CT quantification of pulmonary vessels in lung aging

AIM

To evaluate the effect of aging on pulmonary vessels based on computed tomography (CT) quantification and analyse the correlation between quantitative pulmonary vascular volume and pulmonary function during aging.

MATERIALS AND METHODS

A total of 330 healthy adult volunteers, including 161 men (53 aged 20-39 years, 61 aged 40-59 years, and 47 aged ≥60 years) and 169 women (53 aged 20-39 years, 63 aged 40-59 years, and 53 aged ≥60 years) were recruited in this study. AVIEW software was used to quantitatively measure pulmonary vascular volume, including pulmonary total blood vessel volume (TBV) and small blood vessel volume with a cross-sectional area of <5 mm2 (BV5). Pulmonary vascular volume parameters were standardised using the ratio of vascular volume to the body surface area (BSA; TBV/BSA and BV5/BSA). Subsequently, the effect of aging on the pulmonary vessels was analysed.

RESULTS

The pulmonary vascular volume parameters TBV/BSA and BV5/BSA of the whole lung, right lung, and left lung decreased significantly with increasing age (p<0.05). Additionally, TBV/BSA and BV5/BSA of the whole lung were higher in men than in women. The declining trend of pulmonary vascular volume was consistent in men and women and increased with age.

CONCLUSIONS

The pulmonary vascular volume parameters, TBV/BSA and BV5/BSA, decreased with age and were weakly positively correlated with pulmonary function.

MicroRNA-150-5P regulates Th1/Th2 cytokines expression levels by targeting EGR2 in allergic rhinitis

BACKGROUND

MiR-150-5p is one of the miRNAs in the expression profile of miRNAs, and in many previous studies, it has been shown that miR-150-5p may play an important role in peripheral blood dendritic cells (DCs) of allergic rhinitis (AR) patients. We sought to investigate the role and mechanism of miR-150-5p in regulating DC function by modulating EGR2 and influencing T cell derivation to promote AR development.

METHODS

The expression of miR-150-5p and EGR2 in AR patients was examined by real-time quantitative polymerase chain reaction (qRT-PCR), the expression of IL-4 cytokines in the supernatant of AR patients was tested by enzyme-linked immunosorbent assay (ELISA), and the expression of eosinophils in the supernatant of AR patients was measured by HE staining. The expression of EGR2 was detected by immunohistochemistry and fluorescent m-immunohistochemistry.

RESULTS

MiR-150-5p expression was up-regulated and EGR2 expression was down-regulated in peripheral blood DCs from AR patients. miR-150-5p upregulated DCs, which promoted T-cell differentiation. miR-150-5p further regulated EGR2, which suppressed DCs and caused alteration of T-cell differentiation, in turn triggering the occurrence of AR.

CONCLUSION

MiR-150-5p and its target gene EGR2 are involved in the development of AR, and DCs foster T-cell differentiation in peripheral blood of AR patients.

Predictive value of crossover sign for outcome of ultrasound-guided vacuum aspiration in women with Cesarean scar pregnancy

OBJECTIVE

To examine the value of the crossover sign (COS) in predicting treatment outcome in women with a Cesarean scar pregnancy (CSP) who were treated with ultrasound-guided vacuum aspiration.

METHODS

This was a retrospective cohort study of women with CSP who underwent ultrasound-guided vacuum aspiration. Based on the relationship between the gestational sac, Cesarean scar and anterior wall of the uterus, CSPs were classified by COS type. Analysis was conducted to investigate the association between COS type (COS-1, COS-2) and treatment outcome. The incidence of treatment failure, retained pregnancy tissue, secondary therapy and bleeding ≥ 200 mL were analyzed.

RESULTS

In total, 181 eligible patients with CSP, including 90 (49.7%) women with COS-1 and 91 (50.3%) women with COS-2, were analyzed. COS-1 patients had a higher incidence of treatment failure compared with COS-2 patients (25.6% vs 8.8%; P = 0.003), as well as higher rates of retained pregnancy tissue (18.9% vs 6.6%; P = 0.013), secondary therapy (20.0% vs 6.6%; P = 0.002) and bleeding of ≥ 200 mL (13.3% vs 4.4%; P = 0.034). COS-1 and a large gestational sac (30.1-50.0 mm or >50.0 mm in diameter) were associated independently with increased risk of treatment failure (odds ratio, 4.57 (95% CI, 1.66-12.56); P = 0.003, 4.34 (95% CI, 1.35-13.94); P = 0.014 and 10.50 (95% CI, 2.54-43.46); P = 0.001, respectively).

CONCLUSIONS

Ultrasound evaluation of the relationship between the gestational sac and the endometrial line (COS classification) in women with CSP may help to predict treatment outcome among those undergoing vacuum aspiration. Among COS-1 patients, especially those with a gestational sac diameter of >30.0 mm, vacuum aspiration may be discouraged. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

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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[Prognostic nutritional index application value for acute-on-chronic liver failure co-infection]

Objective: To explore the predictive value of the prognostic nutritional index (PNI) in concurrently infected patients with acute-on-chronic liver failure (ACLF). Methods: 220 cases with ACLF diagnosed and treated at the First Affiliated Hospital of Xi'an Jiaotong University from January 2011 to December 2016 were selected. Patients were divided into an infection and non-infection group according to whether they had co-infections during the course of the disease. Clinical data differences were compared between the two groups of patients. Binary logistic regression analysis was used to screen out influencing factors related to co-infection. The receiver operating characteristic curve was used to evaluate the predictive value of PNI for ACLF co-infection. The measurement data between groups were compared using the independent sample t-test and the Mann-Whitney U rank sum test. The enumeration data were analyzed using the Fisher exact probability test or the Pearson χ(2) test. The Pearson method was performed for correlation analysis. The independent risk factors for liver failure associated with co-infection were analyzed by multivariate logistic analysis. Results: There were statistically significant differences in ascites, hepatorenal syndrome, PNI score, and albumin between the infection and the non-infection group (P < 0.05). Among the 220 ACLF cases, 158 (71.82%) were infected with the hepatitis B virus (HBV). The incidence rate of infection during hospitalization was 69.09% (152/220). The common sites of infection were intraabdominal (57.07%) and pulmonary infection (29.29%). Pearson correlation analysis showed that PNI and MELD-Na were negatively correlated (r = -0.150, P < 0.05). Multivariate logistic analysis results showed that low PNI score (OR=0.916, 95%CI: 0.865~0.970), ascites (OR=4.243, 95%CI: 2.237~8.047), and hepatorenal syndrome (OR=4.082, 95%CI : 1.106~15.067) were risk factors for ACLF co-infection (P < 0.05). The ROC results showed that the PNI curve area (0.648) was higher than the MELD-Na score curve area (0.610, P < 0.05). The effectiveness of predicting infection risk when PNI was combined with ascites and hepatorenal syndrome complications was raised. Patients with co-infections had a good predictive effect when PNI ≤ 40.625. The sensitivity and specificity were 84.2% and 41.2%, respectively. Conclusion: Low PNI score and ACLF co-infection have a close correlation. Therefore, PNI has a certain appraisal value for ACLF co-infection.

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

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

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

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

Quantitative structure-property relationship modelling on autoignition temperature: evaluation and comparative analysis

The autoignition temperature (AIT) serves as a crucial indicator for assessing the potential hazards associated with a chemical substance. In order to gain deeper insights into model performance and facilitate the establishment of effective methodological practices for AIT predictions, this study conducts a benchmark investigation on Quantitative Structure-Property Relationship (QSPR) modelling for AIT. As novelties of this work, three significant advancements are implemented in the AIT modelling process, including explicit consideration of data quality, utilization of state-of-the-art feature engineering workflows, and the innovative application of graph-based deep learning techniques, which are employed for the first time in AIT prediction. Specifically, three traditional QSPR models (multi-linear regression, support vector regression, and artificial neural networks) are evaluated, alongside the assessment of a deep-learning model employing message passing neural network architecture supplemented by graph-data augmentation techniques.

Differentiation of Crohn's disease, ulcerative colitis, and intestinal tuberculosis by dual-layer spectral detector CT enterography

AIM

To investigate the value of radiological features and energy spectrum quantitative parameters in the differential diagnosis of Crohn's disease (CD), ulcerative colitis (UC), and intestinal tuberculosis (ITB) by dual-layer spectral detector computed tomography (CT) enterography (CTE).

MATERIALS AND METHODS

Clinical and CTE data were collected from 182 patients with CD, 29 with UC, and 51 with ITB. CT images were obtained at the enteric phases and portal phases. The quantitative energy spectrum parameters were iodine density (ID), normalised ID (NID), virtual non-contrast (VNC) value, and effective atomic number (Z-eff). The area under curve (AUC) of the receiver operating characteristic curve (ROC) was calculated.

RESULTS

The vascular comb sign (p=0.009) and enlarged lymph nodes (p=0.001) were more common in patients with CD than UC or ITB. In the differentiation of moderate-severe active CD from UC, enteric phase NID (AUC, 0.938; p<0.001) and portal phase Z-eff (AUC, 0.925; p<0.001) had the highest accuracy, which were compared separately. In the differentiation of moderate-severe active CD from ITB, enteric phase NID (AUC, 0.906; p<0.001) and portal phase Z-eff (AUC, 0.947; p<0.001) had the highest accuracy; however, the AUC value was highest when the four parameters are combined (AUC, 0.989; p<0.001; AUC, 0.986; p<0.001; AUC, 0.936; p<0.001; and AUC, 0.986; p<0.001).

CONCLUSION

The present study shows that the combined strategies of four parameters have higher sensitivity and specificity in differentiating CD, UC, and ITB, and may play a key role in guiding treatment.

Estimation and projection of the burden of hearing loss in China: findings from the Global Burden of Disease Study 2019

OBJECTIVES

The comprehensive description of hearing loss in China and the shifting pattern remain unclear. We conducted the study to estimate the burden of hearing loss in China and project the trends from 2020 to 2034.

STUDY DESIGN AND METHOD

Data on the disease burden of hearing loss were extracted from the Global Burden of Disease Study 2019. Estimated annual percentage changes (EAPCs) were calculated to quantify the trends of the age-standardized rates. Projections of hearing loss burden were made until 2034 using Bayesian age-period-cohort analysis.

RESULTS

In China, prevalent cases of hearing loss increased from 224.4 million in 1990 to 426.5 million in 2019, representing an increase of 90.1 %. The age-standardized prevalence rate of hearing loss ranged from 22,592.8/100,000 in 1990-22,612.4/100,000 in 2019, with an EAPC of 0.003 %, representing a stable trend. Of the category of hearing loss, mild hearing loss accounted for the highest proportion, with 331.4 million people. More than 95 million people had moderate-to-complete hearing loss. Moreover, hearing loss was mostly attributable to age-related and other factors for adults and otitis media for children younger than 10 years. Based on the projection results, there will be 561 million people (40.1 % of the total population) have hearing loss by 2034.

CONCLUSIONS

The prevalent cases of hearing loss in China substantially increased over the last 30 years. Over two in five Chinese people will have hearing loss by 2034, thus suggesting more solutions should be established to reduce the burden of hearing loss.

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.

[Research progress on the role of hepatitis B virus DNA integration in chronic hepatitis B]

Chronic hepatitis B virus (HBV) infection will greatly contribute to raising the occurrence probability of cirrhosis and hepatocellular carcinoma in patients. Although existing antiviral treatment regimens have a certain effect on delaying disease progression and improving prognosis, it is still not effective in attaining functional cures. Hepatitis B virus DNA integration may be one of the reasons for this phenomenon. Therefore, this paper reviews the possible mechanisms of HBV DNA integration in maintaining chronic inflammation of the liver, evading existing antiviral treatment methods, and inducing hepatocellular carcinoma so as to further deepen the understanding of the role of HBV DNA integration in the occurrence and development of chronic hepatitis B, providing ideas and references for formulating better treatment strategies.

Discovery of New Isotopes ^{160}Os and ^{156}W: Revealing Enhanced Stability of the N=82 Shell Closure on the Neutron-Deficient Side

Using the fusion-evaporation reaction ^{106}Cd(^{58}Ni,4n)^{160}Os and the gas-filled recoil separator SHANS, two new isotopes _{76}^{160}Os and _{74}^{156}W have been identified. The α decay of ^{160}Os, measured with an α-particle energy of 7080(26) keV and a half-life of 201_{-37}^{+58}  μs, is assigned to originate from the ground state. The daughter nucleus ^{156}W is a β^{+} emitter with a half-life of 291_{-61}^{+86}  ms. The newly measured α-decay data allow us to derive α-decay reduced widths (δ^{2}) for the N=84 isotones up to osmium (Z=76), which are found to decrease with increasing atomic number above Z=68. The reduction of δ^{2} is interpreted as evidence for the strengthening of the N=82 shell closure toward the proton drip line, supported by the increase of the neutron-shell gaps predicted in theoretical models.

[Research progress in clinical diagnosis and treatment of osteosarcoma of the jaw]

Osteosarcoma of the jaw (JOS), is a relatively rare type of osteosarcoma, with a unique pathogenesis and pathological manifestations. The clinical manifestation of JOS is not characteristic, and it often needs to be diagnosed by combining radiological and pathological examination. At present, the conventional treatment of JOS is a comprehensive treatment based on surgery and supplemented by radiotherapy and chemotherapy. Recently, the emergence of new therapies such as immunotherapy, gene therapy, phototherapy and traditional Chinese medicine has provided more choices for treatment and brought new hope to patients with JOS. Therefore, this article summarized the current understanding of diagnosis and the latest treatment development of JOS.

Dysmenorrhea pattern in adolescences informing adult endometriosis

BACKGROUND

Endometriosis (EMs) is a chronic and progressive disease that, if diagnosed late, can lead to infertility and deep infiltrating endometriosis (DIE). Dysmenorrhea is the most prominent symptom of EMs. However, limited research exists on the specific correlation between dysmenorrhea patterns and EMs. Early prevention of EMs is essential to effectively manage the progression of the disease, and is best detected during adolescence. Our objective was to associate the development of EMs with dysmenorrhea patterns during adolescence and quantify the risk of adult EMs for adolescent girls, with the aim of supporting primary intervention strategy planning.

METHODS

This case-control study examined predictors for adult EMs based on dysmenorrhea patterns in adolescents. We collected 1,287 cases of 641 EMs and 646 healthy females regarding their basic demographic information, adolescent menstrual characteristics, adolescent dysmenorrheal patterns, and adolescent lifestyles. Age-matching (1-to-1) was employed to control for the confounding effect of age between the groups. Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression models were utilized to identify predictors for adult EMs. The predictive value of the model was evaluated using the area under the receiver operating characteristic curve (AUC) and the C-index, while Hosmer-Lemeshow Test assessed the goodness of fit of the model. Data from one additional cohort in Shenzhen hospitalized with EMs were used to external validation were analyzed.

RESULTS

Individuals who always experienced dysmenorrhea had a risk of adult endometriosis 18.874 (OR = 18.874; 95%CI = 10.309-34.555) times higher than those occasional dysmenorrhea, The risk of developing EMs was 5.257 times higher in those who experienced dysmenorrhea more than 12 months after menarche than in those who experienced dysmenorrhea less than 6 months after menarche (OR = 5.257, 95% CI = 3.343-8.266), AUC in the external validation cohort was 0.794(95%CI: 0.741-0.847). We further found that high-intensity physical activity and sun-sensitive skin of burning were influential factors in high-frequency dysmenorrhea. The AUC value for the internal evaluation of the model was 0.812 and the AUC value for the external validation was 0.794.

CONCLUSION

Our findings revealed that the frequency of dysmenorrhea during adolescence contributed to the development of adult endometriosis. The frequency and onset of dysmenorrhea in adolescence were promising predictors for adult EMs. Both internal and external validation proved the model's good predictive ability.

TRIAL REGISTRATION

http://www.chictr.org.cn/ , TRN: ChicTR2200060429, date of registration: 2022/06/01, retrospectively registered.

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.

[Prevalence of urinary incontinence in middle-aged and elderly adults in 10 areas in China]

Objective: To describe the population and area distribution differences in the prevalence of urinary incontinence in middle-aged and elderly adults in 10 areas in China. Methods: A total of 24 913 participants aged 45-95 years who completed the third resurvey of China Kadoorie Biobank during 2020-2021 were included. The prevalence of urinary incontinence was assessed by an interviewer-administered questionnaire, and urinary incontinence was classified as only stress urinary incontinence, only urgency urinary incontinence and mixed urinary incontinence. The prevalence of urinary incontinence and its subtypes were reported by sex, age and area, and the severity of urinary incontinence and treatment were described. Results: The average age of the participants was (65.4±9.1) years. According to the seventh national census data in 2020, the age-standardized prevalence rates of urinary incontinence was 25.4% in women and 7.0% in men. The age-standardized prevalence rates of only stress, only urgency and mixed incontinence were 1.7%, 4.2% and 1.2% in men and 13.5%, 5.8% and 6.1% in women, respectively. The prevalence rates of urinary incontinence and all subtypes in men and the prevalence of urinary incontinence and all subtypes except only stress urinary incontinence in women all increased with age (P<0.001). After adjusting for age, the prevalence of urinary incontinence in both men and women were higher in rural area than in urban area (P<0.001). The treatment rates in men and women with urinary incontinence were 15.4% and 8.5%, respectively. Conclusions: The prevalence of urinary incontinence was high in middle-aged and elderly adults in China, and the prevalence rate was higher in women than in men, but the treatment rate of urinary incontinence was low.

[A multi-dimensional analysis of pollen broadcasting concerns in Chinese population: a large-scale multi-center cross-sectional survey]

Objective: To investigate the concern about pollen broadcasting in Chinese population from multiple dimensions and to understand the information about allergic rhinitis (AR) in China by analyzing related factors. Methods: From March 1 to September 30, 2022, a large-scale multi-center cross-sectional survey was conducted based on the Questionnaire Star platform in 21 Chinese hospitals. A total of 7 056 subjects from 7 regions in China: Northeast, North, East, Central, South, Southwest, and Northwest China were included. Basic characteristics (including social demographic characteristics and disease characteristics of AR patients), concern about pollen broadcasting, the willingness of pollen-induced AR (PiAR) patients to receive pollen broadcasting, and the treatment satisfaction rate of AR patients were collected. The chi-square test, multivariate linear regression model, and Logistic regression analysis were used to analyze the concern about pollen broadcasting in the Chinese population and related factors from multiple dimensions. Results: Among 7 056 subjects, 23.02% were concerned about pollen broadcasting. Among 3 176 self-reported AR and 1 019 PiAR patients, 25.60% and 39.16% were concerned about pollen broadcasting, respectively, which was higher than that of non-AR or non-PiAR subjects (χ2 value was 21.74 and 175.11, respectively, both P<0.001). Among AR patients, the proportion of spring and autumn allergen-positive patients concerned about pollen broadcasting was higher than that in perennial allergen-positive patients (χ2 value was 20.90 and 19.51, respectively, both P<0.001). The proportion of AR patients with asthma, sinusitis, allergic conjunctivitis, and cardiovascular and cerebrovascular diseases was higher than those without complications (χ2 value was 50.83, 21.97, 56.78, 7.62, respectively, all P<0.05). The proportion of AR patients in North China who could find pollen broadcasting locally was 31.01%, significantly higher than those in other regions (all P<0.05). Multivariate linear regression model analysis showed that among PiAR patients, those with higher per capita household income and higher AR disease cognition levels had been concerned about pollen broadcasting in the past, and those complicated with allergic conjunctivitis had stronger intention to receive pollen broadcasting (B value was 0.24, 0.13, 0.66, 0.47, respectively, all P<0.05). The higher the disease cognition level of PiAR patients, the stronger their willingness to actively participate in treatment (R2=0.72, P<0.001). Only 18.89% of AR patients felt satisfied with the treatment effect. Logistic regression analysis showed that in AR patients, the treatment satisfaction rate was significantly higher among those concerned about pollen broadcasting compared to those who were not (OR=1.83, P<0.001). Conclusions: Currently, the dissemination of pollen broadcasting in China is hindered by various factors such as disease cognition level. The treatment satisfaction among AR patients remains unsatisfactory.

[Monitoring and analysis on host animals of hemorrhagic fever with renal syndrome in Henan Province from 2019 to 2022]

Objective: To investigate the distribution and hantavirus (HV) carrying state in host animals of hemorrhagic fever with renal syndrome (HFRS) in Henan Province from 2019 to 2022. Methods: Host animal monitoring was carried out at the monitoring sites of HFRS in Henan Province. The real-time fluorescence quantitative PCR was used to detect hantavirus in rat lungs. The types of hantavirus were analyzed. The positive samples were sequenced and then sequence homology and variation were analyzed. Results: A total of 1 308 rodents were captured from 2019 to 2022, 16 specimens of rat lungs tested positive for hantavirus nucleic acid. The positive rate of HV was 1.22% (16/1 308). According to type, the positive rate of HV in Apodius agrarius was the highest (68.75%, 11/16). According to distribution, the positive rate of HV in field samples was the highest (2.50%, 12/480), and the positive rate of HV in residential samples was 0.53% (4/759). The typing results of 16 positive samples showed that all viruses were hantavirus type Ⅰ (hantaan virus). The positive samples were sequenced and eight S gene fragments (GenBank number: OQ681444-OQ681451) and six M gene fragments (OQ681438-OQ681443) were obtained. The S and M gene fragments were similar to the Shaanxi 84FLi strain and Sichuan SN7 strain. Phylogenetic analysis of S and M gene fragments showed that they all belonged to the hantaan virus-H5 subtype. Amino acid sequence analysis revealed that, compared with the hantaan virus vaccine strain 84FLi, the 74th amino acid encoded by eight S fragments was replaced by aspartamide with serine. Tryptophan was replaced by glycine at the 14th position of Gn region in XC2022047, and isoleucine was replaced by alanine at the 359 position of XC2022022 and XC2022024. Conclusion: The hantavirus carried by host animals in Henan Province from 2019 to 2022 belongs to the type Ⅰ (hantaan virus), and Apodemus agrarius is still the dominant host animal of the hantaan virus. Compared with the vaccine strains, amino acid sites are replaced in the immune epitopes of the S and M gene fragments.

Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial

BACKGROUND

Sodium-glucose co-transporter-2 (SGLT2) inhibitors reduce progression of chronic kidney disease and the risk of cardiovascular morbidity and mortality in a wide range of patients. However, their effects on kidney disease progression in some patients with chronic kidney disease are unclear because few clinical kidney outcomes occurred among such patients in the completed trials. In particular, some guidelines stratify their level of recommendation about who should be treated with SGLT2 inhibitors based on diabetes status and albuminuria. We aimed to assess the effects of empagliflozin on progression of chronic kidney disease both overall and among specific types of participants in the EMPA-KIDNEY trial.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA), and included individuals aged 18 years or older with an estimated glomerular filtration rate (eGFR) of 20 to less than 45 mL/min per 1·73 m2, or with an eGFR of 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher. We explored the effects of 10 mg oral empagliflozin once daily versus placebo on the annualised rate of change in estimated glomerular filtration rate (eGFR slope), a tertiary outcome. We studied the acute slope (from randomisation to 2 months) and chronic slope (from 2 months onwards) separately, using shared parameter models to estimate the latter. Analyses were done in all randomly assigned participants by intention to treat. EMPA-KIDNEY is registered at ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and then followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroups of eGFR included 2282 (34·5%) participants with an eGFR of less than 30 mL/min per 1·73 m2, 2928 (44·3%) with an eGFR of 30 to less than 45 mL/min per 1·73 m2, and 1399 (21·2%) with an eGFR 45 mL/min per 1·73 m2 or higher. Prespecified subgroups of uACR included 1328 (20·1%) with a uACR of less than 30 mg/g, 1864 (28·2%) with a uACR of 30 to 300 mg/g, and 3417 (51·7%) with a uACR of more than 300 mg/g. Overall, allocation to empagliflozin caused an acute 2·12 mL/min per 1·73 m2 (95% CI 1·83-2·41) reduction in eGFR, equivalent to a 6% (5-6) dip in the first 2 months. After this, it halved the chronic slope from -2·75 to -1·37 mL/min per 1·73 m2 per year (relative difference 50%, 95% CI 42-58). The absolute and relative benefits of empagliflozin on the magnitude of the chronic slope varied significantly depending on diabetes status and baseline levels of eGFR and uACR. In particular, the absolute difference in chronic slopes was lower in patients with lower baseline uACR, but because this group progressed more slowly than those with higher uACR, this translated to a larger relative difference in chronic slopes in this group (86% [36-136] reduction in the chronic slope among those with baseline uACR <30 mg/g compared with a 29% [19-38] reduction for those with baseline uACR ≥2000 mg/g; ptrend<0·0001).

INTERPRETATION

Empagliflozin slowed the rate of progression of chronic kidney disease among all types of participant in the EMPA-KIDNEY trial, including those with little albuminuria. Albuminuria alone should not be used to determine whether to treat with an SGLT2 inhibitor.

FUNDING

Boehringer Ingelheim and Eli Lilly.

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

BACKGROUND

The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1).

INTERPRETATION

In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease.

FUNDING

Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.

[Anatomical study of the architecture of the cutaneous branch-chained blood vessels in the medial lower leg in adult]

Objective: To investigate the architecture of the cutaneous branch-chained blood vessels in the medial lower leg and provide the anatomical basis for design and clinical application of the cutaneous branch-chained flap from this region. Methods: The experimental research method was used. From March to May 2023, the anatomical study was conducted on the 5 voluntarily donated fresh adult (aged 50 to 70 years, all male) cadaveric specimens from Hangzhou Normal University School of Basic Medical Sciences. The fine anatomy under microscope was performed on each lower leg specimens of 5 corpses (1 lower leg specimen was conducted with digital radiography (DR) scan before fine anatomy), to observe, measure, and record the course of posterior tibial artery, quantity of perforator, the distance between the perforating point of each perforator and the medial condyle of tibia, the external diameter of posterior tibial artery perforator, the length of perforator pedicle, the horizontal distance between the posterior tibial artery perforator and the saphenous nerve, and the course of each perforator within superficial fascia after crossing the deep fascia and the distribution of the cutaneous branch-chains. The DR scan under the perfusion of barium sulfate was conducted in one lower leg specimen to observe the distribution of cutaneous branch-chained vascular network (hereinafter referred to as vascular chain) between perforators. Transparent skin specimen was made from one leg specimen after anatomy to observe the distribution of perforators and vascular chains between perforators. Results: In 5 lower leg specimens, the upper part of posterior tibial artery was located deep in soleus muscle, and the lower part was located between the medial edge of gastrocnemius muscle and flexor digitorum longus muscle. A total of 28 posterior tibial artery perforators were identified, with an average of 5.6 branches in each lower leg. The distance between the perforating point of perforator and the medial condyle of tibia ranged from 6.5 to 36.0 cm, mainly distributed at 22.0 (15.1, 28.1) cm from the medial condyle of tibia, in zones 3 to 6. The external diameters of perforators of posterior tibial arteries were 0.7-1.1 mm. The length of perforator pedicle was 1.0-4.5 cm, and the horizontal distance between the posterior tibial artery perforator and the saphenous nerve was 0.5-3.0 cm. The fine anatomy under microscope showed that the posterior tibial artery perforators had long upward and downward branches after crossing the deep fascia, and the ascending branches and descending branches were anastomosed longitudinally to form the nutrient cutaneous branch-chain in the medial lower leg. DR scan and transparent skin specimen both showed that longitudinal vascular chain was formed between the posterior tibial artery perforators, the transparent skin specimen also showed that longitudinal blood vessel chains included the direct connecting vessels in the adipose layer and the indirect connecting vessels in the subdermal layer. Conclusions: The cutaneous branch-chained vessels in the medial lower leg are constructed by posterior tibial artery perforators, direct connecting vessels, indirect connecting vessels, and traffic branches. The cutaneous branch-chained flap is reliable in terms of vascular anatomy, and can carry the saphenous nerve for partial restoration of its sensation, thus it is an ideal flap.

[Application and evaluation of artificial intelligence TPS-assisted cytologic screening system in urine exfoliative cytology]

Objective: To explore the application of manual screening collaborated with the Artificial Intelligence TPS-Assisted Cytologic Screening System in urinary exfoliative cytology and its clinical values. Methods: A total of 3 033 urine exfoliated cytology samples were collected at the Henan People's Hospital, Capital Medical University, Beijing, China. Liquid-based thin-layer cytology was prepared. The slides were manually read under the microscope and digitally presented using a scanner. The intelligent identification and analysis were carried out using an artificial intelligence TPS assisted screening system. The Paris Report Classification System of Urinary Exfoliated Cytology 2022 was used as the evaluation standard. Atypical urothelial cells and even higher grade lesions were considered as positive when evaluating the recognition sensitivity, specificity, and diagnostic accuracy of artificial intelligence-assisted screening systems and human-machine collaborative cytologic screening methods in urine exfoliative cytology. Among the collected cases, there were also 1 100 pathological tissue controls. Results: The accuracy, sensitivity and specificity of the AI-assisted cytologic screening system were 77.18%, 90.79% and 69.49%; those of human-machine coordination method were 92.89%, 99.63% and 89.09%, respectively. Compared with the histopathological results, the accuracy, sensitivity and specificity of manual reading were 79.82%, 74.20% and 95.80%, respectively, while those of AI-assisted cytologic screening system were 93.45%, 93.73% and 92.66%, respectively. The accuracy, sensitivity and specificity of human-machine coordination method were 95.36%, 95.21% and 95.80%, respectively. Both cytological and histological controls showed that human-machine coordination review method had higher diagnostic accuracy and sensitivity, and lower false negative rates. Conclusions: The artificial intelligence TPS assisted cytologic screening system has achieved acceptable accuracy in urine exfoliation cytologic screening. The combination of manual screening and artificial intelligence TPS assisted screening system can effectively improve the sensitivity and accuracy of cytologic screening and reduce the risk of misdiagnosis.

Determinants of low birth weight among newborns delivered in China: a prospective nested case-control study in a mother and infant cohort

This nested case-control study aimed to investigate the determinants of low birth weight among newborn babies delivered in Shenzhen, Guangdong, China. We recorded socio-demographic data, health status before pregnancy, pregnancy outcomes and complications in a Shenzhen mother and infant cohort. Among 8951 cases, 401 (4.48%) had low birth weight and 1.65% were full-term with LBW. Maternal body mass index, family income, history of pregnancy, hypertension before pregnancy, vaginal bleeding in 1^st trimester, pregnancy-related diabetes, hypertension, placenta previa, placental abruption, premature rupture of membrane, oligohydramnios, and placental types were significantly associated with low birth weight (P < 0.05). In this study, high-risk and mainly preventable factors were linked to low birth weight. Adequate antenatal care, proper maternal nutrition and implementation of proven strategies to prevent high-risk factors may be effective ways to reduce the incidence of low birth weight.

A Cellular atlas of the human fallopian tube reveals the metamorphosis of secretory epithelial cells during the menstrual cycle and menopause

The fallopian tube, connecting the uterus with the ovary, is a dynamic organ that undergoes cyclical changes and is the site of several diseases, including serous cancer. Here, we use single-cell technologies to construct a comprehensive cell map of healthy pre-menopausal fallopian tubes, capturing the impact of the menstrual cycle and menopause on different fallopian tube cells at the molecular level. The comparative analysis between pre- and post-menopausal fallopian tubes reveals substantial shifts in cellular abundance and gene expression patterns, highlighting the physiological changes associated with menopause. Further investigations into menstrual cycle phases illuminate distinct molecular states in secretory epithelial cells caused by hormonal fluctuations. The markers we identified characterizing secretory epithelial cells provide a valuable tool for classifying ovarian cancer subtypes.

Graphical summary

Graphical summary of results. During the proliferative phase (estrogen high ) of the menstrual cycle, SE2 cells (OVGP1 + ) dominate the fallopian tube (FT) epithelium, while SE1 cells (OVGP1 - ) dominate the epithelium during the secretory phase. Though estrogen levels decrease during menopause, SE post-cells (OVGP1 + , CXCL2 + ) make up most of the FT epithelium.

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.

[Efficacy and prognosis of infant kidney transplantation]

Objective: To analyze the effect and prognosis of infant kidney transplantation. Methods: Clinical data of 37 cases of infant kidney transplantation under 3 years old in Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology from June 1, 2017 to July 31, 2022 were retrospectively collected. These 37 cases included 31 primary kidney transplantation and 6 secondary kidney transplantation. Kaplan-Meier method was used to draw the survival curve of the transplanted kidney and the recipient, and the prognosis and complications were analyzed. Median follow-up was 18 months (range: 6-66 months). Results: The recipients were 20 males and 17 females, with a median age of 16 months (range: 2 months, 26 days to 36 months) and a median weight of 8 kg (range: 3.2 to 14.0 kg). The youngest child was only 2 months, 26 days old, and weighed only 3.2 kg. The most common primary disease of recipients was congenital nephrotic syndrome (13 cases, 41.9%). Intra-abdominal transplantation occurred in 19 cases (51.3%) and intra-iliac fossa transplantation occurred in the remaining 18 cases (48.6%). Postoperative renal function recovery was delayed in 7 cases (18.9%), and thrombosis caused renal function loss in 5 cases (13.5%), of which 4 cases received second renal transplantation and were successful. During the follow-up period, there were 11 cases of acute rejection (29.7%) and 6 cases of CMV pneumonia (16.2%). The estimated glomerular filtration rate 1 year after transplantation was higher than that 1 month after surgery [(101.9±22.1) vs (71.1±25.6) ml/(min·1.73m2), P<0.001], and remained constant 2 years after transplantation. Both the 1-year and 2-year survival rates of the transplanted kidney were 85.3%, and both the 1-year and 2-year survival rates of the recipients were 96.8%. Conclusion: Although the implementation of infant kidney transplantation is difficult, it can still achieve relatively satisfactory efficacy and prognosis.

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.

[The epidemiology and pathogeny investigation of two clusters of severe fever with thrombocytopenia syndrome disease outbreaking in Henan Province, 2022]

To investigate two clusters of severe fever with thrombocytopenia syndrome virus (SFTSV) in Xinyang City, Henan Province, in 2022, and analyze their causes, transmission route, risk factors, and the characteristics of virus genetic variation. Case search and case investigation were carried out according to the case definition. Blood samples from cases, family members and neighbors and samples of biological vectors were collected for RT-PCR to detect SFTSV. The whole genome sequencing and bioinformatics analysis were performed on the collected positive samples. A total of two clustered outbreaks occurred, involving two initial cases and ten secondary cases, all of which were family recurrent cases. Among them, nine secondary cases had close contact with the blood of the initial case, and it was determined that close contact with blood was the main risk factor for the two clustered outbreaks. After genome sequencing analysis, we found that the SFTSV genotype in two cases was type A, which was closely related to previous endemic strains in Xinyang. The nucleotide sequence of the SFTSV in the case was highly homologous, with a total of nine amino acid mutation sites in the coding region. It was not ruled out that its mutation sites might have an impact on the outbreak of the epidemic.

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.

A Nomogram to Predict Pathological Axillary Status in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy

PURPOSE/OBJECTIVE(S)

This study aimed to identify factors influencing axillary pathological complete response (pCR) and to develop a predictive nomogram to evaluate axillary pCR rate in breast cancer patients treated with neoadjuvant chemotherapy (NAC).

MATERIALS/METHODS

A total of 2368 patients who received NAC and mastectomy between 2000 and 2014 from 12 grade A tertiary hospitals in China were analyzed retrospectively. The patients treated in three cancer hospitals (training set, n = 1629) were used to construct the nomogram based on multivariate logistic regression analyses. The nomograph was validated by the area under the receiver operating characteristic curve (AUC) and calibration curve in patients from 9 other general hospitals (validation set, n = 739).

RESULTS

The nomogram incorporated seven predicting factors including NACT cycles, response to NACT, clinical T stage, clinical N stage, grade, LVI, and molecular subtype. The AUC for the training set and validation set were 0.762 and 0.802, respectively. In addition, the calibration curve also showed good agreement between the nomogram-based predictions and the actual observations.

CONCLUSION

A nomogram was established to predict the status of axillary lymph nodes in breast cancer patients after NAC. The predictive model performed well both in the training set and external validation set.

Comparison of Supraclavicular Surgery plus Radiotherapy vs. Radiotherapy Alone in Breast Cancer Patients with Synchronous Ipsilateral Supraclavicular Lymph Node Metastasis: A Multicenter Retrospective Study

PURPOSE/OBJECTIVE(S)

To evaluate and compare the outcomes of supraclavicular lymph node dissection (SLND) plus radiotherapy (RT) and RT alone for patients with synchronous ipsilateral supraclavicular lymph node metastasis (sISLM).

MATERIALS/METHODS

In all, 293 patients with sISLM across three centers were included. Of these, 85 (29.0%) received SLND plus RT and 208 (71.0%) received RT alone. All patients received preoperative systemic therapy followed by mastectomy or lumpectomy and axillary dissection. Supraclavicular recurrence-free survival (SCRFS), locoregional recurrence-free survival (LRRFS), distant metastasis-free survival (DMFS), disease-free survival (DFS), and overall survival (OS) were evaluated by using the Kaplan-Meier method and multivariate Cox models. Multiple imputation was used for missing data.

RESULTS

The median follow-up duration of the RT and SLND+RT groups were 53.7 and 63.5 months, respectively. For the RT and SLND+RT groups, the 5-year SCRFS rates were 91.7% vs. 85.5% (P = 0.522), LRRFS rates were 79.1% vs. 73.1% (P = 0.412), DMFS rates were 60.4 vs. 58.8% (P = 0.708), DFS rates were 57.6% vs. 49.7% (P = 0.291), and OS rates were 71.9% vs. 62.2% (P = 0.272), respectively. There was no significant effect on any outcome when comparing SLND+RT versus RT alone in the multivariate analysis. Based on four risk factors of DFS, patients were classified into three risk groups: the intermediate- and high-risk groups had significantly lower survival outcomes than the low-risk group. SLND+RT did not improve outcomes of any risk group compared with RT alone.

CONCLUSION

Patients with sISLM may not benefit from SLND. Distant metastasis remained the major failure pattern, especially for intermediate- and high-risk groups with sISLM may not benefit from SLND. Distant metastasis remained the major failure pattern, especially for intermediate- and high-risk groups.

CT radiomics can predict disease progression within 6 months after chimeric antigen receptor-modified T-cell therapy in relapsed/refractory B-cell non-Hodgkin's lymphoma patients

AIM

To predict progression within 6 months after chimeric antigen receptor-modified (CAR) T-cell therapy for relapsed/refractory (R/R) B-cell non-Hodgkin's lymphoma (B-NHL) patients by radiomic indexes derived from contrast-enhanced computed tomography (CECT) examinations.

MATERIALS AND METHODS

Seventy R/R B-NHL patients who underwent CECT before treatment with CAR T-cells were examined retrospectively. In total, 297 volumes of interest for lesions were segmented from CECT images. Patients without and with disease progression were assigned to groups 1 and 2, respectively. Radiomic and combined predictive models were constructed by three machine-learning algorithms using features from the training set, respectively. Furthermore, predictive models were constructed based on multi-lesion-based and largest-lesion-based radiomic features, respectively.

RESULTS

In the test set, no marked differences were observed between the areas under the curves (AUCs) of the combined and radiomic models for all three machine-learning algorithms (all p>0.05). Differences in machine-learning algorithms did not significantly affect the predictive performances of the models. Radiomics and combined models constructed with multi-lesion-based radiomic features showed better predictive performances than those applying largest-lesion-based radiomic features (all p<0.05 for comparisons between combined models).

CONCLUSION

CECT-based radiomic features may be applied to predict disease progression in R/R B-NHL patients within 6 months after CAR T-cell treatment, and radiomic features from multiple lesions may have better predictive efficacy. Different machine-learning algorithms may not show significant differences in prediction performance.

Recurrence Risk Score Model for Evaluating the Impact of Postmastectomy Radiotherapy in Breast Cancer Patients with Pathologic Nodal Negative after Neoadjuvant Chemotherapy and Mastectomy

PURPOSE/OBJECTIVE(S)

Recurrence risk score model was established to distinguish the recurrent risk of patients with pathologic nodal negative (ypN0) after neoadjuvant chemotherapy (NACT) and mastectomy and determine the impact of postmastectomy radiotherapy (PMRT).

MATERIALS/METHODS

This multicenter retrospective study reviewed 766 patients who underwent mastectomy and NACT with ypN0 from 2000 to 2014. Recurrent risk score model was assigned proportionally to the relative contribution of independent prognostic factors in the multivariate Cox model of disease-free survival (DFS). Decision tree analysis was conducted to determine two optimal cutoff points for stratification.

RESULTS

The median follow-up time was 74 months. The 5-year locoregional control (LRC), DFS, and overall survival (OS) rates for the entire group were 96.5%, 89.1% and 95.3%, respectively. 353 (46.1%) patients received PMRT and 413 (53.9%) patients did not. Patients with PMRT have more high-risk factors, including age <40 years, clinical stage III, grade III, or ER and PR negative. Chest wall and regional nodal region were irradiated in 307 (87.0%) and chest wall only in 46 (13.0%). The median radiation dose was 50 Gy (range: 36-60 Gy) in 25 fractions (range: 15-30 fractions). There were no significant differences between the PMRT and No-PMRT groups in the LRC, DFS and OS rates. Recurrent risk score model consisted of five factors and used a range of zero to eleven scoring points: age <40 years and clinical N1 stage for one point; clinical N2, NACT ≥4 cycles, lymphovascular invasion and ypT1-2 for two points; ypT3-4 for four points. 456 (59.5%) patients scoring zero to four points, 188 (24.5%) scoring five points and 122 (15.9%) scoring six to eleven points were assigned to the low-, intermediate-, and high-risk group. LRC, DFS and OS rates in three risk groups were significantly distinct from each other (5yr-LRC: 98.6% vs. 95.5% vs. 89.8%, p < .001; 5yr-DFS: 94.4% vs. 87.4% vs. 71.5%, p < .001; 5yr-OS: 97.6% vs. 93.2% vs. 90.0%, p < .001). PMRT had no impact on the LRC, DFS and OS rates in either low-, intermediate-, or high-risk group.

CONCLUSION

The recurrence risk score model can effectively distinguish patients with different recurrent risk stratification. PMRT in patients with ypN0 after NAC and mastectomy cannot improve LRC, DFS or OS. Table 1. Survival outcomes and comparison between PMRT and No-PMRT arms in different groups.

Effects of Different Primers on the Bond Strength to Properly and Excessively Etched Ceramic-coated Zirconia

PURPOSE

To determine the effects of various primers on the immediate and long-term bond strength of ceramic-coated ultratranslucent zirconia that is properly or excessively etched.

METHODS AND MATERIALS

Ceramic-coated zirconia plates were etched with 9.5% hydrofluoric acid (HF) for 2 or 5 minutes, after which the surface morphology and elemental composition were examined. The etched specimens were treated with different primers including methacryloyloxydecyl dihydrogen phosphate (MDP)-only containing primer, silane-only containing primer, MDP and silane-containing ceramic primer as well as MDP and silane-containing adhesive system. For surface contact angle and shear bond strength (SBS) data, the difference between groups was evaluated by one-way analysis of variance (ANOVA) and three-way ANOVA factorial analysis, respectively. The statistical significance level of 0.05 was set and the Tukey test and the Dunnett-T3 test were used for post-hoc multiple comparisons.

RESULTS

Excessive etching (9.5% HF for 5 minutes) led to overconsumption of the glass layer and exposure of zirconia substrate compared to proper etching (9.5% HF for 2 minutes). Among different primers, the surface contact angle of the silane-only containing primer group was the lowest. The silane-only containing primer and MDP and silane-containing ceramic primer produced higher shear bond strength of properly and excessively etched ceramic-coated zirconia, respectively, both before and after thermal aging.

CONCLUSIONS

The silane-only containing primer and MDP and silane-containing primer can obtain better immediate and long-term shear bond strength for properly and excessively etched ceramic-coated zirconia, respectively.

[Radiomics-based prediction of microsatellite instability in stage Ⅱ and Ⅲ rectal cancer patients based on T2WI MRI and diffusion-weighted imaging]

Objective: To examine the radiomics model based on high-resolution T2WI and diffusion weighted imaging (DWI) in predicting microsatellite stability in patients with stage Ⅱ and Ⅲ rectal cancer. Methods: From February 2016 to October 2020, 175 patients with stage Ⅱ and Ⅲ rectal cancer who met the inclusion criteria were retrospectively collected. There were 119 males and 56 females, aged (63.9±9.4) years (range: 37 to 85 years), including 152 patients with microsatellite stability and 23 patients with microsatellite instability. All patients were randomly divided into the training group (n=123) and the validation group (n=52) with a ratio of 7∶3. The region of interest was labeled on the T2WI and DWI images of each patient using the ITK-SNAP software, and PyRadiomics was used to extract seven kinds of radiomics features. After removing redundant features and normalizing features, the least absolute shrinkage and selection operation were used for feature selection. One clinical model, three radiomics models and one clinical-radiomics model were constructed in the training group based on a support vector machine. The area under receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy were used to evaluate the performance of the models in the verification group. Results: Three clinical features (age, degree of tumor differentiation, and distance from the lower edge of the tumor to the anal edge) and six radiomics features (two DWI-related features and four T2WI-related features) most related to microsatellite status of rectal cancer patients were selected. The AUC of the clinical-radiomics model in the training group was 0.95. In the validation group, the AUC was 0.81, better than the clinical model (0.68, Z=0.71, P=0.04), and equivalent to the T2WI+DWI model (0.82, Z=0.21, P=0.83). Conclusions: Radiomic features based on preoperative T2WI and DWI were related to microsatellite stability in patients with stage Ⅱ and Ⅲ rectal cancer and showed a high classification efficiency. The model based on the features provided a noninvasive and convenient tool for preoperative determination of microsatellite stability in rectal cancer patients.

Risk factors for bloodstream infection in paediatric haematopoietic stem cell transplantation: a systematic review and meta-analysis

BACKGROUND

Haematopoietic stem cell transplantation (HSCT), a standard treatment for paediatric haematological diseases, is highly associated with bloodstream infection (BSI), which may increase mortality.

AIM

To explore the risk factors for BSI in paediatric HSCT recipients.

METHODS

Three English databases and four Chinese databases were searched from inception to March 17th, 2022. Eligible studies included randomized controlled trials, cohort studies, and case-control studies that enrolled HSCT recipients aged ≤18 years and reported BSI risk factors. Two reviewers independently screened studies, extracted data, and assessed the risk of bias. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE), certainty of body of evidence was assessed.

FINDINGS

Fourteen studies involving 4602 persons were included. The incidences of BSI and associated mortality in paediatric HSCT recipients were approximately 10-50% and 5-15%, respectively. Meta-analysis of all studies revealed that previous BSI before HSCT (relative effect (RE): 2.28; 95% confidence interval (CI) 1.19-4.34, moderate certainty) and receiving an umbilical cord blood transplant (RE: 1.55; 95% CI: 1.22-1.97, moderate certainty) were probably associated with an increased risk of BSI. Meta-analysis of studies with low risk of bias reassured that previous BSI before HSCT probably increased the risk of BSI (RE: 2.28; 95% CI: 1.19-4.34, moderate certainty), and revealed that steroid use (RE: 2.72; 95% CI: 1.31-5.64, moderate certainty) was likely a risk factor whereas autologous HSCT was probably a protective factor of BSI (RE: 0.65; 95% CI: 0.45-0.94, moderate certainty).

CONCLUSION

These findings could inform the management of paediatric HSCT recipients, helping identify who may benefit from prophylactic antibiotics.

Postoperative pulmonary complications in older patients undergoing elective surgery with a supraglottic airway device or tracheal intubation

The two most commonly used airway management techniques during general anaesthesia are supraglottic airway devices and tracheal tubes. In older patients undergoing elective non-cardiothoracic surgery under general anaesthesia with positive pressure ventilation, we hypothesised that a composite measure of in-hospital postoperative pulmonary complications would be less frequent when a supraglottic airway device was used compared with a tracheal tube. We studied patients aged ≥ 70 years in 17 clinical centres. Patients were allocated randomly to airway management with a supraglottic airway device or a tracheal tube. Between August 2016 and April 2020, 2900 patients were studied, of whom 2751 were included in the primary analysis (1387 with supraglottic airway device and 1364 with a tracheal tube). Pre-operatively, 2431 (88.4%) patients were estimated to have a postoperative pulmonary complication risk index of 1-2. Postoperative pulmonary complications, mostly coughing, occurred in 270 of 1387 patients (19.5%) allocated to a supraglottic airway device and 342 of 1364 patients (25.1%) assigned to a tracheal tube (absolute difference -5.6% (95%CI -8.7 to -2.5), risk ratio 0.78 (95%CI 0.67-0.89); p < 0.001). Among otherwise healthy older patients undergoing elective surgery under general anaesthesia with intra-operative positive pressure ventilation of their lungs, there were fewer postoperative pulmonary complications when the airway was managed with a supraglottic airway device compared with a tracheal tube.

[Analysis on influencing factors on loneliness in the elderly aged 60 and above in China]

Objective: To analyze the influential factors of loneliness in the elderly aged ≥60 years in China. Methods: Data used in this study were obtained from participants aged ≥60 years from the China Longitudinal Aging Social Survey, with a sample size of 7 593. Loneliness was measured with loneliness scale, and the influence of subjective and objective factors on loneliness and their interaction were analyzed with stepwise linear regression model and simple slope test. SPSS 25.0 was used for statistical analysis. PROCESS 3.3 macro program was used for simple slope test. Results: A total of 8 926 participants were included. Among the objective factors, the elderly with poor family network have a higher level of loneliness (P<0.05), and community provision of elderly care services could reduce the loneliness of the elderly (P<0.05). Elderly people with subjective aging age ≤60 years old and poor social adaptation and emotional perception have higher levels of loneliness (all P<0.05). Subjective aging age plays a negative regulatory role in the impact of community elderly care services on loneliness (P<0.05), Social adaptation and emotional perception play a negative regulatory role in the impact of family network on loneliness (P<0.05). Conclusions: Elderly people aged ≥60 years of feeling of loneliness was affected by both subjective and objective factors and subjective factors play an important regulatory role in the influence of objective factors on elderly people's feeling of loneliness in China. Therefore, while creating a good aging environment to provide strong external support for the elderly, the subjective initiative of the elderly should also be fully mobilized, to alleviate the loneliness of the elderly from these two aspects.

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

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

[A preliminary discussion on carnosine dipeptidase 1 as a potential novel biomarker for the diagnostic and prognostic evaluation of hepatocellular carcinoma]

Objective: To explore carnosine dipeptidase 1 (CNDP1) potential value as a diagnostic and prognostic evaluator of hepatocellular carcinoma (HCC). Methods: A gene chip and GO analysis were used to screen the candidate marker molecule CNDP1 for HCC diagnosis. 125 cases of HCC cancer tissues, 85 cases of paracancerous tissues, 125 cases of liver cirrhosis tissues, 32 cases of relatively normal liver tissue at the extreme end of hepatic hemangioma, 66 cases from serum samples of HCC, and 82 cases of non-HCC were collected. Real-time fluorescent quantitative PCR, immunohistochemistry, western blot, and enzyme-linked immunosorbent assay were used to detect the differences in mRNA and protein expression levels of CNDP1 in HCC tissue and serum. Receiver operating characteristic (ROC) curves and Kaplan-Meier survival were used to analyze and evaluate the value of CNDP1 in the diagnosis and prognosis of HCC patients. Results: The expression level of CNDP1 was significantly reduced in HCC cancer tissues. The levels of CNDP1 were significantly lower in the cancer tissues and serum of HCC patients than those in liver cirrhosis patients and normal controls. ROC curve analysis showed that the area under the curve of serum CNDP1 in the diagnosis of HCC patients was 0.753 2 (95% CI 0.676-0.830 5), and the sensitivity and specificity were 78.79% and 62.5%, respectively. The combined detection of serum CNDP1 and serum alpha-fetoprotein (AFP) significantly improved the diagnostic accuracy (AUC = 0.820 6, 95% CI 0.753 5-0.887 8). The diagnostic sensitivity and specificity of serum CNDP1 for AFP-negative HCC patients were 73.68% and 68.75% (AUC = 0.793 1, 95% CI 0.708 8-0.877 4), respectively. In addition, the level of serum CNDP1 distinguished small liver cancer (tumor diameter < 3 cm) (AUC = 0.757 1, 95% CI 0.637 4-0.876 8). Kaplan-Meier survival analysis showed that CNDP1 was associated with a poor prognosis in HCC patients. Conclusion: CNDP1 may be a potential biomarker for the diagnostic and prognostic evaluation of HCC, and it has certain complementarity with serum AFP.

[Prevalence of parasitic infections in human stool samples from a hospital in Chenzhou City of Hunan Province]

OBJECTIVE

To investigate the prevalence of parasitic infections in human stool samples from a hospital in Chenzhou City, Hunan Province, so as to provide insights into the management of intestinal parasitic diseases.

METHODS

Stool samples were collected from patients admitted to a hospital in Chenzhou City from September 2020 to March 2021, subjected to physiological saline smearing and microscopy for detection of intestinal parasites. The prevalence of parasitic infections and the species of parasites were descriptively analyzed.

RESULTS

The overall prevalence of intestinal parasitic infections was 1.61% in the 10 728 stool samples, and there were 3 samples with mixed infections of two parasite species. A total of seven parasite species were identified, including Blastocystis hominis (162 cases, 1.55%), Giardia lamblia (5 cases, 0.05%), Dientamoeba fragilis (5 cases, 0.05%), Endolimax nana (one case, 0.01%), Iodamoeba bütschlii (one case, 0.01%), Strongyloides stercoralis (one case, 0.01%) and Trichomonas hominis (one case, 0.01%). The prevalence of intestinal parasitic infection was significantly higher among women than in men (2.14% vs. 1.25%; χ² = 13.01, P < 0.01), and a high prevalence rate was seen among patients at ages of 20 to 30 years (2.99%) and 80 years and older (2.86%); however, no age-specific prevalence of intestinal parasitic infection was detected (χ² = 12.45, P > 0.05).

CONCLUSIONS

The overall prevalence of intestinal parasitic infection was low among patients admitted to a hospital in Chenzhou City, and gender-specific prevalence was found. Food-borne and opportunistic parasites were predominant intestinal parasites, including B. hominis, G. lamblia and D. fragilis.

The diagnostic accuracy of the IFLIP system for binocular visual function anomalies assessment

OBJECTIVE

This study aimed to evaluate the diagnostic accuracy of the intelligent flipper (IFLIP) system in identifying binocular vision anomalies.

PATIENTS AND METHODS

This study comprised 70 participants aged 18 to 22. Participants underwent comprehensive eye assessments, including measurement of visual acuity, refraction, far and near cover test, stereopsis, and worth four dot test. The manual accommodation amplitude and facility, as well as the IFLIP system test, were also evaluated. The correlation between the indices of the IFLIP and manual accommodation tests was analyzed using multiple regression models, and the diagnostic ability of the IFLIP was characterized using Receiver Operating Curve (ROC) analysis. The significance level was 0.05.

RESULTS

The mean age of the 70 participants was 20.03±0.78 years. The mean manual and IFLIP accommodation facilities were 12.00±3.70 cycle per minute (CPM) and 10.01±2.77 CPM, respectively. No correlation was found between the indices of the IFLIP system and manual accommodative amplitude. However, the regression model showed that the contraction/relaxation ratio of the IFLIP system was positively correlated to the manual accommodation facility, and the average contraction time was negatively correlated with the manual accommodation facility. The ROC analysis proposed a cut-off of 10.15 CPM monocularly for the IFLIP accommodation facility assessment.

CONCLUSIONS

This study indicated that the parameters obtained by the IFLIP system and the manual accommodation facility were comparable, and the IFLIP system had good sensitivity and specificity in the assessment of the accommodation facility, thus may serve as a promising tool for screening and diagnosis of binocular visual function anomalies in clinical and community settings.

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

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

[The analysis of a pedigree with hereditary coagulation factor Ⅴ deficiency caused by compound heterozygous variation of F5 gene]

Objective: To analyze the gene variation of a genetic coagulation factor Ⅴ (FⅤ) deficiency pedigree and explore the molecular pathogenesis. Methods: The proband was a 32 years old female. The patient was prone to nose bleeding since childhood which was usually self-healed. On March 10, 2021, the proband went to the First Affiliated Hospital of Air Force Medical University for treatment of knee hematoma caused by a fall. None of the family members reported any history of bleeding. The prothrombin time (PT), activated partial thromboplastin time (APTT) and FⅤ activity (FⅤ: C) were detected by clotting method and the FⅤ antigen (FⅤ: Ag) was tested with enzyme-linked immunosorbent assay (ELISA). All exons and flanks of F5 gene were determined by Sanger sequencing. Clustalx-2.1-win, PolyPhen-2 and Swiss-PDBViewer software were used to analyze the conservatism of missense variation sites, whether the variations were harmful and their influences on protein structure and function. MutationTaster and NetGene2 software were used to analyze whether the splice site variation was harmful and its effect on the splice site. Results: The PT and APTT of the proband prolonged to 24.0 s and 69.8 s, respectively. The FⅤ: C and FⅤ: Ag decreased to 6% and 9%, respectively. There were compound heterozygous variations in F5 gene, which included c.911G>A heterozygous missense variation in exon 6 leading to p.Gly276Glu variation and c.5208+1G>A heterozygous missense variation in intron 15. The father and daughter had the p.Gly276Glu heterozygous variation. Her mother and son had the c.5208+1G>A heterozygous variation. Software analysis results of p.Gly276Glu heterozygous variation showed that Gly276 was conserved among homologous species, the variation was harmful, and it could affect the local structure and function of the protein. The c.5208+1G>A heterozygous variation was deleterious and resulted in the disappearance of the splice site, thereby affecting the protein function. Conclusion: The p.Gly276Glu and c.5208+1G>A compound heterozygous variants are deleterious variants associated with the patient's disease and may be the molecular pathogenesis of inherited FⅤ deficiency in this family.

Effects of UV radiation on natural and synthetic materials

The deleterious effects of solar ultraviolet (UV) radiation on construction materials, especially wood and plastics, and the consequent impacts on their useful lifetimes, are well documented in scientific literature. Any future increase in solar UV radiation and ambient temperature due to climate change will therefore shorten service lifetimes of materials, which will require higher levels of stabilisation or other interventions to maintain their lifetimes at the present levels. The implementation of the Montreal Protocol and its amendments on substances that deplete the ozone layer, controls the solar UV-B radiation received on Earth. This current quadrennial assessment provides a comprehensive update on the deleterious effects of solar UV radiation on the durability of natural and synthetic materials, as well as recent innovations in better stabilising of materials against solar UV radiation-induced damage. Pertinent emerging technologies for wood and plastics used in construction, composite materials used in construction, textile fibres, comfort fabric, and photovoltaic materials, are addressed in detail. Also addressed are the trends in technology designed to increase sustainability via replacing toxic, unsustainable, legacy additives with 'greener' benign substitutes that may indirectly affect the UV stability of the redesigned materials. An emerging class of efficient photostabilisers are the nanoscale particles that include oxide fillers and nanocarbons used in high-performance composites, which provide good UV stability to materials. They also allow the design of UV-shielding fabric materials with impressive UV protection factors. An emerging environmental issue related to the photodegradation of plastics is the generation of ubiquitous micro-scale particles from plastic litter exposed to solar UV radiation.