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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Alekseev M, 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 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 Q, Gao Y, Gao Y, Gao YG, 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, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han S, Han TZ, 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 LQ, Huang XT, 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 CH, Li C, Li DM, Li F, Li G, Li HB, Li HJ, Li JC, Li K, Li LK, Li L, Li PL, Li PR, 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 T, Liu X, Liu XY, Liu YB, Liu ZA, Liu Z, 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 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, 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, 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, Schoenning K, 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, Sosio S, Sowa C, Spataro S, Sui FF, Sun GX, Sun JF, Sun L, Sun SS, Sun T, Sun WY, 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 HP, Wang K, Wang LL, Wang LS, Wang M, Wang MZ, Wang M, Wang PL, Wang WP, Wang X, Wang XF, Wang XL, Wang YD, Wang Y, Wang Y, Wang YF, Wang YQ, Wang Z, Wang ZG, Wang ZY, Wang ZY, Wang Z, Weber T, Wei DH, Weidenkaff P, Weidner F, Wen HW, Wen SP, Wiedner U, Wilkinson G, Wolke M, Wu JF, 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, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan XQ, Yuan Y, Yue CX, 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 JW, Zhang JY, 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 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, 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. Measurement of Proton Electromagnetic Form Factors in e^{+}e^{-}→pp[over ¯] in the Energy Region 2.00-3.08 GeV. PHYSICAL REVIEW LETTERS 2020; 124:042001. [PMID: 32058790 DOI: 10.1103/physrevlett.124.042001] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 09/19/2019] [Indexed: 06/10/2023]
Abstract
The process of e^{+}e^{-}→pp[over ¯] is studied at 22 center-of-mass energy points (sqrt[s]) from 2.00 to 3.08 GeV, exploiting 688.5 pb^{-1} of data collected with the BESIII detector operating at the BEPCII collider. The Born cross section (σ_{pp[over ¯]}) of e^{+}e^{-}→pp[over ¯] is measured with the energy-scan technique and it is found to be consistent with previously published data, but with much improved accuracy. In addition, the electromagnetic form-factor ratio (|G_{E}/G_{M}|) and the value of the effective (|G_{eff}|), electric (|G_{E}|), and magnetic (|G_{M}|) form factors are measured by studying the helicity angle of the proton at 16 center-of-mass energy points. |G_{E}/G_{M}| and |G_{M}| are determined with high accuracy, providing uncertainties comparable to data in the spacelike region, and |G_{E}| is measured for the first time. We reach unprecedented accuracy, and precision results in the timelike region provide information to improve our understanding of the proton inner structure and to test theoretical models which depend on nonperturbative quantum chromodynamics.
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Xing F, Li S, Zhang JJ, Sun CY, Huang JR, Gao ZL, Zhu TT, Zhao Q, Zhang H, Liu CH. [Observation of the therapeutic and characteristic effects of terlipressin on refractory cirrhotic ascites]. ZHONGHUA GAN ZANG BING ZA ZHI = ZHONGHUA GANZANGBING ZAZHI = CHINESE JOURNAL OF HEPATOLOGY 2020; 27:982-988. [PMID: 31941260 DOI: 10.3760/cma.j.issn.1007-3418.2019.12.010] [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 observe the therapeutic effect of terlipressin on refractory ascites (RA) in cirrhosis, and its role and impact on acute kidney injury (AKI). Methods: A non-randomized controlled clinical trial data of 111 hospitalized cases of liver cirrhosis accompanied with RA was collected from Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Zhongshan Hospital of Hubei Province, The First Affiliated Hospital of Zhengzhou University, The First Affiliated Hospital of Medical School of Zhejiang University, and People's Hospital of Pudong New Area of Shanghai between March 2015 and March 2017. 26 cases of conventional treatment group (control group) were divided into two subgroups: RA without AKI (RA-NAKI) and RA with AKI (RA-AKI), and each subgroup consisted 13 cases. Patients with bacterial infection were treated with diuretics, albumin supplementation and antibiotics. 85 cases were presented in terlipressin combined treatment group, of which 27 cases were of RA-NAKI and 58 cases were of RA-AKI. Control group was injected terlipressin 1mg of intravenous drip or static push (once q6 h ~ 12 h) for more than 5 days. The treatment duration lasted for 2 weeks with 4 weeks of follow-up. Body weight, 24-hour urine volume, abdominal circumference, mean arterial pressure (MAP), liver and kidney function, anterior hepatic ascites, deepest point of ascites, and ultrasonographic detection of ascites in supine position before treatment, one and two weeks after treatment and 4 weeks after follow-up were compared. Count data were tested by χ (2). Samples of four groups at baseline were compared. One-way analysis of variance was used for normal distribution data and Kruskal-Wallis H test for non-normal distribution data. Repeated measures analysis of variance was used to compare the difference in efficacy between different time points before and after treatment in the group. The LSD method of one-way ANOVA was used to compare the two groups. A t-test of independent samples was used to compare the efficacy of different time series between the two groups. Mann-Whitney rank- sum test was used to compare the data of non-normal distribution between the two groups. Results: (1) Baseline data were compared among 4 subgroups of terlipressin RA-NAKI and control RA-AKI. Control group age was higher than that of terlipressin group, and the serum creatinine (SCr) of the RA-AKI group was higher than RA-NAKI group, and there was no significant difference in the rest of the baseline data and the combined medication (P > 0.05). (2) An intra-group comparison between control and trelipressin before and after treatment showed that all patients had lower body mass, abdominal circumference and deepest ascites, and higher serum albumin (P < 0.05). 24-hour urine volume and MAP was significantly increased in the terlipressin group, while the pre-ascites, SCr and child Turcotte Pugh (CTP) scores were decreased. Body weight, abdominal circumference, pre-ascites, and deepest ascites of the terlipressin group were decreased, while MAP was increased during the treatment and follow-up periods. The differences were statistically significant when compared with the control group at the same time (P < 0.05). There was a statistically significant difference in the increase of 24-h urine volume in the terlipressin group compared with the control group (P < 0.05). The decrease in SCr and CTP in the terlipressin group after 2 weeks of treatment and 4 weeks of follow-up was statistically significant compared with the control group (P < 0.05). (3) Among the two subgroups of RA-AKI and RA-NAKI in the terlipressin group, the baseline SCr value of the former was higher than that of the latter. After treatment, the body weight, abdominal circumference, pre-ascites, deepest ascites and CTP scores were decreased. In the RA-AKI group, 24-hour urine volume, MAP, SCr and serum albumin concentration were significantly increased. The difference between the two subgroups before and after treatment was compared, and the body weight of RA-AKI group at 1, 2 weeks of treatment and 4 weeks of follow-up was significantly lower than RA-NAKI group, which were (- 2.3 ± 0.2 vs. - 1.5 ± 0.2) kg, (- 4.1 ± 0.2 vs. - 2.6 ± 0.2) kg, (- 4.2 ± 0.3 vs. - 2.4 ± 0.3) kg, respectively. RA-NAKI group urine volume was significantly increased at 2 weeks of treatment and 4 weeks of follow-up, which was (468 ± 42 vs. 110 ± 131) ml, (272 ± 34 ml vs. 11 ± 112) ml, respectively. SCr reduction (18.3 ± 4.7 vs. 0.9 ± 2.4) µmol/l at 4 weeks of follow-up was apparent in RA-NAKI group, and the difference was statistically significant (P < 0.05). Conclusion: Addition of terlipressin to conventional treatment may significantly increase MAP, 24-h urine volume, improve renal function and promote ascites resolution in patients with refractory cirrhotic ascites. Moreover, its combination effect is more obvious in AKI patients, and adverse reactions are mild.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Alekseev M, Amoroso A, An FF, 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, 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 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, Andersson WI, 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 CM, 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, Weidner F, 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 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. Measurement of the Cross Section for e^{+}e^{-}→Ξ^{-}Ξ[over ¯]^{+} and Observation of an Excited Ξ Baryon. PHYSICAL REVIEW LETTERS 2020; 124:032002. [PMID: 32031834 DOI: 10.1103/physrevlett.124.032002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 12/05/2019] [Indexed: 06/10/2023]
Abstract
Using a total of 11.0 fb^{-1} of e^{+}e^{-} collision data with center-of-mass energies between 4.009 and 4.6 GeV and collected with the BESIII detector at BEPCII, we measure fifteen exclusive cross sections and effective form factors for the process e^{+}e^{-}→Ξ^{-}Ξ[over ¯]^{+} by means of a single baryon-tag method. After performing a fit to the dressed cross section of e^{+}e^{-}→Ξ^{-}Ξ[over ¯]^{+}, no significant ψ(4230) or ψ(4260) resonance is observed in the Ξ^{-}Ξ[over ¯]^{+} final states, and upper limits at the 90% confidence level on Γ_{ee}B for the processes ψ(4230)/ψ(4260)→Ξ^{-}Ξ[over ¯]^{+} are determined. In addition, an excited Ξ baryon at 1820 MeV/c^{2} is observed with a statistical significance of 6.2-6.5σ by including the systematic uncertainty, and the mass and width are measured to be M=(1825.5±4.7±4.7) MeV/c^{2} and Γ=(17.0±15.0±7.9) MeV, which confirms the existence of the J^{P}=3/2^{-} state Ξ(1820).
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Zhao Q, Zhang R, Xiao Y, Niu Y, Shao F, Li Y, Peng Z. Comparative Transcriptome Profiling of the Loaches Triplophysa bleekeri and Triplophysa rosa Reveals Potential Mechanisms of Eye Degeneration. Front Genet 2020; 10:1334. [PMID: 32010191 PMCID: PMC6977438 DOI: 10.3389/fgene.2019.01334] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2019] [Accepted: 12/06/2019] [Indexed: 12/30/2022] Open
Abstract
Eye degeneration is one of the most obvious characteristics of organisms restricted to subterranean habitats. In cavefish, eye degeneration has evolved independently numerous times and each process is associated with different genetic mechanisms. To gain a better understanding of these mechanisms, we compared the eyes of adult individuals of the cave loach Triplophysa rosa and surface loach Triplophysa bleekeri. Compared with the normal eyes of the surface loach, those of the cave loach were found to possess a small abnormal lens and a defective retina containing photoreceptor cells that lack outer segments. Sequencing of the transcriptomes of both species to identify differentially expressed genes (DEGs) and genes under positive selection revealed 4,802 DEGs and 50 genes under positive selection (dN/dS > 1, FDR < 0.1). For cave loaches, we identified one Gene Ontology category related to vision that was significantly enriched in downregulated genes. Specifically, we found that many of the downregulated genes, including pitx3, lim2, crx, gnat2, rx1, rho, prph2, and β|γ-crystallin are associated with lens/retinal development and maintenance. However, compared with those in the surface loach, the lower dS rates but higher dN rates of the protein-coding sequences in T. rosa indicate that changes in amino acid sequences might be involved in the adaptation and visual degeneration of cave loaches. We also found that genes associated with light perception and light-stimulated vision have evolved at higher rates (some genes dN/dS > 1 but FDR > 0.1). Collectively, the findings of this study indicate that the degradation of cavefish vision is probably associated with both gene expression and amino acid changes and provide new insights into the mechanisms underlying the degeneration of cavefish eyes.
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Wang Z, Li Y, Fan L, Zhao Q, Tan B, Liu R, Li F. Silencing of TPD52 inhibits proliferation, migration, invasion but induces apoptosis of pancreatic cancer cells by deactivating Akt pathway. Neoplasma 2019; 67:277-285. [PMID: 31847526 DOI: 10.4149/neo_2019_190404n295] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Accepted: 07/02/2019] [Indexed: 11/08/2022]
Abstract
Pancreatic cancer (PC) is a complex and multifactorial human malignancy with a low survival rate. Tumor protein D52 (TPD52) was abnormally expressed in several cancers and participated in tumorigenesis. However, the oncogenic effect of TPD52 on PC remains unknown. In the present study, after transfecting AsPC-1 and PANC-1 cells with NC or sh-TPD52, the CCK-8 assay, Hoechst staining, western blot, transwell assay, flow cytometry were used to examine the cell proliferation, migration, invasion and apoptosis. qRT-PCR results confirmed that the expression of TPD52 was significantly increased in PC cells, especially AsPC-1 and PANC-1 cells. The present study revealed that silencing of TPD52 significantly suppressed the proliferation, migration and invasion, but induced apoptosis of AsPC-1 and PANC-1 cells in vitro by dephosphorylating Akt at Ser473. Conversely, SC79, an Akt activator, could partially reverse the anti-metastatic effects of sh-TPD52, accompanied by the reactivating of Akt pathway. Additional in vivo studies are warranted to elucidate that knockdown of TPD52 could inhibit tumor growth in PC mice models. These findings suggested that TPD52 might be a novel therapeutic target for PC treatment.
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Zhao Q, Zhou J, Xia Q, Zhang S, Zhang H. Non-Destructive Testing of Steel Corrosion Fluctuation Parameters Based on Spontaneous Magnetic Flux Leakage and Its Relationship with Steel Bar Diameter. MATERIALS 2019; 12:ma12244116. [PMID: 31835300 PMCID: PMC6947034 DOI: 10.3390/ma12244116] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 12/02/2019] [Accepted: 12/05/2019] [Indexed: 11/16/2022]
Abstract
In an actual structure, the arrangement of steel bars is complicated, there are many factors affecting the corrosion of steel bars, and these factors affect each other. However, accurately reflecting the corrosion of steel bars in actual engineering through theoretical calculations is difficult. Besides, it is impossible to detect and evaluate steel bars rust completely and accurately. This article is based on spontaneous magnetic leakage detection technology and adopts the method of stage corrosion and scanning along the reinforcing bar. Based on spontaneous magnetic flux leakage detection technology, the linear change rate of the tangential component curve of the magnetic flux leakage signal generated after the corrosion of a steel bar is studied, and a comparison is made between the steel bar coated concrete samples with different steel bar diameters. In this paper, the “origin of magnetic flux leakage signal” is defined as a reference point, which is convenient for effectively comparing the magnetic signal curves under all operating conditions. Besides, the “rust-magnetic fluctuation parameter” is proposed to accurately reflect the sudden change of leakage magnetic field caused by disconnection due to the corrosion of a steel bar. A new data processing method is provided for the non-destructive testing of steel corrosion using the spontaneous magnetic flux leakage effect, which can effectively reduce the influence of steel bar diameter on magnetic flux leakage signal and improve the precision of non-destructive testing technology of steel bar corrosion using the metal magnetic memory effect.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Alekseev M, 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 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 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 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 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. Observation of the Semileptonic D^{+} Decay into the K[over ¯]_{1}(1270)^{0} Axial-Vector Meson. PHYSICAL REVIEW LETTERS 2019; 123:231801. [PMID: 31868427 DOI: 10.1103/physrevlett.123.231801] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 10/01/2019] [Indexed: 06/10/2023]
Abstract
By analyzing a 2.93 fb^{-1} data sample of e^{+}e^{-} collisions, recorded at a center-of-mass energy of 3.773 GeV with the BESIII detector operated at the BEPCII collider, we report the first observation of the semileptonic D^{+} transition into the axial-vector meson D^{+}→K[over ¯]_{1}(1270)^{0}e^{+}ν_{e} with a statistical significance greater than 10σ. Its decay branching fraction is determined to be B[D^{+}→K[over ¯]_{1}(1270)^{0}e^{+}ν_{e}]=(2.30±0.26_{-0.21}^{+0.18}±0.25)×10^{-3}, where the first and second uncertainties are statistical and systematic, respectively, and the third originates from the input branching fraction of K[over ¯]_{1}(1270)^{0}→K^{-}π^{+}π^{0}.
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Zhao Q, Li R, Jin YZ, Sun HY, Zhao SM. Equation Derivation of the Probability Distribution of IBS Score among Full Sibling Pairs. FA YI XUE ZA ZHI 2019; 35:657-661. [PMID: 31970950 DOI: 10.12116/j.issn.1004-5619.2019.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 11/16/2018] [Indexed: 06/10/2023]
Abstract
Objective To derive the general equation of the probability distribution of identity by state (IBS) score among biological full sibling pairs by calculating STR allele frequency. Methods Based on the Mendelian genetics law and the hypothesis that parents of biological full siblings (FS) were unrelated individuals, the IBS score and corresponding probability of different genotype combinations in the offspring when unrelated individuals of different genotype combinations give birth to two offsprings were derived. Results Given fi (i=1, 2, …, m) as the frequency of the ith allele of a STR locus, the probability of sharing 2 alleles (p2FS), 1 allele (p1FS) or 0 allele (p0FS) with biological full sibling pairs on the locus can be respectively expressed as follows: (see the text). The sum of p2FS, p1FS and p0FS must be 1. As for the multiple genotyping system that contained n STR loci, IBS scores between biological full sibling pairs conform to binomial distribution: IBS~B(2n, π1). The population rate π1, can be given by the formula: (see the text). Conclusion The alternative hypothesis in biological full sibling testing is that two appraised individuals are biological full siblings. The probability of the corresponding alternative hypothesis of any STR locus combination or IBS score can be directly calculated by the equations presented in this study, and the calculation results are the basis for explanations of the evidence.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Alekseev M, Amoroso A, An FF, 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, 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 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, Andersson WI, 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 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 CM, 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 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 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. Observation of the Leptonic Decay D^{+}→τ^{+}ν_{τ}. PHYSICAL REVIEW LETTERS 2019; 123:211802. [PMID: 31809130 DOI: 10.1103/physrevlett.123.211802] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Indexed: 06/10/2023]
Abstract
We report the first observation of D^{+}→τ^{+}ν_{τ} with a significance of 5.1σ. We measure B(D^{+}→τ^{+}ν_{τ})=(1.20±0.24_{stat}±0.12_{syst})×10^{-3}. Taking the world average B(D^{+}→μ^{+}ν_{μ})=(3.74±0.17)×10^{-4}, we obtain R_{τ/μ}=Γ(D^{+}→τ^{+}ν_{τ})/Γ(D^{+}→μ^{+}ν_{μ})=3.21±0.64_{stat}±0.43_{syst}., which is consistent with the standard model expectation of lepton flavor universality. Using external inputs, our results give values for the D^{+} decay constant f_{D^{+}} and the Cabibbo-Kobayashi-Maskawa matrix element |V_{cd}| that are consistent with, but less precise than, other determinations.
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Qiu CJ, Jin N, Wang XM, Wang XX, Zhao Q. [Epidemiological analysis of new pneumoconiosis among workers in coal industry in Chongqing]. ZHONGHUA LAO DONG WEI SHENG ZHI YE BING ZA ZHI = ZHONGHUA LAODONG WEISHENG ZHIYEBING ZAZHI = CHINESE JOURNAL OF INDUSTRIAL HYGIENE AND OCCUPATIONAL DISEASES 2019; 37:702-704. [PMID: 31594132 DOI: 10.3760/cma.j.issn.1001-9391.2019.09.017] [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 analyze the incidence of pneumoconiosis among workers in the coal industry in the past 13 years in Chongqing, understand the different epidemiological characteristics of new pneumoconiosis among workers in the coal industry in the city, provide basic evidence for the prevention and treatment of pneumoconiosis. Methods: Collecting new cases of pneumoconiosis diagnosed in the coal industry in Chongqing in January 2006-May 2018, and analyze its epidemiological characteristics. Results: In January 2006-May 2018, 25329 cases of pneumoconiosis were added to workers in the coal industry in Chongqing, and 23, 328 cases were present, all male. Among the existing cases: coal workers' pneumoconiosis accounted for 89.30%, silicosis accounted for 10.70%; age distribution was 50-59 years old. The main, accounting for 45.19%, the average age of onset was 52.21±7.45 years; the actual dusting age was mainly 10-19 years, the average actual working age was 17.52±8.47 years; the distribution of the work was mainly by the main coal mining (53.20%) ; There are more new cases in enterprises, accounting for 88.86%; distributed in 36 districts and counties. Conclusion: There was a large number of new pneumoconiosis diseases in the coal industry in Chongqing. Different measures should be taken according to the characteristics of different enterprises, and relevant enterprises should be urged to take the initiative to carry out occupational health surveillance, effectively protect the health of workers, improve the coordination mechanism, improve medical security, and gradually realize government assistance and Social care is combined.
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Fan HJ, Huang C, Su Y, Wang XD, Zhou YC, Duan C, Zhao W, Zhao Q, Jin M, Ma XL. [Clinical characteristics and prognosis of high-risk neuroblastoma with bone marrow metastasis in children]. ZHONGHUA ER KE ZA ZHI = CHINESE JOURNAL OF PEDIATRICS 2019; 57:863-869. [PMID: 31665841 DOI: 10.3760/cma.j.issn.0578-1310.2019.11.009] [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 analyze the clinical characteristics of newly treated high-risk group neuroblastoma (NB) patients with bone marrow metastasis and to explore the prognostic factors. Methods: The clinical features (sex, age, stage, risk group, pathological type, metastatic site, etc.) of 203 newly treated high-risk NB patients with bone marrow metastasis admitted to Hematology Oncology Center, Beijing Children's Hospital from January 2007 to December 2016 were analyzed retrospectively. There were 118 males (58.1%) and 85 females (41.9%). Kaplan-Meier method was used for survival analysis and Cox regression was used to analyze the prognostic factors. Results: The age at onset of the 203 patients was 41 months (9-147 months). The metastatic sites at diagnosis were as follows: bone in 195 cases (96.1%), distant lymph nodes in 104 cases (51.2%), skull and endomeninx in 61 cases (30.0%), orbit in 30 cases (14.8%), pleura in 16 cases (7.9%), liver in 13 cases(6.4%), canalis spinalis in 13 cases (6.4%), other sites in 11 cases (5.4%) and skin and soft tissue in 10 cases (4.9%). In all, 194 cases were enrolled for prognostic analysis. The follow-up time was 36 months (1 day-138 months) , and the 5-years event free survival (EFS) and overall survival (OS) were 36.1% and 39.7%, respectively. A total of 118 patients (60.8%) had events (first relapse or death) with the time to event occurrence was 15 months (1 day-72 months), whereas 112 patients (57.7%) died with the event occurrence to death time was 3 months (1 day-21 months). There was no significant difference in 5-years OS between radiotherapy group and non-radiotherapy group (42.3% vs. 38.3%, χ(2)=3.671, P=0.055). The 5-years OS in transplantation group was significantly better than the non-transplantation group (44.3% vs. 35.5%, χ(2)=8.878, P=0.003), and the radiotherapy combined transplantation group also had a better 5-years OS rate than the non-radiotherapy combined transplantation group (45.8% vs. 37.3%, χ(2)=5.945, P=0.015). Univariate survival analysis showed lactate dehydrogenase ≥ 1 500 U/L, the amplification of MYCN, the metastatic sites of orbit, canalis spinalis and pleura were associated with poor prognosis of newly diagnosed high-risk NB patients (χ(2)=21.064, 13.601, 3.998, 6.183, 15.307, all P<0.05). The amplification of MYCN and the metastatic sites of pleura were risk factors for prognosis of newly diagnosed high-risk NB patients by Cox regression models (HR=1.896,1.100, 95%CI: 1.113-3.231, 1.020-1.187, both P<0.05). Conclusions: The prognosis is unfavorable in high-risk group NB patients with BM metastasis. Radiotherapy combined with transplantation can further improve the prognosis of these patients. The amplification of MYCN and the metastatic sites of pleura were the poor prognostic factors for high-risk NB patients with bone marrow metastasis.
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Xie MM, Zou RY, Li Y, Liu Y, Chen LL, Liu XQ, Zhao Q, Ding JJ, Chen ZY, Cai HR. [Clinical value of myositis antibodies in patients with connective tissue disease-associated interstitial lung diseases]. ZHONGHUA JIE HE HE HU XI ZA ZHI = ZHONGHUA JIEHE HE HUXI ZAZHI = CHINESE JOURNAL OF TUBERCULOSIS AND RESPIRATORY DISEASES 2019; 42:765-770. [PMID: 31594111 DOI: 10.3760/cma.j.issn.1001-0939.2019.10.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Objective: To investigate the clinical significance of detection of myositis-specific antibodies (MSAs) and myositis-associated antibodies (MAAs) in patients with connective tissue disease-associated interstitial lung diseases (CTD-ILD). Methods: Serum samples of 120 patients with CTD-ILD admitted to the Department of Respiratory, Affiliated Drum Tower Hospital of Nanjing University Medical College from December 2016 to April 2018 were collected for analysis. The patients included 45 with polymyositis/dermatomyositis (PM/DM), 36 with Sjogren's syndrome (SS) and 39 with undifferentiated connective tissue disease (UCTD). There were 37 males and 83 females with an average age of (56±11) years. Thirty-two patients with non-CTD-ILD, 10 males and 22 females with an average age of (42±17) years, were enrolled as the control group. Euroline Autoimmune Inflammatory Myopathies 16 Ag kit was used for detecting MSAs and MAAs, and the positive rates of serum MSAs and MAAs were calculated. The antibody distribution and clinical characteristics of different groups were analyzed and compared. Results: Eighty-nine of the 120 patients with CTD-ILD were positive for MSA and/or MAA (74.2%), and the detection rates of MSAs and MAAs were 52.5% (63/120) and 61.7% (74/120) respectively. No myositis antibody was detected in the non-CTD-ILD group. The detection rates of MSAs in PM/DM-ILD group, SS-ILD group and UCTD-ILD group were 75.6% (34/45), 33.3%(12/36) and 43.6%(17/39) respectively. The total detection rate of MSAs in PM/DM group was significantly higher than that in SS group and UCTD group (χ(2)=14.53, 8.95, 0.01). The anti-ARS was the most frequent (50/120, 41.7%). The positive rates of MAAs in the three groups were 64.4%(29/45), 77.8%(28/36), 43.6%(17/39) respectively, and anti-Ro-52 accounted for 60%(72/120), and were highly correlated with MSAs such as anti-Jo-1 antibodies. Conclusion: Myositis antibody profiling should be performed in patients with ILD who were negative for conventional autoimmune antibody testing and had no CTD. In patients with SS-ILD and UCTD-ILD, the myositis antibody spectrum could detect the presence of myositis-specific antibodies and myositis-related antibodies in some patients, and its role in clinical diagnosis and treatment needed further observation.
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Zhang Q, Li J, Tan XP, Zhao Q. Effects of ME3 on the proliferation, invasion and metastasis of pancreatic cancer cells through epithelial-mesenchymal transition. Neoplasma 2019; 66:896-907. [PMID: 31607129 DOI: 10.4149/neo_2019_190119n59] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2019] [Accepted: 04/23/2019] [Indexed: 11/08/2022]
Abstract
Malic enzyme 3 (ME3) aberrant expression contributes to the development of human malignancies. ME3 expression was higher in pancreatic cancer tissues than that in non-tumor tissues, and patients with higher ME3 levels had significantly shorter survival than those with lower levels analyzed by of Badea and TCGA databases. Further, the abilities of proliferation, migration and invasion in pancreatic cancer cells were inhibited by ME3 knockdown and were promoted by ME3 overexpression. Meanwhile, ME3 can promote EMT in pancreatic cancer cells possibly by regulation of TGF-β/Smad2/3 signaling pathway. In conclusion, ME3 is extensively involved in carcinogenesis of pancreatic cancer and may become a new candidate target for diagnosis, treatment and prognosis of pancreatic cancer.
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Zhu YP, Liu H, Zhang ML, Mei J, Zhao Q. 2223Effect of ticagrelor plus aspirin, ticagrelor alone, or aspirin alone on vein-graft patency 1 year after coronary artery bypass grafting with or without diabetes: a post-hoc analysis of the DACAB tria. Eur Heart J 2019. [DOI: 10.1093/eurheartj/ehz748.0119] [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
Introduction
The association of diabetes and vein graft patency after coronary artery bypass grafting (CABG) remains controversial. In patients with diabetes, impaired endothelial function in vein grafts and high platelet turnover might result in early vein graft failure. The DACAB trial showed ticagrelor plus aspirin significantly increased 1-year vein graft patency vs. aspirin alone, while no significant difference between ticagrelor alone and aspirin alone. However, whether the results is different between the patients with or without diabetes is unknown.
Purpose
To assess the effects of ticagrelor with or without aspirin vs. aspirin alone on 1-year vein grafts patency after CABG in patients with or without diabetes.
Methods
We examined the subgroups of patients with and without diabetes from DACAB trial (NCT02201771), in which 500 patients were randomized to 1 of 3 antiplatelet regimens (ticagrelor 90mg twice daily plus aspirin 100mg once daily, T+A group; ticagrelor 90mg twice daily, T group; or aspirin 100mg once daily, A group) within 24 hours post-CABG. The primary outcome was 1-year vein graft patency (FitzGibbon grade A) assessed by multi-slice computed tomographic angiography or coronary angiography.
Results
According to the baseline medical history and/or glycated hemoglobin (HbA1c) ≥6.5%, 283 patients with 818 vein grafts were allocated to the non-diabetes subgroup, remaining 217 patients with 642 vein grafts to the diabetes subgroup. By per-graft analysis, no significant difference on 1-year vein graft patency rate was observed between non-diabetes and diabetes subgroup (84.6% [692/881] for non-diabetes vs. 80.2% [515/642] for diabetes, adjusted odds ratio (OR) =1.39, 95% CI: 0.92–2.09, P=0.116). In T+A group, 1-year vein graft patency rates were 91.0% (244/268) for non-diabetes vs. 85.8% (188/219) for diabetes; In T group, 85.0% (221/260) for non-diabetes vs. 80.3% (183/228) for diabetes; In A group, 78.3% (227/290) for non-diabetes vs. 73.9% (144/195) for diabetes. Ticagrelor plus aspirin showed higher vein graft patency rate than aspirin alone in both non-diabetes and diabetes subgroup (non-diabetes: adjusted OR = 0.34, 95% CI: 0.17–0.69, and diabetes: adjusted OR = 0.42, 95% CI: 0.19–0.91, P for interaction = 0.524), whereas ticagrelor alone did not show improvement on vein graft patency compared with aspirin alone in both subgroups (non-diabetes: adjusted OR=0.62, 95% CI: 0.32–1.20, and diabetes: adjusted OR = 0.65, 95% CI: 0.33–1.31, P for interaction = 0.795). Similar results were showed by per-patient analysis. A total 16 major adverse cardiovascular events occurred, 8 (2.8%) for non-diabetes and 8 (3.7%) for diabetes.
Conclusion
In the DACAB trial, diabetes was not found to be associated with decreased vein graft patency at 1 year after CABG. The effect of ticagrelor plus aspirin on improvement of 1-year vein graft patency, when compared with aspirin alone, is consistent in patients with or without diabetes.
Acknowledgement/Funding
AstraZeneca
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Lin B, Zeng B, Zhao J, Xu T, Wang Y, Hu B, Li F, Zhao Q, Liu R, Liu J, Chen JM, Huang D, Wang Y. Seven Novel and Three Known Mutations in FOXL2 in 10 Chinese Families with Blepharophimosis Syndrome. Curr Mol Med 2019; 18:152-159. [PMID: 30198434 DOI: 10.2174/1566524018666180907162619] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2018] [Revised: 07/22/2018] [Accepted: 09/05/2018] [Indexed: 11/22/2022]
Abstract
BACKGROUND Blepharophimosis syndrome (BPES) is characterized by eyelid malformation with occasional premature ovarian failure. Mutations in FOXL2 underlie a fraction of BPES cases. OBJECTIVE We aimed to investigate the genetic basis of BPES in 26 Chinese families that included 78 patients. METHODS We performed ophthalmological examinations on each family member. We used Sanger sequencing to screen FOXL2 exons and their flanking sequences. We also performed bioinformatics studies, structural modeling and pathogenicity evaluations on all identified variations. Literature was reviewed and genotype-phenotype correlation analysis was performed. RESULTS The patients had typical manifestations of BPES. Ten mutations were identified in ten of the twenty-six families. Among these, seven were novel mutations. These included the six truncating mutations, p.Glu69*, p.Gly256Glyfs*14, p.Ala14Serfs*135, p.Pro333Profs*200, p.Pro290Leufs*70, and p.Pro157Profs*91, and one missense mutation, p.Tyr59Cys. The mutations were scattered within the gene, and no mutational hotspots were found. Genotype-phenotype correlation analysis showed that frameshift or nonsense mutations were correlated with type I BPES, while in-frame or missense mutations were associated with type II BPES. CONCLUSION We report the largest BPES cohort in China thus far as well as seven novel mutations in FOXL2. The identification of novel mutations has not only expanded the mutational spectrum of the gene (which is valuable for mutation detection-based screening) but also suggests that most mutations within the Chinese population may not have been characterized yet.
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Zhao Q, Li J. [To improve the understanding of CD117-negative gastrointestinal stromal tumor]. ZHONGHUA WEI CHANG WAI KE ZA ZHI = CHINESE JOURNAL OF GASTROINTESTINAL SURGERY 2019; 22:831-834. [PMID: 31550821 DOI: 10.3760/cma.j.issn.1671-0274.2019.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor of the digestive tract. The diagnosis of GIST relies mainly on clinicopathological features, tumor cell morphology and immunohistochemical marker CD117 (c-Kit). However, some tumors (about 3%-4%) have clinicopathological features of GIST but do not express CD117. To determine whether these lesions are true GIST, it is necessary to raise awareness of CD117-negative GIST. This article discusses the immunohistochemical features, gene mutations, prognosis and efficacy of targeted drugs of CD117-negative GIST. Research results suggest that CD117-negative GIST lacks KIT expression but has typical clinical, histopathological and cytogenetic features. These tumors have KIT and/or PDGFRA mutations, or are wild type. Because most KIT-negative GISTs contain PDGFRA or KIT mutation, pathologists and oncologists should not exclude GIST diagnosis based on negative immunohistochemical staining of KIT. It is known that approximately 30% of PDGFRA mutations may be sensitive to imatinib, and patients with such tumors may benefit from imatinib, so imatinib treatment should not be empirically denied in these patients.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Alekseev M, Amoroso A, An FF, An Q, Bai Y, Bakina O, Baldini Ferroli R, 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 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, 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, Khan T, 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 XQ, 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 KY, Liu K, 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 M, Qi TY, Qian S, Qiao CF, Qin N, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Richter M, Ripka M, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sarantsev A, Savrié M, 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 HH, 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 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, 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 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. Complete Measurement of the Λ Electromagnetic Form Factors. PHYSICAL REVIEW LETTERS 2019; 123:122003. [PMID: 31633986 DOI: 10.1103/physrevlett.123.122003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 06/26/2019] [Indexed: 06/10/2023]
Abstract
The exclusive process e^{+}e^{-}→ΛΛ[over ¯], with Λ→pπ^{-} and Λ[over ¯]→p[over ¯]π^{+}, has been studied at sqrt[s]=2.396 GeV for measurement of the timelike Λ electric and magnetic form factors, G_{E} and G_{M}. A data sample, corresponding to an integrated luminosity of 66.9 pb^{-1}, was collected with the BESIII detector for this purpose. A multidimensional analysis with a complete decomposition of the spin structure of the reaction enables a determination of the modulus of the ratio R=|G_{E}/G_{M}| and, for the first time for any baryon, the relative phase ΔΦ=Φ_{E}-Φ_{M}. The resulting values are R=0.96±0.14(stat)±0.02(syst) and ΔΦ=37°±12°(stat)±6°(syst), respectively. These are obtained using the recently established and most precise value of the asymmetry parameter α_{Λ}=0.750±0.010 measured by BESIII. In addition, the cross section is measured with unprecedented precision to be σ=118.7±5.3(stat)±5.1(syst) pb, which corresponds to an effective form factor of |G|=0.123±0.003(stat)±0.003(syst). The contribution from two-photon exchange is found to be negligible. Our result enables the first complete determination of baryon timelike electromagnetic form factors.
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Ablikim M, Achasov MN, Ahmed S, Albrecht M, Alekseev M, Amoroso A, An FF, An Q, Bai JZ, Bai Y, Bakina O, Baldini Ferroli R, Ban Y, Begzsuren K, Bennett JV, Berger N, Bertani M, Bettoni D, Bianchi F, Boger E, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chai J, Chang JF, Chelkov G, Chen G, Chen HS, Chen JC, Chen ML, Chen SJ, Chen XR, Chen YB, Cheng W, Chu XK, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai JP, 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, Gao Q, Gao XL, Gao Y, Gao Y, Gao YG, Gao Z, Garillon B, Garzia I, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu MH, Gu YT, Guo AQ, Guo RP, Guo YP, Guskov A, Han S, Hao XQ, Harris FA, He KL, He XQ, Heinsius FH, Held T, Heng YK, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang JS, Huang XT, Huang ZL, Hussain T, Ikegami Andersson W, Imoehl W, Irshad M, Ji Q, Ji QP, Ji XB, Ji XL, 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, Khan T, 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, Li C, Li C, Li DM, Li F, Li FY, Li G, Li HB, Li HJ, Li JC, Li JW, Li J, Li KJ, Li K, Li K, Li LK, Li L, Li PL, Li PR, Li QY, Li WD, Li WG, Li XL, Li XN, Li XQ, Li ZB, Liang H, Liang H, Liang YF, Liang YT, Liao GR, 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 KY, Liu K, Liu LD, Liu Q, Liu SB, Liu X, Liu XY, Liu YB, Liu ZA, Liu Z, Long YF, Lou XC, Lu HJ, Lu JG, Lu Y, Lu YP, Luo CL, Luo MX, Luo T, Luo XL, Lusso S, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma T, Ma XN, Ma XY, Ma YM, Maas FE, Maggiora M, Maldaner S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min J, Mitchell RE, Mo XH, Mo YJ, Morales Morales C, Muchnoi NY, Muramatsu H, Mustafa A, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu SL, Niu XY, Olsen SL, Ouyang Q, Pacetti S, Pan Y, Papenbrock M, Patteri P, Pelizaeus M, Pellegrino J, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Pitka A, Poling R, Prasad V, Qi M, Qi TY, Qian S, Qiao CF, Qin N, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Richter M, Ripka M, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Sarantsev A, Savrié M, Schoenning K, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Sheng HY, Shi X, Song JJ, Song XY, Sosio S, Sowa C, Spataro S, 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, Tsednee B, Uman I, Wang B, Wang D, Wang DY, Wang K, Wang LL, Wang LS, Wang M, Wang M, Wang P, Wang PL, Wang WP, Wang XL, Wang Y, Wang YF, Wang Z, Wang ZG, Wang ZY, Wang Z, Weber T, Wei DH, Weidenkaff P, Wen SP, Wiedner U, Wolke M, Wu LH, Wu LJ, Wu Z, Xia L, Xia Y, Xiao SY, Xiao YJ, Xiao ZJ, Xie YG, Xie YH, Xiong XA, Xiu QL, Xu GF, Xu JJ, Xu L, Xu QJ, Xu XP, Yan F, Yan L, Yan WB, Yan WC, Yan YH, Yang HJ, Yang HX, Yang L, Yang RX, Yang YH, Yang YX, Yang Y, Yang ZQ, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu JS, Yu JS, Yuan CZ, 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 TJ, Zhang XY, Zhang Y, Zhang YH, Zhang YT, 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 YH, Zhong B, Zhou L, 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. Amplitude Analysis of D_{s}^{+}→π^{+}π^{0}η and First Observation of the W-Annihilation Dominant Decays D_{s}^{+}→a_{0}(980)^{+}π^{0} and D_{s}^{+}→a_{0}(980)^{0}π^{+}. PHYSICAL REVIEW LETTERS 2019; 123:112001. [PMID: 31573268 DOI: 10.1103/physrevlett.123.112001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 06/25/2019] [Indexed: 06/10/2023]
Abstract
We present the first amplitude analysis of the decay D_{s}^{+}→π^{+}π^{0}η. We use an e^{+}e^{-} collision data sample corresponding to an integrated luminosity of 3.19 fb^{-1} collected with the BESIII detector at a center-of-mass energy of 4.178 GeV. We observe for the first time the W-annihilation dominant decays D_{s}^{+}→a_{0}(980)^{+}π^{0} and D_{s}^{+}→a_{0}(980)^{0}π^{+}. We measure the absolute branching fraction B(D_{s}^{+}→a_{0}(980)^{+(0)}π^{0^{(}+)},a_{0}(980)^{+(0)}→π^{+(0)}η)=(1.46±0.15_{stat}±0.23_{sys})%, which is larger than the branching fractions of other measured pure W-annihilation decays by at least one order of magnitude. In addition, we measure the branching fraction of D_{s}^{+}→π^{+}π^{0}η with significantly improved precision.
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Jiang X, Wei J, Zhao Q, Wang B, Wang H, Dong L. Sulforaphane Attenuates Radiation-Induced Skin Damage By Regulating the Effects of Anti-Inflammation and Anti-Oxidation. Int J Radiat Oncol Biol Phys 2019. [DOI: 10.1016/j.ijrobp.2019.06.1049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Wang L, Zhang S, Keatch R, Corner G, Nabi G, Murdoch S, Davidson F, Zhao Q. In-vitro antibacterial and anti-encrustation performance of silver-polytetrafluoroethylene nanocomposite coated urinary catheters. J Hosp Infect 2019; 103:55-63. [DOI: 10.1016/j.jhin.2019.02.012] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 02/16/2019] [Indexed: 10/27/2022]
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Huang X, Meng J, Song L, Hou B, Qiao M, Zhang P, Zhao Q. Combined propidium monoazide pretreatment with high-throughput sequencing evaluated the bacterial diversity in chicken skin after thermal treatment. J Appl Microbiol 2019; 127:1751-1758. [PMID: 31448854 DOI: 10.1111/jam.14425] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2019] [Revised: 04/09/2019] [Accepted: 04/23/2019] [Indexed: 12/30/2022]
Abstract
AIMS The purpose of this experiment was to study the bacterial diversity and predominance of spoilage bacteria in chicken skin at different thermal treatment temperatures (60, 70, 80, 90, 100, 110, 120°C). METHOD AND RESULTS Bacteria in chicken skin was collected, then propidium monoazide treatment to remove the DNA of dead cell, total DNA was extracted by Tiandz Bacterial DNA Kit, and investigated by high-throughput sequencing of the v3/v4 regions of the 16S rDNA gene. A total of 796 008 high-quality bacterial sequences were obtained for assessing the microbial diversity of chicken skin from seven thermal treatment group and control group. The results showed that the bacterial diversity in chicken skin at 90°C was lowest. And Acinetobacter (25·88%), Clostridium (20·70%), Bacteroides (13·93%) and Myroides (13·13%) were the main flora at 25°C; The Clostridium was dominant genus of the samples heat-treated by 60, 70, 80 and 90°C, the proportion of this genus were up to 64·86, 77·42, 52·22 and 87·30% respectively. The Bacillus was the main flora of the samples heat-treated by 100, 110 and 120°C, and the relative percentages were 39·44, 79·61 and 45·96% respectively. In addition, high-temperature-resistant Serratia was found in chicken skin. CONCLUSIONS The study revealed that the relationship between thermal treatment temperature and bacterial diversity and dominant spoilage bacteria in chicken skin, which had a strong guiding significance for the control and prediction of micro-organisms in foods. SIGNIFICANCE AND IMPACT OF THE STUDY The results of this paper could provide a theoretical basis for meat products containing chicken skin, including the safe use of chicken skin, determination of sterilization process parameters and selection of preservatives for compounding, which has strong practicality in China.
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Zhang JC, Zhang WJ, Zhao Q, Chen BN, Wang X, Luo YP, Zhang FX. Adiponectin improves isoflurane-induced cognitive dysfunction in elderly rats via inhibiting p38-MAPK signal pathway in hippocampus. EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES 2019; 23:171-176. [PMID: 31389588 DOI: 10.26355/eurrev_201908_18644] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE To investigate the intervention of exogenous adiponectin in the elderly rats with cognitive dysfunction induced by isoflurane through mitogen-activated protein kinase (MAPK) signaling pathway in hippocampus. MATERIALS AND METHODS A total of 60 healthy elder Sprague Dawley (SD) rats aged 15-20 months and weighing 400-500 g were selected. These rats were randomly divided into four groups, i.e., the control group, the anesthetic group, adiponectin intervention group, and p38-MAPK antagonist group, in which the rats in the control group were treated through inhalation of pure oxygen for 4 h at a rate of 4 L/min, while the rats in the other 3 groups were treated through inhalation of isoflurane for 4 h. During the inhalation of isoflurane, the concentration of isoflurane was 3.5% at the beginning and decreased to 2.2% at 1 h, and 1.7% between 2 h and 4 h. Then, the intraperitoneal injection of 0.5 mL normal saline was performed for the rats in the control group and the anesthetic group, while adiponectin (300 mg/kg) was injected into the rats in the adiponectin intervention group and p38-MAPK antagonist group. Simultaneously, the antagonist (20 mg/kg) diluted to 0.5 mL was given to the rats in the p38-MAPK antagonist group, once/day for 3 days. Morris water maze test was carried out respectively in the 1st, 3rd, and 7th day, and 5 rats participated in the test at each time point, during which we recorded the escape latency, as well as the length of the swimming route of rats. Reverse transcriptase-polymerase chain reaction (RT-PCR) and Western blotting were employed to detect the mRNA and protein expressions of p38 in the hippocampus. RESULTS The escape latency and the length of the swimming route at any time point after the intervention in the anesthetic group were significantly longer than those in the control group (p<0.05), and they were significantly shorter in the adiponectin intervention group than those in the anesthetic group (p<0.05), but there were no differences between the p38-MAPK antagonist group and the anesthetic group (p>0.05). The mRNA and protein expressions of p38 at any time point after intervention in the anesthetic group were higher than those in the control group (p<0.05), and they were significantly lower in the adiponectin intervention group than those in the anesthetic group (p<0.05), but there were no differences between the p38-MAPK antagonist group and the anesthetic group (p>0.05). CONCLUSIONS Exogenous adiponectin can improve the cognitive dysfunction of the elderly rats after anesthesia using isoflurane, possibly by inhibiting the p38-MAPK signal pathway in hippocampus.
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Wu Z, Wu J, Zhao Q, Fu S, Jin J. Emerging roles of aerobic glycolysis in breast cancer. Clin Transl Oncol 2019; 22:631-646. [PMID: 31359335 DOI: 10.1007/s12094-019-02187-8] [Citation(s) in RCA: 121] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Accepted: 07/05/2019] [Indexed: 12/25/2022]
Abstract
Altered aerobic glycolysis is a well-recognized characteristic of cancer cell energy metabolism, known as the Warburg effect. Even in the presence of abundant oxygen, a majority of tumor cells produce substantial amounts of energy through a high glycolytic metabolism, and breast cancer (BC) is no exception. Breast cancer continues to be the second leading cause of cancer-associated mortality in women worldwide. However, the precise role of aerobic glycolysis in the development of BC remains elusive. Therefore, the present review attempts to address the implication of key enzymes of the aerobic glycolytic pathway including hexokinase (HK), phosphofructokinase (PFK) and pyruvate kinase (PK), glucose transporters (GLUTs), together with related signaling pathways including protein kinase B(PI3K/AKT), mammalian target of rapamycin (mTOR) and adenosine monophosphate-activated protein kinase (AMPK) and transcription factors (c-myc, p53 and HIF-1) in the research of BC. Thus, the review of aerobic glycolysis in BC may evoke novel ideas for the BC treatment.
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Wang ZY, Yang WL, Li DJ, Chen W, Zhao Q, Li YF, Cui R, Shen L, Xian JF. [Comparison of biometry with the Pentacam AXL, IOLMaster 700 and IOLMaster 500 in cataract patients]. [ZHONGHUA YAN KE ZA ZHI] CHINESE JOURNAL OF OPHTHALMOLOGY 2019; 55:515-521. [PMID: 31288355 DOI: 10.3760/cma.j.issn.0412-4081.2019.07.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Objective: To compare biometry with new biometers of Pentacam AXL and IOLMaster 700 and the widely used biometer of IOLMaster 500 in cataract patients. Methods: Cross-sectional study. A total of 223 eyes of 147 cataract patients from Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University during 4-8 December 2017 were recruited. There were 67 males and 80 females with an age of (64±11) years.The axial length (AL), mean keratometry (Km), anterior chamber depth (ACD) and white-to-white corneal diameter (WTW) from each device were recorded. The difference and agreement between the measurements were evaluated by ANOVA, LSD test, intraclass correlation coefficient and Bland-Altman analysis. Results: The success rate of AL measurement was 85.2% (190/223) with the Pentacam AXL, 96.9% (216/223) with the IOLMaster 700 and 90.6% (202/223) with the IOLMaster 500. There was no difference among devices in measuring the AL, Km and ACD (all P>0.05). Significant difference was found in WTW [(11.36±0.42) vs. (11.69±0.45) vs. (11.45±0.42) mm; F=34.696, P=0.000]. Intraclass correlation coefficient was 0.859-1.000, and Bland-Altman analysis showed good agreement among three devices. Conclusions: The new biometers of Pentacam AXL and IOLMaster 700 and the widely used IOLMaster 500 show no difference in measuring AL, Km and ACD. All three devices show good agreement in biometry of cataract patients. (Chin J Ophthalmol, 2019, 55: 515-521).
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Zhao Q, Hastie T. CAUSAL INTERPRETATIONS OF BLACK-BOX MODELS. JOURNAL OF BUSINESS & ECONOMIC STATISTICS : A PUBLICATION OF THE AMERICAN STATISTICAL ASSOCIATION 2019; 2019:10.1080/07350015.2019.1624293. [PMID: 33132490 PMCID: PMC7597863 DOI: 10.1080/07350015.2019.1624293] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
The fields of machine learning and causal inference have developed many concepts, tools, and theory that are potentially useful for each other. Through exploring the possibility of extracting causal interpretations from black-box machine-trained models, we briefly review the languages and concepts in causal inference that may be interesting to machine learning researchers. We start with the curious observation that Friedman's partial dependence plot has exactly the same formula as Pearl's back-door adjustment and discuss three requirements to make causal interpretations: a model with good predictive performance, some domain knowledge in the form of a causal diagram and suitable visualization tools. We provide several illustrative examples and find some interesting and potentially causal relations using visualization tools for black-box models.
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Li DJ, Yang WL, Wang ZY, Chen W, Zhao Q, Li YF, Cui R, Shen L, Wei WB. [Comparative analysis on the significances of contrast-enhanced ultrasound and dynamic contrast-enhanced magnetic resonance imaging in uveal melanoma diagnosis]. [ZHONGHUA YAN KE ZA ZHI] CHINESE JOURNAL OF OPHTHALMOLOGY 2019. [PMID: 29518878 DOI: 10.3760/cma.j.issn.0412-4081.2018.03.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To compare the significance of contrast-enhanced ultrasound (CEUS) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the diagnosis of uveal melanoma. Methods: It was a retrospective case series study. Sixty-three cases (63 eyes) of uveal melanoma patients (confirmed by histopathology) who underwent CEUS and DCE-MRI examination at Beijing Tongren Hospital during January 2010 and May 2014 were collected, including 30 males and 33 females, with average age of 47 years (ranged from 27 to 69 years). The data and images of CEUS and DCE-MRI were analyzed and the findings were reviewed and compared to pathology results so as to evaluate the diagnosis coincidence rate of using CEUS, DCE-MRI and both (combined CEUS and DCE-MRI). Fisher's exact test method was used to explore the efficiency of diagnosing uveal melanoma with CEUS, DCE-MRI and the two combined. Results: Among the 63 cases of uveal melanoma, the coincidence rates of CEUS, DCE-MRI and combined diagnosis for uveal melanoma were 93.7% (59/63), 90.5% (57/63) and 100% (63/63) respectively. There was no significant difference between CEUS and DCE-MRI (P=0.663). Fifty-five cases showed fast wash in and fast wash out, and 8 cases showed fast wash in and slow wash out in time-intensity curve of CEUS. Fifty-four cases showed rapid increase and rapid decrease, and 7 cases showed rapid increase and slow decrease, and 2 cases showed sustain enhancement in signal intensity-time curve of DCE-MRI. Conclusions: CEUS is an effective method in diagnosis of uveal melanoma. CEUS and DCE-MRI are of similar value in the diagnosis of uveal melanoma, physicians may be able to acquire more diagnostic information when using the two methods in combination.(Chin J Ophthalmol, 2018, 54: 194-198).
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Alekseev M, Amoroso A, An FF, An Q, Bai Y, Bakina O, Ferroli RB, 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 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, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang JS, Huang XT, Huang XZ, Huesken N, Hussain T, Andersson WI, 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, Khan T, 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 XQ, Li ZB, 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 KY, Liu K, 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 CM, 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 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, Ripka M, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sarantsev A, Savri M, 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 HH, 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 YF, 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, 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 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. Study of e^{+}e^{-}→γωJ/ψ and Observation of X(3872)→ωJ/ψ. PHYSICAL REVIEW LETTERS 2019; 122:232002. [PMID: 31298909 DOI: 10.1103/physrevlett.122.232002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 04/25/2019] [Indexed: 06/10/2023]
Abstract
We study the e^{+}e^{-}→γωJ/ψ process using 11.6 fb^{-1} e^{+}e^{-} annihilation data taken at center-of-mass energies from sqrt[s]=4.008 GeV to 4.600 GeV with the BESIII detector at the BEPCII storage ring. The X(3872) resonance is observed for the first time in the ωJ/ψ system with a significance of more than 5σ. The relative decay ratio of X(3872)→ωJ/ψ and π^{+}π^{-}J/ψ is measured to be R=1.6_{-0.3}^{+0.4}±0.2, where the first uncertainty is statistical and the second systematic (the same hereafter). The sqrt[s]-dependent cross section of e^{+}e^{-}→γX(3872) is also measured and investigated, and it can be described by a single Breit-Wigner resonance, referred to as the Y(4200), with a mass of 4200.6_{-13.3}^{+7.9}±3.0 MeV/c^{2} and a width of 115_{-26}^{+38}±12 MeV. In addition, to describe the ωJ/ψ mass distribution above 3.9 GeV/c^{2}, we need at least one additional Breit-Wigner resonance, labeled as X(3915), in the fit. The mass and width of the X(3915) are determined. The resonant parameters of the X(3915) agree with those of the Y(3940) in B→KωJ/ψ and of the X(3915) in γγ→ωJ/ψ observed by the Belle and BABAR experiments within errors.
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Zhao Q, Small DS, Bhattacharya BB. Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap. J R Stat Soc Series B Stat Methodol 2019. [DOI: 10.1111/rssb.12327] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
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Maakaron J, Zhao Q, Puto M, Von Derau R, Robinson J, Brammer J, Penza S, Baiocchi R, Christian B, Maddocks K, Saad A, Wall S, Benson D, Efebera Y, Rosko A, Ayyappan S, Grieselhuber N, Vasu S, Larkin K, Epperla N, Devarakonda S, Choe H, Chaudhry M, Blaser B, Blachly J, Bhatnagar B, Alinari L, Mims A, Jaglowski S, William B. PHASE I DOSE-ESCALATION STUDY OF VENETOCLAX PLUS BEAM FOLLOWED BY AUTOLOGOUS STEM CELL TRANSPLANT (ASCT) FOR CHEMORESISTANT, RELAPSED/REFRACTORY, OR HIGH-RISK NON-HODGKIN'S LYMPHOMA (NHL); PRELIMINARY RESULTS. Hematol Oncol 2019. [DOI: 10.1002/hon.213_2631] [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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Bowden J, Del Greco M F, Minelli C, Zhao Q, Lawlor DA, Sheehan NA, Thompson J, Davey Smith G. Improving the accuracy of two-sample summary-data Mendelian randomization: moving beyond the NOME assumption. Int J Epidemiol 2019; 48:728-742. [PMID: 30561657 PMCID: PMC6659376 DOI: 10.1093/ije/dyy258] [Citation(s) in RCA: 304] [Impact Index Per Article: 60.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/09/2018] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Two-sample summary-data Mendelian randomization (MR) incorporating multiple genetic variants within a meta-analysis framework is a popular technique for assessing causality in epidemiology. If all genetic variants satisfy the instrumental variable (IV) and necessary modelling assumptions, then their individual ratio estimates of causal effect should be homogeneous. Observed heterogeneity signals that one or more of these assumptions could have been violated. METHODS Causal estimation and heterogeneity assessment in MR require an approximation for the variance, or equivalently the inverse-variance weight, of each ratio estimate. We show that the most popular 'first-order' weights can lead to an inflation in the chances of detecting heterogeneity when in fact it is not present. Conversely, ostensibly more accurate 'second-order' weights can dramatically increase the chances of failing to detect heterogeneity when it is truly present. We derive modified weights to mitigate both of these adverse effects. RESULTS Using Monte Carlo simulations, we show that the modified weights outperform first- and second-order weights in terms of heterogeneity quantification. Modified weights are also shown to remove the phenomenon of regression dilution bias in MR estimates obtained from weak instruments, unlike those obtained using first- and second-order weights. However, with small numbers of weak instruments, this comes at the cost of a reduction in estimate precision and power to detect a causal effect compared with first-order weighting. Moreover, first-order weights always furnish unbiased estimates and preserve the type I error rate under the causal null. We illustrate the utility of the new method using data from a recent two-sample summary-data MR analysis to assess the causal role of systolic blood pressure on coronary heart disease risk. CONCLUSIONS We propose the use of modified weights within two-sample summary-data MR studies for accurately quantifying heterogeneity and detecting outliers in the presence of weak instruments. Modified weights also have an important role to play in terms of causal estimation (in tandem with first-order weights) but further research is required to understand their strengths and weaknesses in specific settings.
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Ablikim M, Achasov MN, Ahmed S, Albrecht M, Alekseev M, Amoroso A, An FF, An Q, Bai Y, Bakina O, Baldini Ferroli R, Ban Y, Begzsuren K, Bennett JV, Berger N, Bertani M, Bettoni D, Bianchi F, 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 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, 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, 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, Khan T, 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 XQ, Li ZB, 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 KY, Liu K, 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, 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 M, Qi TY, Qian S, Qiao CF, Qin N, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Richter M, Ripka M, Rivetti A, Rolo M, Rong G, Rosner C, Rump M, Sarantsev A, Savrié M, 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 HH, Wang K, Wang LL, Wang LS, Wang M, Wang MZ, Wang M, Wang P, Wang PL, Wang RM, Wang WP, Wang X, Wang XF, Wang Y, Wang YF, Wang Z, Wang ZG, Wang ZY, Wang Z, Weber T, Wei DH, Weidenkaff P, Wen HW, Wen SP, Wiedner U, 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, 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 SF, Zhang TJ, Zhang XY, Zhang Y, Zhang YH, Zhang YT, 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. Observation of the Decay X(3872)→π^{0}χ_{c1}(1P). PHYSICAL REVIEW LETTERS 2019; 122:202001. [PMID: 31172749 DOI: 10.1103/physrevlett.122.202001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2019] [Revised: 04/15/2019] [Indexed: 06/09/2023]
Abstract
Using a total of 9.0 fb^{-1} of e^{+}e^{-} collision data with center-of-mass energies between 4.15 and 4.30 GeV collected by the BESIII detector, we search for the processes e^{+}e^{-}→γX(3872) with X(3872)→π^{0}χ_{cJ} for J=0, 1, 2. We report the first observation of X(3872)→π^{0}χ_{c1}, a new decay mode of the X(3872), with a statistical significance of more than 5σ for all systematic fit variations. Normalizing to the previously established process e^{+}e^{-}→γX(3872) with X(3872)→π^{+}π^{-}J/ψ, we find B(X(3872)→π^{0}χ_{c1})/B(X(3872)→π^{+}π^{-}J/ψ)=0.88_{-0.27}^{+0.33}±0.10, where the first error is statistical and the second is systematic. We set 90% confidence level upper limits on the corresponding ratios for the decays to π^{0}χ_{c0} and π^{0}χ_{c2} of 19 and 1.1, respectively.
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Li YM, Xiang L, Zhao Q, Zhao J, Xu XX, Lin QQ, Zhang C, Xiao Q. [Correlation between endogenous EPO levels and electrocardiogram scatter plot changes in patients with coronary heart disease and autonomic nerve function injury]. ZHONGHUA YI XUE ZA ZHI 2019; 99:1412-1417. [PMID: 31137130 DOI: 10.3760/cma.j.issn.0376-2491.2019.18.011] [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 analyze the correlation between endogenous EPO levels and electrocardiogram scatter plot changes in patients with coronary heart disease and autonomic nerve function injury. Methods: Forty-eight patients who underwent coronary arteriography (CAG) inspection due to chronic coronary heart diseases were selected from July 2015 to October 2015. All of them were evaluated by the Ewing standard autonomic nervous function test, and were divided into Ewing(+) group and Ewing(-) group according to the results of the test. The clinical data of the patients was collected and venous blood was extracted to detect EPO level. Results: The EPO level of Ewing (+) group ((13±3) mIU/ml) was significantly higher than that of Ewing (-) group ((10±3) mIU/ml). The Lorenz scatter plot comet shapes between the two groups had a significant difference. As for the quantitative indicators of Lorenz scatterplot, length of the Ewing (+) group ((147±22) ms) was shorter than that of the Ewing (-) group ((164±24) ms) and there was no significant differences in the width between the two groups. EPO level was negatively correlated with length in both groups (r=-0.427, P=0.002), but not with width (r=0.091, P=0.539). Binary logistic regression analysis showed that EPO (OR=1.394) and diastolic blood pressure (OR=1.091) were risk factors for autonomic nervous function damage. Length (OR=0.934) was a protective factor for autonomic nervous function. ROC curve analysis showed that the area under the EPO curve was 0.737 and that under the length curve was 0.719. Conclusions: The endogenous EPO levels are associated with the changes of electrocardiogram scatter plot in patients with coronary heart disease and autonomic nerve function injury. EPO and length of scatter plot have the similar diagnostic value on predicting of autonomic nerve function injury.
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Yu PX, Zhao Q, Meng ZM, Ji YJ. [ Rhabditis axei found in urine routine examination: a case report]. ZHONGGUO XUE XI CHONG BING FANG ZHI ZA ZHI = CHINESE JOURNAL OF SCHISTOSOMIASIS CONTROL 2019; 31:565-566. [PMID: 31713397 DOI: 10.16250/j.32.1374.2018181] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Rhabditis axei is a free-living nematode, which can occasionally invade into humans through drinking and contacting wastewater. It is usually parasitic in the digestive and urinary systems, causing the disease of rhabditelliasis axei. This paper reports a case of R. axei infection found in the urine routine examination.
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Olasege BS, Zhang S, Zhao Q, Liu D, Sun H, Wang Q, Ma P, Pan Y. Genetic parameter estimates for body conformation traits using composite index, principal component, and factor analysis. J Dairy Sci 2019; 102:5219-5229. [PMID: 31056333 DOI: 10.3168/jds.2018-15561] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 03/03/2019] [Indexed: 11/19/2022]
Abstract
Information about genetic parameters is population specific and it is crucial for designing animal breeding programs and predicting response to selection. This study was carried out to estimate the genetic parameters for 23 body conformation traits of 45,517 Chinese Holstein reared in Eastern China from 1995 to 2017 with the Bayesian inference method using a linear animal mixed model. The methods to integrate these traits included (1) using the composite index from the Dairy Association of China and (2) applying principal component analysis and factor analysis to explore the relationship between the conformation traits. Estimates of heritability using the composite index were low (0.04; feet and legs) to moderate (0.23; body capacity). Strong genetic correlations were observed between the individual body conformation traits. Both principal components (1 to 7; eigenvalues ≥ 1) and latent factors (1 to 7; eigenvalues ≥ 1) explained 60.37% of total variability. Principal component 1 and factor 1 accounted for the traits that are usually associated with milk production. Moderate to low heritability were estimated through multi-trait analysis for principal components (from 0.07 to 0.21) and latent factors (from 0.07 to 0.23). Genetic correlations among the 2 multivariate techniques are typically lower compared with the one existing among the measured traits. Results from these analyses suggest the possibility of using both principal component analysis and factor analysis in morphological evaluation, simplifying the information given by the body conformation traits into new variables that could be useful for the genetic improvement of the Chinese Holstein population. This information could also be used to avoid analyzing large number of correlated traits, thereby improving precision and reducing computation burdens to analyze large and complex data.
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Song Z, Chen X, Zhao Q, Lin Z, Yang S, Chen T, Chen J, Yang Y. 889 Trpv3 gain-of-function mutation impairs differentiation of hair follicle inner root sheath. J Invest Dermatol 2019. [DOI: 10.1016/j.jid.2019.03.965] [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]
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Zhao Q, Wang J, Spiller W, Bowden J, Small DS. Two-Sample Instrumental Variable Analyses Using Heterogeneous Samples. Stat Sci 2019. [DOI: 10.1214/18-sts692] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Ablikim M, Achasov M, Adlarson P, Ahmed S, Albrecht M, Alekseev M, Amoroso A, An F, An Q, Bai Y, Bakina O, Ferroli RB, Balossino I, Ban Y, Begzsuren K, Bennett J, Berger N, Bertani M, Bettoni D, Bianchi F, Biernat J, Bloms J, Boyko I, Briere R, Cai H, Cai X, Calcaterra A, Cao G, Cao N, Cetin S, Chai J, Chang J, Chang W, Chelkov G, Chen D, Chen G, Chen H, Chen J, Chen M, Chen S, Chen Y, Cheng W, Cibinetto G, Cossio F, Cui X, Dai H, Dai J, Dai X, Dbeyssi A, Dedovich D, Deng Z, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong L, Dong M, Dou Z, Du S, Fan J, Fang J, Fang S, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng C, Fritsch M, Fu C, Fu Y, Gao Q, Gao X, Gao Y, Gao Y, Gao Y, Gao Z, Garillon B, Garzia I, Gersabeck E, Gilman A, Goetzen K, Gong L, Gong W, Gradl W, Greco M, Gu L, Gu M, Gu S, Gu Y, Guo A, Guo L, Guo R, Guo Y, Guskov A, Han S, Hao X, Harris F, He K, Heinsius F, Held T, Heng Y, Himmelreich M, Hou Y, Hou Z, Hu H, Hu J, Hu T, Hu Y, Huang G, Huang J, Huang X, Huang X, Huesken N, Hussain T, Andersson WI, Imoehl W, Irshad M, Ji Q, Ji Q, Ji X, Ji X, Jiang H, Jiang X, Jiang X, Jiao J, Jiao Z, Jin D, Jin S, Jin Y, Johansson T, Kalantar-Nayestanaki N, Kang X, Kappert R, Kavatsyuk M, Ke B, Keshk I, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu O, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth M, Kurth M, Kühn W, Lange J, Larin P, Lavezzi L, Leithoff H, Lenz T, Li C, Li C, Li D, Li F, Li F, Li G, Li H, Li H, Li J, Li J, Li K, Li L, Li L, Li P, Li P, Li Q, Li W, Li W, Li X, Li X, Li X, Li Z, Li Z, Liang H, Liang H, Liang Y, Liang Y, Liao G, Liao L, Libby J, Lin C, Lin D, Lin Y, Liu B, Liu B, Liu C, Liu D, Liu D, Liu F, Liu F, Liu F, Liu H, Liu H, Liu H, Liu H, Liu J, Liu J, Liu K, Liu K, Liu L, Liu Q, Liu S, Liu T, Liu X, Liu X, Liu Y, Liu Z, Liu Z, Long Y, Lou X, Lu H, Lu J, Lu J, Lu Y, Lu Y, Luo C, Luo M, Luo P, Luo T, Luo X, Lusso S, Lyu X, Ma F, Ma H, Ma L, Ma M, Ma Q, Ma X, Ma X, Ma X, Ma Y, Maas F, Maggiora M, Maldaner S, Malde S, Malik Q, Mangoni A, Mao Y, Mao Z, Marcello S, Meng Z, Messchendorp J, Mezzadri G, Min J, Min T, Mitchell R, Mo X, Mo Y, Morales CM, Muchnoi N, Muramatsu H, Mustafa A, Nakhoul S, Nefedov Y, Nerling F, Nikolaev I, Ning Z, Nisar S, Niu S, Olsen S, Ouyang Q, Pacetti S, Pan Y, Papenbrock M, Patteri P, Pelizaeus M, Peng H, Peters K, Pettersson J, Ping J, Ping R, Pitka A, Poling R, Prasad V, Qi H, Qi M, Qi T, Qian S, Qiao C, Qin N, Qin X, Qin X, Qin Z, Qiu J, Qu S, Rashid K, Ravindran K, Redmer C, 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 X, Shao M, Shen C, Shen P, Shen X, Sheng H, Shi X, Shi XD, Song J, Song Q, Song X, Sosio S, Sowa C, Spataro S, Sui F, Sun G, Sun J, Sun L, Sun S, Sun X, Sun Y, Sun YK, Sun Y, Sun Z, Sun Z, Tan Y, Tang C, Tang G, Tang X, Thoren V, Tsednee B, Uman I, Wang B, Wang B, Wang C, Wang D, Wang K, Wang L, Wang L, Wang M, Wang M, Wang M, Wang P, Wang R, Wang W, Wang X, Wang X, Wang X, Wang Y, Wang Y, Wang Y, Wang Z, Wang Z, Wang Z, Wang Z, Weber T, Wei D, Weidenkaff P, Wen H, Wen S, Wiedner U, Wilkinson G, Wolke M, Wu L, Wu L, Wu Z, Xia L, Xia Y, Xiao S, Xiao Y, Xiao Z, Xie Y, Xie Y, Xing T, Xiong X, Xiu Q, Xu G, Xu J, Xu L, Xu Q, Xu W, Xu X, Yan F, Yan L, Yan W, Yan W, Yan Y, Yang H, Yang H, Yang L, Yang R, Yang S, Yang Y, Yang Y, Yang Y, Yang Z, Ye M, Ye M, Yin J, You Z, Yu B, Yu C, Yu J, Yu T, Yuan C, Yuan X, Yuan Y, Yuncu A, Zafar A, Zeng Y, Zhang B, Zhang B, Zhang C, Zhang D, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang K, Zhang L, Zhang S, Zhang T, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhang Z, Zhang Z, Zhao G, Zhao J, Zhao J, Zhao J, Zhao L, Zhao L, Zhao M, Zhao Q, Zhao S, Zhao T, Zhao Y, Zhao Z, Zhemchugov A, Zheng B, Zheng J, Zheng Y, Zheng Y, Zhong B, Zhou L, Zhou L, Zhou Q, Zhou X, Zhou X, Zhou X, Zhou X, Zhou X, Zhu A, Zhu J, Zhu J, Zhu K, Zhu K, Zhu S, Zhu W, Zhu X, Zhu Y, Zhu Y, Zhu Z, Zhuang J, Zou B, Zou J. First observations of
hc→hadrons. Int J Clin Exp Med 2019. [DOI: 10.1103/physrevd.99.072008] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Ablikim M, Achasov M, Ahmed S, Albrecht M, Amoroso A, An F, An Q, Bai J, Bai Y, Bakina O, Baldini Ferroli R, Ban Y, Bennett D, Bennett J, Berger N, Bertani M, Bettoni D, Bian J, Bianchi F, Boger E, Boyko I, Briere R, Cai H, Cai X, Cakir O, Calcaterra A, Cao G, Cetin S, Chai J, Chang J, Chelkov G, Chen G, Chen H, Chen J, Chen M, Chen P, Chen S, Chen X, Chen Y, Chu X, Cibinetto G, Dai H, Dai J, Dbeyssi A, Dedovich D, Deng Z, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong L, Dong M, Dou Z, Du S, Duan P, Fang J, Fang S, Fang X, Fang Y, Farinelli R, Fava L, Fegan S, Feldbauer F, Felici G, Feng C, Fioravanti E, Fritsch M, Fu C, Gao Q, Gao X, Gao Y, Gao Y, Gao Z, Garzia I, Goetzen K, Gong L, Gong W, Gradl W, Greco M, Gu M, Gu S, Gu Y, Guo A, Guo L, Guo R, Guo Y, Haddadi Z, Han S, Hao X, Harris F, He K, He X, Heinsius F, Held T, Heng Y, Holtmann T, Hou Z, Hu C, Hu H, Hu T, Hu Y, Huang G, Huang J, Huang X, Huang X, Huang Z, Hussain T, Ikegami Andersson W, Ji Q, Ji Q, Ji X, Ji X, Jiang X, Jiang X, Jiao J, Jiao Z, Jin D, Jin S, Jin Y, Johansson T, Julin A, Kalantar-Nayestanaki N, Kang X, Kang X, Kavatsyuk M, Ke B, Khan T, Khoukaz A, Kiese P, Kliemt R, Koch L, Kolcu O, Kopf B, Kornicer M, Kuemmel M, Kuessner M, Kuhlmann M, Kupsc A, Kühn W, Lange J, Lara M, Larin P, Lavezzi L, Leiber S, Leithoff H, Leng C, Li C, Li C, Li D, Li F, Li F, Li G, Li H, Li H, Li J, Li J, Li K, Li K, Li K, Li L, Li P, Li P, Li Q, Li T, Li W, Li W, Li X, Li X, Li X, Li Z, Liang H, Liang Y, Liang Y, Liao G, Lin D, Liu B, Liu B, Liu C, Liu D, Liu F, Liu F, Liu F, Liu H, Liu H, Liu H, Liu H, Liu J, Liu J, Liu J, Liu K, Liu K, Liu K, Liu L, Liu P, Liu Q, Liu S, Liu X, Liu Y, Liu Z, Liu Z, Long Y, Lou X, Lu H, Lu J, Lu Y, Lu Y, Luo C, Luo M, Luo X, Lyu X, Ma F, Ma H, Ma L, Ma M, Ma Q, Ma T, Ma X, Ma X, Ma Y, Maas F, Maggiora M, Malik Q, Mao Y, Mao Z, Marcello S, Meng Z, Messchendorp J, Mezzadri G, Min J, Min T, Mitchell R, Mo X, Mo Y, Morales Morales C, Morello G, Muchnoi N, Muramatsu H, Musiol P, Mustafa A, Nefedov Y, Nerling F, Nikolaev I, Ning Z, Nisar S, Niu S, Niu X, Olsen S, Ouyang Q, Pacetti S, Pan Y, Papenbrock M, Patteri P, Pelizaeus M, Pellegrino J, Peng H, Peters K, Pettersson J, Ping J, Ping R, Pitka A, Poling R, Prasad V, Qi H, Qi M, Qian S, Qiao C, Qin N, Qin X, Qin Z, Qiu J, Qu Z, Rashid K, Redmer C, Richter M, Ripka M, Rolo M, Rong G, Rosner C, Ruan X, Sarantsev A, Savrié M, Schnier C, Schoenning K, Shan W, Shao M, Shen C, Shen P, Shen X, Sheng H, Song J, Song W, Song X, Sosio S, Sowa C, Spataro S, Sun G, Sun J, Sun L, Sun S, Sun X, Sun Y, Sun Y, Sun Y, Sun Z, Sun Z, Tang C, Tang G, Tang X, Tapan I, Tiemens M, Tsednee B, Uman I, Varner G, Wang B, Wang B, Wang D, Wang D, Wang D, Wang K, Wang L, Wang L, Wang M, Wang M, Wang P, Wang P, Wang W, Wang X, Wang Y, Wang Y, Wang Y, Wang Y, Wang Z, Wang Z, Wang Z, Wang Z, Wang Z, Weber T, Wei D, Weidenkaff P, Wen S, Wiedner U, Wolke M, Wu L, Wu L, Wu Z, Xia L, Xia X, Xia Y, Xiao D, Xiao H, Xiao Y, Xiao Z, Xie Y, Xie Y, Xiong X, Xiu Q, Xu G, Xu J, Xu L, Xu Q, Xu Q, Xu X, Yan L, Yan W, Yan W, Yan W, Yan Y, Yang H, Yang H, Yang L, Yang Y, Yang Y, Yang Y, Ye M, Ye M, Yin J, You Z, Yu B, Yu C, Yu J, Yuan C, Yuan Y, Yuncu A, Zafar A, Zallo A, Zeng Y, Zeng Z, Zhang B, Zhang B, Zhang C, Zhang D, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang K, Zhang K, Zhang L, Zhang S, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhang Z, Zhang Z, Zhao G, Zhao J, Zhao J, Zhao J, Zhao L, Zhao L, Zhao M, Zhao Q, Zhao S, Zhao T, Zhao Y, Zhao Z, Zhemchugov A, Zheng B, Zheng J, Zheng W, Zheng Y, Zhong B, Zhou L, Zhou X, Zhou X, Zhou X, Zhou X, Zhou Y, Zhu J, Zhu J, Zhu K, Zhu K, Zhu S, Zhu S, Zhu X, Zhu Y, Zhu Y, Zhu Z, Zhuang J, Zou B, Zou J. Search for baryon and lepton number violation in
J/ψ→Λc+e−+c.c.. Int J Clin Exp Med 2019. [DOI: 10.1103/physrevd.99.072006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Ablikim M, Achasov MN, Ahmed S, Albrecht M, Alekseev M, Amoroso A, An FF, An Q, Bai Y, Bakina O, Baldini Ferroli R, Ban Y, Begzsuren K, Bennett DW, Bennett JV, Berger N, Bertani M, Bettoni D, Bianchi F, Boger E, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cetin SA, Chai J, Chang JF, Chang WL, Chelkov G, Chen G, Chen HS, Chen JC, Chen ML, Chen PL, Chen SJ, Chen XR, Chen YB, Cheng W, Chu XK, Cibinetto G, Cossio F, Dai HL, Dai JP, 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, Duan PF, Fan JZ, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Fritsch M, Fu CD, Gao Q, Gao XL, Gao Y, Gao YG, Gao Z, Garillon B, Garzia I, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Haddadi Z, Han S, Hao XQ, Harris FA, He KL, Heinsius FH, Held T, Heng YK, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang JS, Huang XT, Huang XZ, Huang ZL, 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, Kavatsyuk M, Ke BC, Keshk IK, Khan T, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth M, Kühn W, Lange JS, Larin P, Lavezzi L, Leiber S, Leithoff H, Li C, Li C, Li DM, Li F, Li FY, Li G, Li HB, Li HJ, Li JC, Li JW, Li KJ, Li K, Li K, Li LK, Li L, Li PL, Li PR, Li QY, Li T, Li WD, Li WG, Li XL, Li XN, Li XQ, Li ZB, Liang H, Liang YF, Liang YT, Liao GR, 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 HL, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu KY, Liu K, Liu LD, Liu Q, Liu SB, Liu X, Liu YB, Liu ZA, Liu Z, Long YF, Lou XC, Lu HJ, 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 XY, Ma YM, Maas FE, Maggiora M, Maldaner 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 CM, Muchnoi NY, Muramatsu H, Mustafa A, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu SL, Niu XY, Olsen SL, Ouyang Q, Pacetti S, Pan Y, Papenbrock M, Patteri P, Pelizaeus M, Pellegrino J, Peng HP, Peng ZY, 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 XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Richter M, Ripka M, Rivetti A, Rolo M, Rong G, Rosner C, Sarantsev A, Savrié M, Schoenning K, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Sheng HY, Shi X, Song JJ, Song WM, 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, Tiemens M, Tsednee B, Uman I, Wang B, Wang BL, Wang CW, Wang D, Wang DY, Wang HH, Wang K, Wang LL, Wang LS, Wang M, Wang M, Wang P, Wang PL, Wang WP, Wang XF, Wang Y, Wang YF, Wang YQ, Wang Z, Wang ZG, Wang ZY, Wang Z, Weber T, Wei DH, Weidenkaff P, Wen SP, Wiedner U, Wolke M, Wu LH, Wu LJ, Wu Z, Xia L, Xia X, Xia Y, Xiao D, Xiao YJ, Xiao ZJ, Xie YG, Xie YH, Xiong XA, Xiu QL, Xu GF, Xu JJ, Xu L, Xu QJ, 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, Yuan CZ, 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 SF, Zhang TJ, Zhang XY, Zhang Y, Zhang YH, Zhang YT, 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 WJ, Zheng YH, Zhong B, Zhou L, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou X, Zhou X, Zhu AN, Zhu J, Zhu J, Zhu K, Zhu KJ, Zhu S, Zhu SH, Zhu XL, Zhu YC, Zhu YS, Zhu ZA, Zhuang J, Zou BS, Zou JH. Precision Measurement of the Branching Fractions of η^{'} Decays. PHYSICAL REVIEW LETTERS 2019; 122:142002. [PMID: 31050481 DOI: 10.1103/physrevlett.122.142002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Indexed: 06/09/2023]
Abstract
Based on a sample of (1310.6±7.0)×10^{6}J/ψ events collected with the BESIII detector, we present measurements of J/ψ and η^{'} absolute branching fractions using the process J/ψ→γη^{'}. By analyzing events where the radiative photon converts into an e^{+}e^{-} pair, the branching fraction for J/ψ→γη^{'} is measured to be (5.27±0.03±0.05)×10^{-3}. The absolute branching fractions of the five dominant decay channels of the η^{'} are then measured for the first time and are determined to be B(η^{'}→γπ^{+}π^{-})=(29.90±0.03±0.55)%, B(η^{'}→ηπ^{+}π^{-})=(41.24±0.08±1.24)%, B(η^{'}→ηπ^{0}π^{0})=(21.36±0.10±0.92)%, B(η^{'}→γω)=(2.489±0.018±0.074)%, and B(η^{'}→γγ)=(2.331±0.012±0.035)%, where the first uncertainties are statistical and the second systematic.
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Hamid O, Robert C, Daud A, Hodi FS, Hwu WJ, Kefford R, Wolchok JD, Hersey P, Joseph R, Weber JS, Dronca R, Mitchell TC, Patnaik A, Zarour HM, Joshua AM, Zhao Q, Jensen E, Ahsan S, Ibrahim N, Ribas A. Five-year survival outcomes for patients with advanced melanoma treated with pembrolizumab in KEYNOTE-001. Ann Oncol 2019; 30:582-588. [PMID: 30715153 PMCID: PMC6503622 DOI: 10.1093/annonc/mdz011] [Citation(s) in RCA: 570] [Impact Index Per Article: 114.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Pembrolizumab demonstrated robust antitumor activity and safety in the phase Ib KEYNOTE-001 study (NCT01295827) of advanced melanoma. Five-year outcomes in all patients and treatment-naive patients are reported herein. Patients whose disease progressed following initial response and who received a second course of pembrolizumab were also analyzed. PATIENTS AND METHODS Patients aged ≥18 years with previously treated or treatment-naive advanced/metastatic melanoma received pembrolizumab 2 mg/kg every 3 weeks, 10 mg/kg every 3 weeks, or 10 mg/kg every 2 weeks until disease progression, intolerable toxicity, or patient/investigator decision to withdraw. Kaplan-Meier estimates of overall survival (OS) and progression-free survival (PFS) were calculated. Objective response rate and PFS were based on immune-related response criteria by investigator assessment (data cut-off, September 1, 2017). RESULTS KEYNOTE-001 enrolled 655 patients with melanoma; median follow-up was 55 months. Estimated 5-year OS was 34% in all patients and 41% in treatment-naive patients; median OS was 23.8 months (95% CI, 20.2-30.4) and 38.6 months (95% CI, 27.2-not reached), respectively. Estimated 5-year PFS rates were 21% in all patients and 29% in treatment-naive patients; median PFS was 8.3 months (95% CI, 5.8-11.1) and 16.9 months (95% CI, 9.3-35.5), respectively. Median response duration was not reached; 73% of all responses and 82% of treatment-naive responses were ongoing at data cut-off; the longest response was ongoing at 66 months. Four patients [all with prior response of complete response (CR)] whose disease progressed during observation subsequently received second-course pembrolizumab. One patient each achieved CR and partial response (after data cut-off). Treatment-related AEs (TRAEs) occurred in 86% of patients and resulted in study discontinuation in 7.8%; 17% experienced grade 3/4 TRAE. CONCLUSIONS This 5-year analysis of KEYNOTE-001 represents the longest follow-up for pembrolizumab to date and confirms the durable antitumor activity and tolerability of pembrolizumab in advanced melanoma. CLINICAL TRIAL REGISTRY ClinicalTrials.gov, NCT01295827.
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Zhao Q, He J, Zeng Z. EP-1370 The impact of fractionation on lymphocyte counts in stage III NSCLC received chemoradiotherapy. Radiother Oncol 2019. [DOI: 10.1016/s0167-8140(19)31790-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Zhao Q, He J, Zeng Z. EP-1358 SBRT for de novo pulmonary tumors in patients with completely resected early stage NSCLC. Radiother Oncol 2019. [DOI: 10.1016/s0167-8140(19)31778-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Ablikim M, Achasov MN, Ahmed S, Albrecht M, Alekseev M, Amoroso A, An FF, An Q, Bai JZ, Bai Y, Bakina O, Baldini Ferroli R, Ban Y, Begzsuren K, Bennett DW, Bennett JV, Berger N, Bertani M, Bettoni D, Bianchi F, Boger E, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cetin SA, Chai J, Chang JF, Chelkov G, Chen G, Chen HS, Chen JC, Chen ML, Chen PL, Chen SJ, Chen XR, Chen YB, Cheng W, Chu XK, Cibinetto G, Cossio F, Dai HL, Dai JP, 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, Duan PF, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Fegan S, Feldbauer F, Felici G, Feng CQ, Fioravanti E, Fritsch M, Fu CD, Gao Q, Gao XL, Gao Y, Gao YG, Gao Z, Garillon B, Garzia I, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Haddadi Z, Han S, Hao XQ, Harris FA, He KL, He XQ, Heinsius FH, Held T, Heng YK, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang JS, Huang XT, Huang XZ, Huang ZL, Hussain T, Ikegami Andersson W, Irshad M, Ji Q, Ji QP, Ji XB, Ji XL, Jiang XS, Jiang XY, Jiao JB, Jiao Z, Jin DP, Jin S, Jin Y, Johansson T, Julin A, Kalantar-Nayestanaki N, Kang XS, Kavatsyuk M, Ke BC, Keshk IK, Khan T, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kornicer M, Kuemmel M, Kuessner M, Kupsc A, Kurth M, Kühn W, Lange JS, Larin P, Lavezzi L, Leiber S, Leithoff H, Li C, Li C, Li DM, Li F, Li FY, Li G, Li HB, Li HJ, Li JC, Li JW, Li KJ, Li K, Li K, Li L, Li PL, Li PR, Li QY, Li T, Li WD, Li WG, Li XL, Li XN, Li XQ, Li ZB, Liang H, Liang YF, Liang YT, Liao GR, 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 HL, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu KY, Liu K, Liu LD, Liu Q, Liu SB, Liu X, Liu YB, Liu ZA, Liu Z, Long YF, Lou XC, Lu HJ, Lu JG, Lu Y, Lu YP, Luo CL, Luo MX, Luo T, Luo XL, Lusso S, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma T, Ma XN, Ma XY, Ma YM, Maas FE, Maggiora M, Maldaner 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, Niu XY, Olsen SL, Ouyang Q, Pacetti S, Pan Y, Papenbrock M, Patteri P, Pelizaeus M, Pellegrino J, Peng HP, Peng ZY, 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 XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Richter M, Ripka M, Rivetti A, Rolo M, Rong G, Rosner C, Sarantsev A, Savrié M, Schoenning K, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Sheng HY, Shi X, Song JJ, Song WM, Song XY, Sosio S, Sowa C, Spataro S, 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, Tiemens M, Tsednee B, Uman I, Wang B, Wang BL, Wang CW, Wang D, Wang DY, Wang D, Wang K, Wang LL, Wang LS, Wang M, Wang M, Wang P, Wang PL, Wang WP, Wang XF, Wang Y, Wang YF, Wang Z, Wang ZG, Wang ZY, Wang Z, Weber T, Wei DH, Weidenkaff P, Wen SP, Wiedner U, Wolke M, Wu LH, Wu LJ, Wu Z, Xia L, Xia X, Xia Y, Xiao D, Xiao YJ, Xiao ZJ, Xie YG, Xie YH, Xiong XA, Xiu QL, Xu GF, Xu JJ, Xu L, Xu QJ, Xu XP, Yan F, Yan L, Yan WB, Yan WC, Yan YH, Yang HJ, Yang HX, Yang L, Yang RX, Yang YH, Yang YX, Yang Y, Yang ZQ, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu JS, Yu JS, Yuan CZ, 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 SF, Zhang TJ, Zhang XY, Zhang Y, Zhang YH, Zhang YT, 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 WJ, Zheng YH, Zhong B, Zhou L, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou X, Zhou X, Zhu AN, Zhu J, Zhu J, Zhu K, Zhu KJ, Zhu S, Zhu SH, Zhu XL, Zhu YC, Zhu YS, Zhu ZA, Zhuang J, Zou BS, Zou JH. Measurement of the Dynamics of the Decays D_{s}^{+}→η^{(')}e^{+}ν_{e}. PHYSICAL REVIEW LETTERS 2019; 122:121801. [PMID: 30978074 DOI: 10.1103/physrevlett.122.121801] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 02/27/2019] [Indexed: 06/09/2023]
Abstract
Using e^{+}e^{-} annihilation data corresponding to an integrated luminosity of 3.19 fb^{-1} collected at a center-of-mass energy of 4.178 GeV with the BESIII detector, we measure the absolute branching fractions B_{D_{s}^{+}→ηe^{+}ν_{e}}=(2.323±0.063_{stat}±0.063_{syst})% and B_{D_{s}^{+}→η^{'}e^{+}ν_{e}}=(0.824±0.073_{stat}±0.027_{syst})% via a tagged analysis technique, where one D_{s} is fully reconstructed in a hadronic mode. Combining these measurements with previous BESIII measurements of B_{D^{+}→η^{(')}e^{+}ν_{e}}, the η-η^{'} mixing angle in the quark flavor basis is determined to be ϕ_{P}=(40.1±2.1_{stat}±0.7_{syst})°. From the first measurements of the dynamics of D_{s}^{+}→η^{(')}e^{+}ν_{e} decays, the products of the hadronic form factors f_{+}^{η^{(')}}(0) and the Cabibbo-Kobayashi-Maskawa matrix element |V_{cs}| are determined with different form factor parametrizations. For the two-parameter series expansion, the results are f_{+}^{η}(0)|V_{cs}|=0.4455±0.0053_{stat}±0.0044_{syst} and f_{+}^{η^{'}}(0)|V_{cs}|=0.477±0.049_{stat}±0.011_{syst}.
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Guo BH, Zhao Q, Li HY. TUG1 promotes the development of prostate cancer by regulating RLIM. EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES 2019; 23:1926-1933. [PMID: 30915735 DOI: 10.26355/eurrev_201903_17230] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The aim of this study was to investigate the specific role of Taurine up-regulated gene 1 (TUG1) in the development of prostate cancer (PCa), and to explore its underlying mechanism. PATIENTS AND METHODS The serum level of TUG1 in healthy subjects, benign prostatic hyperplasia (BPH) patients and PCa patients was detected by quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). The correlation between TUG1 expression and clinical indexes of PCa patients was analyzed. TUG1 expression in PCa cells and human normal prostate cells was determined by qRT-PCR as well. Overexpression or knockdown of TUG1 was achieved by liposomal transfection. Subsequently, the regulatory effects of TUG1 on the proliferative and migratory capacities of DU145 cells were accessed by Cell Counting Kit-8 (CCK-8) assay, colony formation assay and transwell assay, respectively. An online software was used to predict whether RLIM could be regulated by TUG1, which was further verified by qRT-PCR. After RLIM knockdown in DU145 cells, the proliferative and migratory capacities were also determined. Finally, Western blot was conducted to determine relative protein expressions in the TGF-β1/Smad pathway after altering TUG1 expression in DU145 cells. RESULTS TUG1 was highly expressed in serum samples of PCa patients when compared with healthy subjects and BPH patients. Besides, TUG1 expression in PCa patients with Gleason ≥ 7 was significantly higher than those with Gleason < 7. Meanwhile, TUG1 expression in PCa patients was remarkably higher than that of BPH patients at the PSA grey zone (4-10 ng/mg). ROC curves indicated that TUG1 might be a crucial hallmark to distinguish PCa patients from BPH patients and healthy subjects. The overexpression of TUG1 markedly promoted the proliferative and migratory capacities of DU145 cells. However, knockdown of TUG1 obtained the opposite results. QRT-PCR confirmed that TUG1 was positively correlated with RLIM at the mRNA level. RLIM knockdown significantly inhibited the proliferative and migratory capacities of DU145 cells. Furthermore, knockdown of TUG1 in DU145 cells markedly down-regulated TGF-β1 and p-Smad2, whereas up-regulated p-Smad7. CONCLUSIONS TUG1 is highly expressed in peripheral blood of PCa patients, which can serve as a potential diagnostic marker for PCa. The overexpression of TUG1 promotes the proliferative and migratory capacities of PCa cells. Furthermore, TUG1 promotes the development of PCa by regulating RLIM through the TGF-β1/Smad pathway.
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Ablikim M, Achasov MN, Ahmed S, Albrecht M, Amoroso A, An FF, An Q, Bai Y, Bakina O, Baldini Ferroli R, Ban Y, Bennett DW, Bennett JV, Berger N, Bertani M, Bettoni D, Bian JM, Bianchi F, Boger E, Boyko I, Briere RA, Cai H, Cai X, Cakir O, Calcaterra A, Cao GF, Cetin SA, Chai J, Chang JF, Chelkov G, Chen G, Chen HS, Chen JC, Chen ML, Chen PL, Chen SJ, Chen YB, Cibinetto G, Dai HL, Dai JP, 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, Duan PF, Fan JZ, Fang J, Fang SS, Fang X, Fang Y, Farinelli R, Fava L, Fegan S, Feldbauer F, Felici G, Feng CQ, Fritsch M, Fu CD, Gao Q, Gao XL, Gao Y, Gao YG, Gao Z, Garzia I, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu MH, Gu S, Gu YT, Guo AQ, Guo LB, Guo RP, Guo YP, Haddadi Z, Han S, Hao XQ, Harris FA, He KL, Heinsius FH, Held T, Heng YK, Holtmann T, Hou ZL, Hu C, Hu HM, Hu T, Hu Y, Huang GS, Huang JS, Huang XT, Huang XZ, Huang ZL, Hussain T, Ikegami Andersson W, Ji Q, Ji QP, Ji XB, Ji XL, Jiang XS, Jiang XY, Jiao JB, Jiao Z, Jin DP, Jin S, Jin Y, Johansson T, Julin A, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kavatsyuk M, Ke BC, Khan T, Khoukaz A, Kiese P, Kliemt R, Koch L, Kolcu OB, Kopf B, Kornicer M, Kuemmel M, Kuessner M, Kuhlmann M, Kupsc A, Kühn W, Lange JS, Lara M, Larin P, Lavezzi L, Leiber S, Leithoff H, Leng C, Li C, Li C, Li DM, Li F, Li FY, Li G, Li HB, Li HJ, Li JC, Li KJ, Li K, Li K, Li L, Li PL, Li PR, Li QY, Li T, Li WD, Li WG, Li XL, Li XN, Li XQ, Li ZB, Liang H, Liang YF, Liang YT, Liao GR, Lin DX, Liu B, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JP, Liu JY, Liu K, Liu KY, Liu K, Liu PL, Liu Q, Liu SB, Liu X, Liu YB, Liu ZA, Liu Z, Long YF, Lou XC, Lu HJ, Lu JG, Lu Y, Lu YP, Luo CL, Luo MX, Luo XL, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma T, Ma XN, Ma XY, Ma YM, Maas FE, Maggiora M, Malik QA, 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, Morello G, Muchnoi NY, Muramatsu H, Mustafa A, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu SL, Niu XY, Olsen SL, Ouyang Q, Pacetti S, Pan Y, Papenbrock M, Patteri P, Pelizaeus M, Pellegrino J, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Pitka A, Poling R, Prasad V, Qi HR, Qi M, Qian S, Qiao CF, Qin N, Qin XS, Qin ZH, Qiu JF, Rashid KH, Redmer CF, Richter M, Ripka M, Rolo M, Rong G, Rosner C, Ruan XD, Sarantsev A, Savrié M, Schnier C, Schoenning K, Shao M, Shen CP, Shen PX, Shen XY, Sheng HY, Song JJ, Song WM, Song XY, Sosio S, Sowa C, Spataro S, Sun GX, Sun JF, Sun L, Sun SS, Sun XH, Sun YJ, Sun YK, Sun YZ, Sun ZJ, Sun ZT, Tang CJ, Tang GY, Tang X, Tapan I, Tiemens M, Tsednee B, Uman I, Varner GS, Wang B, Wang BL, Wang DY, Wang D, Wang K, Wang LL, Wang LS, Wang M, Wang M, Wang P, Wang PL, Wang WP, Wang XF, Wang Y, Wang YD, Wang YF, Wang YQ, Wang Z, Wang ZG, Wang ZH, Wang ZY, Wang Z, Weber T, Wei DH, Weidenkaff P, Wen SP, Wiedner U, Wolke M, Wu LH, Wu LJ, Wu Z, Xia L, Xia X, Xia Y, Xiao D, Xiao H, Xiao YJ, Xiao ZJ, Xie YG, Xie YH, Xiong XA, Xiu QL, Xu GF, Xu JJ, Xu L, Xu QJ, Xu QN, Xu XP, Yan L, Yan WB, Yan WC, Yan WC, Yan YH, Yang HJ, Yang HX, Yang L, Yang YH, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yuan CZ, Yuan Y, Yuncu A, Zafar AA, Zallo A, Zeng Y, Zeng Z, 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 SQ, Zhang XY, Zhang YH, Zhang YT, 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 WJ, Zheng YH, Zhong B, Zhou L, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YX, Zhu J, Zhu J, Zhu K, Zhu KJ, Zhu S, Zhu SH, Zhu XL, Zhu YC, Zhu YS, Zhu ZA, Zhuang J, Zou BS, Zou JH. Evidence of a Resonant Structure in the e^{+}e^{-}→π^{+}D^{0}D^{*-} Cross Section between 4.05 and 4.60 GeV. PHYSICAL REVIEW LETTERS 2019; 122:102002. [PMID: 30932669 DOI: 10.1103/physrevlett.122.102002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 02/10/2019] [Indexed: 06/09/2023]
Abstract
The cross section of the process e^{+}e^{-}→π^{+}D^{0}D^{*-} for center-of-mass energies from 4.05 to 4.60 GeV is measured precisely using data samples collected with the BESIII detector operating at the BEPCII storage ring. Two enhancements are clearly visible in the cross section around 4.23 and 4.40 GeV. Using several models to describe the dressed cross section yields stable parameters for the first enhancement, which has a mass of 4228.6±4.1±6.3 MeV/c^{2} and a width of 77.0±6.8±6.3 MeV, where the first uncertainties are statistical and the second ones are systematic. Our resonant mass is consistent with previous observations of the Y(4220) state and the theoretical prediction of a DD[over ¯]_{1}(2420) molecule. This result is the first observation of Y(4220) associated with an open-charm final state. Fits with three resonance functions with additional Y(4260), Y(4320), Y(4360), ψ(4415), or a new resonance do not show significant contributions from either of these resonances. The second enhancement is not from a single known resonance. It could contain contributions from ψ(4415) and other resonances, and a detailed amplitude analysis is required to better understand this enhancement.
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Gao YJ, Wei YX, Chen Q, Gao M, Luo DM, Chen Y, Wang Y, Zhao Q, Yu CQ, He LH, Xu Y. [Analysis of characteristics and influencing factors of fine particulate matters and submicron particulate matters in printing shop]. ZHONGHUA YU FANG YI XUE ZA ZHI [CHINESE JOURNAL OF PREVENTIVE MEDICINE] 2019; 53:284-288. [PMID: 30841668 DOI: 10.3760/cma.j.issn.0253-9624.2019.03.009] [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 analyze the physical characteristics of fine particulate matters (PM(2.5)) and submicron particulate matters (PM(1)), and investigate the factors influencing the emission peak of printer particles. Methods: A 12-hour particle concentration monitoring for PM(2.5) and PM(1) was conducted in a printing shop on January 5(th), 2018. PM(2.5) in the air was analyzed after the monitoring process to figure out morphological characteristics and element composition of printer particles. Besides, experiments were carried out in an enclosed space to detect the number concentration peaks of PM(1) during every printing process. Influencing factors investigated in this study were printer types, toner coverages and interval time between different printing processes. Results: The 12-hour particles concentration monitoring showed that the number concentration of PM(1) and the mass concentration of PM(2.5) were 7.510×10(4) pt/cm(3) and 96.85 μg/m(3). The diameter of most PM(2.5) was less than 100 nm, with a fractal dimension of 2.591. Most PM(2.5) appeared as regular spheres with typical agglomeration phenomenon, while some were in rhabditiform or irregular shapes. Element analysis showed that PM(2.5) was mainly composed of C, O, Si, Ca, with less metallic element. The PM(1) emission peak values of three printers were 3.60×10(4), 3.43×10(4), 0.31×10(4) pt/cm(3), respectively and the difference was not statistically significant (χ(2)=5.42, P>0.05). When the page coverage rate was 0%, 2.5%, 5%, 10%, 20% and 50%, the PM(1) emission peak value of printer A was 6.74×10(4), 4.62×10(4), 3.82×10(4), 2.82×10(4), 1.00×10(4) and 1.08×10(4) pt/cm(3), and the difference was also not statistically significant (χ(2)=7.01, P>0.05). The natural logarithm of PM(1) emission peak value in printing work was associated with the resting time before printing and the change value of heating roller temperature (r value was 0.83 and 0.89, respectively, all P values<0.05). Conclusion: PM(2.5) and PM(1) in the printing shop stayed at a high level. Particles appeared as various shapes and element compositions were complex. The temperature change of heating roller was one of most important factors that lead to the increased number concentration peak of PM(1).
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Cheng X, Mei B, Zuo Y, Wu H, Peng X, Zhao Q, Liu X, Gu E. Retracted:
A multicentre randomised controlled trial of the effect of intra‐operative dexmedetomidine on cognitive decline after surgery. Anaesthesia 2019; 74:741-750. [PMID: 30835822 DOI: 10.1111/anae.14606] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/18/2019] [Indexed: 12/21/2022]
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Wang YY, Ni Gedeli A, Fu CW, Jiang F, Zhao Q, Wang N, Jiang QW. [A cohort study on the association between dynamics of thyroid volume and the changes of physical growth as well as the comparison of different thyroid volume indexes in school-aged children]. ZHONGHUA LIU XING BING XUE ZA ZHI = ZHONGHUA LIUXINGBINGXUE ZAZHI 2019; 39:1544-1548. [PMID: 30572375 DOI: 10.3760/cma.j.issn.0254-6450.2018.12.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objectives: To investigate the association between the dynamics of thyroid volume and the changes of physical growth in school-aged children as well as to compare the applicability of different thyroid volume indexes, so as to explore more reliable methods for the assessment of thyroid volume. Methods: In October 2012, a multi-stage cluster sampling method was used to select a primary school in Minhang district of Shanghai, Haimen city of Jiangsu province and Yuhuan city of Zhejiang province, respectively. In these areas, a total number of 784 students aged 8-10 years were enrolled in the cohort. Demographic data was collected, while height and weight were measured, with BMI and body surface area (BSA) were calculated. Thyroid volume was examined by B-ultrasonography. Height volume index (HVI), weight and height volume index (WHVI), BMI volume index (BMIV) and BSA volume index (BSAV) were all applied to correct the thyroid volume. All students were followed up, one year later. Results: A total of 769 students with complete data on thyroid volume and physical growth were enrolled, including 378 boys (49.16%) and 391 girls (50.84%). Thyroid volume showed an increase with age, while growth of thyroid volume reduced with the increase of age (P<0.001). The thyroid volume showed a correlation with the changes of physical growth. The growth of height appeared as the dominant influencing factor for thyroid volume growth in those aged 8 and 10 years (P<0.05), while the growth of weight, BMI and BSA were all influencing factors for thyroid volume on students aged 9 years (P<0.05). Conclusions: Thyroid volume in school-aged children was a factor not only associated with age but also with physical growth which had not been considered in the currently used criteria. The inclusion of items as iodine intake, age, physical growth into the thyroid volume indexes seemed to be more reliable, in practice. For the assessment of goiter, HVI for students aged 8 and 10 years and BMIV for students aged 9 years might serve as better indicators.
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Ablikim M, Achasov MN, Ahmed S, Albrecht M, Alekseev M, Amoroso A, An FF, An Q, Bai Y, Bakina O, Ferroli RB, Ban Y, Begzsuren K, Bennett DW, Bennett JV, Berger N, Bertani M, Bettoni D, Bianchi F, Boyko I, Briere RA, Cai H, Cai X, Cakir O, Calcaterra A, Cao GF, Cetin SA, Chai J, Chang JF, Chang WL, Chelkov G, Chen G, Chen HS, Chen JC, Chen ML, Chen PL, Chen SJ, Chen YB, Cibinetto G, Cossio F, Dai HL, Dai JP, 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, Duan PF, Fan JZ, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Fegan S, Feldbauer F, Felici G, Feng CQ, Fritsch M, Fu CD, Fu Y, Gao Q, Gao XL, Gao Y, Gao YG, Gao Z, Garillon B, Garzia I, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Haddadi Z, Han S, Hao XQ, Harris FA, He KL, Heinsius FH, Held T, Heng YK, Holtmann T, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang JS, Huang XT, Huang XZ, Huang ZL, Hussain T, Andersson WI, Irshad M, Ji Q, Ji QP, Ji XB, Ji XL, Jiang XS, Jiang XY, Jiao JB, Jiao Z, Jin DP, Jin S, Jin Y, Johansson T, Julin A, Kalantar-Nayestanaki N, Kang XS, Kavatsyuk M, Ke BC, Khan T, Khoukaz A, Kiese P, Kliemt R, Koch L, Kolcu OB, Kopf B, Kornicer M, Kuemmel M, Kuessner M, Kupsc A, Kurth M, Kühn W, Lange JS, Lara M, Larin P, Lavezzi L, Leiber S, Leithoff H, Li C, Li C, Li DM, Li F, Li FY, Li G, Li HB, Li HJ, Li JC, Li JW, Li K, Li L, Li PL, Li PR, Li QY, Li T, Li WD, Li WG, Li XL, Li XN, Li XQ, Li ZB, Liang H, Liang YF, Liang YT, Liao GR, 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 HL, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu K, Liu Q, Liu SB, Liu X, 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 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, 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 CM, Morello G, 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, Pellegrino J, 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 XS, Qin ZH, Qiu JF, Rashid KH, Redmer CF, Richter M, Ripka M, Rolo M, Rong G, Rosner C, Sarantsev A, Savrié M, Schnier C, Schoenning K, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Sheng HY, Shi X, Song JJ, Song WM, Song XY, Sosio S, Sowa C, Spataro S, 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, Tapan I, Tiemens M, Tsednee B, Uman I, Varner GS, Wang B, Wang BL, Wang CW, Wang DY, Wang D, Wang K, Wang LL, Wang LS, Wang M, Wang M, Wang P, Wang PL, Wang WP, Wang XF, Wang Y, Wang YF, Wang YQ, Wang Z, Wang ZG, Wang ZY, Wang Z, Weber T, Wei DH, Weidenkaff P, Wen SP, Wiedner U, Wolke M, Wu LH, Wu LJ, Wu Z, Xia L, Xia X, Xia Y, Xiao D, Xiao YJ, Xiao ZJ, Xie YG, Xie YH, Xiong XA, Xiu QL, Xu GF, Xu JJ, Xu L, Xu QJ, Xu QN, Xu XP, Yan F, Yan L, Yan WB, Yan WC, Yan YH, Yang HJ, Yang HX, Yang L, Yang SL, Yang YH, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yuan CZ, Yuan Y, Yuncu A, Zafar AA, Zallo A, Zeng Y, Zeng Z, 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 SF, Zhang TJ, Zhang XY, Zhang Y, Zhang YH, Zhang YT, 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 WJ, Zheng YH, Zhong B, Zhou L, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhu AN, Zhu J, Zhu J, Zhu K, Zhu KJ, Zhu S, Zhu SH, Zhu XL, Zhu YC, Zhu YS, Zhu ZA, Zhuang J, Zou BS, Zou JH. Determination of the Pseudoscalar Decay Constant f_{D_{s}^{+}} via D_{s}^{+}→μ^{+}ν_{μ}. PHYSICAL REVIEW LETTERS 2019; 122:071802. [PMID: 30848637 DOI: 10.1103/physrevlett.122.071802] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Revised: 01/18/2019] [Indexed: 06/09/2023]
Abstract
Using a 3.19 fb^{-1} data sample collected at an e^{+}e^{-} center-of-mass energy of E_{cm}=4.178 GeV with the BESIII detector, we measure the branching fraction of the leptonic decay D_{s}^{+}→μ^{+}ν_{μ} to be B_{D_{s}^{+}→μ^{+}ν_{μ}}=(5.49±0.16_{stat}±0.15_{syst})×10^{-3}. Combining our branching fraction with the masses of the D_{s}^{+} and μ^{+} and the lifetime of the D_{s}^{+}, we determine f_{D_{s}^{+}}|V_{cs}|=246.2±3.6_{stat}±3.5_{syst} MeV. Using the c→s quark mixing matrix element |V_{cs}| determined from a global standard model fit, we evaluate the D_{s}^{+} decay constant f_{D_{s}^{+}}=252.9±3.7_{stat}±3.6_{syst} MeV. Alternatively, using the value of f_{D_{s}^{+}} calculated by lattice quantum chromodynamics, we find |V_{cs}|=0.985±0.014_{stat}±0.014_{syst}. These values of B_{D_{s}^{+}→μ^{+}ν_{μ}}, f_{D_{s}^{+}}|V_{cs}|, f_{D_{s}^{+}} and |V_{cs}| are each the most precise results to date.
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