α-CSH/OCP/SH composite in the hemolysis, acute toxicity, pyrogenic, and intracutaneous stimulation tests were within the normal range. Western blot analysis indicated that the expression of bone extracellular matrix (ECM) proteins was notably upregulated and always higher in the α-CSH/OCP/SH group than in the other groups. XRD of the rabbit radius-defect model indicated that bone healing in the area implanted with α-CSH/OCP/SH was excellent approximately 9 weeks after repair.Conclusion: α-CSH/OCP/SH has very good biocompatibility and exhibits clear advantages in the induction of bone regeneration and self-repair, and this compound shows promise in the field of bone tissue engineering. Keywords: sodium hyaluronate, characterization, BMSCs, biocompatibility, osteogenic differentiation

Published
2018

147. Pharmacological mechanism of roflumilast in the treatment of asthma–COPD overlap

Author

Zhang X, Chen Y, Fan L, Ye J, Fan J, Xu X, You D, Liu S, Chen X, and Luo P

Subjects
asthma-chronic obstructive pulmonary disease overlap, roflumilast, phosphodiesterase-4 inhibitors, mechanism., Therapeutics. Pharmacology, RM1-950
Abstract

Xiaoli Zhang,1,* Yuqing Chen,1,* Liyu Fan,1,* Jiaqi Ye,1 Junsheng Fan,2 Xinjie Xu,1 Danming You,3 Sihan Liu,3 Xin Chen,1 Peng Luo1 1Department of Respiratory Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China; 2Department of Respiratory Medicine, Shanghai Tenth People’s Hospital of Tongji University, Shanghai, China; 3Department of Respiratory Medicine, Nangfang Hospital of Southern Medical University, Guangzhou, China *These authors contributed equally to this work Abstract: Asthma–COPD overlap (ACO) is a type of incomplete obstructive airway disease that has a high incidence and mortality. Nevertheless, there is currently no clear definition of ACO and no effective intervention. The newly discovered phosphodiesterase-4 inhibitor, roflumilast, has shown initial efficacy for treating asthma, COPD, and ACO. The mechanism of roflumilast, however, remains unclear, and there has been no interpretation through systematic review to date. The determination of a definite mechanism of roflumilast will guide the clinician’s decisions regarding medication use, standardized diagnosis, and treatment guidelines. For this reason, we have systematically reviewed the therapeutic mechanism of roflumilast for ACO and provided reference for the clinical application of roflumilast in ACO. Keywords: asthma–COPD overlap, roflumilast, phosphodiesterase-4 inhibitors, mechanism

Published
2018

148. Surgical significance and efficacy of epidermal growth factor receptor tyrosine kinase inhibitors in patients with primary lung adenosquamous carcinoma

Author

Zhang C, Yang H, Lang B, Yu X, Xiao P, Zhang D, Fan L, and Zhang X

Subjects
Lung adenosquamous carcinoma, EGFR, surgery, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Chao Zhang,1,* Haitang Yang,2–4,* Baoping Lang,1 Xiangdong Yu,1 Peng Xiao,1 Dian Zhang,1 Liwen Fan,5 Xiao Zhang1 1Department of Thoracic Surgery, The Affiliated Luoyang Central Hospital of Zhengzhou University, Luoyang, China; 2Division of General Thoracic Surgery, Inselspital, Bern University Hospital, Bern, Switzerland; 3Department for BioMedical Research, University of Bern, Bern, Switzerland; 4Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland; 5Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiaotong University, Shanghai, China *These authors contributed equally to this work Background: Primary adenosquamous carcinoma (ASC) of the lung is a rare and aggressive disease. The accurate diagnosis of ASC based on small biopsies is challenging because of the mixed components within the tumor, and this may lead to suboptimal treatment. Furthermore, information about the efficacy of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in lung ASC is limited. Patients and methods: Data on a cohort of patients with lung ASC who underwent surgery between October 2008 and December 2016 at a single institution were retrospectively reviewed. Results: This study analyzed 148 patients. Differences between the pre- and post-resection diagnosis were observed. Based on the results of preoperative biopsy, patients were diagnosed as having squamous cell carcinoma (n=26), adenocarcinoma (n=20), poorly differentiated carcinoma (n=20), and large cell carcinoma (n=1), and finally diagnosed as having ASC based on histopathological examination of the surgical specimens. Thirty patients (20.3%) with EGFR-sensitizing mutations (TKI group) were treated with EGFR-TKIs after surgery, whereas the remaining patients (79.7%) with unknown EGFR-mutation status received chemotherapy or chemoradiotherapy alone (non-TKI group). TKI treatment was associated with better median overall survival (OS) (HR=0.619; p=0.034). Multivariate analysis identified the presence of EGFR-TKI treatment as an independent prognostic factor for OS (HR=0.471; p=0.003). Conclusion: Discrepancies between the pre- and post-operative diagnosis reflect the inadequacy of non-resection approaches to the diagnosis of ASC. ASC patients harboring EGFR-sensitizing mutations who were treated with EGFR-TKIs showed a significantly better prognosis than those receiving chemotherapy or chemoradiotherapy alone. Keywords: adenosquamous carcinoma, lung, EGFR, surgery, recurrence

Published
2018

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