351
|
Wang W, Qin X, Wang R, Xu J, Wu H, Khalid A, Jiang H, Liu D, Pan F. EZH2 is involved in vulnerability to neuroinflammation and depression-like behaviors induced by chronic stress in different aged mice. J Affect Disord 2020; 272:452-464. [PMID: 32553389 DOI: 10.1016/j.jad.2020.03.154] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 02/15/2020] [Accepted: 03/29/2020] [Indexed: 12/22/2022]
Abstract
BACKGROUND Microglial activation and pro-inflammatory cytokines expression is closely related to pathogenesis of depression. Aging is a known risk factor for neuroinflammation in the central nervous system and subsequent behavioral impairment. Enhancer of zeste homolog 2 (EZH2), a methyltransferase of histone H3 lysine 27 which regulates microglial activation, plays a crucial role in proinflammatory cytokines expression. However, whether the EZH2 is involved in susceptibility to depression in different ages remains elusive. METHODS Young and aged C57BL/6 mice were exposed to chronic unpredictable mild stress for three weeks. Depression- and anxiety-like behaviors, spatial memory impairment, and the expression of pro-inflammatory cytokines, P-p65, EZH2, H3K27me3 and SOCS3 in the prefrontal cortex and hippocampus were measured using an established behavioral battery, ELISA, immunohistochemistry and western blotting techniques. Moreover, EPZ-6438, an inhibitor of EZH2, was utilized to detect the role of EZH2 in neuroinflammation and behavioral abnormalities. RESULTS CUMS induced depression-like behaviors and spatial memory impairment, elevated levels of proinflammatory cytokines and P-p65, enhanced M1 microglia activation, and increased levels of EZH2, H3K27me3 and SOCS3 in the prefrontal cortex and hippocampus in young and aged mice. Both unstressed and stressed aged mice displayed attention-deficit behavioral outcomes, alteration of protein levels compared with young mice. However, inhibition of EZH2 could relieve most of behavioral and molecular alterations. LIMITATIONS A relative small sample size is a limitation. CONCLUSIONS EZH2 might be involved in susceptibility to neuroinflammation and depression-like behaviors in different aged mice.
Collapse
|
352
|
Xu J, Miao H, Wang J, Pan G. Molecularly Imprinted Synthetic Antibodies: From Chemical Design to Biomedical Applications. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e1906644. [PMID: 32101378 DOI: 10.1002/smll.201906644] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 01/27/2020] [Indexed: 05/25/2023]
Abstract
Billions of dollars are invested into the monoclonal antibody market every year to meet the increasing demand in clinical diagnosis and therapy. However, natural antibodies still suffer from poor stability and high cost, as well as ethical issues in animal experiments. Thus, developing antibody substitutes or mimics is a long-term goal for scientists. The molecular imprinting technique presents one of the most promising strategies for antibody mimicking. The molecularly imprinted polymers (MIPs) are also called "molecularly imprinted synthetic antibodies" (MISAs). The breakthroughs of key technologies and innovations in chemistry and material science in the last decades have led to the rapid development of MISAs, and their molecular affinity has become comparable to that of natural antibodies. Currently, MISAs are undergoing a revolutionary transformation of their applications, from initial adsorption and separation to the rising fields of biomedicine. Herein, the fundamental chemical design of MISAs is examined, and then current progress in biomedical applications is the focus. Meanwhile, the potential of MISAs as qualified substitutes or even to transcend the performance of natural antibodies is discussed from the perspective of frontier needs in biomedicines, to facilitate the rapid development of synthetic artificial antibodies.
Collapse
|
353
|
Qin X, Wang W, Wu H, Liu D, Wang R, Xu J, Jiang H, Pan F. PPARγ-mediated microglial activation phenotype is involved in depressive-like behaviors and neuroinflammation in stressed C57BL/6J and ob/ob mice. Psychoneuroendocrinology 2020; 117:104674. [PMID: 32422516 DOI: 10.1016/j.psyneuen.2020.104674] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 03/06/2020] [Accepted: 03/25/2020] [Indexed: 01/17/2023]
Abstract
BACKGROUND There is an increased risk for obese patients with chronic low-grade inflammation to develop depression. Stress induces microglial activation and neuroinflammation that play crucial roles in the pathogenesis of depression. Peroxisome proliferator-activated receptor gamma (PPARγ), a nuclear transcription factor, regulates microglial polarization and neuroinflammation. Our study aimed to investigate the role of PPARγ in the development of depressive symptoms and neuroinflammation induced by chronic unpredictable mild stress (CUMS) in wild-type/C57BL/6J (wt) and leptin-deficient (ob/ob) mice. METHODS CUMS was used to build a depression model with wt and ob/ob mice. Depressive-like behaviors were evaluated by sucrose preference test, open field test, tail suspension test, and Morris water maze test. Cytokines, the activated microglial state, and nuclear factor-κB (NF-κB) and PPARγ expression in the prefrontal cortex (PFC) and hippocampus (HIP) were examined by enzyme-linked immunosorbent assay (ELISA), immunofluorescence, and western blotting. Additionally, pioglitazone, an agonist of PPARγ, was used as a treatment intervention. RESULTS After CUMS, ob/ob mice exhibited severe behavioral disorders and spatial memory impairment, and higher levels of pro-inflammatory cytokines, M1/M2 ratios, and NF-κB activation, as well as lower levels of anti-inflammatory cytokines and PPARγ expression in the PFC and HIP compared to wt mice. Administration of pioglitazone relieved these alterations in wt and ob/ob mice. CONCLUSIONS CUMS was able to induce severe depressive-like behaviors, neuroinflammation, and reduced expression of PPARγ in ob/ob mice as compared to wt mice. This suggests that PPARγ mediates the microglial activation phenotype, which might be related to the susceptibility of stressed ob/ob mice to develop depressive disorder.
Collapse
|
354
|
Ma X, Jing J, Wang J, Xu J, Hu Z. Extraction of Low Methoxyl Pectin from Fresh Sunflower Heads by Subcritical Water Extraction. ACS OMEGA 2020; 5:15095-15104. [PMID: 32637782 PMCID: PMC7330903 DOI: 10.1021/acsomega.0c00928] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 06/04/2020] [Indexed: 05/14/2023]
Abstract
Subcritical water extraction (SWE) of pectin from fresh sunflower heads was optimized using the response surface methodology (RSM). The optimal conditions for the maximum yield of pectin (6.57 ± 0.6%) were found to be a pressure of 8 bar, temperature of 120 °C, time of 20 min, and liquid-solid ratio (LSR) of 7 mL/g. The degree of esterification (DE) of pectin was analyzed by titrimetry and Fourier transform infrared (FTIR) methods, which was low methoxyl pectin. The molecular weight (M w), galacturonic acid (GalA) content, and surface tension of pectin were 11.50 kDa, 82%, and 45.38 mN/m (1.5% w/v), respectively. Moreover, thermogravimetric (TG) and differential scanning calorimetry (DSC) analysis confirmed that pectin had excellent thermal stability. FTIR and 1H NMR spectra confirmed its structure. This study demonstrated that SWE could be used as a productive and environmentally friendly method for extracting pectin from fresh sunflower heads.
Collapse
|
355
|
Xu J, Baldonedo‐Mosteiro M, Franco‐Correia S, Mosteiro‐Díaz MP. Spanish oncology nurses: Assessment and relationship between resilience and emotional labour status. Eur J Cancer Care (Engl) 2020; 29:e13256. [DOI: 10.1111/ecc.13256] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 12/04/2019] [Accepted: 04/16/2020] [Indexed: 12/01/2022]
|
356
|
Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Amoroso A, An Q, Bai Y, Bakina O, Ferroli RB, Balossino I, Ban Y, Begzsuren K, Bennett JV, Berger N, Bertani M, Bettoni D, Bianchi F, Biernat J, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Cheng W, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai JP, Dai XC, Dbeyssi A, de Boer RB, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Du SX, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Fritsch M, Fu CD, Fu Y, Gao XL, Gao Y, Gao Y, Gao YG, Garzia I, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu S, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han S, Han TT, Han TZ, Hao XQ, Harris FA, He KL, Heinsius FH, Held T, Heng YK, Himmelreich M, Holtmann T, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huesken N, Hussain T, Andersson WI, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Jiang HB, Jiang XS, Jiang XY, Jiao JB, Jiao Z, Jin S, Jin Y, 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, Kurth MG, Kühn W, Lane JJ, Lange JS, Larin P, Lavezzi L, Leithoff H, Lellmann M, Lenz T, Li C, Li CH, Li C, Li DM, Li F, Li G, Li HB, Li HJ, Li JL, Li JQ, Li K, Li LK, Li L, Li PL, Li PR, Li WD, Li WG, Li XH, Li XL, Li ZB, Li ZY, Liang H, Liang H, Liang YF, Liang YT, Liao LZ, Libby J, Lin CX, Liu B, Liu BJ, Liu CX, Liu D, Liu DY, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LY, Liu Q, Liu SB, Liu T, Liu X, Liu YB, Liu ZA, Liu ZQ, Long YF, Lou XC, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo PW, Luo T, Luo XL, Lusso S, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XN, Ma XX, Ma XY, Ma YM, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min TJ, Mitchell RE, Mo XH, Mo YJ, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Olsen SL, Ouyang Q, Pacetti S, Pan Y, Pan Y, Papenbrock M, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Pitka A, Poling R, Prasad V, Qi H, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sarantsev A, Savrié M, Schelhaas Y, Schnier C, Schoenning K, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song QQ, Song YX, Sosio S, Spataro S, Sui FF, Sun GX, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YK, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Thoren V, Tsednee B, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang Y, Wang YD, Wang YF, Wang YQ, Wang Z, Wang ZY, Wang Z, Wang Z, Weber T, Wei DH, Weidenkaff P, Weidner F, Wen HW, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu Z, Xia L, Xiao H, Xiao SY, Xiao YJ, Xiao ZJ, Xie YG, Xie YH, Xing TY, Xiong XA, Xu GF, Xu JJ, Xu QJ, Xu W, Xu XP, Yan L, Yan WB, Yan WC, Yan WC, Yang HJ, Yang HX, Yang L, Yang RX, Yang SL, Yang YH, 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 W, Yuan XQ, Yuan Y, Yue CX, Yuncu A, Zafar AA, Zeng Y, Zhang BX, Zhang G, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang L, Zhang L, Zhang S, Zhang SF, Zhang TJ, Zhang XY, Zhang Y, Zhang YH, Zhang YT, Zhang Y, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YXZ, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng Y, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu WJ, Zhu XL, Zhu YC, Zhu ZA, Zou BS, Zou JH. Study of Open-Charm Decays and Radiative Transitions of the X(3872). PHYSICAL REVIEW LETTERS 2020; 124:242001. [PMID: 32639837 DOI: 10.1103/physrevlett.124.242001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2020] [Revised: 04/06/2020] [Accepted: 06/01/2020] [Indexed: 06/11/2023]
Abstract
The processes X(3872)→D^{*0}D[over ¯]^{0}+c.c.,γJ/ψ,γψ(2S), and γD^{+}D^{-} are searched for in a 9.0 fb^{-1} data sample collected at center-of-mass energies between 4.178 and 4.278 GeV with the BESIII detector. We observe X(3872)→D^{*0}D^{0}[over ¯]+c.c. and find evidence for X(3872)→γJ/ψ with statistical significances of 7.4σ and 3.5σ, respectively. No evident signals for X(3872)→γψ(2S) and γD^{+}D^{-} are found, and the upper limit on the relative branching ratio R_{γψ}≡{B[X(3872)→γψ(2S)]}/{B[X(3872)→γJ/ψ]}<0.59 is set at 90% confidence level. Measurements of branching ratios relative to decay X(3872)→π^{+}π^{-}J/ψ are also reported for decays X(3872)→D^{*0}D^{0}[over ¯]+c.c.,γψ(2S),γJ/ψ, and γD^{+}D^{-}, as well as the non-D^{*0}D^{0}[over ¯] three-body decays π^{0}D^{0}D^{0}[over ¯] and γD^{0}D^{0}[over ¯].
Collapse
|
357
|
Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Amoroso A, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Begzsuren K, Bennett JV, Berger N, Bertani M, Bettoni D, Bianchi F, Biernat J, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Cheng WS, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai JP, Dai XC, Dbeyssi A, de Boer RB, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Du SX, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Fritsch M, Fu CD, Fu Y, Gao XL, Gao Y, Gao Y, Gao YG, Garzia I, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu S, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guo YP, Guskov A, Han S, Han TT, Han TZ, Hao XQ, Harris FA, He KL, Heinsius FH, Held T, Heng YK, Himmelreich M, Holtmann T, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Huesken N, Hussain T, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Jiang HB, Jiang XS, Jiang XY, Jiao JB, Jiao Z, Jin S, Jin Y, 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, Kurth MG, Kühn W, Lane JJ, Lange JS, Larin P, Lavezzi L, Leithoff H, Lellmann M, Lenz T, Li C, Li CH, Li C, Li DM, Li F, Li G, Li HB, Li HJ, Li JL, Li JQ, Li K, Li LK, Li L, Li PL, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li ZB, Li ZY, Liang H, Liang H, Liang YF, Liang YT, Liao LZ, Libby J, Lin CX, Liu B, Liu BJ, Liu CX, Liu D, Liu DY, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu Q, Liu SB, Liu S, Liu T, Liu X, Liu YB, Liu ZA, Liu ZQ, Long YF, Lou XC, Lu FX, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo PW, Luo T, Luo XL, Lusso S, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XN, Ma XX, Ma XY, Ma YM, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min TJ, Mitchell RE, Mo XH, Mo YJ, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Pitka A, Poling R, Prasad V, Qi H, Qi HR, Qi M, Qi TY, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Shan DC, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song QQ, Song WM, Song YX, Sosio S, Spataro S, Sui FF, Sun GX, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YK, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Thoren V, Tsednee B, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang Y, Wang YD, Wang YF, Wang YQ, Wang Z, Wang ZY, Wang Z, Wang Z, Wei DH, Weidenkaff P, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu Z, Xia L, Xiao H, Xiao SY, Xiao YJ, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xiong XA, Xu GF, Xu JJ, Xu QJ, Xu W, Xu XP, Yan F, Yan L, Yan L, Yan WB, Yan WC, Yan X, Yang HJ, Yang HX, Yang L, Yang RX, Yang SL, Yang YH, 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 W, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Yuncu A, Zafar AA, Zeng Y, Zhang BX, Zhang G, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang L, Zhang L, Zhang S, Zhang SF, Zhang TJ, Zhang XY, Zhang Y, Zhang YH, Zhang YT, Zhang Y, Zhang Y, Zhang Y, Zhang ZH, 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 Y, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu WJ, Zhu XL, Zhu YC, Zhu ZA, Zou BS, Zou JH. Measurements of Absolute Branching Fractions of Fourteen Exclusive Hadronic D Decays to η. PHYSICAL REVIEW LETTERS 2020; 124:241803. [PMID: 32639841 DOI: 10.1103/physrevlett.124.241803] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 06/01/2020] [Indexed: 06/11/2023]
Abstract
Using 2.93 fb^{-1} of e^{+}e^{-} collision data taken at a center-of-mass energy of 3.773 GeV with the BESIII detector, we report the first measurements of the absolute branching fractions of 14 hadronic D^{0(+)} decays to exclusive final states with an η, e.g., D^{0}→K^{-}π^{+}η, K_{S}^{0}π^{0}η, K^{+}K^{-}η, K_{S}^{0}K_{S}^{0}η, K^{-}π^{+}π^{0}η, K_{S}^{0}π^{+}π^{-}η, K_{S}^{0}π^{0}π^{0}η, and π^{+}π^{-}π^{0}η; D^{+}→K_{S}^{0}π^{+}η, K_{S}^{0}K^{+}η, K^{-}π^{+}π^{+}η, K_{S}^{0}π^{+}π^{0}η, π^{+}π^{+}π^{-}η, and π^{+}π^{0}π^{0}η. Among these decays, the D^{0}→K^{-}π^{+}η and D^{+}→K_{S}^{0}π^{+}η decays have the largest branching fractions, which are B(D^{0}→K^{-}π^{+}η)=(1.853±0.025_{stat}±0.031_{syst})% and B(D^{+}→K_{S}^{0}π^{+}η)=(1.309±0.037_{stat}±0.031_{syst})%, respectively. The charge-parity asymmetries for the six decays with highest event yields are determined, and no statistically significant charge-parity violation is found.
Collapse
|
358
|
Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Alekseev M, Ambrose D, Amoroso A, An FF, An Q, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Begzsuren K, Bennett JV, Berger N, Bertani M, Bettoni D, Bianchi F, Biernat J, Bloms J, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chai J, Chang JF, Chang WL, Chelkov G, Chen DY, Chen G, Chen HS, Chen J, Chen JC, Chen ML, Chen SJ, Chen YB, Cheng W, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai JP, Dai XC, Dbeyssi A, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Dou ZL, Du SX, Fan JZ, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Fritsch M, Fu CD, Fu Y, Gao Q, Gao XL, Gao Y, Gao Y, Gao YG, Gao Z, Garillon B, Garzia I, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu S, Gu YT, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han S, Hao XQ, Harris FA, He KL, Heinsius FH, Held T, Heng YK, Himmelreich M, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang JS, Huang XT, Huang XZ, Huesken N, Hussain T, Ikegami Andersson W, Imoehl W, Irshad M, Ji Q, Ji QP, Ji XB, Ji XL, Jiang HL, Jiang XS, Jiang XY, Jiao JB, Jiao Z, Jin DP, Jin S, Jin Y, 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, Kurth M, Kurth MG, Kühn W, Lange JS, Larin P, Lavezzi L, Leithoff H, Lenz T, Li C, Li C, Li DM, Li F, Li FY, Li G, Li HB, Li HJ, Li JC, Li JW, Li K, Li LK, Li L, Li PL, Li PR, Li QY, Li WD, Li WG, Li XH, Li XL, Li XN, Li ZB, Li ZY, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Lin CX, Lin DX, Lin YJ, Liu B, Liu BJ, Liu CX, Liu D, Liu DY, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu K, Liu LY, Liu Q, Liu SB, Liu T, Liu X, Liu XY, Liu YB, Liu ZA, Liu Z, Long YF, Lou XC, Lu HJ, Lu JD, Lu JG, Lu Y, Lu YP, Luo CL, Luo MX, Luo PW, Luo T, Luo XL, Lusso S, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma XN, Ma XX, Ma XY, Ma YM, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min J, Min TJ, Mitchell RE, Mo XH, Mo YJ, Morales Morales C, Muchnoi NY, Muramatsu H, Mustafa A, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu SL, Olsen SL, Ouyang Q, Pacetti S, Pan Y, Papenbrock M, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Pitka A, Poling R, Prasad V, Qi HR, Qi M, Qi TY, Qian S, Qiao CF, Qin N, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Richter M, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sarantsev A, Savrié M, Schelhaas Y, Schoenning K, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Sheng HY, Shi X, Shi XD, Song JJ, Song QQ, Song XY, Sosio S, Sowa C, Spataro S, Sui FF, Sun GX, Sun JF, Sun L, Sun SS, Sun XH, Sun YJ, Sun YK, Sun YZ, Sun ZJ, Sun ZT, Tan YT, Tang CJ, Tang GY, Tang X, Thoren V, Tsednee B, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang K, Wang LL, Wang LS, Wang M, Wang MZ, Wang M, Wang PL, Wang RM, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang Y, Wang YF, Wang YQ, Wang Z, Wang ZG, Wang ZY, Wang Z, Weber T, Wei DH, Weidenkaff P, Wen HW, Wen SP, Wiedner U, Wilkinson G, Wolke M, Wu LH, Wu LJ, Wu Z, Xia L, Xia Y, Xiao SY, Xiao YJ, Xiao ZJ, Xie YG, Xie YH, Xing TY, Xiong XA, Xiu QL, Xu GF, Xu JJ, Xu L, Xu QJ, Xu W, Xu XP, Yan F, Yan L, Yan WB, Yan WC, Yan YH, Yang HJ, Yang HX, Yang L, Yang RX, Yang SL, Yang YH, Yang YX, Yang Y, Yang ZQ, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu JS, Yu T, Yuan CZ, Yuan XQ, Yuan Y, Yuncu A, Zafar AA, Zeng Y, Zhang BX, Zhang BY, Zhang CC, Zhang DH, Zhang HH, Zhang HY, Zhang J, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang K, Zhang L, Zhang L, Zhang SF, Zhang TJ, Zhang XY, Zhang Y, Zhang YH, Zhang YT, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang ZH, Zhang ZP, Zhang ZY, Zhao G, Zhao JW, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao TC, Zhao YB, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng Y, Zheng YH, Zhong B, Zhou L, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou X, Zhou X, Zhu AN, Zhu J, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu WJ, Zhu XL, Zhu YC, Zhu YS, Zhu ZA, Zhuang J, Zou BS, Zou JH. Determination of Strong-Phase Parameters in D→K_{S,L}^{0}π^{+}π^{-}. PHYSICAL REVIEW LETTERS 2020; 124:241802. [PMID: 32639796 DOI: 10.1103/physrevlett.124.241802] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 04/20/2020] [Accepted: 05/21/2020] [Indexed: 06/11/2023]
Abstract
We report the most precise measurements to date of the strong-phase parameters between D^{0} and D[over ¯]^{0} decays to K_{S,L}^{0}π^{+}π^{-} using a sample of 2.93 fb^{-1} of e^{+}e^{-} annihilation data collected at a center-of-mass energy of 3.773 GeV with the BESIII detector at the BEPCII collider. Our results provide the key inputs for a binned model-independent determination of the Cabibbo-Kobayashi-Maskawa angle γ/ϕ_{3} with B decays. Using our results, the decay model sensitivity to the γ/ϕ_{3} measurement is expected to be between 0.7° and 1.2°, approximately a factor of three smaller than that achievable with previous measurements, based on the studies of the simulated data. The improved precision of this work ensures that measurements of γ/ϕ_{3} will not be limited by knowledge of strong phases for the next decade. Furthermore, our results provide critical input for other flavor-physics investigations, including charm mixing, other measurements of CP violation, and the measurement of strong-phase parameters for other D-decay modes.
Collapse
|
359
|
Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Amoroso A, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Begzsuren K, Bennett JV, Berger N, Bertani M, Bettoni D, Bianchi F, Biernat J, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Cheng WS, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai JP, Dai XC, Dbeyssi A, de Boer RB, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Du SX, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Fritsch M, Fu CD, Fu Y, Gao XL, Gao Y, Gao Y, Gao YG, Garzia I, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu S, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guo YP, Guskov A, Han S, Han TT, Han TZ, Hao XQ, Harris FA, He KL, Heinsius FH, Held T, Heng YK, Himmelreich M, Holtmann T, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Huesken N, Hussain T, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Jiang HB, Jiang XS, Jiang XY, Jiao JB, Jiao Z, Jin S, Jin Y, 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, Kurth MG, Kühn W, Lane JJ, Lange JS, Larin P, Lavezzi L, Leithoff H, Lellmann M, Lenz T, Li C, Li CH, Li C, Li DM, Li F, Li G, Li HB, Li HJ, Li JL, Li JQ, Li K, Li LK, Li L, Li PL, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li ZB, Li ZY, Liang H, Liang H, Liang YF, Liang YT, Liao LZ, Libby J, Lin CX, Liu B, Liu BJ, Liu CX, Liu D, Liu DY, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu Q, Liu SB, Liu S, Liu T, Liu X, Liu YB, Liu ZA, Liu ZQ, Long YF, Lou XC, Lu FX, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo PW, Luo T, Luo XL, Lusso S, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XN, Ma XX, Ma XY, Ma YM, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min TJ, Mitchell RE, Mo XH, Mo YJ, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Pitka A, Poling R, Prasad V, Qi H, Qi HR, Qi M, Qi TY, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Shan DC, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song QQ, Song WM, Song YX, Sosio S, Spataro S, Sui FF, Sun GX, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YK, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Thoren V, Tsednee B, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang Y, Wang YD, Wang YF, Wang YQ, Wang Z, Wang ZY, Wang Z, Wang Z, Wei DH, Weidenkaff P, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu Z, Xia L, Xiao H, Xiao SY, Xiao YJ, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xiong XA, Xu GF, Xu JJ, Xu QJ, Xu W, Xu XP, Yan F, Yan L, Yan L, Yan WB, Yan WC, Yan X, Yang HJ, Yang HX, Yang L, Yang RX, Yang SL, Yang YH, 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 W, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Yuncu A, Zafar AA, Zeng Y, Zhang BX, Zhang G, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang L, Zhang L, Zhang S, Zhang SF, Zhang TJ, Zhang XY, Zhang Y, Zhang YH, Zhang YT, Zhang Y, Zhang Y, Zhang Y, Zhang ZH, 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 Y, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu WJ, Zhu XL, Zhu YC, Zhu ZA, Zou BS, Zou JH. First Observation of D^{+}→ημ^{+}ν_{μ} and Measurement of Its Decay Dynamics. PHYSICAL REVIEW LETTERS 2020. [PMID: 32603168 DOI: 10.1016/j.enpol.2020.111655] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
By analyzing a data sample corresponding to an integrated luminosity of 2.93 fb^{-1} collected at a center-of-mass energy of 3.773 GeV with the BESIII detector, we measure for the first time the absolute branching fraction of the D^{+}→ημ^{+}ν_{μ} decay to be B_{D^{+}→ημ^{+}ν_{μ}}=(10.4±1.0_{stat}±0.5_{syst})×10^{-4}. Using the world averaged value of B_{D^{+}→ηe^{+}ν_{e}}, the ratio of the two branching fractions is determined to be B_{D^{+}→ημ^{+}ν_{μ}}/B_{D^{+}→ηe^{+}ν_{e}}=0.91±0.13_{(stat+syst)}, which agrees with the theoretical expectation of lepton flavor universality within uncertainty. By studying the differential decay rates in five four-momentum transfer intervals, we obtain the product of the hadronic form factor f_{+}^{η}(0) and the c→d Cabibbo-Kobayashi-Maskawa matrix element |V_{cd}| to be f_{+}^{η}(0)|V_{cd}|=0.087±0.008_{stat}±0.002_{syst}. Taking the input of |V_{cd}| from the global fit in the standard model, we determine f_{+}^{η}(0)=0.39±0.04_{stat}±0.01_{syst}. On the other hand, using the value of f_{+}^{η}(0) calculated in theory, we find |V_{cd}|=0.242±0.022_{stat}±0.006_{syst}±0.033_{theory}.
Collapse
|
360
|
Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Amoroso A, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Begzsuren K, Bennett JV, Berger N, Bertani M, Bettoni D, Bianchi F, Biernat J, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Cheng WS, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai JP, Dai XC, Dbeyssi A, de Boer RB, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Du SX, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Fritsch M, Fu CD, Fu Y, Gao XL, Gao Y, Gao Y, Gao YG, Garzia I, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu S, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guo YP, Guskov A, Han S, Han TT, Han TZ, Hao XQ, Harris FA, He KL, Heinsius FH, Held T, Heng YK, Himmelreich M, Holtmann T, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Huesken N, Hussain T, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Jiang HB, Jiang XS, Jiang XY, Jiao JB, Jiao Z, Jin S, Jin Y, 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, Kurth MG, Kühn W, Lane JJ, Lange JS, Larin P, Lavezzi L, Leithoff H, Lellmann M, Lenz T, Li C, Li CH, Li C, Li DM, Li F, Li G, Li HB, Li HJ, Li JL, Li JQ, Li K, Li LK, Li L, Li PL, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li ZB, Li ZY, Liang H, Liang H, Liang YF, Liang YT, Liao LZ, Libby J, Lin CX, Liu B, Liu BJ, Liu CX, Liu D, Liu DY, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu Q, Liu SB, Liu S, Liu T, Liu X, Liu YB, Liu ZA, Liu ZQ, Long YF, Lou XC, Lu FX, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo PW, Luo T, Luo XL, Lusso S, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XN, Ma XX, Ma XY, Ma YM, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min TJ, Mitchell RE, Mo XH, Mo YJ, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Pitka A, Poling R, Prasad V, Qi H, Qi HR, Qi M, Qi TY, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Shan DC, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song QQ, Song WM, Song YX, Sosio S, Spataro S, Sui FF, Sun GX, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YK, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Thoren V, Tsednee B, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang Y, Wang YD, Wang YF, Wang YQ, Wang Z, Wang ZY, Wang Z, Wang Z, Wei DH, Weidenkaff P, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu Z, Xia L, Xiao H, Xiao SY, Xiao YJ, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xiong XA, Xu GF, Xu JJ, Xu QJ, Xu W, Xu XP, Yan F, Yan L, Yan L, Yan WB, Yan WC, Yan X, Yang HJ, Yang HX, Yang L, Yang RX, Yang SL, Yang YH, 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 W, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Yuncu A, Zafar AA, Zeng Y, Zhang BX, Zhang G, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang L, Zhang L, Zhang S, Zhang SF, Zhang TJ, Zhang XY, Zhang Y, Zhang YH, Zhang YT, Zhang Y, Zhang Y, Zhang Y, Zhang ZH, 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 Y, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu WJ, Zhu XL, Zhu YC, Zhu ZA, Zou BS, Zou JH. First Observation of D^{+}→ημ^{+}ν_{μ} and Measurement of Its Decay Dynamics. PHYSICAL REVIEW LETTERS 2020; 124:231801. [PMID: 32603168 DOI: 10.1103/physrevlett.124.231801] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 05/22/2020] [Indexed: 06/11/2023]
Abstract
By analyzing a data sample corresponding to an integrated luminosity of 2.93 fb^{-1} collected at a center-of-mass energy of 3.773 GeV with the BESIII detector, we measure for the first time the absolute branching fraction of the D^{+}→ημ^{+}ν_{μ} decay to be B_{D^{+}→ημ^{+}ν_{μ}}=(10.4±1.0_{stat}±0.5_{syst})×10^{-4}. Using the world averaged value of B_{D^{+}→ηe^{+}ν_{e}}, the ratio of the two branching fractions is determined to be B_{D^{+}→ημ^{+}ν_{μ}}/B_{D^{+}→ηe^{+}ν_{e}}=0.91±0.13_{(stat+syst)}, which agrees with the theoretical expectation of lepton flavor universality within uncertainty. By studying the differential decay rates in five four-momentum transfer intervals, we obtain the product of the hadronic form factor f_{+}^{η}(0) and the c→d Cabibbo-Kobayashi-Maskawa matrix element |V_{cd}| to be f_{+}^{η}(0)|V_{cd}|=0.087±0.008_{stat}±0.002_{syst}. Taking the input of |V_{cd}| from the global fit in the standard model, we determine f_{+}^{η}(0)=0.39±0.04_{stat}±0.01_{syst}. On the other hand, using the value of f_{+}^{η}(0) calculated in theory, we find |V_{cd}|=0.242±0.022_{stat}±0.006_{syst}±0.033_{theory}.
Collapse
|
361
|
Liu C, Xu J, Niu J, Chen M, Zhou Y. Direct Z-scheme Ag3PO4/Bi4Ti3O12 heterojunction with enhanced photocatalytic performance for sulfamethoxazole degradation. Sep Purif Technol 2020. [DOI: 10.1016/j.seppur.2020.116622] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
|
362
|
Loh TY, Brito MP, Bose N, Xu J, Tenekedjiev K. Human Error in Autonomous Underwater Vehicle Deployment: A System Dynamics Approach. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2020; 40:1258-1278. [PMID: 32144834 DOI: 10.1111/risa.13467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 07/11/2019] [Accepted: 02/12/2020] [Indexed: 06/10/2023]
Abstract
The use of autonomous underwater vehicles (AUVs) for various applications have grown with maturing technology and improved accessibility. The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extremities in the Antarctic. A thorough analysis of risks is therefore crucial for formulating effective risk control policies and achieving a lower risk of loss. Existing risk analysis approaches focused predominantly on the technical aspects, as well as identifying static cause and effect relationships in the chain of events leading to AUV loss. Comparatively, the complex interrelationships between risk variables and other aspects of risk such as human errors have received much lesser attention. In this article, a systems-based risk analysis framework facilitated by system dynamics methodology is proposed to overcome existing shortfalls. To demonstrate usefulness of the framework, it is applied on an actual AUV program to examine the occurrence of human error during Antarctic deployment. Simulation of the resultant risk model showed an overall decline in human error incident rate with the increase in experience of the AUV team. Scenario analysis based on the example provided policy recommendations in areas of training, practice runs, recruitment policy, and setting of risk tolerance level. The proposed risk analysis framework is pragmatically useful for risk analysis of future AUV programs to ensure the sustainability of operations, facilitating both better control and monitoring of risk.
Collapse
|
363
|
Huang L, Zhang X, Zhang X, Wei Z, Zhang L, Xu J, Liang P, Xu Y, Zhang C, Xu A. Rapid asymptomatic transmission of COVID-19 during the incubation period demonstrating strong infectivity in a cluster of youngsters aged 16-23 years outside Wuhan and characteristics of young patients with COVID-19: A prospective contact-tracing study. J Infect 2020; 80:e1-e13. [PMID: 32283156 PMCID: PMC7194554 DOI: 10.1016/j.jinf.2020.03.006] [Citation(s) in RCA: 226] [Impact Index Per Article: 56.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 03/03/2020] [Indexed: 01/19/2023]
Abstract
BACKGROUND The outbreak of coronavirus-disease-2019 (COVID-19) has rapidly spread to many places outside Wuhan. Previous studies on COVID-19 mostly included older hospitalized-adults. Little information on infectivity among and characteristics of youngsters with COVID-19 is available. METHODS A cluster of 22 close-contacts of a 22-year-old male (Patient-Index) including youngsters with laboratory-confirmed COVID-19 and hospitalized close-contacts testing negative for severe-acute-respiratory-syndrome-coronavirus-2 (SARS-CoV-2) in Anhui Province, China was prospectively-traced. RESULTS Since January 23, 2020, we enrolled a cluster of eight youngsters with COVID-19 (median age [range], 22 [16-23] years; six males) originating from Patient-Index returning from Wuhan to Hefei on January 19. Patient-Index visited his 16-year-old female cousin in the evening on his return, and met 15 previous classmates in a get-together on January 21. He reported being totally asymptomatic and were described by all his contacts as healthy on January 19-21. His very first symptoms were itchy eyes and fever developed at noon and in the afternoon on January 22, respectively. Seven youngsters (his cousin and six classmates) became infected with COVID-19 after a-few-hour-contact with Patient-Index. None of the patients and contacts had visited Wuhan (except Patient-Index), or had any exposure to wet-markets, wild-animals, or medical-institutes within three months. For affected youngsters, the median incubation-period was 2 days (range, 1-4). The median serial-interval was 1 day (range, 0-4). Half or more of the eight COVID-19-infected youngsters had fever, cough, sputum production, nasal congestion, and fatigue on admission. All patients had mild conditions. Six patients developed pneumonia (all mild; one bilateral) on admission. As of February 20, four patients were discharged. CONCLUSIONS SARS-CoV-2-infection presented strong infectivity during the incubation-period with rapid transmission in this cluster of youngsters outside Wuhan. COVID-19 developed in these youngsters had fast onset and various nonspecific atypical manifestations, and were much milder than in older patients as previously reported.
Collapse
|
364
|
Zhang F, Sun Y, Wang Z, Fu D, Li J, Hu J, Xu J, Wu X. Highly Conductive Polymeric Ionic Liquid Electrolytes for Ambient-Temperature Solid-State Lithium Batteries. ACS APPLIED MATERIALS & INTERFACES 2020; 12:23774-23780. [PMID: 32352744 DOI: 10.1021/acsami.9b22945] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
High-energy density solid-state lithium metal batteries are expected to become the next generation of energy storage devices. Polymeric ionic liquid-based solid polymer electrolytes (PIL-based SPEs) are an attractive choice among electrolytes, but their ionic conductivities are generally insufficient due to numerous crystallized polymer regions. To achieve higher conductivity, we use facile copolymerization of an ionic liquid (IL) monomer and poly(ethylene glycol) diacrylate monomer to obtain in situ plasticized polymer chains. The resultant PIL-based SPE exhibits decreased crystallinity, a lower glass-transition temperature, and improved ionic conductivity (1.4 × 10-4 S cm-1 at 30 °C). A solid-state LiFePO4 (LFP)|Li battery based on the SPE displays a high reversible specific capacity of 140 mA h g-1 at 0.2C at 25 °C and excellent cycling stability, accompanying high Coulombic efficiency of approximately 100%. The in situ plasticized PIL-based SPE is significant in developing solid-state Li metal battery systems.
Collapse
|
365
|
Zhu H, Lan L, Zhang Y, Chen Q, Zeng Y, Luo X, Ren J, Chen S, Xiao M, Lin K, Chen M, Li Q, Chen Y, Xu J, Zheng Z, Chen Z, Xie Y, Hu J, Yang T. Epidermal growth factor stimulates exosomal microRNA-21 derived from mesenchymal stem cells to ameliorate aGVHD by modulating regulatory T cells. FASEB J 2020; 34:7372-7386. [PMID: 32314840 DOI: 10.1096/fj.201900847rrrr] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 02/15/2020] [Accepted: 03/14/2020] [Indexed: 12/15/2022]
Abstract
Regulatory T cells (Tregs), a subset of CD4+ T cells, may exert inhibitory effects on alloimmune responses including acute graft-versus-host disease (aGVHD), and several microRNAs are implicated in the pathophysiological process of GVHD. Therefore, we aimed in the present study to characterize the functional relevance of epidermal growth factor (EGF)-stimulated microRNA-21 (miR-21) in regulating bone marrow-derived mesenchymal stem cells (BMSCs) in a mouse model of aGVHD. We first isolated and cultured BMSCs and Tregs. Then, we examined effects of miR-21 knockdown or overexpression and EGF on cell activities of BMSCs and the expression of PTEN, Foxp3, AKT phosphorylation, and extent of c-jun phosphorylation by gain- and loss-of-function approaches. The results showed that miR-21 promoted the proliferation, invasion, and migration of BMSCs. Furthermore, miR-21 in BMSCs-derived exosomes inhibited PTEN, but enhanced AKT phosphorylation and Foxp3 expression in Tregs. In addition, EGF enhanced c-jun phosphorylation to elevate the miR-21 expression. Furthermore, EGF significantly increased the efficacy of BMSCs in a mouse model of aGVHD, manifesting in reduced IFN-γ expression and lesser organ damage. Moreover, EGF treatment promoted the Foxp3 expression of Tregs in BMSCs-treated aGVHD mice. Taken together, EGF induced the BMSCs-derived exosomal miR-21 expression, which enhanced Foxp3 expression in Tregs, thereby improving the therapeutic effect of BMSCs on aGVHD.
Collapse
|
366
|
Liu R, Song L, Jiang L, Tang X, Xu L, Gao Z, Zhao X, Xu J, Gao R, Yuan J. Susceptible gene polymorphism in patients with three-vessel coronary artery disease. BMC Cardiovasc Disord 2020; 20:172. [PMID: 32293292 PMCID: PMC7161109 DOI: 10.1186/s12872-020-01449-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 03/26/2020] [Indexed: 01/24/2023] Open
Abstract
Background Data of susceptible gene polymorphisms related to progression of coronary atherosclerosis in patients with three-vessel disease (TVD) is limited in China. This case-control study aimed to analyze the differences of variant carrier frequencies between cases and controls, and to explain the possible genetic effects on the progression of TVD. Methods A total of 8943 TVD patients were consecutively enrolled. Major adverse cardiac and cerebrovascular events (MACCE) included all-cause death, acute myocardial infarction, repeat revascularization, readmission and stroke. Patients with 1-year MACCE in this cohort were selected as MACCE group. Blood samples from MACCE group and non-CAD control groups were collected, and a deoxyribonucleic acid library was created. A total of 34 tag or hot single nucleotide polymorphisms (SNPs) in six genes including CDKN2B-AS1, ADAMTS7, ABO, ADAMTS13, IL-18, and PECAM1 were analyzed by a SNPscan™ multi-genotyping kit. Carrier frequencies of each SNP were compared between the two groups using dominant, recessive and codominant allele model, respectively. Multivariate logistic regression model was established. Results Variant allele frequencies of rs10757274, rs1333042, rs1333049, rs4977574, rs9632884, rs1063192 and rs3217986 on CDKN2B-AS1 gene showed significant differences between the two groups in at least one allele model. Variant allele frequency of rs3217986 was not statistically significant after adjusting for the false discovery rate using Benjamini-Hochberg procedure (Q > 0.05). Variant allele frequencies of rs1333049, rs10757274, rs4977574 on CDKN2B-AS1 gene were significantly higher in MACCE group in all dominant, recessive and codominant models. Rs1055432 on ADAMTS13 and rs8176694 on ABO gene showed threshold significance between the two groups. After multivariable adjustment, G mutant homozygous rs9632884 (GG vs. GC + CC) (OR: 0.24; 95% CI: 0.09–0.65; P = 0.005) on CDKN2B-AS1 gene were independent protective factor of MACCE in recessive model. Conclusions In patients with TVD in China, variant alleles on CDKN2B-AS1 gene may form part of the genetic basis of coronary atherosclerosis progression, promoting or suppressing ischemic events.
Collapse
|
367
|
Xu J, Wang Y, Ding M, Song G, Wu M, Kang Z, Wang J. Sequence-structure characterization of recombinant polypeptides derived from silk fibroin heavy chain. MATERIALS SCIENCE & ENGINEERING. C, MATERIALS FOR BIOLOGICAL APPLICATIONS 2020; 111:110831. [PMID: 32279784 DOI: 10.1016/j.msec.2020.110831] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 01/09/2020] [Accepted: 03/09/2020] [Indexed: 10/24/2022]
Abstract
The molecular conformation of a biomedical material plays a major role in the stability, bioactivity and controlled release of drugs. In order to identify the impact of fragments derived from Bombyx mori silk fibroin on their structures and to develop a new strategy for controlling drug release, we designed several hydrophobic-hydrophilic recombinants (GS16F1, GS16F4, and GS16F8), and investigated their molecular conformations and conformational changes induced by different storage temperatures and pH values. The results showed that the α-helix characteristic peaks were prominent in the fresh freeze-dried powder with increasing F1 repeats. During storage at 4 °C, 37 °C or 60 °C, the β-turns (especially in GS16F8) and α-helixes turned into β-sheets. The β-sheet content in the polypeptides increased with increasing temperature and F1 repeats. Following induction by different pH values, their molecular conformations changed significantly, but not the same as that of powder storage. The content of β-sheets was GS16F1 > GS16F4 > GS16F8 near the isoelectric point of each polypeptide. With increasing pH value, the β-sheet content of GS16F1 decreased more slowly compared with GS16F4 and GS16F8. These results were satisfactory for structural regulation in the field of drug controlled release research.
Collapse
|
368
|
Wang H, Song Y, Tang X, Xu J, Jiang P, Jiang L, Gao Z, Chen J, Song L, Zhang Y, Zhao X, Qiao S, Yang Y, Gao R, Xu B, Yuan J, Gao L. Impact of unknown diabetes and prediabetes on clinical outcomes in "nondiabetic" Chinese patients after a primary coronary intervention. Nutr Metab Cardiovasc Dis 2020; 30:644-651. [PMID: 32143897 DOI: 10.1016/j.numecd.2019.11.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 11/22/2019] [Accepted: 11/22/2019] [Indexed: 11/18/2022]
Abstract
BACKGROUND AND AIM To explore the prevalence of unknown diabetes (DM) or prediabetes (pre-DM) in "nondiabetic" patients and its association with 2-year clinical outcomes after primary percutaneous coronary intervention (PCI). METHODS AND RESULTS 5202 consecutive "nondiabetic" patients who underwent primary PCI at Fuwai Hospital from January to December 2013 were prospectively enrolled. The patients were grouped according to their glycemia status: unknown DM (HbA1c ≥ 47 mmol/L; FPG≥ 7.0 mmol/L), pre-DM (HbA1c 39-47 mmol/L; FPG: 5.6-6.9 mmol/L) and normoglycemia (NG, HbA1c < 39 mmol/L; FPG < 5.6 mmol/L). The main endpoint was 2-year major adverse cardiovascular events (MACE), including cardiac death, myocardial infarction, and target vessel revascularization. A total of 905 patients had unknown DM, and 3407 patients had pre-DM. Unknown DM and pre-DM were associated with aging (p < 0.001); a greater proportion of hypertension (p < 0.001), previous myocardial infarction (p < 0.001), and chronic kidney disease (p = 0.004). During the 2-year follow-up, the rate of MACE was significantly higher in the unknown DM and pre-DM groups than in the NG group (8.1% vs. 5.8% vs. 4.1%, respectively, p = 0.001). Multivariate analyses demonstrated that unknown DM was associated with a 1.9-fold higher event risk compared to NG (95% CI: 1.2-2.8). CONCLUSIONS The prevalence of abnormal glucose metabolism was high in "nondiabetic" Chinese PCI patients. Patients with unknown DM and pre-DM had higher event risks than those with NG. In "nondiabetes" patients requiring PCI, routine assessment of HbA1c and FPG appears to be of value to identify patients with an increased event risk.
Collapse
|
369
|
Loh TY, Brito MP, Bose N, Xu J, Tenekedjiev K. Fuzzy System Dynamics Risk Analysis (FuSDRA) of Autonomous Underwater Vehicle Operations in the Antarctic. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2020; 40:818-841. [PMID: 31799748 DOI: 10.1111/risa.13429] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2018] [Revised: 07/29/2019] [Accepted: 11/11/2019] [Indexed: 06/10/2023]
Abstract
With the maturing of autonomous technology and better accessibility, there has been a growing interest in the use of autonomous underwater vehicles (AUVs). The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extreme operating environment. To control the risk of loss, existing risk analyses approaches tend to focus more on the AUV's technical aspects and neglect the role of soft factors, such as organizational and human influences. In addition, the dynamic and complex interrelationships of risk variables are also often overlooked due to uncertainties and challenges in quantification. To overcome these shortfalls, a hybrid fuzzy system dynamics risk analysis (FuSDRA) is proposed. In the FuSDRA framework, system dynamics models the interrelationships between risk variables from different dimensions and considers the time-dependent nature of risk while fuzzy logic accounts for uncertainties. To demonstrate its application, an example based on an actual Antarctic AUV program is presented. Focusing on funding and experience of the AUV team, simulation of the FuSDRA risk model shows a declining risk of loss from 0.293 in the early years of the Antarctic AUV program, reaching a minimum of 0.206 before increasing again in later years. Risk control policy recommendations were then derived from the analysis. The example demonstrated how FuSDRA can be applied to inform funding and risk management strategies, or broader application both within the AUV domain and on other complex technological systems.
Collapse
|
370
|
Li J, Milne RI, Ru D, Miao J, Tao W, Zhang L, Xu J, Liu J, Mao K. Allopatric divergence and hybridization withinCupressus chengiana(Cupressaceae), a threatened conifer in the northern Hengduan Mountains of western China. Mol Ecol 2020; 29:1250-1266. [DOI: 10.1111/mec.15407] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 02/21/2020] [Accepted: 02/26/2020] [Indexed: 12/25/2022]
|
371
|
Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Amoroso A, An Q, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Begzsuren K, Bennett JV, Berger N, Bertani M, Bettoni D, Bianchi F, Biernat J, Bloms J, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Cheng W, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai JP, Dai XC, Dbeyssi A, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Du SX, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Fritsch M, Fu CD, Fu Y, Gao XL, Gao Y, Gao Y, Gao YG, Garzia I, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu S, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guo YP, Guskov A, Han S, Han TT, Han TZ, Hao XQ, Harris FA, He KL, Heinsius FH, Held T, Heng YK, Himmelreich M, Holtmann T, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huesken N, Hussain T, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Jiang HB, Jiang XS, Jiang XY, Jiao JB, Jiao Z, Jin DP, Jin S, Jin Y, 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, Kurth MG, Kühn W, Lane JJ, Lange JS, Larin P, Lavezzi L, Leithoff H, Lellmann M, Lenz T, Li C, Li CH, Li C, Li DM, Li F, Li G, Li HB, Li HJ, Li JC, Li JL, Li K, Li LK, Li L, Li PL, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li XN, Li ZB, Li ZY, Liang H, Liang H, Liang YF, Liang YT, Liao LZ, Libby J, Lin CX, Lin DX, Liu B, Liu BJ, Liu CX, Liu D, Liu DY, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LY, Liu Q, Liu SB, Liu S, Liu T, Liu X, Liu XY, Liu YB, Liu ZA, Liu ZQ, Long YF, Lou XC, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo PW, Luo T, Luo XL, Lusso S, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XN, Ma XX, Ma XY, Ma YM, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min J, Min TJ, Mitchell RE, Mo XH, Mo YJ, Morales Morales C, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Papenbrock M, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Pitka A, Poling R, Prasad V, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Richter M, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sarantsev A, Savrié M, Schelhaas Y, Schnier C, Schoenning K, Shan DC, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Sheng HY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song QQ, Song XY, Song YX, Sosio S, Sowa C, Spataro S, Sui FF, Sun GX, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YK, Sun YZ, Sun ZJ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang X, Thoren V, Tsednee B, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang HP, Wang K, Wang LL, Wang LS, Wang M, Wang MZ, Wang M, Wang PL, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang Y, Wang YD, Wang YF, Wang YQ, Wang Z, Wang ZG, Wang ZY, Wang Z, Wang Z, Weber T, Wei DH, Weidenkaff P, Weidner F, Wen HW, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu Z, Xia L, Xiao H, Xiao SY, Xiao YJ, Xiao ZJ, Xie YG, Xie YH, Xing TY, Xiong XA, Xu GF, Xu JJ, Xu QJ, Xu W, Xu XP, Yan L, Yan L, Yan WB, Yan WC, Yan X, Yang HJ, Yang HX, Yang L, Yang RX, Yang SL, Yang YH, 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 W, Yuan XQ, Yuan Y, Yue CX, Yuncu A, Zafar AA, Zeng Y, Zhang BX, Zhang BY, Zhang CC, Zhang DH, Zhang G, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang L, Zhang L, Zhang S, Zhang SF, Zhang TJ, Zhang XY, Zhang Y, Zhang YH, Zhang YT, Zhang Y, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhao G, Zhao J, Zhao JW, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao TC, Zhao YB, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng Y, Zheng YH, Zhong B, Zhong C, Zhou L, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu WJ, Zhu XL, Zhu YC, Zhu YS, Zhu ZA, Zhuang J, Zou BS, Zou JH. Observation of a Resonant Structure in e^{+}e^{-}→K^{+}K^{-}π^{0}π^{0}. PHYSICAL REVIEW LETTERS 2020; 124:112001. [PMID: 32242687 DOI: 10.1103/physrevlett.124.112001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 02/28/2020] [Indexed: 06/11/2023]
Abstract
A partial-wave analysis is performed for the process e^{+}e^{-}→K^{+}K^{-}π^{0}π^{0} at the center-of-mass energies ranging from 2.000 to 2.644 GeV. The data samples of e^{+}e^{-} collisions, collected by the BESIII detector at the BEPCII collider with a total integrated luminosity of 300 pb^{-1}, are analyzed. The total Born cross sections for the process e^{+}e^{-}→K^{+}K^{-}π^{0}π^{0}, as well as the Born cross sections for the subprocesses e^{+}e^{-}→ϕπ^{0}π^{0}, K^{+}(1460)K^{-}, K_{1}^{+}(1400)K^{-}, K_{1}^{+}(1270)K^{-}, and K^{*+}(892)K^{*-}(892), are measured versus the center-of-mass energy. The corresponding results for e^{+}e^{-}→K^{+}K^{-}π^{0}π^{0} and ϕπ^{0}π^{0} are consistent with those of BABAR with better precision. By analyzing the cross sections for the four subprocesses, K^{+}(1460)K^{-}, K_{1}^{+}(1400)K^{-}, K_{1}^{+}(1270)K^{-}, and K^{*+}(892)K^{*-}(892), a structure with mass M=(2126.5±16.8±12.4) MeV/c^{2} and width Γ=(106.9±32.1±28.1) MeV is observed with an overall statistical significance of 6.3σ, although with very limited significance in the subprocesses e^{+}e^{-}→K_{1}^{+}(1270)K^{-} and K^{*+}(892)K^{*-}(892). The resonant parameters of the observed structure suggest it can be identified with the ϕ(2170), thus the results provide valuable input to the internal nature of the ϕ(2170).
Collapse
|
372
|
Liu Y, Xu J, Tao Y, Fang T, Du W, Ye A. Rapid and accurate identification of marine microbes with single-cell Raman spectroscopy. Analyst 2020; 145:3297-3305. [PMID: 32191782 DOI: 10.1039/c9an02069a] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Rapid and accurate identification of individual microorganisms, such as pathogenic or unculturable microbes, is significant in microbiology. In this work, rapid identification of marine microorganisms by single-cell Raman spectroscopy (scRS) using one-dimensional convolutional neural networks (1DCNN) was explored. Here, single-cell Raman spectra of ten species of marine actinomycetes, two species of non-marine actinomycetes and E. coli (as a reference) were individually collected. Several common classification algorithms in chemometrics, including linear discriminant analysis with principal component analysis and a support vector machine, were applied to evaluate the 1DCNN performance based on the raw and pre-processed Raman spectra. 1DCNN showed superior performance on the raw data in terms of its accuracy and recall rate compared with other classification algorithms. Our investigation demonstrated that the scRS-integrating advanced 1DCNN classification algorithm provided a rapid and accurate approach for identifying individual microorganisms without time-consuming cell culture and sophisticated or specific techniques, which could be a useful methodology for discriminating the microbes that cannot be cultured under normal conditions, especially for 'biological risk'-related emergencies.
Collapse
|
373
|
Jiang P, Song Y, Xu JJ, Ma YL, Tang XF, Yao Y, Wang HH, Yang YJ, Gao RL, Qiao SB, Xu B, Yuan JQ, Zhang Y. [Long-term prognostic value of mean platelet volume in patients with stable coronary artery disease undergoing elective percutaneous coronary intervention]. ZHONGHUA YI XUE ZA ZHI 2020; 100:679-684. [PMID: 32187911 DOI: 10.3760/cma.j.issn.0376-2491.2020.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To evaluate the relationship between admission mean platelet volume (MPV) and 2-year cardiac mortality in patients with stable coronary artery disease (CAD) undergoing elective percutaneous coronary intervention (PCI), and explored the consistence of this relationship in diabetes mellitus (DM) and non-DM subgroups. Method: A total of 4 293 patients who underwent PCI in Fuwai Hospital in 2013 were enrolled and divided into two groups according to MPV as follows: lower MPV (n=2 219, MPV≤10.5fL) and higher MPV (n=2 074, MPV>10.5fL). Result: Patients with high MPV had a higher rate of DM (30.4%(674/2 219) vs 34.5%(715/2 074)), smoking (53.3%(1 183/2219) vs 57.0%(1 182/2 074)), and previous coronary artery bypass grafting (CABG) (4.0%(88/2 219) vs 5.4%(112/2 074)), while left ventricular ejection fraction (LVEF) (64±7 vs 63±7), and glomerular filtration rate (eGFR) (92±14 vs 91±15) were lower compared with patients in the low MPV group (all P<0.05). In the laboratory examination, patients with high MPV had higher glycosylated hemoglobin, and lower platelet count (all P<0.05). In coronary angiography, there was no significant difference in SYNTAX scores, left main/three-vessel lesions, stent type, success rate of operation, and total stent length (all P>0.05). Compared with low MPV group, patients with high MPV had ahigher cardiac mortality [18 (0.9%) vs 5 (0.2%), P=0.004]. Kaplan-Meier analysis showed that compared to low MPV group, cardiac mortality in high MPV group was significantly higher (Log-rank P=0.004). Multivariate Cox regression analysis showed that high MPV was independently associated with 2-year cardiac mortality (HR 4.127, 95%CI 1.373 to 12.405, P=0.012). Receiver operating characteristic curve (ROC) analysis also showed that MPV had a good diagnostic value in predicting 2-year cardiac mortality (area under the curve=0.624, 95%CI: 0.511-0.738, P=0.04). Subgroup analysis showed that in patients with DM (HR 2.090, 95%CI 1.217-3.589, P=0.008) and male (HR 1.561, 95%CI 1.007-2.421, P=0.047), MPV was significantly related with cardiac mortality. Conclusion: In patients with stable CAD who underwent elective PCI, high MPV was independently associated with an increase in 2-year cardiac mortality, especially in patients with DM and male gender.
Collapse
|
374
|
Yang L, Xu J, Wang J, Lang F, Liu B, Yang Z. Responsive Single-Chain/Colloid Composite Janus Nanoparticle. Macromolecules 2020. [DOI: 10.1021/acs.macromol.0c00109] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
|
375
|
Zhao X, Tang X, Xu J, Song L, Yuan J. EFFECT OF NPC1L1 AND HMGCR GENETIC VARIANTS WITH PREMATURE TRIPLE-VESSEL CORONARY DISEASE. J Am Coll Cardiol 2020. [DOI: 10.1016/s0735-1097(20)30688-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
|