Spontaneous delayed migration or shortening after pipeline embolization device treatment of intracranial aneurysm: incidence, management, and risk factors

BACKGROUND

Studies reporting spontaneous delayed migration or shortening (SDMS) after treatment with the Pipeline Embolization Device (PED) are limited. This study aimed to evaluate the incidence of SDMS after PED treatment, propose management strategies, and identify the risk factors contributing to its occurrence.

METHODS

We retrospectively reviewed consecutive patients with an intracranial aneurysm (IA) treated with PEDs at three institutions. SDMS was classified as type I or II based on whether the PED covered the aneurysm neck.

RESULTS

The total cohort comprised 790 patients. SDMS was identified in 24 (3.04%) patients. Eighteen of the 24 patients had type I SDMS and did not require retreatment, while the remaining six patients had type II SDMS and all received retreatment. Multivariate logistic regression showed that the difference between the proximal and distal parent artery diameters (DPAD) (adjusted OR 2.977; 95% CI 1.054 to 8.405; P=0.039) and device tortuosity index (DTI) (adjusted OR 8.059; 95% CI 2.867 to 23.428; P<0.001) were independent predictors of SDMS after PED treatment, while the difference in length (DL) (adjusted OR 0.841; 95% CI 0.738 to 0.958; P=0.009) and PED plus coiling (adjusted OR 0.288; 95% CI 0.106 to 0.785; P=0.015) were protective factors.

CONCLUSION

The incidence of SDMS after PED treatment of IA was 3.04%. For patients with type I SDMS with incomplete aneurysm occlusion we recommend continuous imaging follow-up while, for patients with type II SDMS, we recommend aggressive retreatment. The DPAD and DTI were independent risk predictors of SDMS after PED treatment, while the DL and PED plus coiling were protective factors.

Coupled-Channel Analysis of the χ_{c1}(3872) Line Shape with BESIII Data

We perform a study of the χ_{c1}(3872) line shape using the data samples of e^{+}e^{-}→γχ_{c1}(3872), χ_{c1}(3872)→D^{0}D[over ¯]^{0}π^{0}, and π^{+}π^{-}J/ψ collected with the BESIII detector. The effects of the coupled channels and the off-shell D^{*0} are included in the parametrization of the line shape. The line shape mass parameter is obtained to be M_{X}=(3871.63±0.13_{-0.05}^{+0.06})  MeV. Two poles are found on the first and second Riemann sheets corresponding to the D^{*0}D[over ¯]^{0} branch cut. The pole location on the first sheet is much closer to the D^{*0}D[over ¯]^{0} threshold than the other, and is determined to be 7.04±0.15_{-0.08}^{+0.07}  MeV above the D^{0}D[over ¯]^{0}π^{0} threshold with an imaginary part -0.19±0.08_{-0.19}^{+0.14}  MeV.

Observation of the Anomalous Shape of X(1840) in J/ψ→γ3(π^{+}π^{-}) Indicating a Second Resonance Near pp[over ¯] Threshold

Using a sample of (10087±44)×10^{6}  J/ψ events, which is about 45 times larger than that was previously analyzed, a further investigation on the J/ψ→γ3(π^{+}π^{-}) decay is performed. A significant distortion at 1.84  GeV/c^{2} in the line shape of the 3(π^{+}π^{-}) invariant mass spectrum is observed for the first time, which could be resolved by two overlapping resonant structures, X(1840) and X(1880). The new state X(1880) is observed with a statistical significance larger than 10σ. The mass and width of X(1880) are determined to be 1882.1±1.7±0.7  MeV/c^{2} and 30.7±5.5±2.4  MeV, respectively, which indicates the existence of a pp[over ¯] bound state.

Study of the f_{0}(980) and f_{0}(500) Scalar Mesons through the Decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}

Using e^{+}e^{-} collision data corresponding to an integrated luminosity of 7.33  fb^{-1} recorded by the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV, we present an analysis of the decay D_{s}^{+}→π^{+}π^{-}e^{+}ν_{e}, where the D_{s}^{+} is produced via the process e^{+}e^{-}→D_{s}^{*±}D_{s}^{∓}. We observe the f_{0}(980) in the π^{+}π^{-} system and the branching fraction of the decay D_{s}^{+}→f_{0}(980)e^{+}ν_{e} with f_{0}(980)→π^{+}π^{-} measured to be (1.72±0.13_{stat}±0.10_{syst})×10^{-3}, where the uncertainties are statistical and systematic, respectively. The dynamics of the D_{s}^{+}→f_{0}(980)e^{+}ν_{e} decay are studied with the simple pole parametrization of the hadronic form factor and the Flatté formula describing the f_{0}(980) in the differential decay rate, and the product of the form factor f_{+}^{f_{0}}(0) and the c→s Cabibbo-Kobayashi-Maskawa matrix element |V_{cs}| is determined for the first time to be f_{+}^{f_{0}}(0)|V_{cs}|=0.504±0.017_{stat}±0.035_{syst}. Furthermore, the decay D_{s}^{+}→f_{0}(500)e^{+}ν_{e} is searched for the first time but no signal is found. The upper limit on the branching fraction of D_{s}^{+}→f_{0}(500)e^{+}ν_{e}, f_{0}(500)→π^{+}π^{-} decay is set to be 3.3×10^{-4} at 90% confidence level.

Observation of D^{+}→K_{S}^{0}a_{0}(980)^{+} in the Amplitude Analysis of D^{+}→K_{S}^{0}π^{+}η

We perform for the first time an amplitude analysis of the decay D^{+}→K_{S}^{0}π^{+}η and report the observation of the decay D^{+}→K_{S}^{0}a_{0}(980)^{+} using 2.93  fb^{-1} of e^{+}e^{-} collision data taken at a center-of-mass energy of 3.773 GeV with the BESIII detector. As the only W-annihilation-free decay among D to a_{0}(980) pseudoscalar, D^{+}→K_{S}^{0}a_{0}(980)^{+} is the ideal decay in extracting the contributions of the W-emission amplitudes involving a_{0}(980) and to study the final-state interactions. The absolute branching fraction of D^{+}→K_{S}^{0}π^{+}η is measured to be (1.27±0.04_{stat}±0.03_{syst})%. The branching fractions of intermediate processes D^{+}→K_{S}^{0}a_{0}(980)^{+} with a_{0}(980)^{+}→π^{+}η and D^{+}→π^{+}K[over ¯]_{0}^{*}(1430)^{0} with K[over ¯]_{0}^{*}(1430)^{0}→K_{S}^{0}η are measured to be (1.33±0.05_{stat}±0.04_{syst})% and (0.14±0.03_{stat}±0.01_{syst})%, respectively.

Observation of Significant Flavor-SU(3) Breaking in the Kaon Wave Function at 12<Q^{2}<25 GeV^{2} and Discovery of the Charmless Decay ψ(3770)→K_{S}^{0}K_{L}^{0}

We present cross sections for the reaction e^{+}e^{-}→K_{S}^{0}K_{L}^{0} at center-of-mass energies ranging from 3.51 to 4.95 GeV using data samples collected in the BESIII experiment, corresponding to a total integrated luminosity of 26.5  fb^{-1}. The ratio of neutral-to-charged kaon form factors at large momentum transfers (12 Collapse

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Affiliation(s)

M Ablikim Institute of High Energy Physics, Beijing 100049, People's Republic of China
M N Achasov Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
P Adlarson Uppsala University, Box 516, SE-75120 Uppsala, Sweden
X C Ai Zhengzhou University, Zhengzhou 450001, People's Republic of China
R Aliberti Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
A Amoroso University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
M R An Liaoning Normal University, Dalian 116029, People's Republic of China
Q An State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Bai Southeast University, Nanjing 211100, People's Republic of China
O Bakina Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
I Balossino INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
Y Ban Peking University, Beijing 100871, People's Republic of China
H-R Bao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
V Batozskaya Institute of High Energy Physics, Beijing 100049, People's Republic of China National Centre for Nuclear Research, Warsaw 02-093, Poland
K Begzsuren Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
N Berger Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
M Berlowski National Centre for Nuclear Research, Warsaw 02-093, Poland
M Bertani INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
D Bettoni INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
F Bianchi University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
E Bianco University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
A Bortone University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
I Boyko Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
R A Briere Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
A Brueggemann University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
H Cai Wuhan University, Wuhan 430072, People's Republic of China
X Cai Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
A Calcaterra INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
G F Cao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
N Cao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S A Cetin Turkish Accelerator Center Particle Factory Group, Istinye University, 34010 Istanbul, Turkey
J F Chang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
T T Chang Xinyang Normal University, Xinyang 464000, People's Republic of China
W L Chang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G R Che Nankai University, Tianjin 300071, People's Republic of China
G Chelkov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
C Chen Nankai University, Tianjin 300071, People's Republic of China
Chao Chen Soochow University, Suzhou 215006, People's Republic of China
G Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China
H S Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M L Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S J Chen Nanjing University, Nanjing 210093, People's Republic of China
S L Chen North China Electric Power University, Beijing 102206, People's Republic of China
S M Chen Tsinghua University, Beijing 100084, People's Republic of China
T Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X R Chen Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y B Chen Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Q Chen Jilin University, Changchun 130012, People's Republic of China
Z J Chen Hunan University, Changsha 410082, People's Republic of China
S K Choi Chung-Ang University, Seoul, 06974, Republic of Korea
X Chu Nankai University, Tianjin 300071, People's Republic of China
G Cibinetto INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
S C Coen Bochum Ruhr-University, D-44780 Bochum, Germany
F Cossio INFN, I-10125, Turin, Italy
J J Cui Shandong University, Jinan 250100, People's Republic of China
H L Dai Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J P Dai Yunnan University, Kunming 650500, People's Republic of China
A Dbeyssi Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
R E de Boer Bochum Ruhr-University, D-44780 Bochum, Germany
D Dedovich Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Z Y Deng Institute of High Energy Physics, Beijing 100049, People's Republic of China
A Denig Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
I Denysenko Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
M Destefanis University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
F De Mori University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
B Ding Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Jinan, Jinan 250022, People's Republic of China
X X Ding Peking University, Beijing 100871, People's Republic of China
Y Ding Liaoning University, Shenyang 110036, People's Republic of China
Y Ding Jilin University, Changchun 130012, People's Republic of China
J Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L Y Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M Y Dong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Dong Wuhan University, Wuhan 430072, People's Republic of China
M C Du Institute of High Energy Physics, Beijing 100049, People's Republic of China
S X Du Zhengzhou University, Zhengzhou 450001, People's Republic of China
Z H Duan Nanjing University, Nanjing 210093, People's Republic of China
P Egorov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Y H Fan North China Electric Power University, Beijing 102206, People's Republic of China
J Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
S S Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W X Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Q Fang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
R Farinelli INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
L Fava University of Eastern Piedmont, I-15121 Alessandria, Italy INFN, I-10125, Turin, Italy
F Feldbauer Bochum Ruhr-University, D-44780 Bochum, Germany
G Felici INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
C Q Feng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J H Feng Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
K Fischer University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
M Fritsch Bochum Ruhr-University, D-44780 Bochum, Germany
C D Fu Institute of High Energy Physics, Beijing 100049, People's Republic of China
J L Fu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y W Fu Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Gao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y N Gao Peking University, Beijing 100871, People's Republic of China
Yang Gao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
S Garbolino INFN, I-10125, Turin, Italy
I Garzia INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
P T Ge Wuhan University, Wuhan 430072, People's Republic of China
Z W Ge Nanjing University, Nanjing 210093, People's Republic of China
C Geng Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
E M Gersabeck University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
A Gilman University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
K Goetzen GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
L Gong Liaoning University, Shenyang 110036, People's Republic of China
W X Gong Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W Gradl Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
S Gramigna INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
M Greco University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
M H Gu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y T Gu Guangxi University, Nanning 530004, People's Republic of China
C Y Guan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z L Guan Henan University of Technology, Zhengzhou 450001, People's Republic of China
A Q Guo Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L B Guo Nanjing Normal University, Nanjing 210023, People's Republic of China
M J Guo Shandong University, Jinan 250100, People's Republic of China
R P Guo Shandong Normal University, Jinan 250014, People's Republic of China
Y P Guo Fudan University, Shanghai 200433, People's Republic of China
A Guskov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
J Gutierrez Indiana University, Bloomington, Indiana 47405, USA
T T Han Institute of High Energy Physics, Beijing 100049, People's Republic of China
W Y Han Liaoning Normal University, Dalian 116029, People's Republic of China
X Q Hao Henan Normal University, Xinxiang 453007, People's Republic of China
F A Harris University of Hawaii, Honolulu, Hawaii 96822, USA
K K He Soochow University, Suzhou 215006, People's Republic of China
K L He Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F H H Heinsius Bochum Ruhr-University, D-44780 Bochum, Germany
C H Heinz Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y K Heng Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C Herold Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
T Holtmann Bochum Ruhr-University, D-44780 Bochum, Germany
P C Hong Fudan University, Shanghai 200433, People's Republic of China
G Y Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y R Hou University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z L Hou Institute of High Energy Physics, Beijing 100049, People's Republic of China
B Y Hu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H M Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J F Hu South China Normal University, Guangzhou 510006, People's Republic of China
T Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y Hu Institute of High Energy Physics, Beijing 100049, People's Republic of China
G S Huang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
K X Huang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
L Q Huang Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X T Huang Shandong University, Jinan 250100, People's Republic of China
Y P Huang Institute of High Energy Physics, Beijing 100049, People's Republic of China
T Hussain University of the Punjab, Lahore-54590, Pakistan
N Hüsken Indiana University, Bloomington, Indiana 47405, USA Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
N In der Wiesche University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
M Irshad State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J Jackson Indiana University, Bloomington, Indiana 47405, USA
S Jaeger Bochum Ruhr-University, D-44780 Bochum, Germany
S Janchiv Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
J H Jeong Chung-Ang University, Seoul, 06974, Republic of Korea
Q Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q P Ji Henan Normal University, Xinxiang 453007, People's Republic of China
X B Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X L Ji Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Y Ji Shandong University, Jinan 250100, People's Republic of China
X Q Jia Shandong University, Jinan 250100, People's Republic of China
Z K Jia State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H J Jiang Wuhan University, Wuhan 430072, People's Republic of China
P C Jiang Peking University, Beijing 100871, People's Republic of China
S S Jiang Liaoning Normal University, Dalian 116029, People's Republic of China
T J Jiang Hangzhou Normal University, Hangzhou 310036, People's Republic of China
X S Jiang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y Jiang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J B Jiao Shandong University, Jinan 250100, People's Republic of China
Z Jiao Huangshan College, Huangshan 245000, People's Republic of China
S Jin Nanjing University, Nanjing 210093, People's Republic of China
Y Jin University of Jinan, Jinan 250022, People's Republic of China
M Q Jing Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X M Jing University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Johansson Uppsala University, Box 516, SE-75120 Uppsala, Sweden
X Kui Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Kabana Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica 1000000, Chile
N Kalantar-Nayestanaki University of Groningen, NL-9747 AA Groningen, The Netherlands
X L Kang China University of Geosciences, Wuhan 430074, People's Republic of China
X S Kang Liaoning University, Shenyang 110036, People's Republic of China
M Kavatsyuk University of Groningen, NL-9747 AA Groningen, The Netherlands
B C Ke Zhengzhou University, Zhengzhou 450001, People's Republic of China
V Khachatryan Indiana University, Bloomington, Indiana 47405, USA
A Khoukaz University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
R Kiuchi Institute of High Energy Physics, Beijing 100049, People's Republic of China
R Kliemt GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
O B Kolcu Turkish Accelerator Center Particle Factory Group, Istinye University, 34010 Istanbul, Turkey
B Kopf Bochum Ruhr-University, D-44780 Bochum, Germany
M Kuessner Bochum Ruhr-University, D-44780 Bochum, Germany
A Kupsc National Centre for Nuclear Research, Warsaw 02-093, Poland Uppsala University, Box 516, SE-75120 Uppsala, Sweden
W Kühn Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
J J Lane University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
P Larin Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
A Lavania Indian Institute of Technology Madras, Chennai 600036, India
L Lavezzi University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
T T Lei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Z H Lei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H Leithoff Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
M Lellmann Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
T Lenz Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
C Li Qufu Normal University, Qufu 273165, People's Republic of China
C Li Nankai University, Tianjin 300071, People's Republic of China
C H Li Liaoning Normal University, Dalian 116029, People's Republic of China
Cheng Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
D M Li Zhengzhou University, Zhengzhou 450001, People's Republic of China
F Li Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
G Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H B Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H J Li Henan Normal University, Xinxiang 453007, People's Republic of China
H N Li South China Normal University, Guangzhou 510006, People's Republic of China
Hui Li Nankai University, Tianjin 300071, People's Republic of China
J R Li Tsinghua University, Beijing 100084, People's Republic of China
J S Li Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
J W Li Shandong University, Jinan 250100, People's Republic of China
Ke Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
L J Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L K Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
Lei Li Renmin University of China, Beijing 100872, People's Republic of China
M H Li Nankai University, Tianjin 300071, People's Republic of China
P R Li Lanzhou University, Lanzhou 730000, People's Republic of China
Q X Li Shandong University, Jinan 250100, People's Republic of China
S X Li Fudan University, Shanghai 200433, People's Republic of China
T Li Shandong University, Jinan 250100, People's Republic of China
W D Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W G Li Institute of High Energy Physics, Beijing 100049, People's Republic of China
X H Li State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X L Li Shandong University, Jinan 250100, People's Republic of China
Xiaoyu Li Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y G Li Peking University, Beijing 100871, People's Republic of China
Z J Li Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Z X Li Guangxi University, Nanning 530004, People's Republic of China
C Liang Nanjing University, Nanjing 210093, People's Republic of China
H Liang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H Liang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y F Liang Sichuan University, Chengdu 610064, People's Republic of China
Y T Liang Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G R Liao Guangxi Normal University, Guilin 541004, People's Republic of China
L Z Liao Shandong University, Jinan 250100, People's Republic of China
Y P Liao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J Libby Indian Institute of Technology Madras, Chennai 600036, India
A Limphirat Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
D X Lin Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Lin Institute of High Energy Physics, Beijing 100049, People's Republic of China
B J Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
B X Liu Wuhan University, Wuhan 430072, People's Republic of China
C Liu Jilin University, Changchun 130012, People's Republic of China
C X Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
F H Liu Shanxi University, Taiyuan 030006, People's Republic of China
Fang Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Feng Liu Central China Normal University, Wuhan 430079, People's Republic of China
G M Liu South China Normal University, Guangzhou 510006, People's Republic of China
H Liu Lanzhou University, Lanzhou 730000, People's Republic of China
H B Liu Guangxi University, Nanning 530004, People's Republic of China
H M Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Huanhuan Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Huihui Liu Henan University of Science and Technology, Luoyang 471003, People's Republic of China
J B Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J Y Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
K Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
K Y Liu Liaoning University, Shenyang 110036, People's Republic of China
Ke Liu Henan University of Technology, Zhengzhou 450001, People's Republic of China
L Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
L C Liu Nankai University, Tianjin 300071, People's Republic of China
Lu Liu Nankai University, Tianjin 300071, People's Republic of China
M H Liu Fudan University, Shanghai 200433, People's Republic of China
P L Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q Liu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S B Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
T Liu Fudan University, Shanghai 200433, People's Republic of China
W K Liu Nankai University, Tianjin 300071, People's Republic of China
W M Liu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Liu Lanzhou University, Lanzhou 730000, People's Republic of China
Y Liu Lanzhou University, Lanzhou 730000, People's Republic of China
Y Liu Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y B Liu Nankai University, Tianjin 300071, People's Republic of China
Z A Liu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z Q Liu Shandong University, Jinan 250100, People's Republic of China
X C Lou Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F X Lu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H J Lu Huangshan College, Huangshan 245000, People's Republic of China
J G Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
X L Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Lu Central South University, Changsha 410083, People's Republic of China
Y P Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Z H Lu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C L Luo Nanjing Normal University, Nanjing 210023, People's Republic of China
M X Luo Zhejiang University, Hangzhou 310027, People's Republic of China
T Luo Fudan University, Shanghai 200433, People's Republic of China
X L Luo Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
X R Lyu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y F Lyu Nankai University, Tianjin 300071, People's Republic of China
F C Ma Liaoning University, Shenyang 110036, People's Republic of China
H Ma Yunnan University, Kunming 650500, People's Republic of China
H L Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China
J L Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L L Ma Shandong University, Jinan 250100, People's Republic of China
M M Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q M Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China
R Q Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Ma Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y Ma Peking University, Beijing 100871, People's Republic of China
Y M Ma Institute of Modern Physics, Lanzhou 730000, People's Republic of China
F E Maas Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
M Maggiora University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
S Malde University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
Q A Malik University of the Punjab, Lahore-54590, Pakistan
A Mangoni INFN Sezione di Perugia, I-06100 Perugia, Italy
Y J Mao Peking University, Beijing 100871, People's Republic of China
Z P Mao Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Marcello University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
Z X Meng University of Jinan, Jinan 250022, People's Republic of China
J G Messchendorp GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany University of Groningen, NL-9747 AA Groningen, The Netherlands
G Mezzadri INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy
H Miao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T J Min Nanjing University, Nanjing 210093, People's Republic of China
R E Mitchell Indiana University, Bloomington, Indiana 47405, USA
X H Mo Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B Moses Indiana University, Bloomington, Indiana 47405, USA
N Yu Muchnoi Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
J Muskalla Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y Nefedov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
F Nerling Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
I B Nikolaev Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
Z Ning Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
S Nisar COMSATS University Islamabad, Lahore Campus, Defence Road, Off Raiwind Road, 54000 Lahore, Pakistan
Q L Niu Lanzhou University, Lanzhou 730000, People's Republic of China
W D Niu Soochow University, Suzhou 215006, People's Republic of China
Y Niu Shandong University, Jinan 250100, People's Republic of China
S L Olsen University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q Ouyang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Pacetti INFN Sezione di Perugia, I-06100 Perugia, Italy University of Perugia, I-06100 Perugia, Italy
X Pan Soochow University, Suzhou 215006, People's Republic of China
Y Pan Southeast University, Nanjing 211100, People's Republic of China
A Pathak Jilin University, Changchun 130012, People's Republic of China
P Patteri INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044 Frascati, Italy
Y P Pei State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
M Pelizaeus Bochum Ruhr-University, D-44780 Bochum, Germany
H P Peng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Y Peng Lanzhou University, Lanzhou 730000, People's Republic of China
K Peters GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
J L Ping Nanjing Normal University, Nanjing 210023, People's Republic of China
R G Ping Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Plura Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
V Prasad Instituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica 1000000, Chile
F Z Qi Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Qi State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
H R Qi Tsinghua University, Beijing 100084, People's Republic of China
M Qi Nanjing University, Nanjing 210093, People's Republic of China
T Y Qi Fudan University, Shanghai 200433, People's Republic of China
S Qian Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W B Qian University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C F Qiao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J J Qin University of South China, Hengyang 421001, People's Republic of China
L Q Qin Guangxi Normal University, Guilin 541004, People's Republic of China
X S Qin Shandong University, Jinan 250100, People's Republic of China
Z H Qin Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J F Qiu Institute of High Energy Physics, Beijing 100049, People's Republic of China
S Q Qu Tsinghua University, Beijing 100084, People's Republic of China
C F Redmer Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
K J Ren Liaoning Normal University, Dalian 116029, People's Republic of China
A Rivetti INFN, I-10125, Turin, Italy
M Rolo INFN, I-10125, Turin, Italy
G Rong Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Ch Rosner Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
S N Ruan Nankai University, Tianjin 300071, People's Republic of China
N Salone National Centre for Nuclear Research, Warsaw 02-093, Poland
A Sarantsev Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
Y Schelhaas Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
K Schoenning Uppsala University, Box 516, SE-75120 Uppsala, Sweden
M Scodeggio INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122 Ferrara, Italy University of Ferrara, I-44122 Ferrara, Italy
K Y Shan Fudan University, Shanghai 200433, People's Republic of China
W Shan Hunan Normal University, Changsha 410081, People's Republic of China
X Y Shan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J F Shangguan Soochow University, Suzhou 215006, People's Republic of China
L G Shao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
M Shao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C P Shen Fudan University, Shanghai 200433, People's Republic of China
H F Shen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
W H Shen University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Shen Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B A Shi University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H C Shi State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
J L Shi Fudan University, Shanghai 200433, People's Republic of China
J Y Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China
Q Q Shi Soochow University, Suzhou 215006, People's Republic of China
R S Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Shi Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J J Song Henan Normal University, Xinxiang 453007, People's Republic of China
T Z Song Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
W M Song Institute of High Energy Physics, Beijing 100049, People's Republic of China Jilin University, Changchun 130012, People's Republic of China
Y J Song Fudan University, Shanghai 200433, People's Republic of China
Y X Song Peking University, Beijing 100871, People's Republic of China
S Sosio University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
S Spataro University of Turin and INFN, University of Turin, I-10125 Turin, Italy INFN, I-10125, Turin, Italy
F Stieler Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
Y J Su University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
G B Sun Wuhan University, Wuhan 430072, People's Republic of China
G X Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Sun University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H K Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
J F Sun Henan Normal University, Xinxiang 453007, People's Republic of China
K Sun Tsinghua University, Beijing 100084, People's Republic of China
L Sun Wuhan University, Wuhan 430072, People's Republic of China
S S Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
T Sun Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
W Y Sun Jilin University, Changchun 130012, People's Republic of China
Y Sun China University of Geosciences, Wuhan 430074, People's Republic of China
Y J Sun State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Y Z Sun Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z T Sun Shandong University, Jinan 250100, People's Republic of China
Y X Tan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C J Tang Sichuan University, Chengdu 610064, People's Republic of China
G Y Tang Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Tang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Y A Tang Wuhan University, Wuhan 430072, People's Republic of China
L Y Tao University of South China, Hengyang 421001, People's Republic of China
Q T Tao Hunan University, Changsha 410082, People's Republic of China
M Tat University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
J X Teng State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
V Thoren Uppsala University, Box 516, SE-75120 Uppsala, Sweden
W H Tian Shanxi Normal University, Linfen 041004, People's Republic of China
W H Tian Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Y Tian Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z F Tian Wuhan University, Wuhan 430072, People's Republic of China
I Uman Near East University, Nicosia, North Cyprus, 99138, Mersin 10, Turkey
Y Wan Soochow University, Suzhou 215006, People's Republic of China
S J Wang Shandong University, Jinan 250100, People's Republic of China
B Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
B L Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Bo Wang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
C W Wang Nanjing University, Nanjing 210093, People's Republic of China
D Y Wang Peking University, Beijing 100871, People's Republic of China
F Wang University of South China, Hengyang 421001, People's Republic of China
H J Wang Lanzhou University, Lanzhou 730000, People's Republic of China
J P Wang Shandong University, Jinan 250100, People's Republic of China
K Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L L Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
M Wang Shandong University, Jinan 250100, People's Republic of China
Meng Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
N Y Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S Wang Fudan University, Shanghai 200433, People's Republic of China
S Wang Lanzhou University, Lanzhou 730000, People's Republic of China
T Wang Fudan University, Shanghai 200433, People's Republic of China
T J Wang Nankai University, Tianjin 300071, People's Republic of China
W Wang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
W Wang University of South China, Hengyang 421001, People's Republic of China
W P Wang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Wang Peking University, Beijing 100871, People's Republic of China
X F Wang Lanzhou University, Lanzhou 730000, People's Republic of China
X J Wang Liaoning Normal University, Dalian 116029, People's Republic of China
X L Wang Fudan University, Shanghai 200433, People's Republic of China
Y Wang Tsinghua University, Beijing 100084, People's Republic of China
Y D Wang North China Electric Power University, Beijing 102206, People's Republic of China
Y F Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y L Wang Henan Normal University, Xinxiang 453007, People's Republic of China
Y N Wang North China Electric Power University, Beijing 102206, People's Republic of China
Y Q Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Yaqian Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China Hebei University, Baoding 071002, People's Republic of China
Yi Wang Tsinghua University, Beijing 100084, People's Republic of China
Z Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Z L Wang University of South China, Hengyang 421001, People's Republic of China
Z Y Wang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Ziyi Wang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
D Wei University of Science and Technology Liaoning, Anshan 114051, People's Republic of China
D H Wei Guangxi Normal University, Guilin 541004, People's Republic of China
F Weidner University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
S P Wen Institute of High Energy Physics, Beijing 100049, People's Republic of China
C W Wenzel Bochum Ruhr-University, D-44780 Bochum, Germany
U Wiedner Bochum Ruhr-University, D-44780 Bochum, Germany
G Wilkinson University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
M Wolke Uppsala University, Box 516, SE-75120 Uppsala, Sweden
L Wollenberg Bochum Ruhr-University, D-44780 Bochum, Germany
C Wu Liaoning Normal University, Dalian 116029, People's Republic of China
J F Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China China Center of Advanced Science and Technology, Beijing 100190, People's Republic of China
L H Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China
L J Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Wu Fudan University, Shanghai 200433, People's Republic of China
X H Wu Jilin University, Changchun 130012, People's Republic of China
Y Wu University of Science and Technology of China, Hefei 230026, People's Republic of China
Y H Wu Soochow University, Suzhou 215006, People's Republic of China
Y J Wu Institute of Modern Physics, Lanzhou 730000, People's Republic of China
Z Wu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
L Xia State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X M Xian Liaoning Normal University, Dalian 116029, People's Republic of China
T Xiang Peking University, Beijing 100871, People's Republic of China
D Xiao Lanzhou University, Lanzhou 730000, People's Republic of China
G Y Xiao Nanjing University, Nanjing 210093, People's Republic of China
S Y Xiao Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y L Xiao Fudan University, Shanghai 200433, People's Republic of China
Z J Xiao Nanjing Normal University, Nanjing 210023, People's Republic of China
C Xie Nanjing University, Nanjing 210093, People's Republic of China
X H Xie Peking University, Beijing 100871, People's Republic of China
Y Xie Shandong University, Jinan 250100, People's Republic of China
Y G Xie Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y H Xie Central China Normal University, Wuhan 430079, People's Republic of China
Z P Xie State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
T Y Xing Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C F Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C J Xu Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
G F Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China
H Y Xu University of Jinan, Jinan 250022, People's Republic of China
Q J Xu Hangzhou Normal University, Hangzhou 310036, People's Republic of China
Q N Xu Inner Mongolia University, Hohhot 010021, People's Republic of China
W Xu Institute of High Energy Physics, Beijing 100049, People's Republic of China
W L Xu University of Jinan, Jinan 250022, People's Republic of China
X P Xu Soochow University, Suzhou 215006, People's Republic of China
Y C Xu Yantai University, Yantai 264005, People's Republic of China
Z P Xu Nanjing University, Nanjing 210093, People's Republic of China
Z S Xu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
F Yan Fudan University, Shanghai 200433, People's Republic of China
L Yan Fudan University, Shanghai 200433, People's Republic of China
W B Yan State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
W C Yan Zhengzhou University, Zhengzhou 450001, People's Republic of China
X Q Yan Institute of High Energy Physics, Beijing 100049, People's Republic of China
H J Yang Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
H L Yang Jilin University, Changchun 130012, People's Republic of China
H X Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Tao Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Yang Fudan University, Shanghai 200433, People's Republic of China
Y F Yang Nankai University, Tianjin 300071, People's Republic of China
Y X Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Yifan Yang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z W Yang Lanzhou University, Lanzhou 730000, People's Republic of China
Z P Yao Shandong University, Jinan 250100, People's Republic of China
M Ye Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
M H Ye China Center of Advanced Science and Technology, Beijing 100190, People's Republic of China
J H Yin Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z Y You Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
B X Yu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
C X Yu Nankai University, Tianjin 300071, People's Republic of China
G Yu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J S Yu Hunan University, Changsha 410082, People's Republic of China
T Yu University of South China, Hengyang 421001, People's Republic of China
X D Yu Peking University, Beijing 100871, People's Republic of China
C Z Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L Yuan Beihang University, Beijing 100191, People's Republic of China
S C Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China
Y Yuan Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z Y Yuan Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
C X Yue Liaoning Normal University, Dalian 116029, People's Republic of China
A A Zafar University of the Punjab, Lahore-54590, Pakistan
F R Zeng Shandong University, Jinan 250100, People's Republic of China
S H Zeng University of South China, Hengyang 421001, People's Republic of China
X Zeng Fudan University, Shanghai 200433, People's Republic of China
Y Zeng Hunan University, Changsha 410082, People's Republic of China
Y J Zeng Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Y Zhai Jilin University, Changchun 130012, People's Republic of China
Y C Zhai Shandong University, Jinan 250100, People's Republic of China
Y H Zhan Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
A Q Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B L Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B X Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
D H Zhang Nankai University, Tianjin 300071, People's Republic of China
G Y Zhang Henan Normal University, Xinxiang 453007, People's Republic of China
H Zhang University of Science and Technology of China, Hefei 230026, People's Republic of China
H C Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H H Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H H Zhang Jilin University, Changchun 130012, People's Republic of China
H Q Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
H Y Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
J Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
J Zhang Zhengzhou University, Zhengzhou 450001, People's Republic of China
J J Zhang Shanxi Normal University, Linfen 041004, People's Republic of China
J L Zhang Henan University, Kaifeng 475004, People's Republic of China
J Q Zhang Nanjing Normal University, Nanjing 210023, People's Republic of China
J W Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J X Zhang Lanzhou University, Lanzhou 730000, People's Republic of China
J Y Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Z Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Jianyu Zhang University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L M Zhang Tsinghua University, Beijing 100084, People's Republic of China
L Q Zhang Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
Lei Zhang Nanjing University, Nanjing 210093, People's Republic of China
P Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Q Y Zhang Liaoning Normal University, Dalian 116029, People's Republic of China Zhengzhou University, Zhengzhou 450001, People's Republic of China
Shuihan Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Shulei Zhang Hunan University, Changsha 410082, People's Republic of China
X D Zhang North China Electric Power University, Beijing 102206, People's Republic of China
X M Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
X Y Zhang Shandong University, Jinan 250100, People's Republic of China
Y Zhang University of South China, Hengyang 421001, People's Republic of China
Y Zhang University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
Y T Zhang Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y H Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Yan Zhang State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Yao Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z D Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z H Zhang Institute of High Energy Physics, Beijing 100049, People's Republic of China
Z L Zhang Jilin University, Changchun 130012, People's Republic of China
Z Y Zhang Nankai University, Tianjin 300071, People's Republic of China
Z Y Zhang Wuhan University, Wuhan 430072, People's Republic of China
G Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Y Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J Z Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Lei Zhao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Ling Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China
M G Zhao Nankai University, Tianjin 300071, People's Republic of China
R P Zhao University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S J Zhao Zhengzhou University, Zhengzhou 450001, People's Republic of China
Y B Zhao Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
Y X Zhao Institute of Modern Physics, Lanzhou 730000, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Z G Zhao State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
A Zhemchugov Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
B Zheng University of South China, Hengyang 421001, People's Republic of China
J P Zheng Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
W J Zheng Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
Y H Zheng University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
B Zhong Nanjing Normal University, Nanjing 210023, People's Republic of China
X Zhong Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
H Zhou Shandong University, Jinan 250100, People's Republic of China
L P Zhou Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
X Zhou Wuhan University, Wuhan 430072, People's Republic of China
X K Zhou Central China Normal University, Wuhan 430079, People's Republic of China
X R Zhou State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
X Y Zhou Liaoning Normal University, Dalian 116029, People's Republic of China
Y Z Zhou Fudan University, Shanghai 200433, People's Republic of China
J Zhu Nankai University, Tianjin 300071, People's Republic of China
K Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China
K J Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
L Zhu Jilin University, Changchun 130012, People's Republic of China
L X Zhu University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
S H Zhu University of Science and Technology Liaoning, Anshan 114051, People's Republic of China
S Q Zhu Nanjing University, Nanjing 210093, People's Republic of China
T J Zhu Fudan University, Shanghai 200433, People's Republic of China
W J Zhu Fudan University, Shanghai 200433, People's Republic of China
Y C Zhu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China
Z A Zhu Institute of High Energy Physics, Beijing 100049, People's Republic of China University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
J H Zou Institute of High Energy Physics, Beijing 100049, People's Republic of China
J Zu State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China University of Science and Technology of China, Hefei 230026, People's Republic of China

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Investigation of the ΔI=1/2 Rule and Test of CP Symmetry through the Measurement of Decay Asymmetry Parameters in Ξ^{-} Decays

Using (10087±44)×10^{6}  J/ψ events collected with the BESIII detector, numerous Ξ^{-} and Λ decay asymmetry parameters are simultaneously determined from the process J/ψ→Ξ^{-}Ξ[over ¯]^{+}→Λ(pπ^{-})π^{-}Λ[over ¯](n[over ¯]π^{0})π^{+} and its charge-conjugate channel. The precisions of α_{Λ0} for Λ→nπ^{0} and α[over ¯]_{Λ0} for Λ[over ¯]→n[over ¯]π^{0} compared to world averages are improved by factors of 4 and 1.7, respectively. The ratio of decay asymmetry parameters of Λ→nπ^{0} to that of Λ→pπ^{-}, ⟨α_{Λ0}⟩/⟨α_{Λ-}⟩, is determined to be 0.873±0.012_{-0.010}^{+0.011}, where the first and the second uncertainties are statistical and systematic, respectively. The ratio is smaller than unity more than 5σ, which signifies the existence of the ΔI=3/2 transition in Λ for the first time. Besides, we test for CP symmetry in Ξ^{-}→Λπ^{-} and in Λ→nπ^{0} with the best precision to date.

Observation of D_{s}^{+}→η^{'}μ^{+}ν_{μ}, Precision Test of Lepton Flavor Universality with D_{s}^{+}→η^{(')}l^{+}ν_{l}, and First Measurements of D_{s}^{+}→η^{(')}μ^{+}ν_{μ} Decay Dynamics

By analyzing 7.33  fb^{-1} of e^{+}e^{-} annihilation data collected at center-of-mass energies between 4.128 and 4.226 GeV with the BESIII detector, we report the observation of the semileptonic decay D_{s}^{+}→η^{'}μ^{+}ν_{μ}, with a statistical significance larger than 10σ, and the measurements of the D_{s}^{+}→ημ^{+}ν_{μ} and D_{s}^{+}→η^{'}μ^{+}ν_{μ} decay dynamics for the first time. The branching fractions of D_{s}^{+}→ημ^{+}ν_{μ} and D_{s}^{+}→η^{'}μ^{+}ν_{μ} are determined to be (2.235±0.051_{stat}±0.052_{syst})% and (0.801±0.055_{stat}±0.028_{syst})%, respectively, with precision improved by factors of 6.0 and 6.6 compared to the previous best measurements. Combined with the results for the decays D_{s}^{+}→ηe^{+}ν_{e} and D_{s}^{+}→η^{'}e^{+}ν_{e}, the ratios of the decay widths are examined both inclusively and in several ℓ^{+}ν_{ℓ} four-momentum transfer ranges. No evidence for lepton flavor universality violation is found within the current statistics. The products of the hadronic form factors f_{+,0}^{η^{(')}}(0) and the c→s Cabibbo-Kobayashi-Maskawa matrix element |V_{cs}| are determined. The results based on the two-parameter series expansion are f_{+,0}^{η}(0)|V_{cs}|=0.452±0.010_{stat}±0.007_{syst} and f_{+,0}^{η^{'}}(0)|V_{cs}|=0.504±0.037_{stat}±0.012_{syst}, which help to constrain present models on f_{+,0}^{η^{(')}}(0). The forward-backward asymmetries are determined to be ⟨A_{FB}^{η}⟩=-0.059±0.031_{stat}±0.005_{syst} and ⟨A_{FB}^{η^{'}}⟩=-0.064±0.079_{stat}±0.006_{syst} for the first time, which are consistent with the theoretical calculation.

Determination of the Σ^{+} Timelike Electromagnetic Form Factors

Based on data samples collected with the BESIII detector at the BEPCII collider, the process e^{+}e^{-}→Σ^{+}Σ[over ¯]^{-} is studied at center-of-mass energies sqrt[s]=2.3960, 2.6454, and 2.9000 GeV. Using a fully differential angular description of the final state particles, both the relative magnitude and phase information of the Σ^{+} electromagnetic form factors in the timelike region are extracted. The relative phase between the electric and magnetic form factors is determined to be sinΔΦ=-0.67±0.29(stat)±0.18(syst) at sqrt[s]=2.3960  GeV, ΔΦ=55°±19°(stat)±14°(syst) at sqrt[s]=2.6454  GeV, and 78°±22°(stat)±9°(syst) at sqrt[s]=2.9000  GeV. For the first time, the phase of the hyperon electromagnetic form factors is explored in a wide range of four-momentum transfer. The evolution of the phase along with four-momentum transfer is an important input for understanding its asymptotic behavior and the dynamics of baryons.

First Measurement of the Decay Asymmetry in the Pure W-Boson-Exchange Decay Λ_{c}^{+}→Ξ^{0}K^{+}

Based on 4.4  fb^{-1} of e^{+}e^{-} annihilation data collected at the center-of-mass energies between 4.60 and 4.70 GeV with the BESIII detector at the BEPCII collider, the pure W-boson-exchange decay Λ_{c}^{+}→Ξ^{0}K^{+} is studied with a full angular analysis. The corresponding decay asymmetry is measured for the first time to be α_{Ξ^{0}K^{+}}=0.01±0.16(stat)±0.03(syst). This result reflects the noninterference effect between the S- and P-wave amplitudes. The phase shift between S- and P-wave amplitudes has two solutions, which are δ_{p}-δ_{s}=-1.55±0.25(stat)±0.05(syst)  rad or 1.59±0.25(stat)±0.05(syst)  rad.

Automated anatomical labeling of the intracranial arteries via deep learning in computed tomography angiography

Background and purpose: Anatomical labeling of the cerebral vasculature is a crucial topic in determining the morphological nature and characterizing the vital variations of vessels, yet precise labeling of the intracranial arteries is time-consuming and challenging, given anatomical structural variability and surging imaging data. We present a U-Net-based deep learning (DL) model to automatically label detailed anatomical segments in computed tomography angiography (CTA) for the first time. The trained DL algorithm was further tested on a clinically relevant set for the localization of intracranial aneurysms (IAs). Methods: 457 examinations with varying degrees of arterial stenosis were used to train, validate, and test the model, aiming to automatically label 42 segments of the intracranial arteries [e.g., 7 segments of the internal carotid artery (ICA)]. Evaluation metrics included Dice similarity coefficient (DSC), mean surface distance (MSD), and Hausdorff distance (HD). Additionally, 96 examinations containing at least one IA were enrolled to assess the model's potential in enhancing clinicians' precision in IA localization. A total of 5 clinicians with different experience levels participated as readers in the clinical experiment and identified the precise location of IA without and with algorithm assistance, where there was a washout period of 14 days between two interpretations. The diagnostic accuracy, time, and mean interrater agreement (Fleiss' Kappa) were calculated to assess the differences in clinical performance of clinicians. Results: The proposed model exhibited notable labeling performance on 42 segments that included 7 anatomical segments of ICA, with the mean DSC of 0.88, MSD of 0.82 mm and HD of 6.59 mm. Furthermore, the model demonstrated superior labeling performance in healthy subjects compared to patients with stenosis (DSC: 0.91 vs. 0.89, p < 0.05; HD: 4.75 vs. 6.19, p < 0.05). Concurrently, clinicians with model predictions achieved significant improvements when interpreting the precise location of IA. The clinicians' mean accuracy increased by 0.04 (p = 0.003), mean time to diagnosis reduced by 9.76 s (p < 0.001), and mean interrater agreement (Fleiss' Kappa) increased by 0.07 (p = 0.029). Conclusion: Our model stands proficient for labeling intracranial arteries using the largest CTA dataset. Crucially, it demonstrates clinical utility, helping prioritize the patients with high risks and ease clinical workload.

Causal relationships between human blood metabolites and intracranial aneurysm and aneurysmal subarachnoid hemorrhage: a Mendelian randomization study

Objective

The aim of this study was to assess the causal relationships between blood metabolites and intracranial aneurysm, aneurysmal subarachnoid hemorrhage, and unruptured intracranial aneurysm.

Methods

Our exposure sample consisted of 7,824 individuals from a genome-wide association study of human blood metabolites. Our outcome sample consisted of 79,429 individuals (7,495 cases and 71,934 controls) from the International Stroke Genetics Consortium, which conducted a genome-wide association study of intracranial aneurysm, aneurysmal subarachnoid hemorrhage, and unruptured intracranial aneurysm. We identified blood metabolites with a potential causal effect on intracranial aneurysms and conducted sensitivity analyses to validate our findings.

Results

After rigorous screening and Mendelian randomization tests, we found four, two, and three serum metabolites causally associated with intracranial aneurysm, aneurysmal subarachnoid hemorrhage, and unruptured intracranial aneurysm, respectively (all P < 0.05). Sensitivity analyses confirmed the robustness of these associations.

Conclusions

Our Mendelian randomization analysis demonstrated causal relationships between human blood metabolites and intracranial aneurysm, aneurysmal subarachnoid hemorrhage, and unruptured intracranial aneurysm. Further research is required to explore the potential of targeting these metabolites in the management of intracranial aneurysm.

Long-term outcomes and dynamic changes of in-stent stenosis after Pipeline embolization device treatment of intracranial aneurysms

BACKGROUND

Flow diverters have revolutionized the treatment of intracranial aneurysms. However, the delayed complications associated with flow diverter use are unknown.

OBJECTIVE

To evaluate the incidence, severity, clinical outcomes, risk factors, and dynamic changes associated with in-stent stenosis (ISS) after treatment with a Pipeline embolization device (PED).

METHODS

Patients who underwent PED treatment between 2015 and 2020 were enrolled. The angiographic, clinical, and follow-up data of 459 patients were independently reviewed by four neuroradiologists to identify ISS. Binary logistic regression was conducted to determine ISS risk factors, and an ISS-time curve was established to demonstrate dynamic changes in ISS after PED implantation.

RESULTS

Of the 459 treated patients, 69 (15.0%) developed ISS. At follow-up, nine patients (2.0%) with ISS demonstrated reversal, while 18 (3.9%) developed parental artery occlusion. A total of 380 patients (82.8%) achieved complete aneurysm occlusion (O'Kelly-Marotta grade D). Patients with posterior-circulation aneurysm (OR=2.895, 95% CI (1.732 to 4.838; P<0.001) or balloon angioplasty (OR=1.992, 95% CI 1.162 to 3.414; P=0.037) were more likely to develop ISS. Patients aged >54 years (OR=0.464, 95% CI 0.274 to 0.785; P=0.006) or with a body mass index of >28 kg/m2 (OR=0.427, 95% CI 0.184 to 0.991; P=0.026) had a lower ISS risk. Intimal hyperplasia initiated by PED placement peaked within 1 year after the procedure, rarely progressed after 12 months, and tended to reverse within 24 months.

CONCLUSIONS

ISS is a common, benign, and self-limiting complication of PED implantation in the Chinese population.

Test of CP Symmetry in Hyperon to Neutron Decays

The quantum entangled J/ψ→Σ^{+}Σ[over ¯]^{-} pairs from (1.0087±0.0044)×10^{10}  J/ψ events taken by the BESIII detector are used to study the nonleptonic two-body weak decays Σ^{+}→nπ^{+} and Σ[over ¯]^{-}→n[over ¯]π^{-}. The CP-odd weak decay parameters of the decays Σ^{+}→nπ^{+} (α_{+}) and Σ[over ¯]^{-}→n[over ¯]π^{-} (α[over ¯]_{-}) are determined to be 0.0481±0.0031_{stat}±0.0019_{syst} and -0.0565±0.0047_{stat}±0.0022_{syst}, respectively. The decay parameter α[over ¯]_{-} is measured for the first time, and the accuracy of α_{+} is improved by a factor of 4 compared to the previous results. The simultaneously determined decay parameters allow the first precision CP symmetry test for any hyperon decay with a neutron in the final state with the measurement of A_{CP}=(α_{+}+α[over ¯]_{-})/(α_{+}-α[over ¯]_{-})=-0.080±0.052_{stat}±0.028_{syst}. Assuming CP conservation, the average decay parameter is determined as ⟨α_{+}⟩=(α_{+}-α[over ¯]_{-})/2=-0.0506±0.0026_{stat}±0.0019_{syst}, while the ratios α_{+}/α_{0} and α[over ¯]_{-}/α[over ¯]_{0} are -0.0490±0.0032_{stat}±0.0021_{syst} and -0.0571±0.0053_{stat}±0.0032_{syst}, where α_{0} and α[over ¯]_{0} are the decay parameters of the decays Σ^{+}→pπ^{0} and Σ[over ¯]^{-}→p[over ¯]π^{0}, respectively.

Measurement of Energy-Dependent Pair-Production Cross Section and Electromagnetic Form Factors of a Charmed Baryon

We study the process e^{+}e^{-}→Λ_{c}^{+}Λ[over ¯]_{c}^{-} at twelve center-of-mass energies from 4.6119 to 4.9509 GeV using data samples collected by the BESIII detector at the BEPCII collider. The Born cross sections and effective form factors (|G_{eff}|) are determined with unprecedented precision after combining the single and double-tag methods based on the decay process Λ_{c}^{+}→pK^{-}π^{+}. Flat cross sections around 4.63 GeV are obtained and no indication of the resonant structure Y(4630), as reported by Belle, is found. In addition, no oscillatory behavior is discerned in the |G_{eff}| energy dependence of Λ_{c}^{+}, in contrast to what is seen for the proton and neutron cases. Analyzing the cross section together with the polar-angle distribution of the Λ_{c}^{+} baryon at each energy point, the moduli of electric and magnetic form factors (|G_{E}| and |G_{M}|) are extracted and separated. For the first time, the energy dependence of the form factor ratio |G_{E}/G_{M}| is observed, which can be well described by an oscillatory function.

Reactive cutaneous capillary endothelial proliferation predicted the efficacy of camrelizumab in patients with recurrent/metastatic head and neck squamous cell carcinoma

BACKGROUND

Reactive cutaneous capillary endothelial proliferation (RCCEP), a special adverse event (AE) only observed in patients treated with camrelizumab, was reported to be correlated with the efficacy of camrelizumab in patients with advanced hepatocellular carcinoma. This study to analyze the possible correlation between the occurrence of RCCEP and efficacy of camrelizumab in patients with recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC).

MATERIAL AND METHODS

In this study, we retrospectively analyzed the efficacy and RCCEP occurrence of camrelizumab in 58 patients with R/M HNSCC in the Shanghai Ninth People's Hospital affiliated to Shanghai JiaoTong University School of Medicine between January 2019 and June 2022. Kaplan-Meier analysis was used to assess the correlation between the occurrence of RCCEP and the survival of enrolled patients, and COX multifactor analysis was adopted to evaluate associated factors that affected the efficacy of camrelizumab immunotherapy.

RESULTS

A significant correlation between the incidence of RCCEP and a higher objective response rate was observed in this study (p=0.008). The occurrence of RCCEP was associated with better median overall survival (17.0 months vs. 8.7 months, p<0.0001, HR=5.944, 95% CI:2.097-16.84) and better median progression-free survival (15.1 months vs. 4.0 months, p<0.0001, HR=4.329,95% CI:1.683-11.13). In COX multifactor analysis, RCCEP occurrence was also an independent prognostic factor affecting OS and PFS in patients with R/M HNSCC.

CONCLUSIONS

The occurrence of RCCEP can show a better prognosis, it could be used as a clinical biomarker to predict the efficacy of camrelizumab treatment.

Determination of Spin-Parity Quantum Numbers for the Narrow Structure near the pΛ[over ¯] Threshold in e^{+}e^{-}→pK^{-}Λ[over ¯]+c.c

A narrow structure in the pΛ[over ¯] system near the mass threshold, named as X(2085), is observed in the process e^{+}e^{-}→pK^{-}Λ[over ¯] with a statistical significance greater than 20σ. Its spin and parity are determined for the first time to be J^{P}=1^{+} in an amplitude analysis, with a statistical significance greater than 5σ over other quantum numbers (0^{-},1^{-} and 2^{+}). The pole positions of X(2085) are measured to be M_{pole}=(2084_{-2}^{+4}±9)  MeV and Γ_{pole}=(58_{-3}^{+4}±25)  MeV, where the first uncertainties are statistical and the second ones are systematic. The analysis is based on the study of the process e^{+}e^{-}→pK^{-}Λ[over ¯] and uses the data samples collected with the BESIII detector at the center-of-mass energies sqrt[s]=4.008, 4.178, 4.226, 4.258, 4.416, and 4.682 GeV with a total integrated luminosity of 8.35  fb^{-1}.

Precise Measurement of the e^{+}e^{-}→D_{s}^{*+}D_{s}^{*-} Cross Sections at Center-of-Mass Energies from Threshold to 4.95 GeV

The process e^{+}e^{-}→D_{s}^{*+}D_{s}^{*-} is studied with a semi-inclusive method using data samples at center-of-mass energies from threshold to 4.95 GeV collected with the BESIII detector operating at the Beijing Electron Positron Collider. The Born cross sections of the process are measured for the first time with high precision in this energy region. Two resonance structures are observed in the energy-dependent cross sections around 4.2 and 4.4 GeV. By fitting the cross sections with a coherent sum of three Breit-Wigner amplitudes and one phase-space amplitude, the two significant structures are assigned masses of (4186.8±8.7±30) and (4414.6±3.4±6.1)  MeV/c^{2}, widths of (55±15±53) and (122.5±7.5±8.1)  MeV, where the first errors are statistical and the second ones are systematic. The inclusion of a third Breit-Wigner amplitude is necessary to describe a structure around 4.79 GeV.

First Experimental Study of the Purely Leptonic Decay D_{s}^{*+}→e^{+}ν_{e}

Using 7.33  fb^{-1} of e^{+}e^{-} collision data taken with the BESIII detector at the BEPCII collider, we report the first experimental study of the purely leptonic decay D_{s}^{*+}→e^{+}ν_{e}. Our data contain a signal of this decay with a statistical significance of 2.9σ. The branching fraction of D_{s}^{*+}→e^{+}ν_{e} is measured to be (2.1_{-0.9_{stat}}^{+1.2}±0.2_{syst})×10^{-5}, corresponding to an upper limit of 4.0×10^{-5} at the 90% confidence level. Taking the total width of the D_{s}^{*+} [(0.070±0.028)  keV] predicted with the radiative D_{s}^{*+} decay from the lattice QCD calculation as input, the decay constant of the D_{s}^{*+} is determined to be f_{D_{s}^{*+}}=(214_{-46_{stat}}^{+61}±44_{syst})  MeV, corresponding to an upper limit of 354 MeV at the 90% confidence level.

m6A Reader YTHDC1 Inhibits Ferroptosis and Radiosensitivity by Promoting SREBF1 mRNA Nuclear Export in Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

Radioresistance is the main reason for nasopharyngeal carcinoma (NPC) recurrence leading to treatment failure, and inducing ferroptosis has gradually been a new way to enhance radiosensitivity. N6-methyladenosine (m6A) is involved in regulation of numerous biological processes. However, whether m6A affects ferroptosis in NPC is still unclear. In this study, we conducted a siRNA library screening to identify m6A reader YTHDC1 as an essential oncogene that suppressed ferroptosis and radiosensitivity by promoting SREBF1 mRNA nuclear export in nasopharyngeal carcinoma.

MATERIALS/METHODS

The expression and function of YTHDC1 were assessed via CCK8 cell viability assay, immunostaining, real-time PCR, western blot, radiation clonogenic assay and fluorescence in situ hybridization assay. Ferroptosis was determined by detecting cell viability, lipid peroxidation, abnormal mitochondrial and cell death rate. The in vivo effects of YTHDC1 were examined with RSL3 treatment or lentivirus modification of YTHDC1 expression in radiated mouse models.

RESULTS

Based on RSL3-induced ferroptotic cell death model and a siRNA library about m6A modification associated gene screening, we identified m6A reader YTHDC1 could inhibit ferroptosis as well as radiosensitivity of NPC, both in vivo and in vitro. Mechanistically, YTHDC1 protein could recognize m6A sites in the CDS region and 3' untranslated region (3'UTR) of SREBF1 mRNA and promote SREBF1 mRNA nuclear export, which finally resulted in transcriptional upregulation of genes key to ferroptosis such as SCD and FASN. Furthermore, the high expression of YTHDC1 was negatively regulated by ZNF598 via ubiquitination and associated with unfavorable survival in NPC patients due to radioresistance.

CONCLUSION

Our findings reveal the critical role of YTHDC1 specifically in inhibiting ferroptosis and radiosensitivity via m6A-dependent mechanism and provide an exploitable target and therapeutic strategy for overcoming radioresistance in NPC.

[Expression and protective effect of chemerin in idiopathic pulmonary fibrosis]

Objective: To explore the expression and the role of chemerin in idiopathic pulmonary fibrosis (IPF). Methods: Quantitative PCR and Western blotting were used to determine the mRNA and protein levels of chemerin in lung tissues from IPF patients and the controls. Clinical serum level of chemerin was analyzed by enzyme-linked immunosorbent assay. The mouse lung fibroblasts isolated and cultured in vitro were divided into the control, TGF-β, TGF-β+chemerin and chemerin groups. Immunofluorescence staining was used to observe the expression of α-smooth muscle actin (α-SMA). C57BL/6 mice were randomly divided into the control, bleomycin, bleomycin+chemerin, and chemerin groups. Masson and immunohistochemical staining were performed to evaluate the severity of pulmonary fibrosis. Expression of epithelial to mesenchymal transition (EMT) markers was detected by quantitative PCR and immunohistochemical staining in the in vitro and in vivo models of pulmonary fibrosis, respectively. Results: Compared with the control group, the expression of chemerin was downregulated in both the lung tissue and the serum of IPF patients. Immunofluorescence showed that treatment of fibroblasts with TGF-β alone resulted in a robust expression of α-SMA, whereas treatment with TGF-β and chemerin together exhibited the similar expression levels of α-SMA as the control group. Masson staining indicated that the bleomycin-induced pulmonary fibrosis model was constructed successfully, while treatment of chemerin partially alleviated the damage of lung tissue. Immunohistochemical staining showed that the expression of chemerin in the lung tissue was significantly decreased in the bleomycin group. Quantitative PCR and immunohistochemistry showed that chemerin attenuated EMT induced by TGF-β and bleomycin both in vitro and in vivo. Conclusions: The expression of chemerin was reduced in patients with IPF. Chemerin may play a protective role in the development of IPF by regulating EMT, providing a new idea for the clinical treatment of IPF.

First Study of Reaction Ξ^{0}n→Ξ^{-}p Using Ξ^{0}-Nucleus Scattering at an Electron-Positron Collider

Using (1.0087±0.0044)×10^{10}  J/ψ events collected with the BESIII detector at the BEPCII storage ring, the process Ξ^{0}n→Ξ^{-}p is studied, where the Ξ^{0} baryon is produced in the process J/ψ→Ξ^{0}Ξ[over ¯]^{0} and the neutron is a component of the ^{9}Be, ^{12}C, and ^{197}Au nuclei in the beam pipe. A clear signal is observed with a statistical significance of 7.1σ. The cross section of the reaction Ξ^{0}+^{9}Be→Ξ^{-}+p+^{8}Be is determined to be σ(Ξ^{0}+^{9}Be→Ξ^{-}+p+^{8}Be)=(22.1±5.3_{stat}±4.5_{sys})  mb at the Ξ^{0} momentum of 0.818  GeV/c, where the first uncertainty is statistical and the second is systematic. No significant H-dibaryon signal is observed in the Ξ^{-}p final state. This is the first study of hyperon-nucleon interactions in electron-positron collisions and opens up a new direction for such research.

Precision Measurement of the Decay Σ^{+}→pγ in the Process J/ψ→Σ^{+}Σ[over ¯]^{-}

Using (10 087±44)×10^{6} J/ψ events collected with the BESIII detector, the radiative hyperon decay Σ^{+}→pγ is studied at an electron-positron collider experiment for the first time. The absolute branching fraction is measured to be (0.996±0.021_{stat}±0.018_{syst})×10^{-3}, which is lower than its world average value by 4.2 standard deviations. Its decay asymmetry parameter is determined to be -0.652±0.056_{stat}±0.020_{syst}. The branching fraction and decay asymmetry parameter are the most precise to date, and the accuracies are improved by 78% and 34%, respectively.

Measurements of the Electric and Magnetic Form Factors of the Neutron for Timelike Momentum Transfer

We present the first measurements of the electric and magnetic form factors of the neutron in the timelike (positive q^{2}) region as function of four-momentum transfer. We explored the differential cross sections of the reaction e^{+}e^{-}→n[over ¯]n with data collected with the BESIII detector at the BEPCII accelerator, corresponding to an integrated luminosity of 354.6  pb^{-1} in total at twelve center-of-mass energies between sqrt[s]=2.0-2.95  GeV. A relative uncertainty of 18% and 12% for the electric and magnetic form factors, respectively, is achieved at sqrt[s]=2.3935  GeV. Our results are comparable in accuracy to those from electron scattering in the comparable spacelike region of four-momentum transfer. The electromagnetic form factor ratio R_{em}≡|G_{E}|/|G_{M}| is within the uncertainties close to unity. We compare our result on |G_{E}| and |G_{M}| to recent model predictions, and the measurements in the spacelike region to test the analyticity of electromagnetic form factors.

The association of serum testosterone with dyslipidemia is mediated by obesity: the Henan Rural Cohort Study

BACKGROUND AND AIMS

This study aimed to evaluate the relationships of serum testosterone with dyslipidemia and blood lipid levels and test whether obesity mediated these associations by gender in Chinese rural population.

METHODS AND RESULTS

A total of 6150 subjects were finally analyzed in this study. Serum testosterone for each subject was detected by liquid chromatography equipped with tandem mass spectrometry. Logistic regression and linear regression were employed to evaluate the associations of serum testosterone with the prevalence of dyslipidemia and blood lipid levels. Mediation analysis was conducted to identify the mediation effects of obesity on the relationship between serum testosterone and dyslipidemia. After adjusting for multiple confounders, per unit change in serum ln-testosterone levels was associated with a decreased prevalent dyslipidemia in men (odds ratio (OR): 0.785, 95% confidence interval (CI) (0.708, 0.871)). Males with the levels of serum testosterone in the third or fourth quartiles had a 49.4% (OR: 0.506, 95% CI 0.398, 0.644) or 67.1% (OR: 0.329, 95% CI 0.253, 0.428) significantly lower odds of prevalence of dyslipidemia. In addition, a onefold increase in ln-testosterone was related to a 0.043 mmol/L (95% CI 0.028, 0.059) increase in high-density lipoprotein cholesterol (HDL-C) in men. Results of the mediation analysis suggested that obesity played a partial role in the association of testosterone with dyslipidemia in men.

CONCLUSIONS

These findings suggested that serum testosterone levels were negatively associated with lipid levels and prevalent dyslipidemia, and obesity mediated the effects of serum testosterone on dyslipidemia in men, implying that obesity prevention should be highlighted to decrease the prevalence of dyslipidemia related to changes in testosterone levels.

Observation of Three Charmoniumlike States with J^{PC}=1^{--} in e^{+}e^{-}→D^{*0}D^{*-}π^{+}

The Born cross sections of the process e^{+}e^{-}→D^{*0}D^{*-}π^{+} at center-of-mass energies from 4.189 to 4.951 GeV are measured for the first time. The data samples used correspond to an integrated luminosity of 17.9  fb^{-1} and were collected by the BESIII detector operating at the BEPCII storage ring. Three enhancements around 4.20, 4.47, and 4.67 GeV are visible. The resonances have masses of 4209.6±4.7±5.9  MeV/c^{2}, 4469.1±26.2±3.6  MeV/c^{2}, and 4675.3±29.5±3.5  MeV/c^{2} and widths of 81.6±17.8±9.0  MeV, 246.3±36.7±9.4  MeV, and 218.3±72.9±9.3  MeV, respectively, where the first uncertainties are statistical and the second systematic. The first and third resonances are consistent with the ψ(4230) and ψ(4660) states, respectively, while the second one is compatible with the ψ(4500) observed in the e^{+}e^{-}→K^{+}K^{-}J/ψ process. These three charmoniumlike ψ states are observed in the e^{+}e^{-}→D^{*0}D^{*-}π^{+} process for the first time.

Alcohol flushing syndrome is significantly associated with intracranial aneurysm rupture in the Chinese Han population

Objective

Although alcohol flushing syndrome (AFS) has been associated with various diseases, its association with intracranial aneurysm rupture (IAR) is unclear. We aimed to examine this association in the Chinese Han population.

Methods

We retrospectively reviewed Chinese Han patients with intracranial aneurysms who were evaluated and treated at our institution between January 2020 and December 2021. AFS was determined using a semi-structured telephone interview. Clinical data and aneurysm characteristics were assessed. Univariate and multivariate logistic regression were conducted to determine independent factors associated with aneurysmal rupture.

Results

A total of 1,170 patients with 1,059 unruptured and 236 ruptured aneurysms were included. The incidence of aneurysm rupture was significantly higher in patients without AFS (p &lt; 0.001). Meanwhile, there was a significantly difference between the AFS and non-AFS group in habitual alcohol consumption (10.5 vs. 27.2%, p &lt; 0.001). In the univariate analyses, AFS [odds ratio (OR) 0.49; 95% confidence interval (CI), 0.34–0.72] was significantly associated with IAR. In the multivariate analysis, AFS was an independent predictor of IAR (OR 0.50; 95%, CI, 0.35–0.71). Multivariate analysis revealed that AFS was an independent predictor of IAR in both habitual (OR 0.11; 95% CI, 0.03–0.45) and non-habitual drinkers (OR 0.69; 95% CI, 0.49–0.96).

Conclusion

Alcohol flushing syndrome may be a novel clinical marker to assess the risk of IAR. The association between AFS and IAR exists independently of alcohol consumption. Further single nucleotide polymorphism testing and molecular biology studies are warranted.

Tortuosity of parent artery predicts in-stent stenosis after pipeline flow-diverter stenting for internal carotid artery aneurysms

Background and purpose

The relationship between the tortuosity of the parent artery and treatment outcomes is not well established. We investigate the association between parent artery tortuosity and flow diverter (FD) treatment outcomes in patients with internal carotid artery aneurysms in this study.

Methods

A retrospective review study was conducted to identify all patients with internal carotid artery aneurysms who were implanted with Pipeline embolization device (PED) between 2016 and 2020. The relationship between parent artery tortuosity and aneurysm complete occlusion (CO) and in-stent stenosis (ISS) was analyzed. The mathematical parameters “Curvature”, “torsion”, and “DM” extracted from the parent artery were utilized to quantify the parent artery tortuosity. A vascular narrowing of greater than 25% was categorized as ISS. Logistic regression analysis was used to identify significant independent predictors. Furthermore, we compared the performance of four machine learning algorithms and Logistic Regression model in predicting ISS.

Results

This research included 62 patients who with internal carotid artery aneurysms. In 49 (79%) cases, follow-up angiography (mean follow-up duration 11.7 ±7.3 months) revealed CO of the aneurysm. ISS was detected in 22 (35.5%) cases. According to univariate analysis, parent artery tortuosity and other variables were not associated with CO (p > 0.1). Maximum curvature (OR = 1.084; 95% CI, 1.008–1.165; p = 0.03) and DM (OR = 0.01; 95% CI, 0–0.488; p = 0.02) exhibited strong independent associations with ISS in multivariate analysis. The SVM model is superior to the conventional Logistic Regression model and the other models in predicting ISS.

Conclusions

The tortuosity of the parent artery may affect the treatment outcome of FD stenting. We found that parent artery tortuosity was associated with ISS, but not with aneurysm complete occlusion following PED stenting for internal carotid artery aneurysms in this study. Parent arteries with higher maximum curvature and lower DM were more likely to develop ISS.

Atherogenic lipoprotein profile associated with anthropometric indices of obesity and their association with cardiometabolic risk markers: a cross-sectional study in community

Background

Obesity, especially abdominal fat accumulation, is strongly associated with various metabolic comorbidities. Whether simple anthropometric measures are independently associated with atherogenic lipoproteins is not completely clear.

Methods

We randomly recruited 505 participants (51.5% women; mean age: 48.8 years) from the Flemish community, who had undergone lipoprotein particle measurements by nuclear magnetic resonance spectroscopy and conventional lipid measurements. Each lipoprotein fraction was subgrouped into large, medium, and small subclass. Anthropometric measures included body mass index (BMI) and waist-to-hip ratio (WHR), and defined BMI obesity as BMI ≥30 kg/m2, and WHR obesity as WHR ≥0.85 (women) or 0.9 (men).

Results

In the multivariable logistic regression analysis, total very-low-density lipoprotein (VLDL) particle and its subclasses were positively associated with BMI obesity (adjusted odds ratio [OR] for total VLDL: 2.37; 95% confidence interval [CI]: 1.70–3.31) and WHR obesity (OR for total VLDL: 2.06 [95% CI: 1.55–2.73]). The level of total high-density lipoprotein (HDL) particle and its subclass was negatively associated with BMI (OR for total HDL: 0.63 [95% CI: 0.45–0.90), but not with WHR (P≥0.11). None of the low-density lipoprotein (LDL) particles was associated with the two types of obesity (P≥0.092). BMI was inversely associated with the size of LDL and HDL particles, whereas high WHR was significantly associated with smaller VLDL and HDL sizes. For conventional lipid measures, both BMI and WHR were independently associated with high triglyceride and remnant cholesterol, both mainly driven from VLDL particles, and low HDL cholesterol (P≤0.008). These associations were confirmed in multivariable linear regression analysis, except the association of BMI with HDL number and the association of WHR with HDL size. With partial least squares analysis, the lipoprotein profiles of BMI and WHR were significantly associated with a high 10-year cardiovascular disease risk score, the homeostasis model assessment-estimated insulin resistance (HOMA-IR), and C-reactive protein.

Conclusion

BMI and WHR were independently associated with high triglyceride-rich lipoproteins, decreased HDL cholesterol. The size of LDL and HDL was more consistently associated with BMI than WHR. The lipoprotein alterations may link obesity with high cardiometabolic risk.

Funding Acknowledgement

Type of funding sources: Public grant(s) – EU funding. Main funding source(s): The European Research Council; the European Research Area Net for Cardiovascular Diseases

Association of fatal and non-fatal adverse health outcomes with urinary peptides reflecting collagen I turnover

Background

Imbalance of collagen I (COL1) turnover, featured by increased synthesis and decreased degradation of collagen fibers, is a hallmark of fibrosis in the heart and blood vessels that associates with poor cardiovascular outcomes. Such as imbalance of COL1 turnover could be reflected in urine and serve as fingerprint for future adverse outcomes in general population, and high risk subjects.

Purpose

We hypothesize that imbalance of proteomic signatures of urinary peptides (UPs) reflecting COL1 turnover relate to adverse health outcomes in participants from a general population

Methods

We randomly recruited 776 participants (51.2% women; 50.5 years) from the Flemish Study on Environment, Genes and Health Outcomes cohort and measured UPs proteome by capillary electrophoresis coupled with mass spectrometry. Our analyses focused on 148 peptides of COL1 alpha-1 (COL1A1) chain that retained ≥70% signal in the whole sample. The primary endpoint included fatal and nonfatal cardiovascular endpoints. Secondary endpoints consisted of total mortality, fatal and nonfatal cardiac, coronary, and heart failure endpoints. Multivariate Cox proportional models, partial least squares analysis (PLS), log-likelihood test, and receiver operating characteristics (ROC) curve were applied.

Results

Over a median follow up of 12.4 years, 110 primary endpoints occurred, 61 participants died, 81, 41 and 24 experienced cardiac, coronary, and heart failure endpoints; respectively. In PLS analyses, upregulation of UPs signatures closer to C- and N-terminal locations of the COL1A1 chain whereas downregulation of mid-region UPs were associated with lower risk of adverse health outcomes. This pattern was inverted in subjects with cardiovascular disease, as upregulation of terminal and downregulation of mid region UPs increased risk. Adding UPs to a basic model including sex, age and usual cardiovascular risk factors significantly improved model performance between 2.54% to 4.93% (P≤0.001) for prediction of adverse health outcomes. In ROC plots, adding UPs to the basic model increased the area under the curve up to 4.00% (P&lt;0.012).

Conclusions

UPs reflecting COL1 turnover predicted adverse health outcomes. The inverted up- and down regulations of UPs in between participants with and without previous cardiovascular diseases might be explained by a shift in the UPs signatures of COL1 fragments linked to distinct fibrotic processes. Urinary proteomic might have clinical importance in documenting the extent of collagen accumulation that relates to adverse health outcomes. In patients at high cardiovascular risk, modification of collagen I fibers turnover might be a potential treatment target

Funding Acknowledgement

Type of funding sources: Public grant(s) – EU funding. Main funding source(s): The European Union the European Research Council and the European Research Area Net for Cardiovascular Diseases.

Machine learning to predict in-stent stenosis after Pipeline embolization device placement

Background

The Pipeline embolization device (PED) is a flow diverter used to treat intracranial aneurysms. In-stent stenosis (ISS) is a common complication of PED placement that can affect long-term outcome. This study aimed to establish a feasible, effective, and reliable model to predict ISS using machine learning methodology.

Methods

We retrospectively examined clinical, laboratory, and imaging data obtained from 435 patients with intracranial aneurysms who underwent PED placement in our center. Aneurysm morphological measurements were manually measured on pre- and posttreatment imaging studies by three experienced neurointerventionalists. ISS was defined as stenosis rate >50% within the PED. We compared the performance of five machine learning algorithms (elastic net (ENT), support vector machine, Xgboost, Gaussian Naïve Bayes, and random forest) in predicting ISS. Shapley additive explanation was applied to provide an explanation for the predictions.

Results

A total of 69 ISS cases (15.2%) were identified. Six predictors of ISS (age, obesity, balloon angioplasty, internal carotid artery location, neck ratio, and coefficient of variation of red cell volume distribution width) were identified. The ENT model had the best predictive performance with a mean area under the receiver operating characteristic curve of 0.709 (95% confidence interval [CI], 0.697–0.721), mean sensitivity of 77.9% (95% CI, 75.1–80.6%), and mean specificity of 63.4% (95% CI, 60.8–65.9%) in Monte Carlo cross-validation. Shapley additive explanation analysis showed that internal carotid artery location was the most important predictor of ISS.

Conclusion

Our machine learning model can predict ISS after PED placement for treatment of intracranial aneurysms and has the potential to improve patient outcomes.

[Prolonged epidural labor analgesia increases risks of epidural analgesia failure for conversion to cesarean section]

OBJECTIVE

To explore the effect of epidural labor analgesia duration on the outcomes of different anesthetic approaches for conversion to cesarean section.

METHODS

We retrospectively collected the clinical data of pregnant women undergoing conversion from epidural labor analgesia to cesarean section at Sichuan Maternal and Child Health Hospital and Jinjiang District Maternal and Child Health Care Hospital between July, 2019 and June, 2020. For cesarean section, the women received epidural anesthesia when the epidural catheter was maintained in correct position with effective analgesia, spinal anesthesia at the discretion of the anesthesiologists, or general anesthesia in cases requiring immediate cesarean section or following failure of epidural anesthesia or spinal anesthesia. Receiver-operating characteristic curve analysis was performed to determine the cutoff value of the analgesia duration using Youden index. The women were divided into two groups according to the cut off value for analyzing the relative risk using cross tabulations.

RESULTS

A total of 820 pregnant women undergoing conversion to cesarean section were enrolled in this analysis, including 615 (75.0%) in epidural anesthesia group, 186 (22.7%) in spinal anesthesia group, and 19 (2.3%) in general anesthesia group; none of the women experienced failure of epidural or spinal anesthesia. The mean anesthesia duration was 8.2±4.7 h in epidural anesthesia, 10.6±5.1 h in spinal anesthesia group, and 6.7 ± 5.2 h in general anesthesia group. Multivariate logistic regression analysis showed that prolongation of analgesia duration by 1 h (OR=1.094, 95% CI: 1.057-1.132, P < 0.001) and an increase of cervical orifice by 1 cm (OR=1.066, 95% CI: 1.011-1.124, P=0.017) were independent risk factors for epidural analgesia failure. The cutoff value of analgesia duration was 9.5 h, and beyond that duration the relative risk of receiving spinal anesthesia was 1.204 (95% CI: 1.103-2.341, P < 0.001).

CONCLUSION

Prolonged epidural labor analgesia increases the risk of failure of epidural analgesia for conversion to epidural anesthesia. In cases with an analgesia duration over 9.5 h, spinal anesthesia is recommended if immediate cesarean section is not required.

Protocol and Preliminary Results of the Establishment of Intracranial Aneurysm Database for Artificial Intelligence Application Based on CTA Images

Background and Purpose

Unruptured intracranial aneurysms (UIAs) are increasingly being detected in clinical practice. Artificial intelligence (AI) has been increasingly used to assist diagnostic techniques and shows encouraging prospects. In this study, we reported the protocol and preliminary results of the establishment of an intracranial aneurysm database for AI application based on computed tomography angiography (CTA) images.

Methods

Through a review of picture archiving and communication systems, we collected CTA images of patients with aneurysms between January 2010 and March 2021. The radiologists performed manual segmentation of all diagnosed aneurysms on subtraction CTA as the basis for automatic aneurysm segmentation. Then, AI will be applied to two stages of aneurysm treatment, namely, automatic aneurysm detection and segmentation model based on the CTA image and the aneurysm risk prediction model.

Results

Three medical centers have been included in this study so far. A total of 3,190 cases of CTA examinations with 4,124 aneurysms were included in the database. All identified aneurysms from CTA images that enrolled in this study were manually segmented on subtraction CTA by six readers. We developed a structure of 3D-Unet for aneurysm detection and segmentation in CTA images. The algorithm was developed and tested using a total of 2,272 head CTAs with 2,938 intracranial aneurysms. The recall and false positives per case (FP/case) of this model for detecting aneurysms were 0.964 and 2.01, and the Dice values for aneurysm segmentation were 0.783.

Conclusion

This study introduces the protocol and preliminary results of the establishment of the intracranial aneurysm database for AI applications based on CTA images. The establishment of a multicenter database based on CTA images of intracranial aneurysms is the basis for the application of AI in the diagnosis and treatment of aneurysms. In addition to segmentation, AI should have great potential for aneurysm treatment and management in the future.

AB0788 The International Map of Axial Spondyloarthritis (IMAS): a US patient perspective on diagnosis and burden of disease

Background

Axial spondyloarthritis (axSpA) is a chronic inflammatory disease encompassing radiographic (traditionally known as ankylosing spondylitis) and non-radiographic forms that lead to chronic pain, structural damage, and disability.1 The International Map of Axial Spondyloarthritis (IMAS) survey is an initiative developed to generate insights into the real-life experiences of people living with axSpA to ultimately improve quality of life.2

Objectives

To assess the burden and daily experience of patients with axSpA in the United States.

Methods

The IMAS survey generates a report on patient-reported aspects of disease burden and experience with axSpA using adaptations of the original Atlas of axSpA questionnaire developed in collaboration with patients, the Axial Spondyloarthritis International Federation, and clinical academic experts. In this US adaptation of the IMAS survey, a 30-minute quantitative online survey was administered to US patients aged ≥18 years who completed screening questions, self-reported having been diagnosed with axSpA by a healthcare provider, and were under the care of a healthcare provider between July 22, 2021, and November 10, 2021. Survey questions were tailored to reflect differences in the US healthcare systems and the availability of treatments. This analysis presents a portion of the US data describing patient demographics, clinical characteristics, journey to axSpA diagnosis, and the emotional impact and overall burden of disease on quality of life using the General Health Questionnaire 12 (GHQ-12), the Assessment of SpondyloArthritis international Society – Health Index (ASAS-HI), and a global limitation index of 18 activities of daily living. All results were reported descriptively using summary statistics.

Results

Survey data from 228 US patients with axSpA were collected in this analysis. The mean age was 45 years, 60% of patients were female, and the mean BMI was 27.7 kg/m2 (Table 1). Participating patients had an average of 5.6 comorbidities, with anxiety (43%), depression (41%), and hypertension (32%) as the most commonly reported comorbidities. Among all patients, the mean age at onset of first symptoms was 26 years and the mean age at diagnosis was 35 years; overall, mean diagnostic delay was greater in female than in male patients (11.2 vs 5.2 years; Figure 1A). According to the validated GHQ-12, over half of the patients (57%) were at risk for psychological distress (GHQ-12 score ≥3; Figure 1B). Patients who were older (>40 years old), physically inactive, or who had active disease (BASDAI ≥4) were at risk for psychological distress. Most patients (82%) suffered from a high degree of impairment (ASAS-HI ≥6), 47% had a medium or high limitation in activities of daily living, and 46% of patients were not employed at the time of the survey.

Table 1.

Patient Demographic and Clinical Characteristics

CharacteristicPatients with axSpA(N=228)Mean age, years45Female, %60White, %86Mean body mass index, kg/m227.7Nonsmoker, %62Alcohol consumption behavior, %Never19Every day9Mean number of comorbidities5.6Common comorbidities (≥20% of patients), %aAnxiety43Depression41Hypertension32Obesity/overweight31Sleep disorders30Hypercholesterolemia29Uveitis24Psoriatic arthritis23Fibromyalgia20Spinal or other fractures20Psoriasis20Employed, %54

axSpA, axial spondyloarthritis.

aRespondents could have selected ≥1 answer.

Conclusion

This study showed that a high proportion of US patients with axSpA report impaired function and are at risk for psychological distress. Patients also experienced a substantial delay in the time to axSpA diagnosis, with longer delays than those reported in the European Union. Delays were twice as long in women compared to men. These findings highlight the large impact of disease on daily activities and mental distress in US patients with axSpA.

References

[1]Sieper J, Poddubnyy D. Lancet. 2017;390:73-84.

[2]Garrido-Cumbrera M, et al. Curr Rheumatol Rep. 2019;21:19.

Acknowledgements

This study was funded by Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA. Medical writing support was provided by Charli Dominguez, PhD, of Health Interactions, Inc, Hamilton, NJ, USA, and was funded by Novartis Pharmaceuticals Corporation. This abstract was developed in accordance with Good Publication Practice (GPP3) guidelines. Authors had full control of the content and made the final decision on all aspects of this publication.

Disclosure of Interests

Marina Magrey Consultant of: Received consulting fees from Eli Lilly and Novartis, Grant/research support from: Received research grants from AbbVie, Amgen, and UCB, Jessica A. Walsh Consultant of: Received consulting fees from Amgen, Janssen, Eli Lilly, Novartis, Pfizer, and UCB, Grant/research support from: Received research funding from AbbVie, Merck, and Pfizer, Sandra Flierl Employee of: Employee of Ipsos, Renato Calheiros Employee of: Employee of Novartis, David Wei Employee of: Employee of Novartis, Muhammad Asim Khan Consultant of: Has served as a consultant for Novartis

POS0966 DEVELOPMENT AND VALIDATION OF AN ANKYLOSING SPONDYLITIS RISK PREDICTION MODEL USING LONGITUDINAL REAL-WORLD DATA FROM A LARGE INTEGRATED HEALTHCARE DELIVERY SYSTEM

Background

Early detection and diagnosis of Ankylosing spondylitis (AS) is challenging due to heterogeneity in disease presentation, lack of specific biomarkers and high prevalence of mechanical back-pain that is difficult to distinguish from inflammatory back-pain. However, if diagnosed and treated early, the risk of AS complications and disease progression can be slowed.

Objectives

To develop and validate a risk prediction model for early identification of patients at high risk of AS, using a large longitudinal real-world clinical data in the US.

Methods

This retrospective study included all members aged ≥ 21 years with back pain symptoms who were enrolled in the Kaiser Permanente Southern California health plan between 01/2009-12/2013. Patients who presented with back pain symptoms at a physician visit were followed until 12/2020 to see if they subsequently developed AS. The cohort was randomly divided into a training (60%) and a validation (40%) sample. A proportional odds model was specified to create a risk score for AS in the training sample. Best fit model was determined based on Area Under the Curve (AUC) and Akaike Information Criterion (AIC). The cut off threshold of “high-risk” was based on Youden’s (1950) index.1 We assessed the model performance for internal validity using split-samples. The model was further validated using manual chart review of 900 patient records. These 900 records were selected such that 70% (N=630) met the high-risk cut-off and the remainder had scores below the cut-off. We also derived the probability of AS in each chart reviewed case using the method proposed by Feldtkeller et al. (2013) and Rudwaleit et al. (2006).2,3

Results

The cohort comprised 527,509 members with mean age 54 years and majority female (58%). Sixty-six percent were White race and 33% were Hispanic ethnicity. The crude incidence of AS was 1% and increased steadily during the follow-up period (Figure 1). The final risk prediction model included 15 risk factors and had an AUC of 0.72 (Table 1). Using Youden’s index, a cut-off value of 11 or higher was identified as the threshold to define high-risk. No evidence of overfitting to our training sample was observed based on the split-sample analysis. The model validation based on manual chart review of 900 records showed sufficient ability to discriminate between those at high-risk vs those not identified to be high-risk. When a concrete rule out or rule in determination could be made using Feldtkeller et al. approach, our model correctly classified 75% of such records.

Table 1.

Final Model Coefficients and Derived Risk Score

Model CoefficientPr(>|z|)Risk ScoreAge above 45 years0.1460.0111.46Male Sex-0.292<0.001-2.92White Race0.259<0.0012.59Non-Hispanic Ethnicity0.177<0.0011.77Corticosteroid Use (Yes/No)0.235<0.0012.35*NSAID User (Yes/No)0.202<0.0012.02Opioid Analgesic User (Yes/No)0.416<0.0014.16Had Enthesitis (Yes/No)0.298<0.0012.98Had Disorders of the Back (Yes/No)0.973<0.0019.73Had Fatigue and/or Malaise (Yes/No)0.1550.0561.55Had Psoriasis (Yes/No)0.2880.0082.88Had Spondylosis (Yes/No)0.838<0.0018.38Had Synovitis (Yes/No)0.1430.0661.43Had Uveitis (Yes/No)0.6210.0076.21Depression Diagnosis (Yes/No)0.0990.0170.99

* NSAID: Non-steroidal anti-inflammatory drugs

Figure 1.

Cumulative Incidence Over Time (in Days)

Conclusion

To aid early detection, we have developed and validated an AS risk prediction model with an easy to implement scoring system using demographics, medication use and diagnosis data that is routinely collected in clinical practice.

References:

[1]Youden WJ. Index for rating diagnostic tests. Cancer. 1950;3(1):32-35.

[2]Feldtkeller E, Rudwaleit M, Zeidler H. Easy probability estimation of the diagnosis of early axial spondyloarthritis by summing up scores. Rheumatology (Oxford, England). 2013;52(9):1648-1650

[3]Rudwaleit M, Feldtkeller E, Sieper J. Easy assessment of axial spondyloarthritis (early ankylosing spondylitis) at the bedside. Ann Rheum Dis 2006;65:1251-2.

Disclosure of Interests

Aniket Kawatkar Grant/research support from: Novartis, Medac, Esther Yi Employee of: Novartis, Erika Estrada Grant/research support from: Novartis, Jose Pio Grant/research support from: Novartis, Cecilia Portugal Grant/research support from: Novartis, David Yi Grant/research support from: Novartis, Talar Habeshian Grant/research support from: Novartis, David Wei Employee of: Novartis, Steven Lee Grant/research support from: Novartis

Negative associations of morning serum cortisol levels with obesity: the Henan rural cohort study

AIMS

To evaluate the associations of morning serum cortisol levels with obesity defined by different indices in Chinese rural populations.

MATERIALS AND METHODS

A cross-sectional study was performed including 6198 participants (2566 males and 3632 females). Serum cortisol was collected in morning and quantified by liquid chromatography-tandem mass spectrometry. Obesity was defined by body mass index (BMI), body fat percentage (BFP), waist-to-height ratio (WHtR), waist circumference (WC), visceral fat index (VFI) and waist-to-hip ratio (WHR). Both multivariable liner regression, logistic regression and restrictive cubic splines models were used to estimate the gender-specific relationships between cortisol levels and obesity defined by different indices, respectively.

RESULTS

After adjusting for potential confounders, serum cortisol was negatively associated with different obesity measures, except obese females defined by BFP (for instance, overall obesity defined by BMI, Quartile 4 vs. Quartile 1, odds ratio (OR) = 0.25, 95% confidence interval (CI):0.15, 0.41 in males, and OR = 0.58, 95% CI: 0.42,0.80 in females, central obesity defined by WC, OR = 0.52, 95% CI:0.39,0.69 in males and OR = 0.63, 95% CI:0.51,0.77 in females). Similarly, restrictive cubic splines showed the nonlinear relationship between high levels of cortisol and different obesity indices. Furthermore, ROC curve analysis indicated that cortisol could improve the discrimination of model with common biomarkers.

CONCLUSION

Morning serum cortisol were negatively related to obesity defined by different indices in Chinese rural populations. In addition, cortisol could be as a biomarker for prediction of obesity in males.

lnc94638 is a testis-specific long non-coding RNA involved in spermatozoa formation in Zeugodacus cucurbitae (Coquillett)

Long non-coding RNAs (lncRNAs) generally display tissue-specific distributions, and testis-specific lncRNAs form the highest proportion of lncRNAs in many species. Here, we presented a detailed analysis of testis-specific lncRNAs in the melon fly, Zeugodacus cucurbitae, a highly destructive insect pest of cucurbitaceous and other related crops. Most testis-specific lncRNAs were found to be long intergenic non-coding RNAs (lincRNA). The size distribution of these lncRNAs ranged between 600 and 1000 nucleotides. Testis-specific lncRNAs that harboured one isoform number and two exons were the most abundant. Compared to other male tissues, the testis had more highly expressed lncRNAs. The quantitative real-time polymerase chain reaction results of 10 randomly selected testis-specific lncRNAs showed expression patterns consistent with RNA-seq data. Further analysis of the most highly expressed testis-specific lncRNA, lnc94638, was undertaken. Fluorescent in situ hybridization assays localized lnc94638 to the apical region of the testis that contains mature spermatozoa. RNA interference-mediated knockdown of lnc94638 expression reduced spermatozoa numbers and impaired the fertility of Z. cucurbitae male. This study provides a catalogue of testis-specific lncRNAs, shows that the testis-specific lnc94638 is involved in spermatogenesis and has the potential to be used for treating male sterility.

Associations of maternal hypertensive disorders during pregnancy with offspring risks of ischemic heart disease and stroke: a Nordic cohort study

Background

A substantial body of evidence suggests that children exposed to maternal hypertensive disorders during pregnancy (HDP) have increased risks of preterm birth, fetal growth restriction and several cardiovascular risk factors (e.g., hypertension, obesity, diabetes) later in life. However, the direct evidence on the link between maternal HDP and the risk of severe cardiovascular diseases such as ischemic heart disease (IHD) and stroke in the offspring is very limited.

Objective

To investigate the associations between maternal HDP and the risk of IHD and stroke in the offspring.

Methods

We conducted a population-based cohort study by linking several national registers in Sweden and Finland. Live singleton births from the Swedish Medical Birth Register (1973–2014) and the Finnish Medical Birth Register (1987- 2014) were followed for IHD and stroke until 2014 by the national patient and cause of death registers. We performed Cox regression models to examine the association between maternal HDP and its subtypes, i.e., pre-existing chronic hypertension, gestational hypertension, and preeclampsia, and the risk of IHD, and stroke in the offspring while adjusting for relevant maternal and pregnancy-related confounders. We conducted sibling analyses to control for unmeasured shared familial (genetic and/or environmental) risk factors.

Results

Among the 5,807,122 singletons included in the study, 218,322 (3.76%) children were born to mothers with HDP. During the up to 41 years of follow-up, 2,340 (0.04%) offspring were diagnosed with IHD and 5,360 (0.09%) were diagnosed with stroke. Offspring exposed to maternal HDP had an increased risk of IHD (adjusted hazard ratio (aHR), 1.29; 95% confidence interval (CI), 1.01–1.63), and stroke (aHR,1.33; 95% CI, 1.14–1.56). Significantly increased rates of stroke were also observed in children exposed to the subtypes of maternal HDP: pre-existing chronic hypertension (aHR, 1.64; 95% CI, 1.03–2.60), gestational hypertension (HR, 1.38; 95% CI, 1.08–1.77), and preeclampsia (HR, 1.26; 95% CI, 1.02–1.55). The associations between maternal HDP and offspring's IHD and stroke were independent of preterm birth and small for gestational age at birth. Maternal HDP remained associated with stroke in the offspring (aHR, 1.94; 95% CI, 1.16–3.22), but not with IHD (aHR, 0.89; 95% CI, 0.47–1.67) in the sibling analyses.

Conclusion

Children to mothers with HDP have increased rates of IHD and stroke from childhood to young adulthood. While the link between maternal HDP and IHD in the offspring seemed to be attributed to confounding by familial factors, the relation between maternal HDP and stroke persisted even when considering such confounding. Persons born to mothers with HDP may benefit from early screening and prevention efforts to reduce the risk of IHD and stroke later in life.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): Swedish Heart and Lung Foundation

Death of a child and the risk of heart failure: a population-based cohort study from Denmark and Sweden

Background

Increasing evidence suggests that the death of a child is associated with increased risks of ischemic heart diseases and atrial fibrillation and the association is in part attributable to stress-related mechanisms. However, knowledge regarding the risk of heart failure (HF) after the death of a child is very limited.

Purpose

To study the association between the death of a child and the parents' risk of HF.

Methods

We conducted a population-based cohort study involving parents of live-born children recorded in the Danish and Swedish Medical Birth Registers during 1973–2016 and 1973–2014, respectively (n=6,717,531). We retrieved information on child death, HF diagnosis and parents' sociodemographic characteristics from several nationwide registries. We performed Poisson regression models to estimate incidence rate ratio (IRR) and 95% confidence intervals (CI) for HF.

Results

A total of 129,829 (1.9%) parents lost at least one child during the follow-up. Bereaved parents had a 35% higher risk of HF than non-bereaved parents [IRR (95% CI): 1.35 (1.29–1.41)]. The association was present not only if the child died due to cardiovascular or other natural causes [IRR (95% CI): 1.48 (1.25–1.75) and 1.35 (1.27–1.44), respectively], but also in case of unnatural deaths [IRR (95% CI): 1.32 (1.24–1.42)]. There was a trend toward a U-shaped association according to the deceased child's age at loss and the risk of HF. Bereaved parents who lost their only child or had three or more remaining live children at the time of loss had higher HF risk than those with one or two live children at the time of loss. We found no clear evidence for a difference in the association of interest over time.

Conclusions

The death of a child was associated with an increased risk of HF. The finding that not only cardiovascular and other natural deaths, but also unnatural deaths were associated with HF suggests that stress-related mechanisms may contribute to the development of HF.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): Swedish Council for Working Life and Social Research and Karolinska Institutet's Research Foundation

Association of maternal gestational weight gain with intellectual developmental disorder in the offspring: a nationwide follow-up study in Sweden

OBJECTIVES

To investigate the association between maternal gestational weight gain (GWG) and offspring's intellectual developmental disorders (IDD); how this association is modified by maternal early-pregnancy BMI.

DESIGN

Population-based cohort study.

SETTING AND POPULATION

All liveborn singletons with information on maternal GWG in the Swedish Medical Register during 1992-2006 (n = 467 485).

METHODS

We used three GWG classifications, (1) Institute of Medicine (IOM) guidelines ('ideal' GWG: maternal underweight = 12.7-18.1 kg; normal = 11.3-15.9 kg; overweight = 6.8-11.3 kg; obesity = 5.0-9.1 kg), (2) LifeCycle project recommendation ('ideal' GWG: maternal underweight = 14.0-16.0 kg; normal = 10.0-18.0 kg; overweight = 2.0-16.0 kg; obesity class I = 2.0-6.0 kg; obesity class II ≤0.0-4.0 kg; obesity class III ≤0.0-6.0 kg) and (3) GWG centiles. Hazard ratio (HR) and 95% CI for offspring's IDD risk using Cox regression.

MAIN OUTCOME MEASURES

IDD was extracted from Swedish National Patient Register (code ICD-9:317-319/ICD-10:F70-F79).

RESULTS

Forty-one per cent of children were born to mothers with excessive GWG, 32.8% with ideal GWG and 26.2% with inadequate GWG according to IOM guidelines. Inadequate GWG was associated with 21% higher risk of offspring's IDD (95% CI 1.11-1.31) relative to ideal GWG. In contrast, when using the LifeCycle classification, children of mothers with inadequate GWG (HR 1.14, 95% CI 1.05-1.24) or excessive GWG (HR 1.09, 95% CI 1.01-1.17) had higher risks of IDD than those of mothers with ideal GWG. When using GWG centiles, extremely low GWG (<20th centile) and low GWG (20th-40th centile) were associated with elevated offspring's IDD risk. Further stratified analysis by maternal early-pregnancy body mass index (BMI) showed that overweight/obese mothers (BMI ≥25 kg/m² ) with extremely excessive GWG (>25 kg) was associated with an increased offspring's IDD.

CONCLUSION

Our findings suggest that inadequate maternal GWG may increase offspring's IDD risk, irrespective of maternal early-pregnancy BMI. Extremely excessive GWG (>25 kg) may increase offspring's IDD risk, but only among mothers with an early-pregnancy BMI ≥25 kg/m² .

TWEETABLE ABSTRACT

Inadequate maternal weight gain during pregnancy may increase the risk of offspring's intellectual disability, regardless of maternal BMI.

Coordination of primary metabolism and virulence factors expression mediates the virulence of Vibrio parahaemolyticus towards cultured shrimp (Penaeus vannamei)

AIMS

Acute hepatopancreatic necrosis disease (AHPND) caused by Vibrio parahaemolyticus has emerged as a severe bacterial disease of cultured shrimp. To identify the key virulence factors, two AHPND-causing V. parahaemolyticus (Vp_AHPND ) strains (123 and 137) and two non-Vp_AHPND strains (HZ56 and ATCC 17082) were selected.

METHODS AND RESULTS

Challenge tests showed that the four strains exhibited different virulence towards shrimp with cumulative mortalities at 48 h postinfection (hpi) ranging from 10 to 92%. The expression of pirAB^VP in strain 123 and 137 was not significantly different. Genomic analysis revealed that the two Vp_AHPND strains contain a plasmid with the PirAB^VP toxins (pirAB^VP ) flanked by the insertion sequence (ISVal1) that has been identified in various locations of chromosomes in Vp_AHPND strains. The two Vp_AHPND strains possessed almost identical virulence factors, while ISVal1 disrupted three genes related to flagellar motility in strain 137. Phenotype assay showed that strain 123 possessed the highest growth rate and swimming motility, followed by strain 137, suggesting that the disruption of essential genes mediated by ISVal1 significantly affected the virulence level. Transcriptome analysis of two Vp_AHPND strains (123 and 137) further suggested that virulence genes related to the capsule, flagella and primary metabolism were highly expressed in strain 123.

CONCLUSIONS

Here for the first time, it is demonstrated that the virulence of Vp_AHPND is not only determined by the expression of pirAB^VP , but also is mediated by ISVal1 which affects the genes involved in flagellar motility and primary metabolism.

SIGNIFICANCE AND IMPACT OF THE STUDY

The genomic and transcriptomic analysis of Vp_AHPND strains provides valuable information on the virulence factors affecting the pathogenicity of Vp_AHPND.

Community diversity and abundance of ammonia-oxidizing archaea and bacteria in shrimp pond sediment at different culture stages

AIMS

Ammonia oxidation is a significant process of nitrogen cycles in a lot of ecosystems sediments while there are few studies in shrimp culture pond (SCP) sediments. This paper attempted to explore the community diversity and abundance of ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) in SCP sediments at different culture stages.

METHODS AND RESULTS

We collected SCP sediments and analysed the community diversity and abundance of AOA and bacteria in shrimp pond sediment at different culture stages using the ammonia monooxygenase (amoA) gene with quantitative PCR (qPCR) and 16S rRNA gene sequencing. The AOB-amoA gene abundance was showed higher than AOA-amoA gene abundance in SCP sediments on Day 50 and Day 60 after shrimp larvae introducing into the pond, and the diversity of AOA in SCP sediments was higher than that of AOB. The phylogenetic tree revealed that the most of AOA were the member of Nitrosopumilus and Nitrososphaera, and the majority of AOB sequences were clustered into Nitrosospira, Nitrosomonas clusters 6a and 7. The AOA community has close relationship with total organic carbon (TOC), pH, total phosphorus (TP), nitrate reductase, urease, acid phosphatase and β-glucosidase. The AOB community was related to TOC, C/N and nitrate reductase.

CONCLUSIONS

AOA and AOB play the different ecological roles in SCP sediments at different culture stages.

SIGNIFICANCE AND IMPACT OF THE STUDY

Our results suggested that the different community diversity and abundance of AOA and AOB in SCP sediments, which may improve our ecological cognition of shrimp culture stages in SCP ecosystems.

Automated Measurements of Key Morphological Features of Human Embryos for IVF

A major challenge in clinical In-Vitro Fertilization (IVF) is selecting the highest quality embryo to transfer to the patient in the hopes of achieving a pregnancy. Time-lapse microscopy provides clinicians with a wealth of information for selecting embryos. However, the resulting movies of embryos are currently analyzed manually, which is time consuming and subjective. Here, we automate feature extraction of time-lapse microscopy of human embryos with a machine-learning pipeline of five convolutional neural networks (CNNs). Our pipeline consists of (1) semantic segmentation of the regions of the embryo, (2) regression predictions of fragment severity, (3) classification of the developmental stage, and object instance segmentation of (4) cells and (5) pronuclei. Our approach greatly speeds up the measurement of quantitative, biologically relevant features that may aid in embryo selection.

Analysis of the clinicopathological characteristics and prognosis of adenoid cystic carcinoma of the intraoral minor salivary glands: a retrospective study of 40 cases

The clinicopathological aspects and prognostic factors of 40 patients with adenoid cystic carcinoma (ACC) of the intraoral minor salivary glands, treated between 2007 and 2017 at a single institution, were evaluated retrospectively. Twenty-six were female and 14 were male, and they ranged in age from 26 to 81 years (median 55 years). ACC occurred mainly in the palate, with 54.8% of cases presenting T3-T4 lesions. Curative surgery was performed in all patients, and 62.5% of patients were treated with postoperative adjuvant radiotherapy. In the final analysis, positive surgical margins were noted in 57.5% of cases and perineural invasion in 70%. Follow-up was at least 13 months (range 13-141 months, median 59 months). Nineteen patients (47.5%) developed recurrent disease after initial surgery and nine patients had died at the end of follow-up. The 5- and 10-year overall survival rates were 88.3% and 25.6%, respectively. The 5- and 10-year disease-free survival rates were 75.6% and 34.0%, respectively. Patients with a tumour size >4cm and those with positive surgical margins showed a significantly higher risk of local recurrence. Elective neck dissection is suggested for patients with clinically positive lymph nodes or a locally advanced tumour, especially those undergoing microvascular reconstruction. The survival analysis results are similar to those reported previously in the literature.