Role of prostaglandin E2 and its receptors in chronic liver disease

Chronic liver disease (CLD) is a major global health burden in terms of growing morbidity and mortality. Although many conditions can cause CLD, leading to cirrhosis and hepatocellular carcinoma (HCC), viral hepatitis, drug-induced liver injury (DILI), alcoholic liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD) are the most common culprits. Prostaglandin E2 (PGE2), produced in the liver, is an important lipid mediator derived from the ω-6 polyunsaturated fatty acid, arachidonic acid, and plays a critical role in hepatic homeostasis. The physiological effects of PGE2 are mediated through four classes of E-type prostaglandin (EP) receptors, namely EP1, EP2, EP3 and EP4. In recent years, an increasing number of studies has been done to clarify the effects of PGE2 and EP receptors in regulating liver function and the pathogenesis of CLD to create a new potential clinical impact. In this review, we overview the biosynthesis and regulation of PGE2 and discuss the role of its synthesizing enzymes and receptors in the maintenance of normal liver function and the development and progress of CLD. We also discuss the potential of the PGE2-EP receptors system in treating CLD with various etiologies.

Association between workplace health promotion service utilisation and depressive symptoms among workers: a nationwide survey

OBJECTIVES

Workplace-related factors are associated with the risk of depression. Despite implementation of workplace health promotion (WHP) programmes in China to promote the physical and mental well-being of workers, the relationship between WHP and depression has received limited attention. This study investigated the association between WHP service utilisation and depressive symptoms among workers.

STUDY DESIGN

This was a cross-sectional survey.

METHODS

A researcher-designed questionnaire was used to collect information on socio-demographic and occupational characteristics, WHP service utilisation, and mental health status. The Lasso method was used for variable selection to achieve dimension reduction, and logistic regression was used to assess the association between WHP service utilisation and depressive symptoms.

RESULTS

The analysis included 11,710 workers, of whom 17.0% had depressive symptoms. Lasso regression resulted in 6 of 18 WHP services showing significant negative associations with depressive symptoms, including occupational safety training, mental health services, health check-ups, sports activities, fitness rooms, and healthy canteens. The logistic regression results showed that, after adjusting for sociodemographic and occupational factors, utilisation of these six services was associated with a decreased likelihood of depressive symptoms. The adjusted odds ratio (aOR) was 0.84 (95% confidence interval [CI]: 0.73-0.96) for occupational safety training, aOR: 0.82 (95% CI: 0.68-0.99) for mental health services, aOR: 0.80 (95% CI: 0.71-0.90) for health check-ups, aOR: 0.68 (95% CI: 0.57-0.80) for sports activities, aOR: 0.59 (95% CI: 0.47-0.74) for fitness rooms and aOR: 0.72 (95% CI: 0.59-0.87) for healthy canteens.

CONCLUSIONS

Utilisation of WHP services was associated with a lower prevalence of depressive symptoms. Implementation of WHP services and the provision of a supportive workplace environment should be prioritised to benefit the mental health of workers.

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.

Floating-Point Approximation Enabling Cost-Effective and High-Precision Digital Implementation of FitzHugh-Nagumo Neural Networks

The study of neuron interactions and hardware implementations are crucial research directions in neuroscience, particularly in developing large-scale biological neural networks. The FitzHugh-Nagumo (FHN) model is a popular neuron model with highly biological plausibility, but its complexity makes it difficult to apply at scale. This paper presents a cost-saving and improved precision approximation algorithm for the digital implementation of the FHN model. By converting the computational data into floating-point numbers, the original multiplication calculations are replaced by adding the floating-point exponent part and fitting the mantissa part with piecewise linear. In the hardware implementation, shifters and adders are used, greatly reducing resource overhead. Implementing FHN neurons by this approximation calculations on FPGA reduces the normalized root mean square error (RMSE) to 3.5% of the state-of-the-art (SOTA) while maintaining a performance overhead ratio improvement of 1.09 times. Compared to implementations based on approximate multipliers, the proposed method achieves a 20% reduction in error at the cost of a 2.8% increase in overhead.This model gained additional biological properties compared to LIF while reducing the deployment scale by only 9%. Furthermore, the hardware implementation of nine coupled circular networks with eight nodes and directional diffusion was carried out to demonstrate the algorithm's effectiveness on neural networks. The error decreased to 60% compared to the single neuron of the SOTA. This hardware-friendly algorithm allows for the low-cost implementation of high-precision hardware simulation, providing a novel perspective for studying large-scale, biologically plausible neural networks.

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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PI-RADS v2.1 evaluation of prostate "nodule in nodule" variants: clinical, imaging, and pathological features

OBJECTIVES

To analyze the correlation among the imaging features of prostate "nodule in nodule," clinical prostate indices, and pathology results.

METHODS

We retrospectively analyzed the prostate images from 47 male patients who underwent MRI scans and pathological biopsy from January 2022 to July 2023. Two radiologists (R1/R2) evaluated the morphology and signal intensity of the "nodule in nodule" in a double-blind manner and calculated the PI-RADS v2.1 score, which was compared with clinical prostate indices and pathological results.

RESULTS

34.04% (16/47) of patients were pathologically diagnosed with clinically significant prostate cancer (csPCa). Total prostate-specific antigen (tPSA), free/t PSA, PSA density (PSAD), and prostate gland volume (PGV) were significantly different between csPCa patients and benign prostatic hyperplasia (BPH) patients with prostate "nodule in nodule". R1/R2 detected 17/17 prostate "nodule in nodule" pathologically confirmed as csPCa on MRI; 10.60% (16/151) (R1) and 11.11% (17/153) (R2) had diffusion-weighted imaging (DWI) PI-RADS v2.1 score of 4, and 0.66% (1/151) (R1) had a score of 3. The percentages of encapsulated, circumscribed, and atypical nodules and obscured margins were 0.00% (0/151), 0.00% (0/151), 5.96% (9/151), and 5.30% (8/151), respectively, for R1, and 0.00% (0/153), 0.00% (0/153), 5.88% (9/153), and 4.58% (7/153) for R2.

CONCLUSION

When the inner nodules of "nodule in nodule" lesions in PI-RADS v2.1 category 1 in the TZ show incomplete capsulation or obscured margins, they are considered atypical nodules and might be upgraded to PI-RADS v2.1 category 3 if they exhibit marked diffusion restriction. However, further validation is needed.

CRITICAL RELEVANCE STATEMENT

This study first analyzed the relationship between clinical and pathological findings and the size, margin, and multimodal MRI manifestations of the prostate "nodule in nodule." These findings could improve the diagnostic accuracy of PI-RADS v2.1 for prostate lesions.

KEY POINTS

• The margin of the prostate inner nodules affects the PI-RADS v2.1 score. • The morphology of prostate "nodule in nodule" is related to their pathology. • The PI-RADS v2.1 principle requires consideration of prostate "nodule in nodule" variants.

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.

Fully semantic segmentation for rectal cancer based on post-nCRT MRl modality and deep learning framework

PURPOSE

Rectal tumor segmentation on post neoadjuvant chemoradiotherapy (nCRT) magnetic resonance imaging (MRI) has great significance for tumor measurement, radiomics analysis, treatment planning, and operative strategy. In this study, we developed and evaluated segmentation potential exclusively on post-chemoradiation T2-weighted MRI using convolutional neural networks, with the aim of reducing the detection workload for radiologists and clinicians.

METHODS

A total of 372 consecutive patients with LARC were retrospectively enrolled from October 2015 to December 2017. The standard-of-care neoadjuvant process included 22-fraction intensity-modulated radiation therapy and oral capecitabine. Further, 243 patients (3061 slices) were grouped into training and validation datasets with a random 80:20 split, and 41 patients (408 slices) were used as the test dataset. A symmetric eight-layer deep network was developed using the nnU-Net Framework, which outputs the segmentation result with the same size. The trained deep learning (DL) network was examined using fivefold cross-validation and tumor lesions with different TRGs.

RESULTS

At the stage of testing, the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean surface distance (MSD) were applied to quantitatively evaluate the performance of generalization. Considering the test dataset (41 patients, 408 slices), the average DSC, HD95, and MSD were 0.700 (95% CI: 0.680-0.720), 17.73 mm (95% CI: 16.08-19.39), and 3.11 mm (95% CI: 2.67-3.56), respectively. Eighty-two percent of the MSD values were less than 5 mm, and fifty-five percent were less than 2 mm (median 1.62 mm, minimum 0.07 mm).

CONCLUSIONS

The experimental results indicated that the constructed pipeline could achieve relatively high accuracy. Future work will focus on assessing the performances with multicentre external validation.

[Clinical features and prognostic analysis of testicular relapse in pediatric acute lymphoblastic leukemia]

Objective: To investigate the clinical features and prognosis of testicular relapse in pediatric acute lymphoblastic leukemia (ALL). Methods: Clinical data including the age, time from initial diagnosis to recurrence, relapse site, and therapeutic effect of 37 pediatric ALL with testicular relapse and treated in Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences between November 2011 and December 2022 were analyzed retrospectively. Patients were grouped according to different clinical data. Kaplan-Meier analysis was used to evaluate the overall survival (OS) rate and event free survival (EFS) rate for univariate analysis, and Cox proportional-hazards regression model was used to evaluate the influencing factors of OS rate and EFS rate for multivariate analysis. Results: The age at initial diagnosis of 37 pediatric testicular relapse patients was (5±3) years and the time from initial diagnosis to testicular recurrence was (37±15) months. The follow-up time was 43 (22, 56) months. Twenty-three patients (62%) were isolated testis relapse. The 5-year OS rate and EFS rate of the 37 relapsed children were (60±9) % and (50±9) % respectively. Univariate analysis showed that the 2-year EFS rate in the group of patients with time from initial diagnosis to testicular recurrence >28 months was significantly higher than those ≤28 months ((69±10)% vs. (11±11)%, P<0.05), 2-year EFS rate of the isolated testicular relapse group was significantly higher than combined relapse group ((66±11)% vs. (20±13) %, P<0.05), 2-year EFS rate of chimeric antigen receptor T (CAR-T) cell treatment after relapse group was significantly higher than without CAR-T cell treatment after relapse group ((78±10)% vs. (15±10)%, P<0.05). ETV6-RUNX1 was the most common genetic aberration in testicular relapsed ALL (38%, 14/37). The 4-year OS and EFS rate of patients with ETV6-RUNX1 positive were (80±13) % and (64±15) %, respectively. Multivariate analysis identified relapse occurred≤28 months after first diagnosis (HR=3.09, 95%CI 1.10-8.72), combined relapse (HR=4.26, 95%CI 1.34-13.52) and CAR-T cell therapy after relapse (HR=0.15,95%CI 0.05-0.51) were independent prognostic factors for 2-year EFS rate (all P<0.05). Conclusions: The outcome of testicular relapse in pediatric ALL was poor. They mainly occurred 3 years after initial diagnosis. ETV6-RUNX1 is the most common abnormal gene.Patients with ETV6-RUNX1 positive often have a favorable outcome. Early relapse and combined relapse indicate unfavorable prognosis, while CAR-T cell therapy could significantly improve the survival rate of children with testicular recurrence.

[Clinical and prognostic characteristics of pediatric acute myeloid leukemia with myelodysplasia-related changes under different diagnostic criteria]

Objective: To evaluate the clinical and prognostic differences in acute myeloid leukemia with myelodysplasia-related changes (AML-MRC) children under different diagnostic criteria (World Health Organization (WHO) 2016 and WHO 2022 criteria). Methods: In this retrospective cohort study, clinical characteristics and prognosis information of 260 acute myeloid leukemia (AML) children admitted to Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences from August 2017 to August 2021 were analyzed retrospectively. According to WHO 2016 and WHO 2022 diagnostic criteria, patients were divided into AML-MRC group and non-AML-MRC group, the prognostic and genetic differences between two groups were compared respectively. Meanwhile, the characteristics of children with 8 MRC-related genes defined in WHO 2022 diagnostic criteria were described. Mann-Whitney U test, chi-square test were used for comparison between groups. Survival curve was plotted by Kaplan-Meier method, and comparison between groups was performed by Log-Rank method. Results: Among the 260 children, there were 148 males and 112 females. The follow-up time was 26 (16, 38) months. A total of 28 children (10.8%) were diagnosed with AML-MRC according to the WHO 2016 diagnostic criteria. Compared with non-AML-MRC children, the frequency of PTPN11, RUNX11, SH2B3, MPL and STAG2 mutations was higher in AML-MRC children (25.0% (7/28) vs. 4.3% (10/232), 14.3% (4/28) vs. 3.9% (9/232), 10.7% (3/28) vs. 2.2% (5/232), 10.7% (3/28) vs. 2.2% (5/232), 10.7% (3/28) vs. 0.9% (2/232), all P<0.05). The 2-year overall survival (OS) and events free survival (EFS) rate of 28 AML-MRC children under WHO 2016 diagnostic criteria were worse than those of 232 non-AML-MRC children ((62.1±10.8)% vs. (94.5±1.6)%, χ2=22.1,P<0.001;(48.0±10.6)% vs. (70.9±3.2)%, χ2=6.33,P=0.012). Twenty-seven children (10.4%) were eventually diagnosed with AML-MRC according to WHO 2022 criteria, their 2-year OS rate were worse than 233 non-AML-MRC children ((60.8±11.1)% vs. (94.5±1.6)%, χ2=24.49,P<0.001), and there was no statistically significant difference in EFS rate between two groups at 2 years ((55.1±10.8)% vs. (70.1±3.2)%, χ2=2.44, P=0.119). Conclusions: Compared with the 2022 WHO diagnostic criteria, the survival rates of children with AML-MRC under the 2016 WHO diagnostic criteria were worse than that of children without MRC.The new version of the AML-MRC diagnostic criteria emphasizes the importance of genes.

[Safety and efficacy of acute stent implantation during endovascular treatment for patients with emergent large vessel occlusion due to intracranial atherosclerotic stenosis]

Objective: To investigate the efficacy and safety of acute stent implantation during endovascular treatment for patients with emergent large vessel occlusion due to intracranial atherosclerotic stenosis. Methods: A retrospective analysis was carried out on 46 patients with emergent large vessel occlusion due to intracranial atherosclerotic stenosis who received endovascular treatment at the Strategic Support Force Medical Center from January 2015 to August 2022. Twenty-seven patients underwent balloon angioplasty alone and 19 patients underwent acute stent implantation. The baseline characteristics, modified thrombolysis in cerebral infarction (mTICI) score of the responsible vessels, modified Rankin scale (mRS) score 90 days after operation, incidence of symptomatic intracranial hemorrhage and mortality of the two groups were evaluated. Results: The proportion of effective recanalization of the offending vessels (mTICI≥2b) in the acute stenting group was slightly higher than that in the balloon angioplasty group (16/19 vs. 81.5%), but the difference was not statistically significant (P>0.05). Besides, there was no significant difference in the median of mRS between the acute stenting group [3.0(0, 4.0)] and the balloon angioplasty group [4.0(1.0, 5.0)] 90 days after operation (P>0.05). In terms of safety, the incidence of symptomatic intracranial hemorrhage and mortality were comparable between the two groups (P>0.05). Conclusions: The effect of acute stent implantation during endovascular treatment for patients with emergent large vessel occlusion due to intracranial atherosclerotic stenosis is not inferior to that of balloon angioplasty, and it does not increase the risk of intracranial bleeding complications.

Extranodal Extension at Pretreatment MRI and the Prognostic Value for Patients with Rectal Cancer

Background Detection of extranodal extension (ENE) at pathology is a poor prognostic indicator for rectal cancer, but whether ENE can be identified at pretreatment MRI is, to the knowledge of the authors, unknown. Purpose To evaluate the performance of pretreatment MRI in detecting ENE using a matched pathologic reference standard and to assess its prognostic value in patients with rectal cancer. Materials and Methods This single-center study included a prospective development data set consisting of participants with rectal adenocarcinoma who underwent pretreatment MRI and radical surgery (December 2021 to January 2023). MRI characteristics were identified by their association with ENE-positive nodes (χ2 test and multivariable logistic regression) and the performance of these MRI features was assessed (area under the receiver operating characteristic curve [AUC]). Interobserver agreement was assessed by Cohen κ coefficient. The prognostic value of ENE detected with MRI for predicting 3-year disease-free survival was assessed by Cox regression analysis in a retrospective independent validation cohort of patients with locally advanced rectal cancer (December 2019 to July 2020). Results The development data set included 147 participants (mean age, 62 years ± 11 [SD]; 87 male participants). The retrospective cohort included 110 patients (mean age, 60 years ± 9; 79 male participants). Presence of vessel interruption and fusion (both P < .001), heterogeneous internal structure, and the broken-ring and tail signs (odds ratio range, 4.10-23.20; P value range, <.001 to .002) were predictors of ENE at MRI, and together achieved an AUC of 0.91 (95% CI: 0.88, 0.93) in detecting ENE. Interobserver agreement was moderate for the presence of vessel interruption and fusion (κ = 0.46 for both) and substantial for others (κ = 0.61-0.67). The presence of ENE at pretreatment MRI was independently associated with worse 3-year disease-free survival (hazard ratio, 3.00; P = .02). Conclusion ENE can be detected at pretreatment MRI, and its presence was associated with worse prognosis for patients with rectal cancer. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Eberhardt in this issue.

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.

Value of multiple models of diffusion-weighted imaging to predict hepatic lymph node metastases in colorectal liver metastases patients

BACKGROUND

About 10%-31% of colorectal liver metastases (CRLM) patients would concomitantly show hepatic lymph node metastases (LNM), which was considered as sign of poor biological behavior and a relative contraindication for liver resection. Up to now, there's still lack of reliable preoperative methods to assess the status of hepatic lymph nodes in patients with CRLM, except for pathology examination of lymph node after resection.

AIM

To compare the ability of mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted imaging (DWI) models in distinguishing between benign and malignant hepatic lymph nodes in patients with CRLM who received neoadjuvant chemotherapy prior to surgery.

METHODS

In this retrospective study, 97 CRLM patients with pathologically confirmed hepatic lymph node status underwent magnetic resonance imaging, including DWI with ten b values before and after chemotherapy. Various parameters, such as the apparent diffusion coefficient from the mono-exponential model, and the true diffusion coefficient, the pseudo-diffusion coefficient, and the perfusion fraction derived from the intravoxel incoherent motion model, along with distributed diffusion coefficient (DDC) and α from the stretched-exponential model (SEM), were measured. The parameters before and after chemotherapy were compared between positive and negative hepatic lymph node groups. A nomogram was constructed to predict the hepatic lymph node status. The reliability and agreement of the measurements were assessed using the coefficient of variation and intraclass correlation coefficient.

RESULTS

Multivariate analysis revealed that the pre-treatment DDC value and the short diameter of the largest lymph node after treatment were independent predictors of metastatic hepatic lymph nodes. A nomogram combining these two factors demonstrated excellent performance in distinguishing between benign and malignant lymph nodes in CRLM patients, with an area under the curve of 0.873. Furthermore, parameters from SEM showed substantial repeatability.

CONCLUSION

The developed nomogram, incorporating the pre-treatment DDC and the short axis of the largest lymph node, can be used to predict the presence of hepatic LNM in CRLM patients undergoing chemotherapy before surgery. This nomogram was proven to be more valuable, exhibiting superior diagnostic performance compared to quantitative parameters derived from multiple b values of DWI. The nomogram can serve as a preoperative assessment tool for determining the status of hepatic lymph nodes and aiding in the decision-making process for surgical treatment in CRLM patients.

[Swyer syndrome with gonadal non-dysgerminoma malignant germ cell tumors: a report of 15 cases in a national medical center]

Objective: To evaluate the incidence, treatment, and survival outcomes of Swyer syndrome with gonadal non-dysgerminoma malignant germ cell tumor (MGCT-NDG). Methods: A retrospective study was performed on Swyer syndrome patients with MGCT-NDG between January 2011 and December 2022 in Peking Union Medical College Hospital to investigate their characteristics and outcomes. Results: A total of 15 patients (4.9%, 15/307) with Swyer syndrome were identified in 307 MGCT-NDG patients. The average age at diagnosis of MGCT-NDG and Swyer syndrome were (16.8±6.7) and (16.7±6.6) years, respectively. Six cases were preoperatively diagnosed as Swyer syndrome, of which 4 cases received bilateral gonadectomy with or without hysterectomy, while the other 2 cases underwent removal of gonadal tumor and unilateral gonadectomy with hysterectomy, respectively. Of the 9 patients postoperatively diagnosed as Swyer syndrome, unilateral gonadectomy, removal of gonadal tumor, and unilateral gonadectomy with hysterectomy were performed in 6 patients, 2 patients, and 1 patient, respectively. Mixed malignant germ cell tumor (MGCT;10 cases), yolk sac tumor (4 cases), and immature teratoma (1 case) were the pathological subtypes, in the descending order. There were International Federation of Gynecology and Obstetrics (FIGO) stage Ⅰ in 6 cases, stage Ⅱ in 3 cases, stage Ⅲ in 5 cases, and stage Ⅳ in 1 case, respectively. Eleven patients received reoperation for residual gonadectomy after a average delay of (7.9±6.2) months, including 8 MGCT-NDG patients and 1 gonadoblastoma patient, no tumor involved was seen in the remaining gonads in the other 2 cases. Ten patients experienced at least one recurrence, with a median event free survival of 9 months (5, 30 months), of which 2 patients received surgery only at the time of initial treatment. All patients with recurrence received surgery and combined with postoperative chemotherapy. After a median follow-up of 25 months (15, 42 months), 10 patients were disease-free, 3 patients died of the tumor, 1 died of side effects of leukemia chemotherapy, and 1 survived with disease. Conclusion: The incidence rate of Swyer syndrome in patients with MGCT-NDG is about 4.9%; timely diagnosis and bilateral gonadectomy should be emphasized to reduce the risk of reoperation and second carcinogenesis in this population.

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.

Small arteriole sign: an imaging feature for staging T4a colon cancer

OBJECTIVES

By analyzing the distribution of existing and newly proposed staging imaging features in pT1-3 and pT4a tumors, we searched for a salient feature and validated its diagnostic performance.

METHODS

Preoperative multiphase contrast-enhanced CT images of the training cohort were retrospectively collected at three centers from January 2016 to December 2017. We used the chi-square test to analyze the distribution of several stage-related imaging features in pT1-3 and pT4a tumors, including small arteriole sign (SAS), outer edge of the intestine, tumor invasion range, and peritumoral adipose tissue. Preoperative multiphase contrast-enhanced CT images of the validation cohort were retrospectively collected at Beijing Cancer Hospital from January 2018 to December 2018. The diagnostic performance of the selected imaging feature, including accuracy, sensitivity, and specificity, was validated and compared with the conventional clinical tumor stage (cT) by the McNemar test.

RESULTS

In the training cohort, a total of 268 patients were enrolled, and only SAS was significantly different between pT1-3 and pT4a tumors. The accuracy, sensitivity, and specificity of the SAS and conventional cT in differentiating T1-3 and T4a tumors were 94.4%, 81.6%, and 97.3% and 53.7%, 32.7%, and 58.4%, respectively (all p < 0.001). In the validation cohort, a total of 135 patients were collected. The accuracy, sensitivity, and specificity of the SAS and the conventional cT were 93.3%, 76.2%, and 96.5% and 62.2%, 38.1%, and 66.7%, respectively (p < 0.001, p = 0.021, p < 0.001).

CONCLUSION

Small arteriole sign positivity, an indirect imaging feature of serosa invasion, may improve the accuracy of identifying T4a colon cancer.

CLINICAL RELEVANCE STATEMENT

Small arteriole sign helps to distinguish T1-3 and T4a colon cancer and further improves the accuracy of preoperative CT staging of colon cancer.

KEY POINTS

• The accuracy of preoperative CT staging of colon cancer is not ideal, especially for T4a tumors. • Small arteriole sign (SAS) is a newly defined imaging feature that shows the appearance of tumor-supplying arterioles at the site where they penetrate the intestine wall. • SAS is an indirect imaging marker of tumor invasion into the serosa with a great value in distinguishing between T1-3 and T4a colon cancer.

PET/CT Examination of Teratomas after Stem Cell Transplantation for a Spinal Cord Injury: A Case Report

BACKGROUND

In clinical practice, stem cell transplantation has become an effective method for treating spinal cord nerve injury. Up to now, there has been no report on teratoma caused by transplanted stem cell's abnormal differentiation in the clinic, especially in the analysis of imaging manifestations. Therefore, this article aims to analyze the PET/CT imaging manifestations of teratoma caused by stem cell transplantation to improve the imaging diagnosing capability.

CASE PRESENTATION

A patient with a spinal cord injury who had received a stem cell transplant was examined by PET/CT on September 10th, 2020. The PET/CT images of the lesion showed irregular mixed low density on the right side of the erector spinae muscle area at the level of the cervical 3-5 vertebral body, with a maximum cross-section of 9.1×3.9 cm. The 18F-FDG metabolism of the lesion was increased, and the maximum standard uptake value (SUVmax) was 10.7. The boundary was unclear with the third cervical vertebra and cervical 3 and 4-level vertebral plates. Based on the patient's medical history, the lesion was diagnosed as an abnormal proliferative tumor, which was consistent with the pathological examination results.

CONCLUSION

To date, there have been no clinical reports on teratomas caused by stem cell transplantation for spinal cord injury at home or abroad. This case report enhances the knowledge of the diagnosis and treatment methods of this type of disease and confirms the diagnostic value of PET/CT examination.

Radiomics analysis from magnetic resonance imaging in predicting the grade of nonfunctioning pancreatic neuroendocrine tumors: a multicenter study

OBJECTIVES

To explore the potential of radiomics features to predict the histologic grade of nonfunctioning pancreatic neuroendocrine tumor (NF-PNET) patients using non-contrast sequence based on MRI.

METHODS

Two hundred twenty-eight patients with NF-PNETs undergoing MRI at 5 centers were retrospectively analyzed. Data from center 1 (n = 115) constituted the training cohort, and data from centers 2-5 (n = 113) constituted the testing cohort. Radiomics features were extracted from T2-weighted images and the apparent diffusion coefficient. The least absolute shrinkage and selection operator was applied to select the most important features and to develop radiomics signatures. The area under receiver operating characteristic curve (AUC) was performed to assess models.

RESULTS

Tumor boundary, enhancement homogeneity, and vascular invasion were used to construct the radiological model to stratify NF-PNET patients into grade 1 and 2/3 groups, which yielded AUC of 0.884 and 0.684 in the training and testing groups. A radiomics model including 4 features was constructed, with an AUC of 0.941 and 0.871 in the training and testing cohorts. The fusion model combining the radiomics signature and radiological characteristics showed good performance in the training set (AUC = 0.956) and in the testing set (AUC = 0.864), respectively.

CONCLUSION

The developed model that integrates radiomics features with radiological characteristics could be used as a non-invasive, dependable, and accurate tool for the preoperative prediction of grade in NF-PNETs.

CLINICAL RELEVANCE STATEMENT

Our study revealed that the fusion model based on a non-contrast MR sequence can be used to predict the histologic grade before operation. The radiomics model may be a new and effective biological marker in NF-PNETs.

KEY POINTS

The diagnostic performance of the radiomics model and fusion model was better than that of the model based on clinical information and radiological features in predicting grade 1 and 2/3 of nonfunctioning pancreatic neuroendocrine tumors (NF-PNETs). Good performance of the model in the four external testing cohorts indicated that the radiomics model and fusion model for predicting the grades of NF-PNETs were robust and reliable, indicating the two models could be used in the clinical setting and facilitate the surgeons' decision on risk stratification. The radiomics features were selected from non-contrast T2-weighted images (T2WI) and diffusion-weighted imaging (DWI) sequence, which means that the administration of contrast agent was not needed in grading the NF-PNETs.

Network pharmacology-based approach to understand the effect and mechanism of chrysophanol against cognitive impairment in Wilson disease

Wilson disease (WD) is a rare hereditary copper metabolism disorder, wherein cognitive impairment is a common clinical symptom. Chrysophanol (CHR) is an active compound with neuroprotective effects. The study aims to investigate the neuroprotective effect of CHR in WD and attempted to understand the potential mechanisms. Network pharmacology analysis was applied to predict the core target genes of CHR against cognitive impairment in WD. The rats fed with copper-laden diet for 12 weeks, and the effect of CHR on the copper content in liver and 24-h urine, the learning and memory ability, the morphological changes and the apoptosis level of neurons in hippocampal CA1 region, the expression level of Bax, Bcl-2, Cleaved Caspase-3, p-PI3K, PI3K, p-AKT, and AKT proteins were detected. Network pharmacology analysis showed that cell apoptosis and PI3K-AKT signaling pathway might be the main participants in CHR against cognitive impairment in WD. The experiments showed that CHR could reduce the copper content in liver, increase the copper content in 24-h urine, improve the ability of the learning and memory, alleviate the damage and apoptosis level of hippocampal neurons, down-regulate the expression of Bax, Cleaved Caspase-3, and up-regulate the expressions of Bcl-2, p-PI3K/PI3K, p-AKT/AKT. These results suggested that CHR could alleviate cognitive impairment in WD by inhibiting cell apoptosis and triggering the PI3K-AKT signaling pathway.

Synthesis, Characterization and Biosafety Evaluation of Hollow Gold Nanospheres

OBJECTIVES

In order to assess the biosafety of HAuNS using zebrafish models and the cancer cell lines HepG2, HEK293, and A549, this study prepared HAuNS in a variety of sizes and alterations.

METHODS

By oxidizing cobalt nanoparticles encased in gold shells, HAuNS were created. In the meantime, PEG- and PEI-coated HAuNS were created. The diameters of the HAuNS that were produced were 30~40 nm, 50~60 nm, and 70~80 nm. MTT assay was used to assess the toxicity of HAuNS on HepG2, HEK293, and A549 cells. For the investigation of their toxicities, HAuNS (50~60 nm) of various concentrations were incubated with zebrafish embryos. Then, cell death was determined using acridine orange staining.

RESULTS

In a cell line model, it was demonstrated that purified HAuNS exhibit lower toxicity than unpurified HAuNS. Meanwhile, it was discovered that surface-modified HAuNS was less hazardous than unmodified HAuNS. Unpurified HAuNS (50.60 nm) exposure to embryos caused deformity and increased mortality. Moreover, embryos exposed to HAuNS displayed an increase in cell death, showing that HAuNS can put zebrafish under physiological stress.

CONCLUSION

The possible toxicity of HAuNS is now more understood thanks to this investigation. The details could improve our comprehension of the nanotoxicity of medication delivery systems. Comparing HAuNS (50~60 nm) to the other two particle sizes, its toxicity was quite low. Compared to unpurified HAuNS, purified HAuNS displayed less toxicity. Comparing PEI-HAuNS and HAuNS to PEG-HAuNS, cytotoxicity was found to be lower. Our data support the use of pure HAuNS, HAuNS-PEG, and HAuNS (50~60 nm) as possible photothermal conductors when seen as a whole.

[Progress and application of liver organoids in the study of liver cancer]

The incidence rate of liver cancer has been rising in recent years. Traditional cell line culture and human patient-derived tumor xenograft models, which are commonly used tools to simulate the occurrence of human liver cancer, have deepened the understanding of tumor occurrence, development, and drug resistance mechanisms. However, they cannot reflect the accurate state of cancer cells, the tumor microenvironment, or spatial structural characteristics. Recently, more in vitro-produced physiological liver organoids have been applied in the study of liver cancer. Liver organoid models have made breakthroughs in the occurrence and development mechanisms of liver cancer, personalized drug screening and biomarker identification, immunotherapy, and regenerative medicine applications. This paper mainly summarizes the progress and application of liver organoids processed in the study of liver cancer.

[Clinical analysis of allogeneic hematopoietic stem cell transplantation for seven cases of acute myeloid leukemia with BCR::ABL1 fusion]

Objective: To explore the efficacy of allogeneic hematopoietic stem cell transplantation (allo-HSCT) in acute myeloid leukemia (AML) patients with BCR::ABL1 fusion. Methods: The clinical data of seven AML patients with BCR::ABL1 fusion from November 2012 to January 2022 were retrospectively analyzed, and their survival status was followed up. Results: The median age of patients at the time of diagnosis was 35 years. Four cases (57.1%) were diagnosed with high leukocyte counts. All cases were assayed as BCR::ABL1 positive and accompanied by four types of gene mutations (NPM1, RUNX1, ASXL1, PHF6) . Seven patients received tyrosine kinase inhibitor (TKI) combined with induction chemotherapy and bridged to allo-HSCT, and six patients received maintenance therapy with TKI. Before allo-HSCT, six patients achieved complete remission, and four patients achieved complete molecular remission (CMR) . After allo-HSCT, the three remaining cases also achieved CMR. All patients were in remission post-allo-HSCT. One case died of infection, and the remaining cases survived without relapse. The 3-year cumulative overall survival rate was (80.0±17.9) %. Conclusions: TKI combined with traditional chemotherapy could achieve a high response rate in AML patients with BCR::ABL1 fusion. In addition, allo-HSCT could enhance the molecular response rate. Maintenance therapy post-HSCT with TKI could improve prognosis.

STAT3-EphA7 axis contributes to the progression of esophageal squamous cell carcinoma

BACKGROUND

Our previous study has revealed that EphA7 was upregulated in patient-derived esophageal squamous cell carcinoma (ESCC) xenografts with hyper-activated STAT3, but its mechanism was still unclear.

MATERIALS AND METHODS

To assess the association between EphA7 and STAT3, western blotting, immunofluorescence, ChIP assay, and qRT-PCR were conducted. Truncated mutation and luciferase assay were performed to examine the promoter activity of EphA7. CCK-8 assay and colony formation were performed to assess the proliferation of ESCC. Cell-derived xenograft models were established to evaluate the effects of EphA7 on ESCC tumor growth. RNA-seq analyses were used to assess the effects of EphA7 on related signals.

RESULTS

In this study, EphA7 was found upregulated in ESCC cell lines with high STAT3 activation, and immunofluorescence also showed that EphA7 was co-localized with phospho-STAT3 in ESCC cells. Interestingly, suppressing STAT3 activation by the STAT3 inhibitor Stattic markedly inhibited the protein expression of EphA7 in ESCC cells, in contrast, activation of STAT3 by IL-6 obviously upregulated the protein expression of EphA7. Moreover, the transcription of EphA7 was also mediated by the activation of STAT3 in ESCC cells, and the -2000∼-1500 region was identified as the key promoter of EphA7. Our results also indicated that EphA7 enhanced the cell proliferation of ESCC, and silence of EphA7 significantly suppressed ESCC tumor growth. Moreover, EphA7 silence markedly abolished STAT3 activation-derived cell proliferation of ESCC. Additionally, RNA-seq analyses indicated that several tumor-related signaling pathways were significantly changed after EphA7 downregulation in ESCC cells.

CONCLUSION

Our results showed that the transcriptional expression of EphA7 was increased by activated STAT3, and the STAT3 signaling may act through EphA7 to promote the development of ESCC.

[Prognostic comparison of active surveillance and adjuvant chemotherapy in the treatment of patients with stage Ⅰ ovarian immature teratoma after fertility-sparing surgery]

Objective: To compare the survival outcomes between surveillance and adjuvant chemotherapy in patients with stage Ⅰ ovarian immature teratoma (IMT) underwent fertility-sparing surgery. Methods: Clinical and pathological records of patients with stage Ⅰ ovarian IMT between Jan. 2011 to Feb. 2023 were collected from Peking Union Medical College Hospital, except stage Ⅰa grade 1. The consultation of risks and benefits regarding adjuvant chemotherapy was conducted by gynecologic oncologists. A shared decision about surveillance or chemotherapy was made by physician and patients or their guardians. Patients who finally decided to undergo surveillance were included in the surveillance group (n=40), the others were included in the adjuvant chemotherapy group (n=63). Clinical characteristics, treatment and survival outcomes were analyzed and compared between two groups. Results: A total of 103 patients were included. The median age of initial diagnosis was 20 years old (range: 3-39 years old), and the median follow-up time was 31 months (range: 1-254 months). The age, International Federation of Gynecology and Obstetrics (FIGO) stage, pathological grade, surgical method, and preoperative and postoperative alpha-fetoprotein levels in the surveillance group and the adjuvant chemotherapy group were similar (all P>0.05). The surgical approach and maximum tumor diameter between two groups were significantly different (all P<0.05). Forty patients of the surveillance group were identified, only one patient with stage Ⅰa grade 2 IMT who underwent cystectomy had malignant recurrence on the same ovary. Another 63 patients received adjuvant chemotherapy after surgery, five patients had malignant recurrence, and two of them died of disease progression after relapsed. There were no significant differences in disease-free survival (DFS;20 vs 36 months) and overall survival (OS; 23 vs 39 months) between the surveillance group and the adjuvant chemotherapy group (follow-up time censored at 72 months; DFS: P=0.325, OS: P=0.278). Conclusions: There are no differences in survival outcomes between patients with stage Ⅰ ovarian IMT underwent adjuvant chemotherapy or not. Active surveillance might be safe and preferable in stage Ⅰ IMT patients underwent complete resection of tumor.

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.

Establishment of a digital electrocardiogram telemonitoring system and remote consultation service

BACKGROUND

The use of telemonitoring electrocardiogram (ECG) improves the detection rate of various arrhythmias as it offers an extended recording time and does not impose activity restrictions. However, many community hospitals lack the resources to conduct this test due to a lack of cardiac function specialists and antiquated screening equipment.

OBJECTIVE

To establish a digital ECG telemonitoring system and remote consultation service between tertiary hospitals and community medical service stations to improve diagnosis and treatment effectiveness.

METHODS

We used the PI ECG telemonitoring data acquisition system, with a personal digital assistant (PDA) or computer serving as the platform for ECG acquisition, storage, display, printing, and transmission. We introduced this system to standardize the storage and transmission of ECG telemonitoring data, and ensure accurate transmission, reproducibility, and preservation of data.

RESULTS

The implementation of the PI ECG telemonitoring data acquisition system enabled the sharing of remote ambulatory electrocardiography data between Beijing Shijitan Hospital and its affiliated community hospitals. This has resulted in reduced waiting times for patients to receive reports (from 0.3 to 1 hour, to 0.1 or less), shortened consultation times (from 2 hours to 0.1 hour), and improved patient satisfaction with consultations (> 20% of the patients reported they were highly satisfied). The system successfully combined the goals of intelligence, real-time synchronization, and efficiency, revolutionizing ECG telemonitoring diagnosis in the network era.

CONCLUSION

Sharing digital telematics information between tertiary and community hospitals enables a tiered approach to diagnosis and treatment and allows for more efficient, accurate, and convenient remote diagnostics.

[Feasibility of a three-sided encapsulation procedure based on fascia anatomy in laparoscopic lateral lymph node dissection for middle and low rectal cancer]

Objective: To explore the feasibility and value of performing a three-sided encapsulation procedure based on fascia anatomy in laparoscopic lateral lymph node dissection (LLND) for middle and low rectal cancer. Methods: This was a retrospective review. The study cohort comprised patients who met the diagnostic criteria for rectal cancer according to the Chinese Guidelines for the Diagnosis and Treatment of Colorectal Cancer, had a short lymph node diameter of >5 mm on the lateral side within the 15 days before surgery, were evaluated as feasible candidates for laparoscopic total mesorectal excision+LLND surgery, had been diagnosed with low or intermediate level rectal cancer, and whose tumor was less than 8 cm away from the anal verge according to pathological examination of the operative specimen. Patients with a history of other malignant tumors of the abdomen or with incomplete follow-up data were excluded. Forty-two patients with middle and low rectal cancer who had undergone lateral lymph node dissection in diagnosis and treatment center of Gastrointestinal Cancer of Guangdong Hospital of Chinese Medicine from Jan.2018 to Dec.2022 were enrolled. There were 24 men (57.1%) and 18 women (42.9%) aged 58.4±11.8 years and the median BMI was 22.5 (19.3-24.1) kg/m2. The main point of the three-sided encapsulation procedure is to expand the external side medial to the external iliac artery and vein, narrowing the range of exterior side dissection. The anterior-medial side is designed to expand the vesical fascia to define the range of anterior-medial side extension. The internal side is fully extended to the ureterohypogastric nerve fascia; the distal point of the caudal extension reaches the level of the Alcock canal and the bottom reaches the piriformis, enabling dissection of the obturator nerve and No.283 lymph nodes. No.263D lymph nodes are dissected by exposing the internal iliac artery and its branches, dissecting the group No.263P lymph nodes, and severing the inferior vesical artery. Finally, the lateral lymphatic tissue is completely resected. Relevant variables were recorded, including the number of lateral lymph nodes detected, the rate of lymph node metastasis, operation duration, intraoperative blood loss, postoperative complications, postoperative hospital stay, and 3-year overall survival rate. Results: Laparoscopic surgery was successfully completed in all patients with no conversions to open surgery and no intraoperative complications. Twenty-seven (64.3%) of the study patients underwent left-sided LLND, 10 (23.8%) right-sided LLND, and five (11.9%) bilateral LLND, with lymph nodes cleared on both sides. All patients' lymph nodes were examined pathologically. A median of 17.0 (11.7, 26.0) lymph nodes was detected, the median of lateral lymph nodes being 5.0 (2.0, 10.2). The median operation time was 254.5 (199.0, 325.2) minutes. The median intra-operative blood loss was 50.0 (30.0, 100.0) mL. All patients were diagnosed with adenocarcinoma by pathological examination of the operative specimen. Two patients developed postoperative intestinal obstruction, one lymphatic leakage, and one a perineal incision infection. There were no cases of anastomotic leakage. The median postoperative hospital stay was 6.0 (5.0, 7.0) days and the median follow-up time 23.5 (9.0, 36.7) months. During follow-up, three patients (7.1%) died of tumor recurrence and metastasis. Two (4.8%) experienced mild urinary dysfunction, and one (2.4%) had moderate postoperative erectile dysfunction. One patient (2.4%) was found to have prostate and lung metastases 3 month after surgery. The 3-year overall survival rate was 74.4%. Conclusions: Three sided encapsulation is a safe and feasible procedure for LLND, achieving accurate and complete clearance of lateral lymphatic tissue.

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.

[Mediating effects of obesity and metabolic factors in hyperuricemia and prehypertension]

Objective: To assess the mediating effects of obesity and metabolic factors in the relationship between hyperuricemia (HUA) and prehypertension. Methods: A total of 9 399 individuals were selected using a multistage stratified whole-group random sampling method from 90 villages (neighborhood committees) in 30 towns (streets) of 5 districts (counties) in Fuzhou. A total of 4 754 study subjects were included. A linear regression model was used to analyze the association of HUA with obesity and metabolic factors. Single-factor and multi-factor logistic regression models were used to analyze the association of HUA, obesity, and metabolic factors with prehypertension. Mediating effects models were used to analyze the mediating effects of obesity and metabolic factors on the association between HUA and prehypertension. Results: After adjusting for confounders, the association between HUA and cholesterol, triglycerides, HDL-C, LDL-C, BMI, waist circumference, creatinine, and urea nitrogen were significantly correlated (P<0.001). HUA, waist circumference, BMI, and triglycerides were significantly associated with prehypertension (P<0.001). Waist circumference, BMI, and triglycerides mediated the relationship between HUA and prehypertension, with OR (95%CI) of 1.018 (1.007-1.027), 1.010 (1.002-1.018), and 1.010 (1.003-1.017) (P<0.001), with mediating proportions of 7.76%, 4.31%, and 4.31% respectively. No mediating effect of cholesterol, HDL-C, LDL-C, creatinine, and urea nitrogen was found on the relationship (P>0.05). Conclusions: Waist circumference, BMI, and triglycerides all had mediating effects in the association between HUA and prehypertension. For the general population, weight control, waist circumference, and a high-fat diet should be used to reduce the occurrence of prehypertension.

[Research progress in the pathologic mechanism of temporomandibular joint osteoarthritis]

Temporomandibular joint osteoarthritis (TMJOA) is a kind of degenerative lesion in temporomandibular joint disorders. The pathogenesis of TMJOA is complex. Among them, excessive mechanical stress plays an important role, which can cause a series of pathological changes, including synovial inflammation, chondrocyte death, osteogenic and adipogenic differentiation, degradation of extracellular matrix of cartilage, angiogenesis, osteochondral interface sclerosis, subchondral bone remodeling, degeneration of articular discs, etc. In the pathogenesis of TMJOA, it involves multiple signal pathways and epigenetic regulation, which may become potential therapeutic targets of TMJOA. In this paper, the research progress on the pathologic mechanism of TMJOA in recent years is reviewed to provide a basis for finding new therapeutic targets of TMJOA.

Molecular characterization of Clostridium perfringens isolates from a tertiary children's hospital in Guangzhou, China, establishing an association between bacterial colonization and food allergies in infants

BACKGROUND

Cow's milk protein allergy (CMPA) is one of the most common types of food allergy in infants. Faecal pathogen cultures showed that the positive rate of Clostridium perfringens was more than 30%, which was significantly higher than that for other bacteria. Therefore, it is speculated that Clostridium perfringens colonization may be one of the pathogenetic factors for CMPA in infants. We conducted a real-world evidence study. Infants aged 0-6 months with diarrhoea and mucoid and/or bloody stools were recruited from a large tertiary hospital in China. Faecal pathogen cultures for the detection of Clostridium perfringens were confirmed by flight mass spectrometry, and potential toxin genes were identified using PCR. After 12 months of follow-up, the diagnoses of CMPA and food allergy were recorded. The correlation was assessed by Pearson correlation analysis.

RESULTS

In this study, 358 infants aged 0-6 months with gastrointestinal symptoms and faecal pathogen cultures were recruited. A total of 270 (44.07% girls; mean age, 2.78 ± 2.84 months) infants were followed up for 12 months. Overall, the rate of positivity for Clostridium perfringens in faecal pathogen cultures was 35.75% (128/358) in infants aged ≤ 6 months. The earliest Clostridium perfringens colonization was detected within 2 days after birth. The majority of Clostridium perfringens isolates were classified as type C in 85 stool samples. In the Clostridium perfringens-positive group, 48.21% (54/112) of infants were clinically diagnosed with food allergies after 12 months, including 37.5% (42/112) with CMPA, which was significantly higher than that of the negative group, with 7.59% (12/158) exhibiting food allergies and 5.06% (8/158) presenting CMPA (P < 0.0001). Faecal Clostridium perfringens positivity was significantly correlated with CMPA, food allergy, faecal occult blood, faecal white blood cells, antibiotic use, increased peripheral blood platelet counts, and decreased haemoglobin levels (P < 0.0001).

CONCLUSIONS

This study demonstrates that intestinal colonization by Clostridium perfringens is common in infants. The majority of Clostridium perfringens isolates are classified as type C. Colonization of the intestine by Clostridium perfringens is associated with the development of CMPA and food allergy in infants.

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.

16α-OHE1, a novel oestrogen metabolite, attenuates dysfunction of left ventricle contractility via regulation of autophagy after myocardial ischemia and reperfusion

BACKGROUND

Myocardial ischemia-reperfusion (MI/R) can exacerbate the initial cardiac damage in the myocardial functional changes, including dysfunction of left ventricular contractility. Oestrogen has been proven to protect the cardiovascular system. However, whether the oestrogen or its metabolites play the main role in attenuating dysfunction of left ventricular contractility is unknown.

METHODS AND RESULTS

This study used the LC-MS/MS to detect oestrogen and its metabolites in clinical serum samples (n = 62) with heart diseases. After correlation analysis with markers of myocardial injury including cTnI (P < 0.01), CK-MB (P < 0.05), and D-Dimer (P < 0.001), 16α-OHE1 was identified. The result from LC-MS/MS in female and ovariectomised (OVX) rat serum samples (n = 5) matched the findings in patients. In MI/R model of animal, the recovery of left ventricular developed pressure (LVDP), rate pressure product (RPP), dp/dtmax and dp/dtmin after MI/R in OVX or male group were worsened than those in female group. Also, the infarction area of OVX or male group was larger than that in females (n = 5, p < 0.01). Furthermore, LC3 II in the left ventricle of OVX and male group was lower than that in females (n = 5, p < 0.01) by immunofluorescence. In H9C2 cells, after the application of 16α-OHE1, the number of autophagosomes was further increased and other organelles improved in MI/R. Simultaneously, LC3 II, Beclin1, ATG5, and p-AMPK/AMPK were increased, and p-mTOR/mTOR was decreased (n = 3, p < 0.01) by Simple Western.

CONCLUSION

16α-OHE1 could attenuate left ventricle contractility dysfunction via autophagy regulation after MI/R, which also offered fresh perspectives on therapeutical treatment for attenuating MI/R injury.

Pregnane X receptor activation alleviates renal fibrosis in mice via interacting with p53 and inhibiting the Wnt7a/β-catenin signaling

Renal fibrosis is a common pathological feature of chronic kidney disease (CKD) with various etiologies, which seriously affects the structure and function of the kidney. Pregnane X receptor (PXR) is a member of the nuclear receptor superfamily and plays a critical role in regulating the genes related to xenobiotic and endobiotic metabolism in mammals. Previous studies show that PXR is expressed in the kidney and has protective effect against acute kidney injury (AKI). In this study, we investigated the role of PXR in CKD. Adenine diet-induced CKD (AD) model was established in wild-type and PXR humanized (hPXR) mice, respectively, which were treated with pregnenolone-16α-carbonitrile (PCN, 50 mg/kg, twice a week for 4 weeks) or rifampicin (RIF, 10 mg·kg-1·d-1, for 4 weeks). We showed that both PCN and RIF, which activated mouse and human PXR, respectively, improved renal function and attenuated renal fibrosis in the two types of AD mice. In addition, PCN treatment also alleviated renal fibrosis in unilateral ureter obstruction (UUO) mice. On the contrary, PXR gene deficiency exacerbated renal dysfunction and fibrosis in both adenine- and UUO-induced CKD mice. We found that PCN treatment suppressed the expression of the profibrotic Wnt7a and β-catenin in AD mice and in cultured mouse renal tubular epithelial cells treated with TGFβ1 in vitro. We demonstrated that PXR was colocalized and interacted with p53 in the nuclei of tubular epithelial cells. Overexpression of p53 increased the expression of Wnt7a, β-catenin and its downstream gene fibronectin. We further revealed that p53 bound to the promoter of Wnt7a gene to increase its transcription and β-catenin activation, leading to increased expression of the downstream profibrotic genes, which was inhibited by PXR. Taken together, PXR activation alleviates renal fibrosis in mice via interacting with p53 and inhibiting the Wnt7a/β-catenin signaling pathway.

A Case of Tuberculosis Cutis Orificialis

This work reports a case of a 49-year-old male suffering from chronic tuberculosis who developed painful ulcers around the anus for approximately eight months. The colonoscopy revealed the presence of ulcers in the transverse colon, which were also found in the skin and intestine, as revealed by microscopic examination. The skin ulcer was positive for tuberculosis bacilli, leading to the final diagnosis of Tuberculosis cutis orificialis. The patient had a previous history of tuberculosis, which indicated that the infection in the lungs moved down to invade the intestines and finally the skin.

Search for Λ[over ¯]-Λ Baryon-Number-Violating Oscillations in the Decay J/ψ→pK^{-}Λ[over ¯]+c.c

We report on the first search for Λ[over ¯]-Λ oscillations in the decay J/ψ→pK^{-}Λ[over ¯]+c.c. by analyzing 1.31×10^{9}  J/ψ events accumulated with the BESIII detector at the BEPCII collider. The J/ψ events are produced using e^{+}e^{-} collisions at a center of mass energy sqrt[s]=3.097  GeV. No evidence for hyperon oscillations is observed. The upper limit for the oscillation rate of Λ[over ¯] to Λ hyperons is determined to be P(Λ)=[B(J/ψ→pK^{-}Λ+c.c.)/B(J/ψ→pK^{-}Λ[over ¯]+c.c.)]<4.4×10^{-6} corresponding to an oscillation parameter δm_{ΛΛ[over ¯]} of less than 3.8×10^{-18}  GeV at the 90% confidence level.

Complete chloroplast genome of Adonis pseudoamurensis W.T.Wang (Ranunculaceae)

Adonis pseudoamurensis W.T. Wang 1980 is an important traditional medicinal plant used for the treatment of cardiac diseases. The complete chloroplast (cp) genome of Adonis pseudoamurensis is reported for the first time in this study. The circular cp genome is 156,917 bp in length, consisting of a large single-copy region (86,262 bp), a small single-copy region (18,067 bp), and two inverted repeat regions (26,294 bp). The genome encodes 129 genes, comprising 84 protein-coding genes, 37 transfer RNA (tRNA) genes, and 8 ribosomal RNA (rRNA) genes. Phylogenetic analysis showed that A. pseudoamurensis is closely related to A. amurensis.

The psoas muscle density as a predictor of postoperative complications in elderly patients undergoing rectal cancer resection

Background

Muscle depletion that impairs normal physiological function in elderly patients leads to poor prognosis. This study aimed to evaluate the association between total abdominal muscle area (TAMA), total psoas area (TPA), psoas muscle density (PMD), and short-term postoperative complications in elderly patients with rectal cancer.

Methods

All elderly patients underwent rectal cancer resection with perioperative abdominal computed tomography (CT). Complications were assessed according to the Clavien-Dindo classification. Severe complications were defined as grade III-V following the Clavien-Dindo classification. Univariate and multivariate analyses were performed to evaluate risk factors of short-term severe postoperative complications.

Results

The cohort consisted of 191 patients with a mean age of 73.60 ± 8.81 years. Among them, 138 (72.25%) patients had Clavien-Dindo 0- II, 53 (27.75%) patients had severe postoperative complications (Clavien-Dindo III-V), and 1(0.52%) patient died within 30 days of surgery. PMD was significantly higher in the Clavien-Dindo 0-II cohort compared to the Clavien-Dindo III-V cohort (p=0.004). Nevertheless, TAMA and TPA failed to exhibit significant differences. Moreover, the multivariate regression analysis implied that advanced age [OR 1.07 95%CI (1.02-1.13) p=0.013], male [OR 5.03 95%CI (1.76-14.41) p=0.003], high charlson comorbidity index (CCI) score [OR 3.60 95%CI (1.44-9.00) p=0.006], and low PMD [OR 0.94 95%CI (0.88-0.99) p=0.04] were independent risk factors of Clavien-Dindo III-V.

Conclusion

Preoperative assessment of the PMD on CT can be a simple and practical method for identifying elderly patients with rectal cancer at risk for severe postoperative complications.

[The effect of strengthening nutrition education in the second trimester on the basis of the first trimester on blood glucose]

Objective: To explore the effect of strengthening individualized nutrition education in the second trimester based on first trimester on blood glucose. Methods: A retrospective study was conducted on 398 pregnant women aged (31.79±3.48) (23-41) years old who underwent an oral glucose tolerance test (OGTT) from October 2021 to December 2022 at Beijing Tsinghua Changgung Hospital. They were divided into two groups according to whether the women were re-visited in second trimester or not. The routine group consisted of 205 pregnant women aged between 24 and 41 (31.49±3.36) years old who only received the first trimester nutrition education and the strengthening group consisted of 193 pregnant women aged (31.92±3.97) (23-41) years old who received both the first and second trimester nutrition education. Then according to pre pregnancy body mass index (BMI), they were divided into normal (18.5 kg/m2≤BMI<24 kg/m2) and overweight (24 kg/m2≤BMI<28 kg/m2). The OGTT blood glucose level, the positive rate of gestational diabetes (GDM) and the weight gain during pregnancy were compared between the two groups with different BMI, in order to analyze the effect of strengthening nutrition education in the second trimester of pregnancy on blood glucose. Results: The differences between the two groups were not statistically significant in terms of the pregnant women's age, proportion of pregnant women aged≥35, proportion of pre-pregnancy BMI and overweight, parity and early pregnancy blood glucose (all P>0.05). The blood glucose levels of OGTT at 0, 1, and 2 hour were (4.57±0.37), (8.41±1.70), and (7.28±1.51) mmol/L, respectively, lower than those in the routine group [(4.74±0.48), (9.44±1.55), and (8.27±1.58) mmol/L, respectively, all P<0.001]. The positive rate of GDM in the strengthening group was 35.23% (68/193), which was lower than that in the routine group (91.71%, 188/205) (P<0.001). After the BMI stratification, the OGTT blood glucose levels and the positive rate of GDM in the strengthening group were still lower than those in the routine group (all P<0.05). The weight gain with normal BMI in the early pregnancy in routine group was higher than that in the strengthening group (P=0.003), but there was no significant statistical difference in weight gain of overweight pregnant women at different gestational weeks (all P>0.05). Conclusion: Strengthening a nutrition education about second trimester for pregnant women in the early stages of pregnancy can effectively improve blood glucose levels and reduce the positive rate of GDM.

[The influence of interaction between polygenic risk score and intestinal fungal microbiota on the risk of schizophrenia]

Objective: To investigate the effect of interaction between polygenic risk score (PRS) and intestinal fungal microbiota on the risk of Schizophrenia (SCH). Methods: A case-control study was carried out. Drug-naïve, first-episode SCH patients were selected from the Psychiatric Department of the First Affiliated Hospital of Zhengzhou University between October 2017 and October 2019. Meanwhile, healthy controls (HCs) were recruited from local communities through online advertisement or physical examination center. Intestinal fungal microbiota was characterized by the 18S rRNA sequencing platform. The association of fungal microbial dysbiosis (F_MD) index, α-diversity indices and PRS with SCH was detected by logistic regression analysis. Results: A total of 137 SCH patients (62 males and 75 females) and 76 HCs (31 males and 45 females) were included in the study. The age of SCH patients and HCs was (22.5±7.5) years and (22.8±2.3) years, respectively. The results of logistic regression analysis revealed that PRS (OR=1.111, 95%CI: 1.036-1.178, P=0.002) and the increase of F_MD index (OR=1.200, 95%CI: 1.124-1.281, P<0.001) were risk factors for developing SCH. The increase of fungal α-diversity Shannon (OR=0.813, 95%CI: 0.755-0.874, P<0.001) index, Simpson index (OR=0.218, 95%CI: 0.091-0.523, P<0.001) and abundance of key Aspergillus (OR=0.928, 95%CI: 0.864-0.996, P=0.040) decreased the risk of SCH. Aspergillus abundance was positively correlated with cognitive domains including working memory (r=0.280, P=0.001), verbal learning (r=0.253, P=0.003), reasoning and problem solving (r=0.191, P=0.028). Conclusion: The increase of PRS may increase the risk of SCH. The increase of fungal α-diversity indices and Aspergillus abundance may decrease the risk of SCH. The interaction between PRS and intestinal fungi (Shannon index, Simpson index and Aspergillus) is a related factor for the risk of SCH.

Bidirectional crosstalk of the cAMP/ROS-dependent signaling pathways in inflammatory macrophage: An activation of formononetin

Bacterial lipopolysaccharide (LPS) is a toxic stimulant to macrophage inflammation. Inflammation intersects cell metabolism and often directs host immunopathogenesis stress. We aim here at pharmacological discovering of formononetin (FMN) action, to which anti-inflammatory signaling spans across immune membrane receptors and second messenger metabolites. In ANA-1 macrophage stimulated by LPS, and simultaneous treatment with FMN, results show the Toll-like receptor 4 (TLR4) and estrogen receptor (ER) signals, in concert with reactive oxygen species (ROS) and cyclic adenosine monophosphate (cAMP), respectively. LPS stimulates inactivation of the ROS-dependent nuclear factor erythroid 2-related factor 2 (Nrf2) by upregulating TLR4, but it does not affect cAMP. However, FMN treatment not only activates Nrf2 signaling by TLR4 inhibition, but also it activates cAMP-dependent protein kinase activities by upregulating ER. The cAMP activity gives rise to phosphorylation (p-) of protein kinase A, liver kinase B1 and 5'-AMP activated protein kinase (AMPK). Moreover, bidirectional signal crosstalk is amplified between p-AMPK and ROS, as FMN combinational validation with AMPK activator/inhibitor/target small-interfering RNA or ROS scavenger. The signal crosstalk is well positioned serving as the 'plug-in' knot for rather long signaling axis, and the immune-to-metabolic circuit via ER/TLR4 signal transduction. Collectively, convergence of the FMN-activated signals drives significant reduction of cyclooxygenase-2, interleukin-6 and NLR family pyrin domain-containing protein 3, in LPS-stimulated cell. Although anti-inflammatory signaling is specifically related to the immune-type macrophage, the p-AMPK antagonizing effect arises from FMN combination with ROS scavenger H-bond donors. Information of our work assists in predictive traits against macrophage inflammatory challenges, using phytoestrogen discoveries.

[Effect of Inhibiting SIX1 Expression on Drug-resistance of Acute Myeloid Leukemia Cell Line HL-60/ADR Cells]

OBJECTIVE

To establish HL-60 cells and adriamycin resistant HL-60 cells (H-60/ADR) in which the expression of homologous box gene 1 (SIX1) was inhibited, and investigate the effect of inhibiting the expression of SIX1 on the drug resistance.

METHODS

Lentivirus was used to transfect HL-60 and HL-60/ADR cells, and the cell lines stably inhibiting the expression of SIX1 were screened by puromycin. CCK-8 assay was used to detect the proliferation ability of cells in each group, apoptosis kit was used to detect the cell apoptosis, and real-time quantitative PCR was used to detect the expression level of drug-resistant related genes.

RESULTS

HL-60 and HL-60/ADR stably transfected cell lines with down-regulation of SIX1 expression were successfully constructed. Compared with control group, the inhibition of SIX1 expression significantly inhibited the proliferation of HL-60 and HL-60/ADR cells (P <0.05), increased the apoptosis rate (P <0.05), and the sensitivity of cells to adriamycin increased after inhibition of SIX1 expression.

CONCLUSION

Inhibition of SIX1 expression can improve cell sensitivity to adriamycin, and its role in reversing drug resistance may be related to the promotion of apoptosis gene expression.