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Fu M, Yang L, Wang H, Chen Y, Chen X, Hu Q, Sun H. Research progress into adipose tissue macrophages and insulin resistance. Physiol Res 2023; 72:287-299. [PMID: 37449743 PMCID: PMC10668993 DOI: 10.33549/physiolres.935046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/07/2023] [Indexed: 08/26/2023] Open
Abstract
In recent years, there has been an increasing incidence of metabolic syndrome, type 2 diabetes, and cardiovascular events related to insulin resistance. As one of the target organs for insulin, adipose tissue is essential for maintaining in vivo immune homeostasis and metabolic regulation. Currently, the specific adipose tissue mechanisms involved in insulin resistance remain incompletely understood. There is increasing evidence that the process of insulin resistance is mostly accompanied by a dramatic increase in the number and phenotypic changes of adipose tissue macrophages (ATMs). In this review, we discuss the origins and functions of ATMs, some regulatory factors of ATM phenotypes, and the mechanisms through which ATMs mediate insulin resistance. We explore how ATM phenotypes contribute to insulin resistance in adipose tissue. We expect that modulation of ATM phenotypes will provide a novel strategy for the treatment of diseases associated with insulin resistance.
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, H XT, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner MK, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner UW, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. First Study of Reaction Ξ^{0}n→Ξ^{-}p Using Ξ^{0}-Nucleus Scattering at an Electron-Positron Collider. PHYSICAL REVIEW LETTERS 2023; 130:251902. [PMID: 37418739 DOI: 10.1103/physrevlett.130.251902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 05/20/2023] [Accepted: 05/25/2023] [Indexed: 07/09/2023]
Abstract
Using (1.0087±0.0044)×10^{10} J/ψ events collected with the BESIII detector at the BEPCII storage ring, the process Ξ^{0}n→Ξ^{-}p is studied, where the Ξ^{0} baryon is produced in the process J/ψ→Ξ^{0}Ξ[over ¯]^{0} and the neutron is a component of the ^{9}Be, ^{12}C, and ^{197}Au nuclei in the beam pipe. A clear signal is observed with a statistical significance of 7.1σ. The cross section of the reaction Ξ^{0}+^{9}Be→Ξ^{-}+p+^{8}Be is determined to be σ(Ξ^{0}+^{9}Be→Ξ^{-}+p+^{8}Be)=(22.1±5.3_{stat}±4.5_{sys}) mb at the Ξ^{0} momentum of 0.818 GeV/c, where the first uncertainty is statistical and the second is systematic. No significant H-dibaryon signal is observed in the Ξ^{-}p final state. This is the first study of hyperon-nucleon interactions in electron-positron collisions and opens up a new direction for such research.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao XL, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jang E, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Measurements of Normalized Differential Cross Sections of Inclusive π^{0} and K_{S}^{0} Production in e^{+}e^{-} Annihilation at Energies from 2.2324 to 3.6710 GeV. PHYSICAL REVIEW LETTERS 2023; 130:231901. [PMID: 37354421 DOI: 10.1103/physrevlett.130.231901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 03/22/2023] [Accepted: 04/03/2023] [Indexed: 06/26/2023]
Abstract
Based on electron positron collision data collected with the BESIII detector operating at the BEPCII storage rings, the differential cross sections of inclusive π^{0} and K_{S}^{0} production as a function of hadron momentum, normalized by the total cross section of the e^{+}e^{-}→hadrons process, are measured at six center-of-mass energies from 2.2324 to 3.6710 GeV. Our results, which cover a relative hadron energy range from 0.1 to 0.9, significantly deviate from several theoretical calculations based on existing fragmentation functions.
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Zhang SM, Qiu F, Sun X, Sun H, Wu L, Huang DH, Wu WP. [Analysis of the clinical characteristics and misdiagnosis of area postrema syndrome manifesting as intractable nausea, vomiting, and hiccups in neuromyelitis optica spectrum disorders]. ZHONGHUA NEI KE ZA ZHI 2023; 62:705-710. [PMID: 37263955 DOI: 10.3760/cma.j.cn112138-20220621-00468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Objective: To investigate the misdiagnosis of area postrema syndrome (APS) manifesting as intractable nausea, vomiting and hiccups in neuromyelitis optic spectrum disease (NMOSD) and reduce the risk of misdiagnosis. Methods: We retrospectively analyzed data from NMOSD patients attending the Department of Neurology at the First Medical Center of PLA General Hospital between January 2019 and July 2021. SPSS25.0 was then used to analyze the manifestations, misdiagnosis, and mistreatment of APS. Results: A total of 207 patients with NMOSD were included, including 21 males and 186 females. The mean age of onset was 39±15 years (range: 5-72 years). The proportion of patients who were positive for serum aquaporin 4 antibody was 82.6% (171/207). In total, 35.7% (74/207) of the NMOSD patients experienced APS during the disease course; of these patients, 70.3% (52/74) had APS as the first symptom and 29.7% (22/74) had APS as a secondary symptom. The misdiagnosis rates for these conditions were 90.4% (47/52) and 50.0% (11/22), respectively. As the first symptom, 19.2% (10/52) of patients during APS presented only with intractable nausea, vomiting and hiccups; 80.8% (42/52) of patients experienced other neurological symptoms. The Departments of Gastroenterology and General Medicine were the departments that most frequently made the first diagnosis of APS, accounting for 54.1% and 17.6% of patients, respectively. The most common misdiagnoses related to diseases of the digestive system and the median duration of misdiagnosis was 37 days. Conclusions: APS is a common symptom of NMOSD and is associated with a high rate of misdiagnosis. Other concomitant symptoms often occur with APS. Gaining an increased awareness of this disease/syndrome, obtaining a detailed patient history, and performing physical examinations are essential if we are to reduce and avoid misdiagnosis.
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, H XT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu WL, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Precision Measurement of the Decay Σ^{+}→pγ in the Process J/ψ→Σ^{+}Σ[over ¯]^{-}. PHYSICAL REVIEW LETTERS 2023; 130:211901. [PMID: 37295102 DOI: 10.1103/physrevlett.130.211901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/29/2023] [Accepted: 05/08/2023] [Indexed: 06/12/2023]
Abstract
Using (10 087±44)×10^{6} J/ψ events collected with the BESIII detector, the radiative hyperon decay Σ^{+}→pγ is studied at an electron-positron collider experiment for the first time. The absolute branching fraction is measured to be (0.996±0.021_{stat}±0.018_{syst})×10^{-3}, which is lower than its world average value by 4.2 standard deviations. Its decay asymmetry parameter is determined to be -0.652±0.056_{stat}±0.020_{syst}. The branching fraction and decay asymmetry parameter are the most precise to date, and the accuracies are improved by 78% and 34%, respectively.
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Fan L, Zhang S, Li X, Hu Z, Yang J, Zhang S, Zheng H, Su Y, Luo H, Liu X, Fan Y, Sun H, Zhang Z, Miao J, Song B, Xia Z, Shi C, Mao C, Xu Y. CHCHD2 p.Thr61Ile knock-in mice exhibit motor defects and neuropathological features of Parkinson's disease. Brain Pathol 2023; 33:e13124. [PMID: 36322611 PMCID: PMC10154378 DOI: 10.1111/bpa.13124] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 10/07/2022] [Indexed: 05/04/2023] Open
Abstract
The p.Thr61Ile (p.T61I) mutation in coiled-coil-helix-coiled-coil-helix domain containing 2 (CHCHD2) was deemed a causative factor in Parkinson's disease (PD). However, the pathomechanism of the CHCHD2 p.T61I mutation in PD remains unclear. Few existing mouse models of CHCHD2-related PD completely reproduce the features of PD, and no transgenic or knock-in (KI) mouse models of CHCHD2 mutations have been reported. In the present study, we generated a novel CHCHD2 p.T61I KI mouse model, which exhibited accelerated mortality, progressive motor deficits, and dopaminergic (DA) neurons loss with age, accompanied by the accumulation and aggregation of α-synuclein and p-α-synuclein in the brains of the mutant mice. The mitochondria of mouse brains and induced pluripotent stem cells (iPSCs)-derived DA neurons carrying the CHCHD2 p.T61I mutation exhibited aberrant morphology and impaired function. Mechanistically, proteomic and RNA sequencing analysis revealed that p.T61I mutation induced mitochondrial dysfunction in aged mice likely through repressed insulin-degrading enzyme (IDE) expression, resulting in the degeneration of the nervous system. Overall, this CHCHD2 p.T61I KI mouse model recapitulated the crucial clinical and neuropathological aspects of patients with PD and provided a novel tool for understanding the pathogenic mechanism and therapeutic interventions of CHCHD2-related PD.
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Sun H, Liu J, Mao X, Wang C, Zhao Y, Qian Y. Rapid detection of ultratrace urinary arsenic by direct sampling microplasma vaporization based on silicon nitride. Anal Chim Acta 2023; 1251:341008. [PMID: 36925294 DOI: 10.1016/j.aca.2023.341008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 02/17/2023] [Accepted: 02/23/2023] [Indexed: 02/25/2023]
Abstract
At present, immediate monitoring urinary arsenic is still a challenge for treating arsenic poisoning patients. Thus, a fast, reliable and accurate analytical approach is indispensable to monitor ultratrace arsenic in urine sample for health warning. In this work, a silicon nitride (SN) rod was first integrally utilized as a sample carrier for ≤50 μL urinary aliquot, an electric heater for removing water and ashing sample as well as a high voltage electrode for dielectric barrier discharge vaporization (DBDV). The direct analytical method of arsenic in urine without sample digestion was thus developed using atomic fluorescence spectrometer (AFS) as a model detector. After 4 V electrically heating the SN rod for 60 s, urine sample was dehydrated and ashed outside; then, DBD was exerted under 0.8 A with 0.8 L/min H2 + Ar (1:9, v:v) for 20 s to vaporize arsenic analyte from the SN rod. After optimization, 0.014 μg/L arsenic detection limit (LOD) was reached with favorable analytical precision (RSD <5%) and accuracy (91-110% recoveries) for real sample analysis. As a result, the whole analysis process only consumes <3 min to exclude complicated sample preparation; furthermore, the designed DBDV system only occupies 25 W and <2 kg, which renders a miniature sampling component to hyphenate with a miniature detector to detect arsenic. Thus, this direct sampling DBDV method extremely fulfills the fast, sensitive and precise detection of ultratrace arsenic in urine sample.
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, H XT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BX, Liu BJ, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu WL, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Measurements of the Electric and Magnetic Form Factors of the Neutron for Timelike Momentum Transfer. PHYSICAL REVIEW LETTERS 2023; 130:151905. [PMID: 37115883 DOI: 10.1103/physrevlett.130.151905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/27/2023] [Accepted: 03/23/2023] [Indexed: 06/19/2023]
Abstract
We present the first measurements of the electric and magnetic form factors of the neutron in the timelike (positive q^{2}) region as function of four-momentum transfer. We explored the differential cross sections of the reaction e^{+}e^{-}→n[over ¯]n with data collected with the BESIII detector at the BEPCII accelerator, corresponding to an integrated luminosity of 354.6 pb^{-1} in total at twelve center-of-mass energies between sqrt[s]=2.0-2.95 GeV. A relative uncertainty of 18% and 12% for the electric and magnetic form factors, respectively, is achieved at sqrt[s]=2.3935 GeV. Our results are comparable in accuracy to those from electron scattering in the comparable spacelike region of four-momentum transfer. The electromagnetic form factor ratio R_{em}≡|G_{E}|/|G_{M}| is within the uncertainties close to unity. We compare our result on |G_{E}| and |G_{M}| to recent model predictions, and the measurements in the spacelike region to test the analyticity of electromagnetic form factors.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jang E, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Observation of a New X(3872) Production Process e^{+}e^{-}→ωX(3872). PHYSICAL REVIEW LETTERS 2023; 130:151904. [PMID: 37115900 DOI: 10.1103/physrevlett.130.151904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 03/16/2023] [Accepted: 03/20/2023] [Indexed: 06/19/2023]
Abstract
Using 4.7 fb^{-1} of e^{+}e^{-} collision data at center-of-mass energies from 4.661 to 4.951 GeV collected by the BESIII detector at the BEPCII collider, we observe the X(3872) production process e^{+}e^{-}→ωX(3872) for the first time. The significance is 7.8σ, including both the statistical and systematic uncertainties. The e^{+}e^{-}→ωX(3872) Born cross section and the corresponding upper limit at 90% confidence level at each energy point are reported. The line shape of the cross section indicates that the ωX(3872) signals may be from the decays of some nontrivial structures.
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Hayley S, Vahid-Ansari F, Sun H, Albert PR. Mood disturbances in Parkinson's disease: From prodromal origins to application of animal models. Neurobiol Dis 2023; 181:106115. [PMID: 37037299 DOI: 10.1016/j.nbd.2023.106115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 03/09/2023] [Accepted: 04/05/2023] [Indexed: 04/12/2023] Open
Abstract
Parkinson's disease (PD) is a complex illness with a constellation of environmental insults and genetic vulnerabilities being implicated. Strikingly, many studies only focus on the cardinal motor symptoms of the disease and fail to appreciate the major non-motor features which typically occur early in the disease process and are debilitating. Common comorbid psychiatric features, notably clinical depression, as well as anxiety and sleep disorders are thought to emerge before the onset of prominent motor deficits. In this review, we will delve into the prodromal stage of PD and how early neuropsychiatric pathology might unfold, followed by later motor disturbances. It is also of interest to discuss how animal models of PD capture the complexity of the illness, including depressive-like characteristics along with motor impairment. It remains to be determined how the underlying PD disease processes contributes to such comorbidity. But some of the environmental toxicants and microbial pathogens implicated in PD might instigate pro-inflammatory effects favoring α-synuclein accumulation and damage to brainstem neurons fueling the evolution of mood disturbances. We posit that comprehensive animal-based research approaches are needed to capture the complexity and time-dependent nature of the primary and co-morbid symptoms. This will allow for the possibility of early intervention with more novel and targeted treatments that fit with not only individual patient variability, but also with changes that occur over time with the evolution of the disease.
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Zhang Q, Ke L, Huang S, Yang Y, He T, Sun H, Wu Z, Zhang X, Zhang H, Lv W, Hu J. 98P Adjuvant aumolertinib in resected EGFR-mutated non-small cell lung cancer: A multiple-center real-world experience. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00353-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, H XT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BX, Liu BJ, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Observation of Three Charmoniumlike States with J^{PC}=1^{--} in e^{+}e^{-}→D^{*0}D^{*-}π^{+}. PHYSICAL REVIEW LETTERS 2023; 130:121901. [PMID: 37027853 DOI: 10.1103/physrevlett.130.121901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/16/2023] [Accepted: 02/24/2023] [Indexed: 06/19/2023]
Abstract
The Born cross sections of the process e^{+}e^{-}→D^{*0}D^{*-}π^{+} at center-of-mass energies from 4.189 to 4.951 GeV are measured for the first time. The data samples used correspond to an integrated luminosity of 17.9 fb^{-1} and were collected by the BESIII detector operating at the BEPCII storage ring. Three enhancements around 4.20, 4.47, and 4.67 GeV are visible. The resonances have masses of 4209.6±4.7±5.9 MeV/c^{2}, 4469.1±26.2±3.6 MeV/c^{2}, and 4675.3±29.5±3.5 MeV/c^{2} and widths of 81.6±17.8±9.0 MeV, 246.3±36.7±9.4 MeV, and 218.3±72.9±9.3 MeV, respectively, where the first uncertainties are statistical and the second systematic. The first and third resonances are consistent with the ψ(4230) and ψ(4660) states, respectively, while the second one is compatible with the ψ(4500) observed in the e^{+}e^{-}→K^{+}K^{-}J/ψ process. These three charmoniumlike ψ states are observed in the e^{+}e^{-}→D^{*0}D^{*-}π^{+} process for the first time.
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Li H, Sun H, Yang Y, Ma Y, Li N, Tan J, Sun C. Integrated analysis of mRNA and microRNA expression pattern reveals differential transcriptome signatures in RIPK2 over-expressing chicken macrophages infected with avian pathogenic E. coli. Br Poult Sci 2023:1-13. [PMID: 36607339 DOI: 10.1080/00071668.2022.2163153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
1. As RIPK2 (receptor interacting serine/threonine kinase 2) has been shown to to alleviate excessive inflammatory responses, the following study conducted a systematic and in-depth analysis of the mRNA-seq and miRNA-seq data from chicken macrophages with/without over-expression of RIPK2 (oeRIPK2) combined with/without avian pathogenic E. coli (APEC) infection to identify the miRNA-mRNA interaction network and potential signalling pathways involved.2. A total of 9,201 differentially expressed (DE) mRNAs and 300 DE miRNA were identified in both oeRIPK2+APEC vs. APEC and oeRIPK2 vs. the wild-type (WT). Moreover, 4,269 instances of co-expression between miRNAs and mRNAs were seen involving 1,652 DE mRNAs and 164 DE miRNAs.3. Functional analysis of the DE mRNAs in the miRNA-mRNA interaction network showed that 223 biological processes and five KEGG pathways were significantly enriched in the two comparisons. In total, 128 pairs of miRNA-mRNA interactions were involved in the identified MAPK signalling pathway and focal adhesion immune related pathways.4. Significantly, these screened miRNAs (gga-miR-222b-5p and gga-miR-214) and their target genes were highly correlated with APEC infection and RIPK2. These recognised key genes, miRNA and the overall miRNA-mRNA regulatory network, enables better understanding of the molecular mechanism of host response to APEC infection, especially related to RIPK2.
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Xie Y, Wang M, Xia H, Sun H, Yuan Y, Jia J, Chen L. Development and validation of a CECT-based radiomics model for predicting IL1B expression and prognosis of head and neck squamous cell carcinoma. Front Oncol 2023; 13:1121485. [PMID: 36969073 PMCID: PMC10036854 DOI: 10.3389/fonc.2023.1121485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 02/23/2023] [Indexed: 03/12/2023] Open
Abstract
IntroductionIt is necessary to explore a noninvasive method to stratify head and neck squamous cell carcinoma (HNSCC)’s prognosis and to seek new indicators for individualized precision treatment. As a vital inflammatory cytokine, IL1B might drive a new tumor subtype that could be reflected in overall survival (OS) and predicted using the radiomics method.MethodsA total of 139 patients with RNA-Seq data from The Cancer Genome Atlas (TCGA) and matched CECT data from The Cancer Image Archive (TCIA) were included in the analysis. The prognostic value of IL1B expression in patients with HNSCC was analyzed using Kaplan-Meier analysis, Cox regression analysis and subgroup analysis. Furthermore, the molecular function of IL1B on HNSCC was explored using function enrichment and immunocytes infiltration analyses. Radiomic features were extracted with PyRadiomics and processed using max-relevance minredundancy, recursive feature elimination, and gradient boosting machine algorithm to construct aradiomics model for predicting IL1B expression. The area under the receiver operating characteristic curve (AUC), calibration curve, precision recall (PR) curve, and decision curve analysis (DCA) curve were used to examine the performance of the model.ResultsIncreased IL1B expression in patients with HNSCC indicated a poor prognosis (hazard ratio [HR] = 1.56, P = 0.003) and was harmful in patients who underwent radiotherapy (HR = 1.87, P = 0.007) or chemotherapy (HR = 2.514, P < 0.001). Shape_Sphericity, glszm_SmallAreaEmphasis, and firstorder_Kurtosis were included in the radiomics model (AUC: training cohort, 0.861; validation cohort, 0.703). The calibration curves, PR curves and DCA showed good diagnostic effect of the model. The rad-score was close related to IL1B (P = 4.490*10-9), and shared the same corelated trend to EMT-related genes with IL1B. A higher rad-score was associated with worse overall survival (P = 0.041).DiscussionThe CECT-based radiomics model provides preoperative IL1B expression predictionand offers non-invasive instructions for the prognosis and individualized treatment of patients withHNSCC.
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Tang X, Tian G, Huang Y, Ran J, Wen Z, Xu J, Song S, Liu B, Han R, Shi F, Zhang X, Sun H, Gong Y, Li Y, Zhang Z, Chen Z, Luo P. Activation cross sections for reactions induced by 14 MeV neutrons on natural titanium. Appl Radiat Isot 2023; 193:110636. [PMID: 36584411 DOI: 10.1016/j.apradiso.2022.110636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 11/22/2022] [Accepted: 12/23/2022] [Indexed: 12/28/2022]
Abstract
Cross sections for the neutrons around 14 MeV interaction with natural titanium were precisely measured by neutron activation and off-line measurement technique. The fast neutrons were produced by 3H(d,n)4He reaction and the neutron energy was obtained by using the cross section ratio method of 90Zr(n,2n)89Zr to 93Nb(n,2n)92mNb reactions. Experimental cross sections have been acquired for natTi(n,x)46Sc, natTi(n,x)47Sc, 50Ti(n,x)47Ca and 48Ti(n,x)48Sc reactions. The measured cross section data are compared with the experimental data available in the previous literature and evaluated nuclear data from the ENDF/B-VIII.0, JEFF-3.3, JENDL-5, BROND-3.1, CENDL-3.2 and FENDL-3.2b libraries. Furthermore, excitation functions for these reactions were calculated by using the theoretical model based on Talys-1.96 code with default and adjusted parameters. Within experimental error, evaluated nuclear data are mostly consistent with experimental data. The excitation function with adjusted parameters can roughly reproduce the experimental data.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang HB, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pathak A, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schönning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang YD, Wang YF, Wang YH, Wang YQ, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu SY, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang L, Yang SL, Yang T, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Evidence for the Cusp Effect in η' Decays into ηπ^{0}π^{0}. PHYSICAL REVIEW LETTERS 2023; 130:081901. [PMID: 36898113 DOI: 10.1103/physrevlett.130.081901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 11/19/2022] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
Using a sample of 4.3×10^{5} η^{'}→ηπ^{0}π^{0} events selected from the ten billion J/ψ event dataset collected with the BESIII detector, we study the decay η^{'}→ηπ^{0}π^{0} within the framework of nonrelativistic effective field theory. Evidence for a structure at π^{+}π^{-} mass threshold is observed in the invariant mass spectrum of π^{0}π^{0} with a statistical significance of around 3.5σ, which is consistent with the cusp effect as predicted by the nonrelativistic effective field theory. After introducing the amplitude for describing the cusp effect, the ππ scattering length combination a_{0}-a_{2} is determined to be 0.226±0.060_{stat}±0.013_{syst}, which is in good agreement with theoretical calculation of 0.2644±0.0051.
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Lu Q, Yang X, Li K, Sun H. Effect of adjuvant therapy on non-metastatic high risk upper urothelial carcinoma after radical nephroureterectomy: A single-center retrospective analysis. Eur Urol 2023. [DOI: 10.1016/s0302-2838(23)00556-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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Li Y, Sun H, Liu X, Hu Z, Jiang H, Guo H, Long X. Transglutaminase 2 inhibitors attenuate osteoarthritic degeneration of TMJ-osteoarthritis by suppressing NF-κB activation. Int Immunopharmacol 2023; 114:109486. [PMID: 36508923 DOI: 10.1016/j.intimp.2022.109486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 10/24/2022] [Accepted: 11/20/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND The temporomandibular joint osteoarthritis (TMJ-OA) is characterized by progressive cartilage degradation, subchondral bone erosion, and chronic pain, leading to articular damage and chewing dysfunction. Studies have shown that interleukin-1β (IL-1β) plays a critical role in the development of TMJ-OA. Transglutaminase 2 (TG2) has been identified as a marker of chondrocyte hypertrophy and IL-1β was able to increase TG2 expression in chondrocytes. Therefore, the aim of this study was to explore the ability of TG2 inhibitors to suppress TMJ-OA progression. METHODS Firstly, toluidine blue staining, cell counting kit-8 assay, immunocytofluorescent staining and western blot were used to investigate the anti-inflammatory effects of TG2 inhibitors in IL-1β-stimulated murine chondrocytes and the underlying mechanisms. Afterwards, micro-CT analysis, histological staining, immunohistochemical and immunohistofluorescent staining were used to evaluate the therapeutic efficacy of TG2 inhibitors in monosodium iodoacetate (MIA)-induced TMJ-OA in rats. RESULTS TG2 inhibitors suppressed the IL-1β-induced upregulation of COX-2, iNOS, MMP-13, and MMP-3 and reversed the IL-1β-induced proteoglycan loss in chondrocytes through inhibiting NF-κB activation. Consistently, the MIA-induced upregulation of MMP-13 and MMP-3, and loss of structural integrity of the articular cartilage and subchondral bone were markedly reversed by TG2 inhibitors via inhibiting NF-κB activation. CONCLUSIONS TG2 inhibitors demonstrated a potent therapeutic efficacy on cartilage and subchondral bone structures of TMJ-OA by reducing inflammation and cartilage degradation through suppressing NF-κB activation.
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Sun H, Cai RR, Bi YW. [Solitary fibrous tumor in choroid: a clinicopathologic analysis of two cases]. [ZHONGHUA YAN KE ZA ZHI] CHINESE JOURNAL OF OPHTHALMOLOGY 2022; 58:1068-1071. [PMID: 36480891 DOI: 10.3760/cma.j.cn112142-20220718-00344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Solitary fibrous tumor (SFT) is an uncommon spindle cell tumor that occurs mainly in the pleura, but also in other parts of the body. Intraocular SFT is very rare. This paper reports 2 cases of choroidal SFT which were diagnosed by clinical, imaging, histopathological and immunohistochemical staining. The patient remained asymptomatic with no sign of recurrence and metastasis after operation.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jang E, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang HB, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schönning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu SY, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang L, Yang SL, Yang T, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Study of the Semileptonic Decay Λ_{c}^{+}→Λe^{+}ν_{e}. PHYSICAL REVIEW LETTERS 2022; 129:231803. [PMID: 36563214 DOI: 10.1103/physrevlett.129.231803] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 11/01/2022] [Indexed: 06/17/2023]
Abstract
The study of the Cabibbo-favored semileptonic decay Λ_{c}^{+}→Λe^{+}ν_{e} is reported using a 4.5 fb^{-1} data sample of e^{+}e^{-} annihilations collected at center-of-mass energies ranging from 4.600 GeV to 4.699 GeV with the BESIII detector at the BEPCII collider. The branching fraction of the decay is measured to be B(Λ_{c}^{+}→Λe^{+}ν_{e})=(3.56±0.11_{stat}±0.07_{syst})%, which is the most precise measurement to date. Furthermore, we perform an investigation of the internal dynamics in Λ_{c}^{+}→Λe^{+}ν_{e}. We provide the first direct comparisons of the differential decay rate and form factors with those predicted from lattice quantum chromodynamics (LQCD) calculations. Combining the measured branching fraction with a q^{2}-integrated rate predicted by LQCD, we determine |V_{cs}|=0.936±0.017_{B}±0.024_{LQCD}±0.007_{τ_{Λ_{c}}}.
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Ip HW, Tang WF, Leung AYH, Sun H, So JCC, Wong JWH. Long noncoding RNA profiling for prognostication in adult acute myeloid leukaemia: abridged secondary publication. Hong Kong Med J 2022; 28 Suppl 6:8-9. [PMID: 36535790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
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Liu M, Zhou Z, Liu F, Wang M, Wang Y, Gao M, Sun H, Zhang X, Yang T, Ji L, Li J, Si Q, Dai L, Ouyang S. CT and CEA-based machine learning model for predicting malignant pulmonary nodules. Cancer Sci 2022; 113:4363-4373. [PMID: 36056603 DOI: 10.1111/cas.15561] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 08/22/2022] [Accepted: 08/25/2022] [Indexed: 12/15/2022] Open
Abstract
Computed tomography (CT), an efficient radiological technology, is used to detect lung cancer in the clinic. Carcinoembryonic antigen (CEA), a common tumor biomarker, is applied in the detection of various tumors. To highlight the advantages of two-dimensional techniques and assist clinicians in optimizing lung cancer diagnostic schemes, we established a favorable model combining CT and CEA. In the study, univariate analysis was performed to screen independent predictors in a training cohort of 271 patients with malignant pulmonary nodules (MPNs) and 92 with benign pulmonary nodules (BPNs). Six machine learning-based models involving five CT predictors (mediastinal lymph node enlargement, lobulation, vascular notch sign, spiculation, and nodule number) and lnCEA were constructed and validated in an independent cohort of 129 participants (92 MPNs and 37 BPNs) by SPSS Modeler. A nomogram and the Delong test were generated by R software. Finally, the model established by logistic regression had highest diagnostic efficiency (area under the curve [AUC] = 0.912). Moreover, the diagnostic ability of the logistic model in the validation cohort (AUC = 0.882, 80.4% sensitivity, 75.7% specificity) was higher than that of the Peking University model (AUC = 0.712, 68.5% sensitivity, 70.3% specificity) and the Mayo model (AUC = 0.745, 62.0% sensitivity, 75.7% specificity). Interestingly, for the participants with intermediate (10-30 mm) and CEA-negative nodule, the model reached an AUC of 0.835 (72.3% sensitivity, 83.3% specificity). The AUC for the early lung cancer was as high as 0.822 with 67.3% sensitivity and 78.9% specificity. As a conclusion, this promising model presents a new diagnostic strategy for the clinic to distinguish MPNs from BPNs.
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Li J, Mi L, Ran B, Sui C, Zhou L, Li F, Dionigi G, Sun H, Liang N. Identification of potential diagnostic and prognostic biomarkers for papillary thyroid microcarcinoma (PTMC) based on TMT-labeled LC-MS/MS and machine learning. J Endocrinol Invest 2022; 46:1131-1143. [PMID: 36418670 DOI: 10.1007/s40618-022-01960-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 11/01/2022] [Indexed: 11/24/2022]
Abstract
OBJECTIVES To explore the molecular mechanisms underlying aggressive progression of papillary thyroid microcarcinoma and identify potential biomarkers. METHODS Samples were collected and sequenced using tandem mass tag-labeled liquid chromatography-tandem mass spectrometry. Differentially expressed proteins (DEPs) were identified and further analyzed using Mfuzz and protein-protein interaction analysis (PPI). Parallel reaction monitoring (PRM) and immunohistochemistry (IHC) were performed to validate the DEPs. RESULTS Five thousand, two hundred and three DEPs were identified and quantified from the tumor/normal comparison group or the N1/N0 comparison group. Mfuzz analysis showed that clusters of DEPs were enriched according to progressive status, followed by normal tissue, tumors without lymphatic metastases, and tumors with lymphatic metastases. Analysis of PPI revealed that DEPs interacted with and were enriched in the following metabolic pathways: apoptosis, tricarboxylic acid cycle, PI3K-Akt pathway, cholesterol metabolism, pyruvate metabolism, and thyroid hormone synthesis. In addition, 18 of the 20 target proteins were successfully validated with PRM and IHC in another 20 paired validation samples. Based on machine learning, the five proteins that showed the best performance in discriminating between tumor and normal nodules were PDLIM4, ANXA1, PKM, NPC2, and LMNA. FN1 performed well in discriminating between patients with lymph node metastases (N1) and N0 with an AUC of 0.690. Finally, five validated DEPs showed a potential prognostic role after examining The Cancer Genome Atlas database: FN1, IDH2, VDAC1, FABP4, and TG. Accordingly, a nomogram was constructed whose concordance index was 0.685 (confidence interval: 0.645-0.726). CONCLUSIONS PDLIM4, ANXA1, PKM, NPC2, LMNA, and FN1 are potential diagnostic biomarkers. The five-protein nomogram could be a prognostic biomarker.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jang E, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang HB, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp J, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang L, Yang SL, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Measurement of the Absolute Branching Fraction and Decay Asymmetry of Λ→nγ. PHYSICAL REVIEW LETTERS 2022; 129:212002. [PMID: 36461970 DOI: 10.1103/physrevlett.129.212002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 09/27/2022] [Accepted: 10/24/2022] [Indexed: 06/17/2023]
Abstract
The radiative hyperon decay Λ→nγ is studied using (10087±44)×10^{6} J/ψ events collected with the BESIII detector operating at BEPCII. The absolute branching fraction of the decay Λ→nγ is determined to be (0.832±0.038_{stat}±0.054_{syst})×10^{-3}, which is a factor of 2.1 lower and 5.6 standard deviations different than the previous measurement. By analyzing the joint angular distribution of the decay products, the first determination of the decay asymmetry α_{γ} is reported with a value of -0.16±0.10_{stat}±0.05_{syst}.
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Cheng Y, Zhang L, Hu J, Wang D, Hu C, Zhou J, Wu L, Cao L, Liu J, Zhang H, Sun H, Wang Z, Gao H, Sun Y, Hu X, Jensen E, Schwarzenberger P, Paz-Ares L. 328P Long-term follow-up of pembrolizumab plus chemotherapy in Chinese patients with metastatic squamous non-small cell lung cancer (NSCLC) from KEYNOTE-407. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.10.367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2022] Open
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Cheng Y, Han L, Wu L, Chen J, Sun H, Wen G, Ji Y, Dvorkin M, Shi J, Pan Z, Shi J, Wang X, Bai Y, Melkadze T, Pan Y, Min X, Viguro M, Kang W, Wang Q, Zhu J. LBA9 Updated results of first-line serplulimab versus placebo combined with chemotherapy in extensive-stage small cell lung cancer: An international multicentre phase III study (ASTRUM-005). Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.10.351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
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Sun H, Wang Q, Wang Y, Zhang Y, Zhang W, Shen W, Zhao L, Ge X, Yang N, Tan B, Su X, Ma J, Wang F, Dong W, Zhang J, Sun D, Liu T, Zhang Q, Li B, Huang W. Treatment Strategies for Limited-Stage Primary Small Cell Carcinoma of the Esophagus: A Multicenter Retrospective Trial from China. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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Zhang Q, Sun H, Wang Q, Huang W. Pattern of Lymph Node Metastases and its Implication in Radiotherapeutic Clinical Target Volume in Patients with Small Cell Carcinoma of the Esophagus. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Li X, Sun H, Ning Z, Yang W, Cai Y, Yin R, Zhao J. Mild acid hydrolysis on Fucan sulfate from Stichopus herrmanni: Structures, depolymerization mechanism and anticoagulant activity. Food Chem 2022; 395:133559. [DOI: 10.1016/j.foodchem.2022.133559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 06/12/2022] [Accepted: 06/20/2022] [Indexed: 11/04/2022]
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Sun H, Shen F, Bai X, Liu LX, Xiang BD, Song T, Chen M, Kuang M, Huang ZY, Li D, Wen T, Zhao HT, Zeng YY, Zhu X, Zhou J, Fan J. 92P Safety of liver resection following atezolizumab plus bevacizumab treatment in hepatocellular carcinoma (HCC) patients with macrovascular invasion: A pre-specified analysis of the TALENTop study. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.10.128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
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Zhang Y, Dilimulati D, Chen D, Cai M, You H, Sun H, Gao X, Shao X, Zhang M, Qu S. Serum fibrinogen-like protein 1 as a novel biomarker in polycystic ovary syndrome: a case-control study. J Endocrinol Invest 2022; 45:2123-2130. [PMID: 35790683 DOI: 10.1007/s40618-022-01844-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 06/17/2022] [Indexed: 11/26/2022]
Abstract
PURPOSE To investigate the relationship between fibrinogen-like protein 1 (FGL-1) concentrations and various metabolic characteristics in patients with polycystic ovary syndrome (PCOS) and explore whether FGL-1 could be a predictive biomarker for PCOS. METHODS This case-control study included 136 patients with PCOS and 34 normal controls recruited in the Department of Endocrinology and Metabolism, Shanghai Tenth People's Hospital between May 2017 and June 2021. Anthropometric characteristics, metabolic parameters, and reproductive hormones were collected. Serum FGL-1 measurement was conducted using enzyme-linked immunosorbent assay (ELISA) kits. RESULTS Serum FGL-1 concentrations were higher in patients with PCOS than in control subjects in body mass index (BMI) subgroups, insulin resistance (IR) subgroups, and hepatic function subgroups, respectively. Serum FGL-1 concentrations were significantly associated with BMI, glycosylated hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), homeostasis model assessment of insulin resistance (HOMA-IR), alanine aminotransferase (ALT), aspartate aminotransferase (AST), high-density lipoprotein cholesterol (HDL-c), and serum uric acid (SUA) in all individuals. The receiver operating characteristic (ROC) curve analysis revealed that the best cutoff value for FGL-1 levels to predict PCOS was 21.02 ng/ml with a sensitivity of 74.3% and a specificity of 70.6%. Both univariate and multiple logistic regressions indicated that the odds ratio (OR) for PCOS significantly increased in the subjects with high levels of FGL-1. CONCLUSION In our study, FGL-1 was associated with serum aminotransferase and various metabolic indexes. Moreover, the high risk of PCOS was independently associated with the increased FGL-1 levels, which suggested that FGL-1 could be a predictive biomarker for PCOS.
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Deng X, Cai W, Lin F, Jia L, Dai Z, Zhang W, Li J, Lei R, Sun H, Jiang P, Wang J. A Deep Learning-Based Method with Prior Information for Auto-Delineation of Clinical Target Volume in Postmastectomy Radiotherapy. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Ferroli RB, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang HB, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muramatsu H, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pathak A, Pelizaeus M, Peng HP, Pettersson J, Ping JL, Ping RG, Plura S, Pogodin S, Poling R, Prasad V, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu SY, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang L, Yang SL, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Observation of an a_{0}-like State with Mass of 1.817 GeV in the Study of D_{s}^{+}→K_{S}^{0}K^{+}π^{0} Decays. PHYSICAL REVIEW LETTERS 2022; 129:182001. [PMID: 36374689 DOI: 10.1103/physrevlett.129.182001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 07/08/2022] [Accepted: 09/13/2022] [Indexed: 06/16/2023]
Abstract
Using e^{+}e^{-} annihilation data corresponding to an integrated luminosity of 6.32 fb^{-1} collected at center-of-mass energies between 4.178 and 4.226 GeV with the BESIII detector, we perform the first amplitude analysis of the decay D_{s}^{+}→K_{S}^{0}K^{+}π^{0} and determine the relative branching fractions and phases for intermediate processes. We observe an a_{0}-like state with mass of 1.817 GeV in its decay to K_{S}^{0}K^{+} for the first time. In addition, we measure the ratio {B[D_{s}^{+}→K[over ¯]^{*}(892)^{0}K^{+}]/B[D_{s}^{+}→K[over ¯]^{0}K^{*}(892)^{+}]} to be 2.35_{-0.23stat}^{+0.42}±0.10_{syst}. Finally, we provide a precision measurement of the absolute branching fraction B(D_{s}^{+}→K_{S}^{0}K^{+}π^{0})=(1.46±0.06_{stat}±0.05_{syst})%.
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Sun H, Lai A, Yan B. Low-density lipoprotein cholesterol target attainment among statin-naive Chinese atherosclerotic vascular disease patients. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.2668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Low-density lipoprotein cholesterol (LDL-C) of patients with atherosclerotic vascular disease (ASCVD) is expected to be lowered by ≥50% and <1.4 mmol/L. Despite the use of lipid-lowering therapies, most of Chinese patients failed to meet the treatment target.
Purpose
We aimed to evaluate the potential of different statin intensities on LDL-C target attainment among statin-naïve Chinese ASCVD patients.
Methods
We retrospectively analyzed statin-naïve ASCVD patients who were initiated with statin therapy between January and July 2020 from 43 public hospitals or clinics in Hong Kong. Patients were divided into high-intensity (HI-S, atorvastatin 40–80 mg, rosuvastatin 20–40 mg), moderate-intensity (MI-S, atorvastatin 10–20 mg, rosuvastatin 5–10 mg, simvastatin 20–40 mg) and low-intensity (LI-S, simvastatin 10 mg) statin groups. With baseline and follow-up LDL-C, percentage reduction was calculated and the distance to LDL-C target was investigated within groups.
Results
Of 7,241 patients (mean age 61.8±12.4 years and 64.2% male), 4,451 (61.5%) had coronary artery disease, 109 (1.5%) peripheral artery disease, and 2,879 (39.8%) cerebrovascular disease. HI-S, MI-S and LI-S were prescribed in 20% (n=1,450), 61.1% (n=4,421) and 18.9% (n=1,370) patients, respectively. Mean baseline LDL-C was 2.9±1.0 mmol/L and mean follow-up value was 1.9±0.8 mmol/L with median LDL-C reduction of 46.1%, 40.4%, and 32.0% by HI-S, MI-S, and LI-S, respectively. 42.1%, 31.8%, and 14.7% of patients on HI-S, MI-S, and LI-S achieved ≥50% LDL-C reduction and only 23.5%, 18.2%, and 8.8% reached both ≥50% LDL-C reduction and <1.4 mmol/L. One in ten patients require further ≥50% LDL-C reduction to reach <1.4 mmol/L.
Conclusion
In statin-naïve Chinese ASCVD patients, most patients did not reach guidelines recommended LDL-C target even with high-intensity statin. Early statin up-titration or addition of non-statin lipid-lowering therapy may be required in majority of patients.
Funding Acknowledgement
Type of funding sources: None.
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Sun X, Liu W, Liu L, Sun H. Coinfection of pulmonary nocardiosis and nontuberculous mycobacterial pulmonary disease in patients without known immunodeficiency. Pulmonology 2022. [DOI: 10.1016/j.pulmoe.2022.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Sun H, Zweig Y, Perskin M, Chodosh J, Blachman NL. Hospital volunteers: An innovative pipeline to increase the geriatrics workforce. GERONTOLOGY & GERIATRICS EDUCATION 2022; 43:564-570. [PMID: 34229562 DOI: 10.1080/02701960.2021.1946045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Objectives: There is an urgent need to expand the geriatrics workforce. By providing volunteers meaningful experiences with older adults, we hoped to stimulate interest in geriatrics.Design: Electronic mixed methods survey of volunteers from April 2018-October 2019Setting: Academic medical centerParticipants: 32 volunteersMeasurements: We conducted a mixed methods survey of volunteers to understand their experiences in the program, in part using a Likert scale. Two coders independently compared themes to ensure consensus.Results: Thirty-six percent (n = 32) completed surveys; 69% (n = 22) were women; most (59%) were first in their family to work in healthcare, and 81% (n = 26) had prior healthcare experience. Volunteers found patients to be engaging, and recognized that older adults need attention. Almost half (47%, n = 15) expressed interest in working with older adults before starting the program, which increased to 63% (n = 20) after the program. Most volunteers (n = 30, 94%) answered 'definitely yes' or 'probably yes' for feeling appreciated by patients, and 88% (n = 28) felt appreciated by patients' families.Conclusion: A volunteer program pairing companions with older age inpatients increased interest and appreciation for older adults. While additional research should examine whether such experiences influence career choices, this intervention proposes an innovative pipeline to increase the geriatrics workforce.
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Beeson K, Parilov E, Potasek M, Zhu T, Sun H, Sourvanos D. Photodynamic therapy in a pleural cavity using monte carlo simulations with 2D/3D Graphical Visualization. GLOBAL JOURNAL OF CANCER THERAPY 2022; 8:34-35. [PMID: 37337581 PMCID: PMC10278094 DOI: 10.17352/2581-5407.000045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
Cancer therapy using Photodynamic Therapy (PDT) has been investigated for some time [1,2] and now it is a growing area of interest in clinical trials [3]. Monte Carlo (MC) simulations were used for early laboratory studies [4,5] for analysis in PDT. Various improvements in the MC method have advanced the field in recent years.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jang E, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang HB, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schönning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang L, Yang SL, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Precise Measurements of Decay Parameters and CP Asymmetry with Entangled Λ-Λ[over ¯] Pairs. PHYSICAL REVIEW LETTERS 2022; 129:131801. [PMID: 36206435 DOI: 10.1103/physrevlett.129.131801] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 09/01/2022] [Indexed: 06/16/2023]
Abstract
Based on 10 billion J/ψ events collected at the BESIII experiment, a search for CP violation in Λ decay is performed in the difference between CP-odd decay parameters α_{-} for Λ→pπ^{-} and α_{+} for Λ[over ¯]→p[over ¯]π^{+} by using the process e^{+}e^{-}→J/ψ→ΛΛ[over ¯]. With a five-dimensional fit to the full angular distributions of the daughter baryon, the most precise values for the decay parameters are determined to be α_{-}=0.7519±0.0036±0.0024 and α_{+}=-0.7559±0.0036±0.0030, respectively. The Λ and Λ[over ¯] averaged value of the decay parameter is extracted to be α_{avg}=0.7542±0.0010±0.0024 with unprecedented accuracy. The CP asymmetry A_{CP}=(α_{-}+α_{+})/(α_{-}-α_{+}) is determined to be -0.0025±0.0046±0.0012, which is one of the most precise measurements in the baryon sector. The reported results for the decay parameter will play an important role in the studies of the polarizations and CP violations for the strange, charmed and beauty baryons.
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Li K, Sun H, Wu CX. [Research progress of compound injection of traditional Chinese medicine in the treatment of liver cancer]. ZHONGHUA GAN ZANG BING ZA ZHI = ZHONGHUA GANZANGBING ZAZHI = CHINESE JOURNAL OF HEPATOLOGY 2022; 30:1007-1011. [PMID: 36299199 DOI: 10.3760/cma.j.cn501113-20210927-00486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The incidence and mortality of liver cancer are high, which seriously threatens human life and health. Common treatment methods for liver cancer include surgical treatment, transcatheter arterial chemoembolization, targeted therapy, radiotherapy and chemotherapy, etc. These methods have various problems when used alone. This paper reviews the research on the treatment of liver cancer with compound injection of traditional Chinese medicine and its mechanism in recent years, in order to provide some reference for clinical treatment and improvement of prognosis of liver cancer.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Ferroli RB, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao H, Gao YN, Gao Y, Garzia I, Ge PT, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Plura S, Pogodin S, Poling R, Prasad V, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao QT, Teng JX, Thoren V, Tian WH, Tian YT, Uman I, Wang B, Wang DY, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu Z, Xia L, Xiang T, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu QJ, Xu SY, Xu XP, Xu YC, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HX, Yang L, Yang SL, Yang YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. First Observation of the Direct Production of the χ_{c1} in e^{+}e^{-} Annihilation. PHYSICAL REVIEW LETTERS 2022; 129:122001. [PMID: 36179210 DOI: 10.1103/physrevlett.129.122001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 06/22/2022] [Accepted: 07/26/2022] [Indexed: 06/16/2023]
Abstract
We study the direct production of the J^{PC}=1^{++} charmonium state χ_{c1}(1P) in electron-positron annihilation by carrying out an energy scan around the mass of the χ_{c1}(1P). The data were collected with the BESIII detector at the BEPCII collider. An interference pattern between the signal process e^{+}e^{-}→χ_{c1}(1P)→γJ/ψ→γμ^{+}μ^{-} and the background processes e^{+}e^{-}→γ_{ISR}J/ψ→γ_{ISR}μ^{+}μ^{-} and e^{+}e^{-}→γ_{ISR}μ^{+}μ^{-} is observed by combining all the data samples. The χ_{c1}(1P) signal is observed with a significance of 5.1σ. This is the first observation of a C-even state directly produced in e^{+}e^{-} annihilation. The electronic width of the χ_{c1}(1P) resonance is determined to be Γ_{ee}=(0.12_{-0.08}^{+0.13}) eV, which is of the same order of magnitude as theoretical calculations.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Ferroli RB, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang HB, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang L, Yang SL, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Evidence for a Neutral Near-Threshold Structure in the K_{S}^{0} Recoil-Mass Spectra in e^{+}e^{-}→K_{S}^{0}D_{s}^{+}D^{*-} and e^{+}e^{-}→K_{S}^{0}D_{s}^{*+}D^{-}. PHYSICAL REVIEW LETTERS 2022; 129:112003. [PMID: 36154413 DOI: 10.1103/physrevlett.129.112003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/17/2022] [Accepted: 06/30/2022] [Indexed: 06/16/2023]
Abstract
We study the processes e^{+}e^{-}→K_{S}^{0}D_{s}^{+}D^{*-} and e^{+}e^{-}→K_{S}^{0}D_{s}^{*+}D^{-}, as well as their charge conjugated processes, at five center-of-mass energies between 4.628 and 4.699 GeV, using data samples corresponding to an integrated luminosity of 3.8 fb^{-1} collected by the BESIII detector at the BEPCII storage ring. Based on a partial reconstruction technique, we find evidence of a structure near the thresholds for D_{s}^{+}D^{*-} and D_{s}^{*+}D^{-} production in the K_{S}^{0} recoil-mass spectrum, which we refer to as the Z_{cs}(3985)^{0}. Fitting with a Breit-Wigner line shape, we find the mass of the structure to be (3992.2±1.7±1.6) MeV/c^{2} and the width to be (7.7_{-3.8}^{+4.1}±4.3) MeV, where the first uncertainties are statistical and the second are systematic. The significance of the Z_{cs}(3985)^{0} signal is found to be 4.6σ including both the statistical and systematic uncertainty. We report the Born cross section multiplied by the branching fraction at different energy points. The mass of the Z_{cs}(3985)^{0} is close to that of the Z_{cs}(3985)^{+}. Assuming SU(3) symmetry, the cross section of the neutral channel is consistent with that of the charged one. Hence, we conclude that the Z_{cs}(3985)^{0} is the isospin partner of the Z_{cs}(3985)^{+}.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fu CD, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang HB, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Poling R, Prasad V, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xiang T, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang L, Yang SL, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Observation of Resonance Structures in e^{+}e^{-}→π^{+}π^{-}ψ_{2}(3823) and Mass Measurement of ψ_{2}(3823). PHYSICAL REVIEW LETTERS 2022; 129:102003. [PMID: 36112441 DOI: 10.1103/physrevlett.129.102003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 07/21/2022] [Accepted: 08/09/2022] [Indexed: 06/15/2023]
Abstract
Using a data sample corresponding to an integrated luminosity of 11.3 fb^{-1} collected at center-of-mass energies from 4.23 to 4.70 GeV with the BESIII detector, we measure the product of the e^{+}e^{-}→π^{+}π^{-}ψ_{2}(3823) cross section and the branching fraction B[ψ_{2}(3823)→γχ_{c1}]. For the first time, resonance structure is observed in the cross section line shape of e^{+}e^{-}→π^{+}π^{-}ψ_{2}(3823) with significances exceeding 5σ. A fit to data with two coherent Breit-Wigner resonances modeling the sqrt[s]-dependent cross section yields M(R_{1})=4406.9±17.2±4.5 MeV/c^{2}, Γ(R_{1})=128.1±37.2±2.3 MeV, and M(R_{2})=4647.9±8.6±0.8 MeV/c^{2}, Γ(R_{2})=33.1±18.6±4.1 MeV. Though weakly disfavored by the data, a single resonance with M(R)=4417.5±26.2±3.5 MeV/c^{2}, Γ(R)=245±48±13 MeV is also possible to interpret data. This observation deepens our understanding of the nature of the vector charmoniumlike states. The mass of the ψ_{2}(3823) state is measured as (3823.12±0.43±0.13) MeV/c^{2}, which is the most precise measurement to date.
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Jin Y, Han Y, Zhang L, Jin Y, Sun H. 402P Updated results from the multicenter phase II, ALTER-C001 trial: Efficacy and safety of anlotinib plus XELOX regimen as first-line treatment followed by maintenance monotherapy of anlotinib for patients with mCRC. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Liu J, Sun H, Meng Y, Ye X, Li S, Han Y, Ge J, Yang H, Liang J, Kong F. EP05.01-015 Validate Radiomics Features and XGBoost Model in Radiation Pneumonitis (RP) Prediction in Patients with Primary Lung Cancer: A MultiCenter Study. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Lou JQ, Li Q, Cui QW, Zhang P, Sun H, Tang H, Zhuang MM, Sun Y. [A prospective randomized controlled study on the curative effects of enteral immunonutrition support therapy in adult burn patients at nutritional risk]. ZHONGHUA SHAO SHANG YU CHUANG MIAN XIU FU ZA ZHI 2022; 38:722-734. [PMID: 36058695 DOI: 10.3760/cma.j.cn501225-20220327-00094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To explore the effects of enteral immunonutrition support therapy on nutritional metabolism, immune function, and inflammatory response in adult burn patients at nutritional risk as assessed by the modified 2nd nutrition risk screening (NRS) 2002. Methods: A prospective randomized controlled study was conducted. From December 2019 to January 2022, 500 adult patients who were admitted to the Affiliated Huaihai Hospital of Xuzhou Medical University and had nutritional risk assessed by the modified 2nd NRS 2002 were recruited into the study. According to burn severity, the patients were divided into common burn patients (n=450) and severe burn patients (n=50). According to the random number table, the patients with common burn were divided into common burn diet nutrition group and common burn diet enteral immunonutrition group, with 225 patients in each group, and the patients with severe burn were divided into severe burn diet enteral non-immunonutrition group and severe burn diet enteral immunonutrition group, with 25 patients in each group. The patients in each group were given the corresponding nutritional support therapies on the basis of routine burn treatment. On post injury day (PID) 1, 3, 7, 14, and 21, the total energy intake and total protein intake of the patients in 4 groups were recorded, the plasma prealbumin, albumin, transferrin, serum immunoglobulin A (IgA), IgG, IgM, peripheral blood CD3 positive T cell percentage, CD4 positive T cell count, CD8 positive T cell count, the ratio of CD4 positive T cells to CD8 positive T cells, natural killer cell percentage, plasma interleukin-6 (IL-6), free mitochondrial DNA (mtDNA) copy number, and soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) of the patients in 4 groups were detected, and the nitrogen balance of the patients in 4 groups on the day was calculated. On PID 7, 14, and 21, the modified 2nd NRS 2002 scores of the patients in 4 groups were reassessed. The sepsis incidence during treatment and the length of hospital stay of the patients in 4 groups and the length of intensive care unit (ICU) stay of the patients in the 2 severe burn groups were recorded. Data were statistically analyzed with chi-square test, Fisher's exact probability test, Mann-Whitney U test, independent sample t test, analysis of variance for repeated measurement, and Bonferroni correction. Results: A total of 476 patients completed the trial, with 213 patients in common burn diet nutrition group (112 males and 101 females, aged (37±19) years), 218 patients in common burn diet enteral immunonutrition group (115 males and 103 females, aged (42±16) years), 22 patients in severe burn diet enteral non-immunonutrition group (11 males and 11 females, aged (35±8) years), and 23 patients in severe burn diet enteral immunonutrition group (12 males and 11 females, aged (35±8) years). Compared with those in common burn diet nutrition group, the patients in common burn diet enteral immunonutrition group had significantly higher total energy intake on PID 1 (t=6.06, P<0.01), significantly lower total energy intake on PID 7 and significantly lower total protein intake on PID 1 (with t values of 6.17 and 4.59, respectively,P<0.01). On PID 21, the total energy intake of patients in severe burn diet enteral immunonutrition group was significantly lower than that in severe burn diet enteral non-immunonutrition group (t=2.70, P<0.01). The total protein intake of patients in severe burn diet enteral immunonutrition group and severe burn diet enteral non-immunonutrition group were similar at each time point post injury (P>0.05). Compared with those in common burn diet nutrition group, the patients in common burn diet enteral immunonutrition group had significantly higher level of prealbumin on PID 3, 7, 14, and 21 (with t values of 2.05, 2.33, 2.45, and 2.11, respectively, P<0.05), significantly higher level of albumin on PID 7, 14, and 21 (with t values of 2.30, 2.56, and 2.15, respectively, P<0.05), significantly higher level of transferrin on PID 7 and 14 (with t values of 1.99 and 2.27, respectively, P<0.05), significantly higher nitrogen balance on PID 14 and 21 (with t values of 2.51 and 2.07, respectively, P<0.05), and significantly lower modified 2nd NRS 2002 score on PID 21 (t=1.99, P<0.05). Compared with those in severe burn diet enteral non-immunonutrition group, the patients in severe burn diet enteral immunonutrition group had significantly higher level of prealbumin on PID 3, 7, 14, and 21 (with t values of 2.50, 2.64, 2.18, and 2.39, respectively, P<0.05), significantly higher level of albuminon PID 7, 14, and 21 (with t values of 2.27, 2.39, and 2.69, respectively, P<0.05), significantly higher level of transferrin and nitrogen balance but significantly lower modified 2nd NRS 2002 score on PID 14 and 21 (with t values of 2.30, 2.35, 2.41, 2.16, 2.31, and 2.73, respectively, P<0.05). Compared with those in common burn diet nutrition group, patients in common burn diet enteral immunonutrition group had significantly higher level of IgA and IgG on PID 7, 14, and 21 (with t values of 2.19, 2.36, 2.17, 2.49, 1.97, and 2.24, respectively, P<0.05), significantly higher level of IgM on PID 21 (t=2.06, P<0.05), significantly higher percentage of CD3 positive T cells and ratio of CD4 positive T cells to CD8 positive T cells on PID 3, 7, 14, and 21 (with t values of 2.49, 2.25, 2.33, 2.41, 2.39, 2.24, 2.46, and 2.18, respectively, P<0.05), significantly higher CD4 positive T cell count (with t values of 2.15 and 2.27, respectively, P<0.05) but significantly lower CD8 positive T cell count on PID 14 and 21 (with t values of 2.58 and 2.35, P<0.05), and significantly higher percentage of natural killer cells on PID 7, 14, and 21 (with t values of 2.53, 2.21, and 2.36, respectively, P<0.05). Compared with those in severe burn diet enteral non-immunonutrition group, patients in severe burn diet immunonutrition group had significantly higher level of IgA on PID 7 and 14 (with t values of 2.15 and 2.03, respectively, P<0.05), significantly higher level of IgG on PID 7, 14, and 21 (with t values of 2.09, 2.56, and 2.15, respectively, P<0.05), significantly higher level of IgM on PID 21 (t=2.08, P<0.05), significantly higher percentage of CD3 positive T cells, CD4 positive T cell count, and percentage of natural killer cells on PID 14 and 21 (with t values of 2.52, 2.14, 2.14, 2.39, 2.56, and 2.19, respectively, P<0.05), significantly lower CD8 positive T cell count but significantly higher ratio of CD4 positive T cells to CD8 positive T cells on PID 7, 14, and 21 (with t values of 2.27, 2.81, 2.01, 2.11, 2.69, and 2.05, respectively, P<0.05). Compared with those in common burn diet nutrition group, patients in common burn diet enteral immunonutrition group had significantly lower level of IL-6 (with t values of 2.34 and 2.32, respectively, P<0.05) and significantly lower free mtDNA copy number on PID 14 and 21 (with Z values of -2.28 and -2.34,respectively, P<0.05), significantly lower level of sTREM-1 on PID 7, 14, and 21 (with t values of 2.02, 2.94, and 3.72, respectively, P<0.05). Compared with those in severe burn diet enteral non-immunonutrition group, patients in severe burn diet enteral immunonutrition group had significantly lower level of IL-6 and sTREM-1 on PID 7, 14, and 21 (with t values of 2.15, 2.29, 2.47, 2.43, 2.07, and 2.32, respectively, P<0.05), and significantly lower free mtDNA copy number on PID 14 and 21 (with Z values of -2.49 and -2.21, respectively, P<0.05). During treatment, the sepsis incidences of patients in 2 common burn groups were similar (P>0.05), the sepsis incidences of patients in 2 severe burn groups were similar (P>0.05). The length of ICU stay of patients in severe burn diet enteral immunonutrition group was (11±3) d, which was significantly shorter than (14±3) d in severe burn diet enteral non-immunonutrition group (t=3.12, P<0.01). The length of hospital stay of patients in common burn diet enteral immunonutrition group was significantly shorter than that in common burn diet nutrition group (t=3.11, P<0.01). The length of hospital stay of patients in severe burn diet enteral non-immunonutrition group was similar to that in severe burn diet enteral immunonutrition group (P>0.05). Conclusions: Enteral immunonutrition support therapy for adult burn patients at nutritional risk assessed by the modified 2nd NRS 2002 can better improve the nutritional status and the immune function of patients, reduce inflammatory response of the body, and shorten the length of hospital stay in common burn patients and the length of ICU stay in severe burn patients.
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Zhou L, Zhou Z, Liu F, Sun H, Zhou B, Dai L, Zhang G. Establishment and validation of a clinical model for diagnosing solitary pulmonary nodules. J Surg Oncol 2022; 126:1316-1329. [PMID: 35975732 DOI: 10.1002/jso.27041] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 07/22/2022] [Indexed: 12/09/2022]
Abstract
OBJECTIVES The main purpose of this study was to develop and validate a clinical model for estimating the risk of malignancy in solitary pulmonary nodules (SPNs). METHODS A total of 672 patients with SPNs were retrospectively reviewed. The least absolute shrinkage and selection operator algorithm was applied for variable selection. A regression model was then constructed with the identified predictors. The discrimination, calibration, and clinical validity of the model were evaluated by the area under the receiver-operating-characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). RESULTS Ten predictors, including gender, age, nodule type, diameter, lobulation sign, calcification, vascular convergence sign, mediastinal lymphadenectasis, the natural logarithm of carcinoembryonic antigen, and combination of cytokeratin 19 fragment 21-1, were incorporated into the model. The prediction model demonstrated valuable prediction performance with an AUC of 0.836 (95% CI: 0.777-0.896), outperforming the Mayo (0.747, p = 0.024) and PKUPH (0.749, p = 0.018) models. The model was well-calibrated according to the calibration curves. The DCA indicated the nomogram was clinically useful over a wide range of threshold probabilities. CONCLUSION This study proposed a clinical model for estimating the risk of malignancy in SPNs, which may assist clinicians in identifying the pulmonary nodules that require invasive procedures and avoid the occurrence of overtreatment.
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Abbott R, Abbott TD, Acernese F, Ackley K, Adams C, Adhikari N, Adhikari RX, Adya VB, Affeldt C, Agarwal D, Agathos M, Agatsuma K, Aggarwal N, Aguiar OD, Aiello L, Ain A, Ajith P, Albanesi S, Allocca A, Altin PA, Amato A, Anand C, Anand S, Ananyeva A, Anderson SB, Anderson WG, Andrade T, Andres N, Andrić T, Angelova SV, Ansoldi S, Antelis JM, Antier S, Appert S, Arai K, Araya MC, Areeda JS, Arène M, Arnaud N, Aronson SM, Arun KG, Asali Y, Ashton G, Assiduo M, Aston SM, Astone P, Aubin F, Austin C, Babak S, Badaracco F, Bader MKM, Badger C, Bae S, Baer AM, Bagnasco S, Bai Y, Baird J, Ball M, Ballardin G, Ballmer SW, Balsamo A, Baltus G, Banagiri S, Bankar D, Barayoga JC, Barbieri C, Barish BC, Barker D, Barneo P, Barone F, Barr B, Barsotti L, Barsuglia M, Barta D, Bartlett J, Barton MA, Bartos I, Bassiri R, Basti A, Bawaj M, Bayley JC, Baylor AC, Bazzan M, Bécsy B, Bedakihale VM, Bejger M, Belahcene I, Benedetto V, Beniwal D, Bennett TF, Bentley JD, BenYaala M, Bergamin F, Berger BK, Bernuzzi S, Berry CPL, Bersanetti D, Bertolini A, Betzwieser J, Beveridge D, Bhandare R, Bhardwaj U, Bhattacharjee D, Bhaumik S, Bilenko IA, Billingsley G, Bini S, Birney R, Birnholtz O, Biscans S, Bischi M, Biscoveanu S, Bisht A, Biswas B, Bitossi M, Bizouard MA, Blackburn JK, Blair CD, Blair DG, Blair RM, Bobba F, Bode N, Boer M, Bogaert G, Boldrini M, Bonavena LD, Bondu F, Bonilla E, Bonnand R, Booker P, Boom BA, Bork R, Boschi V, Bose N, Bose S, Bossilkov V, Boudart V, Bouffanais Y, Bozzi A, Bradaschia C, Brady PR, Bramley A, Branch A, Branchesi M, Brau JE, Breschi M, Briant T, Briggs JH, Brillet A, Brinkmann M, Brockill P, Brooks AF, Brooks J, Brown DD, Brunett S, Bruno G, Bruntz R, Bryant J, Bulik T, Bulten HJ, Buonanno A, Buscicchio R, Buskulic D, Buy C, Byer RL, Cadonati L, Cagnoli G, Cahillane C, Bustillo JC, Callaghan JD, Callister TA, Calloni E, Cameron J, Camp JB, Canepa M, Canevarolo S, Cannavacciuolo M, Cannon KC, Cao H, Capote E, Carapella G, Carbognani F, Carlin JB, Carney MF, Carpinelli M, Carrillo G, Carullo G, Carver TL, Diaz JC, Casentini C, Castaldi G, Caudill S, Cavaglià M, Cavalier F, Cavalieri R, Ceasar M, Cella G, Cerdá-Durán P, Cesarini E, Chaibi W, Chakravarti K, Subrahmanya SC, Champion E, Chan CH, Chan C, Chan CL, Chan K, Chandra K, Chanial P, Chao S, Charlton P, Chase EA, Chassande-Mottin E, Chatterjee C, Chatterjee D, Chatterjee D, Chaturvedi M, Chaty S, Chatziioannou K, Chen HY, Chen J, Chen X, Chen Y, Chen Z, Cheng H, Cheong CK, Cheung HY, Chia HY, Chiadini F, Chiarini G, Chierici R, Chincarini A, Chiofalo ML, Chiummo A, Cho G, Cho HS, Choudhary RK, Choudhary S, Christensen N, Chu Q, Chua S, Chung KW, Ciani G, Ciecielag P, Cieślar M, Cifaldi M, Ciobanu AA, Ciolfi R, Cipriano F, Cirone A, Clara F, Clark EN, Clark JA, Clarke L, Clearwater P, Clesse S, Cleva F, Coccia E, Codazzo E, Cohadon PF, Cohen DE, Cohen L, Colleoni M, Collette CG, Colombo A, Colpi M, Compton CM, Constancio M, Conti L, Cooper SJ, Corban P, Corbitt TR, Cordero-Carrión I, Corezzi S, Corley KR, Cornish N, Corre D, Corsi A, Cortese S, Costa CA, Cotesta R, Coughlin MW, Coulon JP, Countryman ST, Cousins B, Couvares P, Coward DM, Cowart MJ, Coyne DC, Coyne R, Creighton JDE, Creighton TD, Criswell AW, Croquette M, Crowder SG, Cudell JR, Cullen TJ, Cumming A, Cummings R, Cunningham L, Cuoco E, Curyło M, Dabadie P, Canton TD, Dall'Osso S, Dálya G, Dana A, DaneshgaranBajastani LM, D'Angelo B, Danilishin S, D'Antonio S, Danzmann K, Darsow-Fromm C, Dasgupta A, Datrier LEH, Datta S, Dattilo V, Dave I, Davier M, Davies GS, Davis D, Davis MC, Daw EJ, Dean R, DeBra D, Deenadayalan M, Degallaix J, De Laurentis M, Deléglise S, Del Favero V, De Lillo F, De Lillo N, Del Pozzo W, DeMarchi LM, De Matteis F, D'Emilio V, Demos N, Dent T, Depasse A, De Pietri R, De Rosa R, De Rossi C, DeSalvo R, De Simone R, Dhurandhar S, Díaz MC, Diaz-Ortiz M, Didio NA, Dietrich T, Di Fiore L, Di Fronzo C, Di Giorgio C, Di Giovanni F, Di Giovanni M, Di Girolamo T, Di Lieto 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Ju L, Junker J, Juste V, Kalaghatgi CV, Kalogera V, Kamai B, Kandhasamy S, Kang G, Kanner JB, Kao Y, Kapadia SJ, Kapasi DP, Karat S, Karathanasis C, Karki S, Kashyap R, Kasprzack M, Kastaun W, Katsanevas S, Katsavounidis E, Katzman W, Kaur T, Kawabe K, Kéfélian F, Keitel D, Key JS, Khadka S, Khalili FY, Khan S, Khazanov EA, Khetan N, Khursheed M, Kijbunchoo N, Kim C, Kim JC, Kim K, Kim WS, Kim YM, Kimball C, Kinley-Hanlon M, Kirchhoff R, Kissel JS, Kleybolte L, Klimenko S, Knee AM, Knowles TD, Knyazev E, Koch P, Koekoek G, Koley S, Kolitsidou P, Kolstein M, Komori K, Kondrashov V, Kontos A, Koper N, Korobko M, Kovalam M, Kozak DB, Kringel V, Krishnendu NV, Królak A, Kuehn G, Kuei F, Kuijer P, Kumar A, Kumar P, Kumar R, Kumar R, Kuns K, Kuwahara S, Lagabbe P, Laghi D, Lalande E, Lam TL, Lamberts A, Landry M, Lane BB, Lang RN, Lange J, Lantz B, La Rosa I, Lartaux-Vollard A, Lasky PD, Laxen M, Lazzarini A, Lazzaro C, Leaci P, Leavey S, Lecoeuche YK, Lee HM, Lee HW, Lee J, Lee K, Lehmann J, Lemaître A, Leroy N, Letendre N, Levesque C, Levin Y, Leviton JN, Leyde K, Li AKY, Li B, Li J, Li TGF, Li X, Linde F, Linker SD, Linley JN, Littenberg TB, Liu J, Liu K, Liu X, Llamas F, Llorens-Monteagudo M, Lo RKL, Lockwood A, London LT, Longo A, Lopez D, Portilla ML, Lorenzini M, Loriette V, Lormand M, Losurdo G, Lott TP, Lough JD, Lousto CO, Lovelace G, Lucaccioni JF, Lück H, Lumaca D, Lundgren AP, Lynam JE, Macas R, MacInnis M, Macleod DM, MacMillan IAO, Macquet A, Hernandez IM, Magazzù C, Magee RM, Maggiore R, Magnozzi M, Mahesh S, Majorana E, Makarem C, Maksimovic I, Maliakal S, Malik A, Man N, Mandic V, Mangano V, Mango JL, Mansell GL, Manske M, Mantovani M, Mapelli M, Marchesoni F, Marion F, Mark Z, Márka S, Márka Z, Markakis C, Markosyan AS, Markowitz A, Maros E, Marquina A, Marsat S, Martelli F, Martin IW, Martin RM, Martinez M, Martinez VA, Martinez V, Martinovic K, Martynov DV, Marx EJ, Masalehdan H, Mason K, Massera E, Masserot A, Massinger TJ, Masso-Reid M, Mastrogiovanni S, Matas A, Mateu-Lucena M, Matichard F, Matiushechkina M, Mavalvala N, McCann JJ, McCarthy R, McClelland DE, McClincy PK, McCormick S, McCuller L, McGhee GI, McGuire SC, McIsaac C, McIver J, McRae T, McWilliams ST, Meacher D, Mehmet M, Mehta AK, Meijer Q, Melatos A, Melchor DA, Mendell G, Menendez-Vazquez A, Menoni CS, Mercer RA, Mereni L, Merfeld K, Merilh EL, Merritt JD, Merzougui M, Meshkov S, Messenger C, Messick C, Meyers PM, Meylahn F, Mhaske A, Miani A, Miao H, Michaloliakos I, Michel C, Middleton H, Milano L, Miller A, Miller AL, Miller B, Millhouse M, Mills JC, Milotti E, Minazzoli O, Minenkov Y, Mir LM, Miravet-Tenés M, Mishra C, Mishra T, Mistry T, Mitra S, Mitrofanov VP, Mitselmakher G, Mittleman R, Mo G, Moguel E, Mogushi K, Mohapatra SRP, Mohite SR, Molina I, Molina-Ruiz M, Mondin M, Montani M, Moore CJ, Moraru D, Morawski F, More A, Moreno C, Moreno G, Morisaki S, Mours B, Mow-Lowry CM, Mozzon S, Muciaccia F, Mukherjee A, Mukherjee D, Mukherjee S, 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Pereira A, Pereira T, Perez CJ, Périgois C, Perkins CC, Perreca A, Perriès S, Petermann J, Petterson D, Pfeiffer HP, Pham KA, Phukon KS, Piccinni OJ, Pichot M, Piendibene M, Piergiovanni F, Pierini L, Pierro V, Pillant G, Pillas M, Pilo F, Pinard L, Pinto IM, Pinto M, Piotrzkowski K, Pirello M, Pitkin MD, Placidi E, Planas L, Plastino W, Pluchar C, Poggiani R, Polini E, Pong DYT, Ponrathnam S, Popolizio P, Porter EK, Poulton R, Powell J, Pracchia M, Pradier T, Prajapati AK, Prasai K, Prasanna R, Pratten G, Principe M, Prodi GA, Prokhorov L, Prosposito P, Prudenzi L, Puecher A, Punturo M, Puosi F, Puppo P, Pürrer M, Qi H, Quetschke V, Quitzow-James R, Raab FJ, Raaijmakers G, Radkins H, Radulesco N, Raffai P, Rail SX, Raja S, Rajan C, Ramirez KE, Ramirez TD, Ramos-Buades A, Rana J, Rapagnani P, Rapol UD, Ray A, Raymond V, Raza N, Razzano M, Read J, Rees LA, Regimbau T, Rei L, Reid S, Reid SW, Reitze DH, Relton P, Renzini A, Rettegno P, Rezac M, Ricci F, Richards D, Richardson JW, Richardson L, Riemenschneider G, Riles K, Rinaldi S, Rink K, Rizzo M, Robertson NA, Robie R, Robinet F, Rocchi A, Rodriguez S, Rolland L, Rollins JG, Romanelli M, Romano R, Romel CL, Romero-Rodríguez A, Romero-Shaw IM, Romie JH, Ronchini S, Rosa L, Rose CA, Rosińska D, Ross MP, Rowan S, Rowlinson SJ, Roy S, Roy S, Roy S, Rozza D, Ruggi P, Ryan K, Sachdev S, Sadecki T, Sadiq J, Sakellariadou M, Salafia OS, Salconi L, Saleem M, Salemi F, Samajdar A, Sanchez EJ, Sanchez JH, Sanchez LE, Sanchis-Gual N, Sanders JR, Sanuy A, Saravanan TR, Sarin N, Sassolas B, Satari H, Sathyaprakash BS, Sauter O, Savage RL, Sawant D, Sawant HL, Sayah S, Schaetzl D, Scheel M, Scheuer J, Schiworski M, Schmidt P, Schmidt S, Schnabel R, Schneewind M, Schofield RMS, Schönbeck A, Schulte BW, Schutz BF, Schwartz E, Scott J, Scott SM, Seglar-Arroyo M, Sellers D, Sengupta AS, Sentenac D, Seo EG, Sequino V, Sergeev A, Setyawati Y, Shaffer T, Shahriar MS, Shams B, Sharma A, Sharma P, Shawhan P, Shcheblanov NS, Shikauchi M, Shoemaker DH, Shoemaker DM, ShyamSundar S, Sieniawska M, Sigg D, Singer LP, Singh D, Singh N, Singha A, Sintes AM, Sipala V, Skliris V, Slagmolen BJJ, Slaven-Blair TJ, Smetana J, Smith JR, Smith RJE, Soldateschi J, Somala SN, Son EJ, Soni K, Soni S, Sordini V, Sorrentino F, Sorrentino N, Soulard R, Souradeep T, Sowell E, Spagnuolo V, Spencer AP, Spera M, Srinivasan R, Srivastava AK, Srivastava V, Staats K, Stachie C, Steer DA, Steinlechner J, Steinlechner S, Stevenson S, Stops DJ, Stover M, Strain KA, Strang LC, Stratta G, Strunk A, Sturani R, Stuver AL, Sudhagar S, Sudhir V, Suh HG, Summerscales TZ, Sun H, Sun L, Sunil S, Sur A, Suresh J, Sutton PJ, Swinkels BL, Szczepańczyk MJ, Szewczyk P, Tacca M, Tait SC, Talbot CJ, Talbot C, Tanasijczuk AJ, Tanner DB, Tao D, Tao L, Martín ENTS, Taranto C, Tasson JD, Tenorio R, Terhune JE, Terkowski L, Thirugnanasambandam MP, Thomas M, Thomas P, Thompson JE, Thondapu SR, Thorne KA, Thrane E, Tiwari S, Tiwari S, Tiwari V, Toivonen AM, Toland K, Tolley AE, Tonelli M, Torres-Forné A, Torrie CI, E Melo IT, Töyrä D, Trapananti A, Travasso F, Traylor G, Trevor M, Tringali MC, Tripathee A, Troiano L, Trovato A, Trozzo L, Trudeau RJ, Tsai DS, Tsai D, Tsang KW, Tse M, Tso R, Tsukada L, Tsuna D, Tsutsui T, Turbang K, Turconi M, Ubhi AS, Udall RP, Ueno K, Unnikrishnan CS, Urban AL, Utina A, Vahlbruch H, Vajente G, Vajpeyi A, Valdes G, Valentini M, Valsan V, van Bakel N, van Beuzekom M, van den Brand JFJ, Van Den Broeck C, Vander-Hyde DC, van der Schaaf L, van Heijningen JV, Vanosky J, van Remortel N, Vardaro M, Vargas AF, Varma V, Vasúth M, Vecchio A, Vedovato G, Veitch J, Veitch PJ, Venneberg J, Venugopalan G, Verkindt D, Verma P, Verma Y, Veske D, Vetrano F, Viceré A, Vidyant S, Viets AD, Vijaykumar A, Villa-Ortega V, Vinet JY, Virtuoso A, Vitale S, Vo T, Vocca H, von Reis ERG, von Wrangel JSA, Vorvick C, Vyatchanin SP, Wade LE, Wade M, Wagner KJ, Walet RC, Walker M, Wallace GS, Wallace L, Walsh S, Wang JZ, Wang WH, Ward RL, Warner J, Was M, Washington NY, Watchi J, Weaver B, Webster SA, Weinert M, Weinstein AJ, Weiss R, Weller CM, Wellmann F, Wen L, Weßels P, Wette K, Whelan JT, White DD, Whiting BF, Whittle C, Wilken D, Williams D, Williams MJ, Williamson AR, Willis JL, Willke B, Wilson DJ, Winkler W, Wipf CC, Wlodarczyk T, Woan G, Woehler J, Wofford JK, Wong ICF, Wu DS, Wysocki DM, Xiao L, Yamamoto H, Yang FW, Yang L, Yang Y, Yang Z, Yap MJ, Yeeles DW, Yelikar AB, Ying M, Yoo J, Yu H, Yu H, Zadrożny A, Zanolin M, Zelenova T, Zendri JP, Zevin M, Zhang J, Zhang L, Zhang T, Zhang Y, Zhao C, Zhao G, Zhao Y, Zhou R, Zhou Z, Zhu XJ, Zimmerman AB, Zucker ME, Zweizig J, Jeong D, Shandera S. Search for Subsolar-Mass Binaries in the First Half of Advanced LIGO's and Advanced Virgo's Third Observing Run. PHYSICAL REVIEW LETTERS 2022; 129:061104. [PMID: 36018635 DOI: 10.1103/physrevlett.129.061104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 03/18/2022] [Accepted: 06/07/2022] [Indexed: 06/15/2023]
Abstract
We report on a search for compact binary coalescences where at least one binary component has a mass between 0.2 M_{⊙} and 1.0 M_{⊙} in Advanced LIGO and Advanced Virgo data collected between 1 April 2019 1500 UTC and 1 October 2019 1500 UTC. We extend our previous analyses in two main ways: we include data from the Virgo detector and we allow for more unequal mass systems, with mass ratio q≥0.1. We do not report any gravitational-wave candidates. The most significant trigger has a false alarm rate of 0.14 yr^{-1}. This implies an upper limit on the merger rate of subsolar binaries in the range [220-24200] Gpc^{-3} yr^{-1}, depending on the chirp mass of the binary. We use this upper limit to derive astrophysical constraints on two phenomenological models that could produce subsolar-mass compact objects. One is an isotropic distribution of equal-mass primordial black holes. Using this model, we find that the fraction of dark matter in primordial black holes in the mass range 0.2 M_{⊙}<m_{PBH}<1.0 M_{⊙} is f_{PBH}≡Ω_{PBH}/Ω_{DM}≲6%. This improves existing constraints on primordial black hole abundance by a factor of ∼3. The other is a dissipative dark matter model, in which fermionic dark matter can collapse and form black holes. The upper limit on the fraction of dark matter black holes depends on the minimum mass of the black holes that can be formed: the most constraining result is obtained at M_{min}=1 M_{⊙}, where f_{DBH}≡Ω_{DBH}/Ω_{DM}≲0.003%. These are the first constraints placed on dissipative dark models by subsolar-mass analyses.
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Wu Y, Bu X, Ke Y, Sun H, Li J, Chen L, Cui W, He Y, Wu L. Insight into the Stereocontrol of DNA Polymerase‐Catalysed Reaction by Chiral Cobalt Complexes. Adv Synth Catal 2022. [DOI: 10.1002/adsc.202200786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Wang LJ, Xu Y, Sun H, Zhang BG, Kong XL, Han HT, Li J, Li YJ, Yang LM, Guo YH, Wang YB. [First report of invasive Pomacea snails in Shandong Province]. ZHONGGUO XUE XI CHONG BING FANG ZHI ZA ZHI = CHINESE JOURNAL OF SCHISTOSOMIASIS CONTROL 2022; 34:407-411. [PMID: 36116933 DOI: 10.16250/j.32.1374.2022115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
OBJECTIVE To characterize the species of invasive Pomacea snails that were discovered for the first time in Shandong Province. METHODS Pomacea snails samples were collected in the field of Jining City, Shandong Province on October 2021 for morphological identification. Pomacea snails were randomly sampled and genomic DNA was extracted from foot muscle tissues of Pomacea snails for multiplex PCR amplification. The PCR amplification product was sequenced. Then, the sequence was aligned and a phylogenetic tree was created using the software MegAlign 7.1.0. In addition, Angiostongylus cantonensis infection was detected in Pomacea snails with the lung microscopy. RESULTS A total of 104 living Pomacea snails were collected, and all were characterized as Pomacea spp. based on morphological features. Of 12 randomly selected adult Pomacea snails, multiplex PCR assay and sequencing identified eleven snails as P. canaliculata and one as P. maculata. No A. cantonensis infection was detected in 104 Pomacea snails. CONCLUSIONS This is the first report of invasive Pomacea snails in Shandong Province, where P. canaliculata and P. maculata are found.
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Gao J, Zhang L, Peng K, Sun H. [Diagnostic value of serum tumor markers CEA, CYFRA21-1, SCCAg, NSE and ProGRP for lung cancers of different pathological types]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2022; 42:886-891. [PMID: 35790439 DOI: 10.12122/j.issn.1673-4254.2022.06.12] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
OBJECTIVE To evaluate the diagnostic value of the serum tumor markers carcinoembryonic antigen (CEA), cytokeratin-19-fragment (CYFRA21-1), squamous cell carcinoma associated antigen (SCCAg), neuron-specificenolase (NSE) and pro-gastrin-releasing peptide (ProGRP) for lung cancers of different pathological types. METHODS This study was conducted among patients with established diagnoses of lung adenocarcinoma (LADC, n=137), lung squamous cell carcinoma (LSCC, n=82), small cell lung carcinoma (SCLC, n=59), and benign chest disease (BCD, n=102). The serum tumor markers were detected for all the patients for comparison of the positivity rates and their serum levels. ROC curve was used for analysis of the diagnostic efficacy of these tumor markers either alone or in different combinations. RESULTS In patients with LADC, the positivity rate and serum level of CEA were significantly higher than those in the other groups (P < 0.05); the patients with LSCC had the highest positivity rate and serum level of SCCAg among the 4 groups (P < 0.05). The positivity rates and serum levels of ProGRP and NSE were significantly higher in SCLC group than in the other groups (P < 0.05). CYFRA21-1 showed the highest positivity rate and serum level in LADC group and LSCC group. With the patients with BCD as control, CEA showed a diagnostic sensitivity of 62.8% and a specificity of 93.1% for LADC, and the sensitivity and specificity of SCCAg for diagnosing LSCC were 64.6% and 91.2%, respectively. CYFRA21-1 had the highest diagnostic sensitivity for LADC and LSCC. The diagnostic sensitivity and specificity of ProGRP for SCLC were 83.1% and 98.0%, respectively. When combined, CYFRA21-1 and CEA showed a high sensitivity (78.8%) and specificity (86.3%) for diagnosing LADC with an AUC of 0.891; CYFRA21-1 and SCCAg had a high sensitivity (84.1%) and specificity (87.3%) for diagnosing LSCC with an AUC of 0.912. NSE combined with ProGRP was highly sensitive (88.1%) and specific (98.0%) for diagnosis of SCLC, with an AUC of 0.952. For lung cancers of different pathological types, the combination of all the 5 tumor markers showed no significant differences in the diagnostic power from a combined detection with any two of the markers (P>0.05). CONCLUSION CEA, CYFRA21-1, SCCAg, NSE and ProGRP are all related to the pathological type of lung cancers and can be used in different combinations as useful diagnostic indicators for lung cancers.
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