Niraparib maintenance therapy using an individualised starting dose in patients with platinum-sensitive recurrent ovarian cancer (NORA): final overall survival analysis of a phase 3 randomised, placebo-controlled trial

Background

Niraparib significantly prolonged progression-free survival versus placebo in patients with platinum-sensitive, recurrent ovarian cancer (PSROC), regardless of germline BRCA mutation (gBRCAm) status, in NORA. This analysis reports final data on overall survival (OS).

Methods

This randomised, double-blind, placebo-controlled, phase 3 trial enrolled patients across 30 centres in China between 26 September 2017 and 2 February 2019 (clinicaltrials.gov, NCT03705156). Eligible patients had histologically confirmed, recurrent, (predominantly) high-grade serous epithelial ovarian cancer, fallopian tube carcinoma, or primary peritoneal carcinoma (no histological restrictions for those with gBRCAm) and had received ≥2 prior lines of platinum-based chemotherapy. Patients were randomised (2:1) to receive niraparib or placebo, with stratification by gBRCAm status, time to recurrence following penultimate platinum-based chemotherapy, and response to last platinum-based chemotherapy. Following a protocol amendment, the starting dose was individualised: 200 mg/day for patients with bodyweight <77 kg and/or platelet count <150 × 103/μL at baseline and 300 mg/day otherwise. OS was a secondary endpoint.

Findings

Totally, 265 patients were randomised to receive niraparib (n = 177) or placebo (n = 88), and 249 (94.0%) received an individualised starting dose. As of 14 August 2023, median follow-up for OS was 57.9 months (IQR, 54.8-61.6). Median OS (95% CI) with niraparib versus placebo was 51.5 (41.4-58.9) versus 47.6 (33.3-not evaluable [NE]) months, with hazard ratio [HR] of 0.86 (95% CI, 0.60-1.23), in the overall population; 56.0 (36.1-NE) versus 47.6 (31.6-NE) months, with HR of 0.86 (95% CI, 0.46-1.58), in patients with gBRCAm; and 46.5 (41.0-NE) versus 46.9 (31.8-NE) months, with HR of 0.87 (95% CI, 0.56-1.35), in those without. No new safety signals were identified, and myelodysplastic syndromes/acute myeloid leukaemia occurred in three (1.7%) niraparib-treated patients.

Interpretation

Niraparib maintenance therapy with an individualised starting dose demonstrated a favourable OS trend versus placebo in PSROC patients, regardless of gBRCAm status.

Funding

Zai Lab (Shanghai) Co., Ltd; National Major Scientific and Technological Special Project for "Significant New Drugs Development" in 2018, China [grant number 2018ZX09736019].

Prognostic factors of 87 ovarian yolk sac tumor (OYST) patients and molecular characteristics of persistent and recurrent OYST

OBJECTIVE

We aimed to explore the characteristics of OYST, particularly for persistent and recurrent OYST, in order to explore potential treatment options and thereby improve patient outcomes.

METHODS

We retrospectively reviewed the clinical records of all patients with OYST at Fudan university Shanghai Cancer Center from December 3, 2005 to November 27, 2020. Furthermore, and performed whole-exome sequencing on 17 paired OYST (including 8 paired persistent and recurrent OYST) tumor and blood samples to elucidate the aberrant molecular features.

RESULTS

Totally, 87 OYST patients were included between 2007/03/13 and 2020/11/17. With a median follow-up of 73 [3-189] months, 22 patients relapsed or disease persisted. Overall, 17 patients died with a median overall survival of 21 [3-54] months. Univariate and multivariate analysis revealed tumor histology and residual lesions were independently associated with event free survival and overall survival, cycles to AFP normalization were another independent risk factor for overall survival. For the 8 persistent and recurrent OYST: cancer driver genes including ANKRD36, ANKRD62, DNAH8, MUC5B, NUP205, RYR2, STARD9, MUC16, TTN, ARID1A and PIK3CA were frequently mutated; cell cycle, ABC transporters, HR, NHEJ and AMPK signal pathway demonstrated as the most significantly enriched pathways; TMB, DNA MMR gene mutation and MSI were significantly higher. Mutation signature 11, 19 and 30 were the dominant contributors in persistent and recurrent OYST mutation.

CONCLUSION

Persistent and recurrent OYST associated with poor prognosis, and probably susceptible to immune checkpoint blockade therapy. Molecular characteristics contributed to predict the persistence and recurrence of OYST.

Prognostic factors and the role of primary debulking in operable stage IVB ovarian cancer with supraclavicular lymph node metastasis: a retrospective study in Chinese patients

BACKGROUND

Recent studies showed heterogeneity in stage IVB patients. However, few studies focused on the prognosis of supraclavicular metastatic ovarian cancer. This study aimed to explore the prognostic factors and the role of primary debulking in IVB ovarian cancer patients with supraclavicular lymph node metastasis.

METHODS

We retrospectively analyzed patients newly diagnosed as primary epithelial ovarian cancer with supraclavicular lymph node metastasis from January 2015 to July 2020. Supraclavicular lymph node metastasis was defined as either the pathological diagnosis by supraclavicular lymph node biopsy, or the radiological diagnosis by positron emission tomography-computed tomography (PET-CT).

RESULTS

In 51 patients, 37 was diagnosed with metastatic supraclavicular lymph nodes by histology, 46 by PET-CT, and 32 by both methods. Forty-four (86.3%) with simultaneous metastatic paraaortic lymph nodes (PALNs) by imaging before surgery or neoadjuvant chemotherapy were defined as "continuous-metastasis type", while the other 7 (13.7%) defined as "skip-metastasis type". Nineteen patients were confirmed with metastatic PALNs by histology. Thirty-four patients were investigated for BRCA mutation, 17 had germline or somatic BRCA1/2 mutations (g/sBRCAm). With a median follow-up of 30.0 months (6.3-63.4 m), 16 patients (31.4%) died. The median PFS and OS of the cohort were 17.3 and 48.9 months. Survival analysis showed that "continuous-metastasis type" had longer OS and PFS than "skip-metastasis type" (OS: 50.0/26.6 months, PFS: 18.5/7.2months, p=0.005/0.002). BRCA mutation carriers also had longer OS and PFS than noncarriers (OS: 57.4 /38.5 m, p=0.031; PFS: 23.6/15.2m, p=0.005). Multivariate analysis revealed only metastatic PALNs was independent prognostic factor for OS (p=0.040). Among "continuous-metastasis type" patients, 22 (50.0%) achieved R0 abdominopelvic debulking, who had significantly longer OS (55.3/42.3 months, p =0.034) than those with residual abdominopelvic tumors.

CONCLUSIONS

In stage IVB ovarian cancer patients with supraclavicular lymph nodes metastasis, those defined as "continuous-metastasis type" with positive PALNs had better prognosis. For them, optimal abdominopelvic debulking had prognostic benefit, although metastatic supraclavicular lymph nodes were not resected. Higher BRCA mutation rate than the general population of ovarian cancer patients was observed in patients with IVB supraclavicular lymph node metastasis, leading to better survival as expected.

Determination of Spin-Parity Quantum Numbers of X(2370) as 0^{-+} from J/ψ→γK_{S}^{0}K_{S}^{0}η^{'}

Based on (10087±44)×10^{6}  J/ψ events collected with the BESIII detector, a partial wave analysis of the decay J/ψ→γK_{S}^{0}K_{S}^{0}η^{'} is performed. The mass and width of the X(2370) are measured to be 2395±11(stat)_{-94}^{+26}(syst)  MeV/c^{2} and 188_{-17}^{+18}(stat)_{-33}^{+124}(syst)  MeV, respectively. The corresponding product branching fraction is B[J/ψ→γX(2370)]×B[X(2370)→f_{0}(980)η^{'}]×B[f_{0}(980)→K_{S}^{0}K_{S}^{0}]=(1.31±0.22(stat)_{-0.84}^{+2.85}(syst))×10^{-5}. The statistical significance of the X(2370) is greater than 11.7σ and the spin parity is determined to be 0^{-+} for the first time. The measured mass and spin parity of the X(2370) are consistent with the predictions of the lightest pseudoscalar glueball.

Differential selection of yield and quality traits has shaped genomic signatures of cowpea domestication and improvement

Cowpeas (tropical legumes) are important in ensuring food and nutritional security in developing countries, especially in sub-Saharan Africa. Herein, we report two high-quality genome assemblies of grain and vegetable cowpeas and we re-sequenced 344 accessions to characterize the genomic variations landscape. We identified 39 loci for ten important agronomic traits and more than 541 potential loci that underwent selection during cowpea domestication and improvement. In particular, the synchronous selections of the pod-shattering loci and their neighboring stress-relevant loci probably led to the enhancement of pod-shattering resistance and the compromise of stress resistance during the domestication from grain to vegetable cowpeas. Moreover, differential selections on multiple loci associated with pod length, grain number per pod, seed weight, pod and seed soluble sugars, and seed crude proteins shaped the yield and quality diversity in cowpeas. Our findings provide genomic insights into cowpea domestication and improvement footprints, enabling further genome-informed cultivar improvement of cowpeas.

Current treatment strategies for ovarian cancer in the East Asian Gynecologic Oncology Trial Group (EAGOT)

Ovarian cancer, notable for its severe prognosis among gynecologic cancers, has seen substantial progress in treatment approaches recently. Enhanced protocols in chemotherapy and the introduction of poly (ADP-ribose) polymerase (PARP) inhibitors for maintenance therapy have markedly improved outcomes for patients with specific genetic profiles, such as those positive for BRCA mutations or exhibiting homologous recombination deficiency (HRD). Additionally, the method of intraperitoneal chemotherapy administration has emerged as a valuable alternative to traditional transvenous routes, showing promise for wider clinical adoption. The field of surgery has also evolved, with increasing exploration into the benefits and feasibility of laparoscopic methods over more invasive traditional surgeries, aiming for complete tumor removal but with reduced patient impact. The hereditary nature of ovarian cancer underscores the importance of genetic testing, which has become integral in tailoring treatment strategies, particularly in determining suitability for PARP inhibitors. The formation of the East Asian Gynecologic Oncology Trial Group (EAGOT) aims to optimize treatment across Japan, Korea, China, and Taiwan. The ovarian cancer committee of EAGOT shared the current policies, focusing on 5 topics: 1) strategies for maintenance therapy after initial surgery and chemotherapy, 2) drug regimens for platinum-sensitive and platinum-resistant recurrence, 3) intraperitoneal chemotherapy, 4) laparoscopic surgery as an alternative to laparotomy, and 5) current status of genetic testing (BRCA, HRD, and panel tests) for ovarian cancer and its prospects. EAGOT's multi-national trials aim to harmonize these evolving treatment strategies, ensuring that the latest and most effective protocols are accessible across the region, thereby significantly impacting patient outcomes in East Asia.

Observation of Structures in the Processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2}

We present measurements of the Born cross sections for the processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2} at center-of-mass energies sqrt[s] from 4.308 to 4.951 GeV. The measurements are performed with data samples corresponding to an integrated luminosity of 11.0  fb^{-1} collected with the BESIII detector operating at the Beijing Electron Positron Collider storage ring. Assuming the e^{+}e^{-}→ωχ_{c2} signals come from a single resonance, the mass and width are determined to be M=(4413.6±9.0±0.8)  MeV/c^{2} and Γ=(110.5±15.0±2.9)  MeV, respectively, which is consistent with the parameters of the well-established resonance ψ(4415). In addition, we also use one single resonance to describe the e^{+}e^{-}→ωχ_{c1} line shape and determine the mass and width to be M=(4544.2±18.7±1.7)  MeV/c^{2} and Γ=(116.1±33.5±1.7)  MeV, respectively. The structure of this line shape, observed for the first time, requires further understanding.

Myocardial deformation characteristics assessed by cardiovascular magnetic resonance feature tracking in a healthy Chinese population

Purpose

To explore global/regional myocardial deformation across various layers, vascular distributions, specific levels and distinct walls in healthy individuals using cardiovascular magnetic resonance feature tracking (CMR-FT).

Methods

We selected a cohort of 55 healthy participants and CMR cine images were used to obtain the left ventricular (LV) peak longitudinal, circumferential, radial strains (LS, CS, RS). The characteristics of normal LV strain in various layers (endocardium, myocardium, epicardium), territories [left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA)], levels (basal, middle, apical) and walls (anterior, septum, inferior, lateral) were compared.

Results

The absolute values of the LV global LS and CS gradually decreased from endocardium to epicardium. The absolute LV global RS (65.7 ± 47.7%) was maximum relative to LS (-22.0 ± 10.8%) and CS (-22.8 ± 7.7%). The absolute values of the LCX territorial strain were the largest compared with the LAD and RCA territorial strains. Regional RS, endo-CS and endo-LS gradually increased from the basal to the apical level. The LV lateral walls had the highest strain values (CS, LS, and RS).

Conclusions

Variations in normal LV strain values across various layers, territories, levels, and walls were observed, suggesting the necessity for careful clinical interpretation of these strain values. These findings also partially revealed the complexity of normal cardiac mechanics.

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

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

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

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

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

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

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

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

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

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

Key Words Collapse

MESH Headings Collapse

Grants Collapse

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

Collapse

Pembrolizumab in patients from China with microsatellite instability-high/mismatch repair deficient tumors: KEYNOTE-158

Aim: To evaluate pembrolizumab in patients of Chinese descent with microsatellite instability-high (MSI-H)/deficient mismatch repair (dMMR) tumors enrolled in KEYNOTE-158 (Cohort L). Methods: Patients with MSI-H/dMMR advanced tumors received pembrolizumab 200 mg IV Q3W. Primary end point was overall response rate (ORR). Secondary end points were duration of response (DOR), progression-free survival (PFS) and overall survival (OS). Results: 24 patients were enrolled (20 were evaluable for efficacy). With median follow-up of 12.4 months, the ORR was 70%. DOR, PFS and OS were all not reached. A total of 19 (79%) patients had a treatment-related adverse event (AE; grade ≥3 in 4 [17%]), and 8 (33%) had an immune-mediated AE (grade ≥3 in (4 [17%]). Conclusion: Pembrolizumab provided meaningful and durable responses with manageable safety. These results are consistent with those reported for the global trial.

Corrigendum: Integrated analysis of transcriptome and metabolome reveals the mechanism of chlorine dioxide repressed potato (Solanum tuberosum L.) tuber sprouting

[This corrects the article DOI: 10.3389/fpls.2022.887179.].

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.

Using the sulfide-oxidizing bacterium Geobacillus thermodenitrificans to restrict H2S release during chicken manure composting

Hydrogen sulfide (H2S) is a toxic gas massively released during chicken manure composting. Diminishing its release requires efficient and low cost methods. In recent years, heterotrophic bacteria capable of rapid H2S oxidation have been discovered but their applications in environmental improvement are rarely reported. Herein, we investigated H2S oxidation activity of a heterotrophic thermophilic bacterium Geobacillus thermodenitrificans DSM465, which contains a H2S oxidation pathway composed by sulfide:quinone oxidoreductase (SQR) and persulfide dioxygenase (PDO). This strain rapidly oxidized H2S to sulfane sulfur and thiosulfate. The oxidation rate reached 5.73 μmol min-1·g-1 of cell dry weight. We used G. thermodenitrificans DSM465 to restrict H2S release during chicken manure composting. The H2S emission during composting process reduced by 27.5% and sulfate content in the final compost increased by 34.4%. In addition, this strain prolonged the high temperature phase by 7 days. Thus, using G. thermodenitrificans DSM465 to control H2S release was an efficient and economic method. This study provided a new strategy for making waste composting environmental friendly and shed light on perspective applications of heterotrophic H2S oxidation bacteria in environmental improvements.

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.

Assessment of Non-Invasive Ventilation Combined with Naloxone for the Management of Acute Respiratory Failure in Patients with Chronic Obstructive Pulmonary Disease

Background

Chronic obstructive pulmonary disease (COPD) poses a significant global health burden. Finding effective interventions for COPD is crucial to alleviating this health burden and enhancing patient outcomes and quality of life.

Objective

This study aimed to evaluate the therapeutic efficacy of the combination of non-invasive ventilation and naloxone in the management of acute respiratory failure among patients with COPD.

Methods

A retrospective analysis was conducted on the clinical data of 102 COPD patients experiencing acute respiratory failure who were treated at our hospital between October 2020 and October 2022. Patients were categorized into an observation group (receiving non-invasive ventilation combined with naloxone) and a control group (receiving non-invasive ventilation alone). Parameters such as lung function, blood gas levels, endocrine hormone concentrations, treatment efficacy, and patient prognosis were carefully recorded and compared.

Results

The observation group demonstrated enhanced lung function, optimized endocrine hormone levels, and improved blood gas parameters compared to the control group. Following treatment, the observation group exhibited significant reductions in plasma renin activity (PRA), angiotensin II (AngII), aldosterone (ALD), and norepinephrine (NE) levels. The total effective rate was notably higher in the observation group. This group also presented higher scores for Acute Physiology and Chronic Health Evaluation II (APACHE II) and Chronic Obstructive Pulmonary Disease Assessment Test (CAT).

Conclusions

The combination of non-invasive ventilation with naloxone emerged as a significantly effective strategy in managing acute respiratory failure in COPD patients. This approach led to improvements in lung function, endocrine hormone levels, and blood gas parameters and highlights its potential as an impactful treatment strategy for COPD patients experiencing acute respiratory failure.

PARP1-stabilised FOXQ1 promotes ovarian cancer progression by activating the LAMB3/WNT/β-catenin signalling pathway

Metastasis is an important factor that causes ovarian cancer (OC) to become the most lethal malignancy of the female reproductive system, but its molecular mechanism is not fully understood. In this study, through bioinformatics analysis, as well as analysis of tissue samples and clinicopathological characteristics and prognosis of patients in our centre, it was found that Forkhead box Q1 (FOXQ1) was correlated with metastasis and prognosis of OC. Through cell function experiments and animal experiments, the results show that FOXQ1 can promote the progression of ovarian cancer in vivo and in vitro. Through RNA-seq, chromatin immunoprecipitation sequencing (ChIP-seq), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), Western blotting (WB), quantitative real-time polymerase chain reaction (qRT‒PCR), immunohistochemistry (IHC), luciferase assay, and ChIP-PCR, it was demonstrated that FOXQ1 can mediate the WNT/β-catenin pathway by targeting the LAMB promoter region. Through coimmunoprecipitation (Co-IP), mass spectrometry (MS), ubiquitination experiments, and immunofluorescence (IF), the results showed that PARP1 could stabilise FOXQ1 expression via the E3 ubiquitin ligase Hsc70-interacting protein (CHIP). Finally, the whole mechanism pathway was verified by animal drug combination experiments and clinical specimen prognosis analysis. In summary, our results suggest that PARP1 can promote ovarian cancer progression through the LAMB3/WNT/β-catenin pathway by stabilising FOXQ1 expression.

A modified diffusion-weighted magnetic resonance imaging-based model from the radiologist's perspective: improved performance in determining the surgical resectability of advanced high-grade serous ovarian cancer

BACKGROUND

Complete resection of all visible lesions during primary debulking surgery is associated with the most favorable prognosis in patients with advanced high-grade serous ovarian cancer. An accurate preoperative assessment of resectability is pivotal for tailored management.

OBJECTIVE

This study aimed to assess the potential value of a modified model that integrates the original 8 radiologic criteria of the Memorial Sloan Kettering Cancer Center model with imaging features of the subcapsular or diaphragm and mesenteric lesions depicted on diffusion-weighted magnetic resonance imaging and growth patterns of all lesions for predicting the resectability of advanced high-grade serous ovarian cancer.

STUDY DESIGN

This study included 184 patients with high-grade serous ovarian cancer who underwent preoperative diffusion-weighted magnetic resonance imaging between December 2018 and May 2023 at 2 medical centers. The patient cohort was divided into 3 subsets, namely a study cohort (n=100), an internal validation cohort (n=46), and an external validation cohort (n=38). Preoperative radiologic evaluations were independently conducted by 2 radiologists using both the Memorial Sloan Kettering Cancer Center model and the modified diffusion-weighted magnetic resonance imaging-based model. The morphologic characteristics of the ovarian tumors depicted on magnetic resonance imaging were assessed as either mass-like or infiltrative, and transcriptomic analysis of the primary tumor samples was performed. Univariate and multivariate statistical analyses were performed.

RESULTS

In the study cohort, both the scores derived using the Memorial Sloan Kettering Cancer Center (intraclass correlation coefficients of 0.980 and 0.959, respectively; both P<.001) and modified diffusion-weighted magnetic resonance imaging-based models (intraclass correlation coefficients of 0.962 and 0.940, respectively; both P<.001) demonstrated excellent intra- and interobserver agreement. The Memorial Sloan Kettering Cancer Center model (odds ratio, 1.825; 95% confidence interval, 1.390-2.395; P<.001) and the modified diffusion-weighted magnetic resonance imaging-based model (odds ratio, 1.776; 95% confidence interval, 1.410-2.238; P<.001) independently predicted surgical resectability. The modified diffusion-weighted magnetic resonance imaging-based model demonstrated improved predictive performance with an area under the curve of 0.867 in the study cohort and 0.806 and 0.913 in the internal and external validation cohorts, respectively. Using the modified diffusion-weighted magnetic resonance imaging-based model, patients with scores of 0 to 2, 3 to 4, 5 to 6, 7 to 10, and ≥11 achieved complete tumor debulking rates of 90.3%, 66.7%, 53.3%, 11.8%, and 0%, respectively. Most patients with incomplete tumor debulking had infiltrative tumors, and both the Memorial Sloan Kettering Cancer Center and the modified diffusion-weighted magnetic resonance imaging-based models yielded higher scores. The molecular differences between the 2 morphologic subtypes were identified.

CONCLUSION

When compared with the Memorial Sloan Kettering Cancer Center model, the modified diffusion-weighted magnetic resonance imaging-based model demonstrated enhanced accuracy in the preoperative prediction of resectability for advanced high-grade serous ovarian cancer. Patients with scores of 0 to 6 were eligible for primary debulking surgery.

MUC1 promotes RIF by regulating macrophage ROS-SHP2 signaling pathway to up-regulate inflammatory response and inhibit angiogenesis

OBJECTIVE

To explore the effect of MUC1 on recurrent implantation failure (RIF) and its molecular mechanism.

METHODS

Bioinformation analysis was used to find possible molecular mechanisms of specific genes in the pathogenesis of RIF. The number of M1 and M2 macrophages was measured by flow cytometry. Immunohistochemical staining and western blotting were used to detect the expression of related proteins. Angiogenesis capacity was measured by cell tube-formation assay.

RESULTS

Bioinformatics analysis results suggest that MUC1 may play an important role in RIF. The results of flow cytometry showed that compared with NC group, M1 macrophages increased significantly and M2 macrophages decreased significantly in MUC1 OE group. The results of immunohistochemical staining showed that MUC1 could inhibit the expression of VEGF. Western blotting results showed that MUC1 could significantly increase the expression of P22, P47, gp91, p-TBK1, IFNγ and IL-1β, and decrease the expression of p-SHP2, p-PI3K, p-mTOR, HIF1α and VEGF. After the addition of ROS inhibitor and PI3K inhibitor, the effect of MUC1 on the above proteins was eliminated. The results of tube formation experiments showed that MUC1 could inhibit vascular formation.

CONCLUSION

As a promising biomarker for the diagnosis of RIF, MUC1 can promote RIF by regulating macrophage ROS-SHP2 signaling pathway to up-regulate inflammatory response and inhibit angiogenesis.

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.

MutSβ protects common fragile sites by facilitating homology-directed repair at DNA double-strand breaks with secondary structures

Common fragile sites (CFSs) are regions prone to chromosomal rearrangements, thereby contributing to tumorigenesis. Under replication stress (RS), CFSs often harbor under-replicated DNA regions at the onset of mitosis, triggering homology-directed repair known as mitotic DNA synthesis (MiDAS) to complete DNA replication. In this study, we identified an important role of DNA mismatch repair protein MutSβ (MSH2/MSH3) in facilitating MiDAS and maintaining CFS stability. Specifically, we demonstrated that MutSβ is required for the increased mitotic recombination induced by RS or FANCM loss at CFS-derived AT-rich and structure-prone sequences (CFS-ATs). We also found that MSH3 exhibits synthetic lethality with FANCM. Mechanistically, MutSβ is required for homologous recombination (HR) especially when DNA double-strand break (DSB) ends contain secondary structures. We also showed that upon RS, MutSβ is recruited to Flex1, a specific CFS-AT, in a PCNA-dependent but MUS81-independent manner. Furthermore, MutSβ interacts with RAD52 and promotes RAD52 recruitment to Flex1 following MUS81-dependent fork cleavage. RAD52, in turn, recruits XPF/ERCC1 to remove DNA secondary structures at DSB ends, enabling HR/break-induced replication (BIR) at CFS-ATs. We propose that the specific requirement of MutSβ in processing DNA secondary structures at CFS-ATs underlies its crucial role in promoting MiDAS and maintaining CFS integrity.

Prognostic model of ER-positive, HER2-negative breast cancer predicted by clinically relevant indicators

PURPOSE

To study the clinicopathological variables connected with disease-free survival (DFS) as well as overall survival (OS) in patients who are ER-positive or HER2-negative and to propose nomograms for predicting individual risk.

METHODS

In this investigation, we examined 585 (development cohort) and 291 (external validation) ER-positive, HER2-negative breast cancer patients from January 2010 to January 2014. From January 2010 to December 2014, we retrospectively reviewed and analyzed 291 (external validation) and 585 (development cohort) HER2-negative, ER-positive breast cancer patients. Cox regression analysis, both multivariate and univariate, confirmed the independence indicators for OS and DFS.

RESULTS

Using cox regression analysis, both multivariate and univariate, the following variables were combined to predict the DFS of development cohort: pathological stage (HR = 1.391; 95% CI = 1.043-1.855; P value = 0.025), luminal parting (HR = 1.836; 95% CI = 1.142-2.952; P value = .012), and clinical stage (HR = 1.879; 95% CI = 1.102-3.203; P value = 0.021). Endocrine therapy (HR = 3.655; 95% CI = 1.084-12.324; P value = 0.037) and clinical stage (HR = 6.792; 95% CI = 1.672-28.345; P value = 0.009) were chosen as predictors of OS. Furthermore, we generated RS-OS and RS-DFS. According to the findings of Kaplan-Meier curves, patients who are classified as having a low risk have considerably longer DFS and OS durations than patients who are classified as having a high risk.

CONCLUSION

To generate nomograms that predicted DFS and OS, independent predictors of DFS in ER-positive/HER2-negative breast cancer patients were chosen. The nomograms successfully stratified patients into prognostic categories and worked well in both internal validation and external validation.

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 frailty and related factors in middle-aged and elderly people in island and mountainous areas of Taizhou, Zhejiang Province]

Objective: To compare the prevalence of frailty and related factors in middle-aged and elderly people aged ≥45 years in island and mountainous areas of Taizhou, Zhejiang Province. Methods: Based on cross-sectional design, stratified cluster sampling and quota sampling methods were adopted. One administrative district was randomly selected from each of six coastal and three inland administrative districts in Taizhou during July to August, representing two different geographical terrains. In the island area (Jiaojiang District), all residents aged ≥45 years were included by cluster sampling. In the mountainous area (Xianju County), participants were selected through quota sampling, with same gender and age distributions. Data about their demographic characteristics, lifestyle and health-related factors were collected through questionnaire surveys and laboratory examinations. The prevalence of frailty was assessed using the Fried frailty phenotype scale. Hierarchical analysis and multivariate logistic regression analysis were used to compare the influencing factors of frailty. Results: A total of 1 011 local residents were studied, in whom island and mountainous residents accounted for 48.1% (486/1 011) and 51.9% (525/1 011) respectively; men and women accounted for 45.9% (464/1 011) and 54.1% (547/1 011) respectively. Middle-aged (45-49 years), younger elderly (60-74 years), and older elderly (≥75 years) residents accounted for 38.6% (390/1 011), 44.6% (451/1 011), and 16.8% (170/1 011) respectively. The overall prevalence rate of frailty was 3.6% (36/1 011), the prevalence rate was 3.7% (17/464) in men and 3.5% (19/547) in women. The prevalence rates in age groups 45-59,60-74 years and ≥75 years were 0.3% (1/390), 2.2% (10/451), and 14.7% (25/170), respectively. The prevalence rates of frailty and pre-frailty in island area were 6.0% (29/486) and 39.1% (190/486), respectively, which was higher than those in mountainous area (1.3%, 7/525) and (30.9%, 162/525). After adjusting for potential confounding factors, the risk for frailty in island residents was significantly higher than that in mountainous residents (aOR=1.55,95%CI: 1.07-2.25,P=0.019). In island area, older age (60-74 years:aOR=2.52,95%CI: 1.56-4.13; ≥75 years:aOR=11.65,95%CI:5.38-26.70), being women (aOR=1.94,95%CI: 1.20-3.17), suffering from depression (aOR=1.09,95%CI:1.02-1.17) were associated with frailty symptoms. In mountainous area, older age was also associated with an increased risk of frailty symptoms, but the OR value was lower than those in island area (60-74 years: aOR=1.74,95%CI:1.04-2.94;≥75 years: aOR=4.78,95%CI:2.45-9.50). Polydrug use (aOR=2.08,95%CI: 1.14-3.80) and suffering from depression (aOR=1.10,95%CI: 1.02-1.18) had significant positive association with frailty symptoms. Higher education level had significant negative association with frailty symptoms (junior high school: aOR=0.40,95%CI: 0.21-0.75; senior high school and technical secondary school: aOR=0.29,95%CI: 0.15-0.53; college or above:aOR=0.22,95%CI: 0.11-0.42). Conclusions: The prevalence of frailty in middle-aged and elderly community residents was significantly higher in island area than in mountainous area in Taizhou. The frailty-related factors varied with area. The elderly people (≥75 years) and women in island area had higher risk for frailty. Older age and suffering from depression were the independent risk factors for frailty. It is necessary to pay attention to the health risk factors and special environment in island area, and take comprehensive intervention measures to delay the process of debilitation and improve the quality of life of middle-aged and elderly people.

Bioactivity and genome analysis of Bacillus amyloliquefaciens GL18 isolated from the rhizosphere of Kobresia myosuroides in an alpine meadow

The unique eco-environment of the Qinghai-Tibet Plateau breeds abundant microbial resources. In this research, Bacillus amyloliquefaciens GL18, isolated from the rhizosphere of Kobresia myosuroides from an alpine meadow, and the antagonistic activity, bacteriostatic hydrolase activity, and low temperature, salt, and drought resistance of it were determined and analysed. The seedlings of Avena sativa were root-irrigated using bacteria suspensions (cell concentration 1 × 107 cfu/mL) of GL18, and the growth-promoting effect of GL18 on it was determined under cold, salt and drought stress, respectively. The whole genome of GL18 was sequenced, and its functional genes were analysed. GL18 presented significant antagonistic activity to Fusarium graminearum, Fusarium acuminatum, Fusarium oxysporum and Aspergillus niger (inhibition zone diameter > 17 mm). Transparent zones formed on four hydrolase detection media, indicating that GL18 secreted cellulase, protease, pectinase and β-1,3-glucanase. GL18 tolerated conditions of 10 °C, 11% NaCl and 15% PEG-6000, presenting cold, salt and drought resistance. GL18 improved the cold, salt and drought tolerance of A. sativa and it showed significant growth effects under different stress. The total length of the GL18 genome was 3,915,550 bp, and the number of coding DNA sequence was 3726. Compared with the clusters of orthologous groups of proteins, gene ontology and kyoto encyclopedia of genes and genomes databases, 3088, 2869 and 2357 functional genes were annotated, respectively. GL18 contained gene clusters related to antibacterial substances, functional genes related to the synthesis of plant growth-promoting substances, and encoding genes related to stress resistance. This study identified an excellent Bacillus strain and provided a theoretical basis for improving stress resistance and promoting the growth of herbages under abiotic stress.

Long-read transcriptome landscapes of primary and metastatic liver cancers at transcript resolution

BACKGROUND

The liver ranks as the sixth most prevalent site of primary cancer in humans, and it frequently experiences metastases from cancers originating in other organs. To facilitate the development of effective treatments and improve survival rates, it is crucial to comprehend the intricate and diverse transcriptome landscape of primary and metastatic liver cancers.

METHODS

We conducted long-read isoform sequencing and short-read RNA sequencing using a cohort of 95 patients with primary and secondary liver cancer who underwent hepatic resection. We compared the transcriptome landscapes of primary and metastatic liver cancers and systematically investigated hepatocellular carcinoma (HCC), paired primary tumours and liver metastases, and matched nontumour liver tissues.

RESULTS

We elucidated the full-length isoform-level transcriptome of primary and metastatic liver cancers in humans. Our analysis revealed isoform-level diversity in HCC and identified transcriptome variations associated with liver metastatis. Specific RNA transcripts and isoform switching events with clinical implications were profound in liver cancer. Moreover, we defined metastasis-specific transcripts that may serve as predictors of risk of metastasis. Additionally, we observed abnormalities in adjacent paracancerous liver tissues and characterized the immunological and metabolic alterations occurring in the liver.

CONCLUSIONS

Our findings underscore the power of full-length transcriptome profiling in providing novel biological insights into the molecular mechanisms underlying tumourigenesis. These insights will further contribute to improving treatment strategies for primary and metastatic liver cancers.

Real-Time Temperature Prediction of Power Devices Using an Improved Thermal Equivalent Circuit Model and Application in Power Electronics

As a core component of photovoltaic power generation systems, insulated gate bipolar transistor (IGBT) modules continually suffer from severe temperature swings due to complex operation conditions and various environmental conditions, resulting in fatigue failure. The junction temperature prediction guarantees that the IGBT module operates within the safety threshold. The thermal equivalent circuit model is a common approach to predicting junction temperature. However, the model parameters are easily affected by the solder aging. An accurate temperature prediction by the model is impossible during service. This paper proposes an improved thermal equivalent circuit model that can remove the effect of solder aging. Firstly, the solder aging process is monitored in real-time based on the case temperatures. Secondly, the model parameters are corrected by the thermal impedance from chip to baseplate based on the linear thermal characteristic. The simulation and experimental results show that the proposed model can reduce the temperature prediction error by more than 90% under the same aging condition. The proposed method only depends on the case temperatures to correct the model parameters, which is more economical. In addition, the experimental and simulation analysis in this work can help students of power electronics courses have an in-depth knowledge of power devices' mechanical structure, heat dissipation principles, temperature distribution, junction temperature monitoring, and so on.

Human HELQ regulates DNA end resection at DNA double-strand breaks and stalled replication forks

Following a DNA double strand break (DSB), several nucleases and helicases coordinate to generate single-stranded DNA (ssDNA) with 3' free ends, facilitating precise DNA repair by homologous recombination (HR). The same nucleases can act on stalled replication forks, promoting nascent DNA degradation and fork instability. Interestingly, some HR factors, such as CtIP and BRCA1, have opposite regulatory effects on the two processes, promoting end resection at DSB but inhibiting the degradation of nascent DNA on stalled forks. However, the reason why nuclease actions are regulated by different mechanisms in two DNA metabolism is poorly understood. We show that human HELQ acts as a DNA end resection regulator, with opposing activities on DNA end resection at DSBs and on stalled forks as seen for other regulators. Mechanistically, HELQ helicase activity is required for EXO1-mediated DSB end resection, while ssDNA-binding capacity of HELQ is required for its recruitment to stalled forks, facilitating fork protection and preventing chromosome aberrations caused by replication stress. Here, HELQ synergizes with CtIP but not BRCA1 or BRCA2 to protect stalled forks. These findings reveal an unanticipated role of HELQ in regulating DNA end resection at DSB and stalled forks, which is important for maintaining genome stability.

Efficacy and safety of zimberelimab (GLS-010) monotherapy in patients with recurrent or metastatic cervical cancer: a multicenter, single-arm, phase II study

OBJECTIVE

There is an unmet need to improve clinical outcomes for patients with recurrent/metastatic cervical cancer. Checkpoint inhibitors represent a promising treatment strategy. We evaluated the safety and anti-tumor activity of zimberelimab, an anti-programmed cell death protein-1 antibody, in patients with previously treated, recurrent, metastatic cervical cancer.

METHODS

This phase II, single-arm, open-label study used a Simon two-stage minimax design. Eligible patients were women aged 18-75 years with programmed death ligand-1-positive recurrent or metastatic cervical cancer that had progressed after first- or subsequent-line chemotherapy (Eastern Cooperative Oncology Group (ECOG) performance status 0-1). Patients received intravenous zimberelimab (240 mg every 2 weeks) for 2 years until disease progression, intolerable adverse effects, or withdrawal from the study. The primary endpoint was objective response rate assessed per Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1, by an independent review committee.

RESULTS

A total of 105 patients were enrolled. Median age was 51 (range, 31-75) years; 63.8% had an ECOG performance status of 1. The median number of previous treatment lines was 1 (range, 1-4). Median follow-up was 16.9 (range, 16.3-18.4) months. The objective response rate was 27.6%, and the disease control rate was 55.2%. Median duration of response was not reached. Median overall survival was 16.8 months, and median progression-free survival was 3.7 months. The incidence of treatment-related adverse events of any grade was 78.1%, of which the most common were hypothyroidism (26.7%) and anemia (19.0%).

CONCLUSION

Zimberelimab monotherapy demonstrated durable anti-tumor activity and an acceptable safety profile in patients with cervical cancer.

CLINICAL TRIAL REGISTRATION

NCT03972722.

Effects of MFG-E8 expression on the biological characteristics of ovarian cancer cells via the AKT/mTOR/S6K signalling pathway

In this study, we assessed the effects of MFG-E8 on the biological characteristics of ovarian cancer cells and explored the underlying mechanisms. Human ovarian cancer SKOV3 cells were transfected with MFG-E8 siRNA or NC siRNA. CCK-8, cell adhesion, scratch-wound, and Transwell assays were used to detect changes in cell metastatic processes. Effects of MFG-E8 silencing on the proteins involved in AKT/mTOR/S6K signalling pathway were assessed using qRT-PCR and Western blotting. Transient silencing of MFG-E8 in SKOV3 cells decreased cell proliferation and downregulated the expression of CDK4, cyclin D1, and caspase-3 proteins. Cell adhesion, migration, and invasion were also suppressed. p-AKT, p-mTORC1, and p-p70S6K levels decreased following MFG-E8 knockdown. Hence, MFG-E8 enhances carcinogenesis and affects the AKT/mTOR/S6K signalling pathway in ovarian cancer cells. In conclusion, our results suggested that MFG-E8 could promote ovarian cancer via AKT/mTOR/S6K signalling pathway which improved our understanding of the molecular mechanisms involved in ovarian cancer.IMPACT STATEMENTWhat is already known on this subject? Milk fat globule-epidermal growth factor 8 (MFG-E8) is expressed in several types of cancers such as oesophageal, breast, and liver. However, the mechanism of MFG-E8 involving in EOC remains unknown. We previously found that MFG-E8 expression was related to pathological staging, tissue differentiation, platinum sensitivity, ascites state, and other clinicopathological characteristics.What the results of this study add? Due to a series of in vitro studies, we confirmed that MFG-E8 is involved in the process of proliferation, invasion and metastasis. Our results show that silencing MFG-E8 can significantly inhibit the expression of cyclin D1 and CDK4 in EOC SKOV3 cells. MFG-E8 enhances carcinogenesis and affects the AKT/mTOR/S6K signaling pathway in ovarian cancer.What the implications are of these findings for clinical practice and/or further research? Taken together, our findings suggest that MFG-E8 may be an oncogene in EOC and provide new insights into the mechanism of MFG-E8 in the progression of EOC.

Predicting Lymph Node Metastasis From Primary Cervical Squamous Cell Carcinoma Based on Deep Learning in Histopathologic Images

We developed a deep learning framework to accurately predict the lymph node status of patients with cervical cancer based on hematoxylin and eosin-stained pathological sections of the primary tumor. In total, 1524 hematoxylin and eosin-stained whole slide images (WSIs) of primary cervical tumors from 564 patients were used in this retrospective, proof-of-concept study. Primary tumor sections (1161 WSIs) were obtained from 405 patients who underwent radical cervical cancer surgery at the Fudan University Shanghai Cancer Center (FUSCC) between 2008 and 2014; 165 and 240 patients were negative and positive for lymph node metastasis, respectively (including 166 with positive pelvic lymph nodes alone and 74 with positive pelvic and para-aortic lymph nodes). We constructed and trained a multi-instance deep convolutional neural network based on a multiscale attention mechanism, in which an internal independent test set (100 patients, 228 WSIs) from the FUSCC cohort and an external independent test set (159 patients, 363 WSIs) from the Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma cohort of the Cancer Genome Atlas program database were used to evaluate the predictive performance of the network. In predicting the occurrence of lymph node metastasis, our network achieved areas under the receiver operating characteristic curve of 0.87 in the cross-validation set, 0.84 in the internal independent test set of the FUSCC cohort, and 0.75 in the external test set of the Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma cohort of the Cancer Genome Atlas program. For patients with positive pelvic lymph node metastases, we retrained the network to predict whether they also had para-aortic lymph node metastases. Our network achieved areas under the receiver operating characteristic curve of 0.91 in the cross-validation set and 0.88 in the test set of the FUSCC cohort. Deep learning analysis based on pathological images of primary foci is very likely to provide new ideas for preoperatively assessing cervical cancer lymph node status; its true value must be validated with cervical biopsy specimens and large multicenter datasets.

Identifying tumor markers-stratified subtypes (CA-125/CA19-9/carcinoembryonic antigen) in cervical adenocarcinoma

OBJECTIVE

There is a lack of research evaluating the effect of tumor markers for prognosis in cervical adenocarcinoma. We aimed to develop and validate a preoperative tumor-marker-based model including clinicopathological factors to clarify the prognostic value of endocervical adenocarcinoma.

METHODS

A total of 572 patients with cervical adenocarcinoma who were staged at the International Federation of Gynecology and Obstetrics (FIGO) IA-IIA were reviewed retrospectively. Preoperative serum carcinoembryonic antigen (CEA), carbohydrate antigen (CA)-125 and CA19-9 levels were measured. The survival and recurrence patterns were analyzed according to the tumor-marker-related stratification. The predictive values of biomarkers and clinical variables were assessed with Cox regression and competing risk models.

RESULTS

Patients with elevated preoperative tumor markers had evidently poor overall survival and recurrence-free survival. The triple-elevated tumor marker (TETM) subgroup had the worst overall survival and progression-free survival than the triple-negative tumor marker (TNTM) subgroup and the single-elevated tumor marker (SETM) subgroup. The most important predictors for overall survival were elevated tumor markers, FIGO-stage, tumor differentiation, lymphovascular space invasion (LVSI) and lymph nodes metastasis. The most important predictors for recurrence-free survival were elevated tumor markers, FIGO-stage, tumor differentiation, LVSI and deep stromal invasion. Stratified analysis showed that elevated CA-125 and CA19-9 were significantly associated with postoperative distant metastasis. A decision curve analysis confirmed that a combination of tumor markers as predictors significantly outperformed the other common predictors used (FIGO-stage, intermediate and high-risk factors, tumor differentiation, lymph nodes).

CONCLUSIONS

Elevated preoperative serum CEA, CA-125, and CA19-9 levels exhibited poor overall survival and recurrence-free survival in cervical adenocarcinoma patients. Combined preoperative serum CA-125 and CA19-9 independently predicted distant metastasis in patients with endocervical adenocarcinoma.

Durvalumab versus placebo with chemoradiotherapy for locally advanced cervical cancer (CALLA): a randomised, double-blind, phase 3 trial

BACKGROUND

Concurrent chemoradiotherapy has been the standard of care for locally advanced cervical cancer for over 20 years; however, 30-40% of treated patients have recurrence or progression within 5 years. Immune checkpoint inhibition has improved outcomes for patients with PD-L1 positive metastatic or recurrent cervical cancer. We assessed the benefit of adding durvalumab, a PD-L1 antibody, with and following chemoradiotherapy for locally advanced cervical cancer.

METHODS

The CALLA randomised, double-blind, phase 3 trial included 105 hospitals across 15 countries. Patients aged at least 18 years with previously untreated locally advanced cervical cancer (adenocarcinoma, squamous, or adenosquamous; International Federation of Gynaecology and Obstetrics [FIGO] 2009 stage IB2-IIB lymph node positive, stage ≥III any lymph node status) and WHO or Eastern Cooperative Oncology Group performance status of 0 or 1 were randomly assigned (1:1) through an interactive web response system using a permuted block size of 4 to receive durvalumab (1500 mg intravenously once every 4 weeks) or placebo with and following chemoradiotherapy, for up to 24 cycles. Chemoradiotherapy included 45 Gy external beam radiotherapy at 5 fractions per week concurrent with intravenous cisplatin (40 mg/m2) or carboplatin (area under the concentration-time curve 2) once weekly for 5 weeks, followed by image-guided brachytherapy (high-dose rate, 27·5-30 Gy or low-dose/pulse-dose rate, 35-40 Gy). Randomisation was stratified by disease stage status (FIGO stage and node status) and geographical region. Chemoradiotherapy quality was continuously reviewed. The primary endpoint was progression-free survival, assessed by the investigator using Response Evaluation Criteria in Solid Tumors, version 1.1, in the intention-to-treat population. Safety was assessed in patients who received at least one dose of study treatment. This study is registered with ClinicalTrials.gov, NCT03830866.

FINDINGS

Between Feb 15, 2019, and Dec 10, 2020, 770 women were randomly assigned (385 to durvalumab and 385 to placebo; median age 49 years [IQR 41-57]). Median follow-up was 18·5 months (IQR 13·2-21·5) in the durvalumab group and 18·4 months (13·2-23·7) in the placebo group. At data cutoff, median progression-free survival had not been reached (95% CI not reached-not reached) for either group (HR 0·84; 95% CI 0·65-1·08; p=0·17); 12-month progression-free survival was 76·0% (71·3-80·0) with durvalumab and 73·3% (68·4-77·5) with placebo. The most frequently reported grade 3-4 adverse events in both groups were anaemia (76 [20%] of 385 in the durvalumab group vs 56 [15%] of 384 in the placebo group) and decreased white blood cells (39 [10%] vs 49 [13%]). Serious adverse events occurred for 106 (28%) patients who received durvalumab and 89 (23%) patients who received placebo. There were five treatment-related deaths in the durvalumab group (one case each of urinary tract infection, blood loss anaemia, and pulmonary embolism related to chemoradiotherapy only; one case of endocrine disorder related to durvalumab only; and one case of sepsis related to both durvalumab and chemoradiotherapy). There was one treatment-related death in the placebo group (pneumonia related to chemoradiotherapy).

INTERPRETATION

Durvalumab concurrent with chemoradiotherapy was well tolerated in participants with locally advanced cervical cancer, however it did not significantly improve progression-free survival in a biomarker unselected, all-comers population. Concurrent durvalumab plus chemoradiotherapy warrants further exploration in patients with high tumoral PD-L1 expression. Rigorous monitoring ensured high chemoradiotherapy compliance with advanced technology and allowed patients to receive optimal care.

FUNDING

AstraZeneca.

The Therapeutic Monoclonal Antibody Bamlanivimab Does Not Enhance SARS-CoV-2 Infection by FcR-Mediated Mechanisms

As part of the non-clinical safety package characterizing bamlanivimab (SARS-CoV-2 neutralizing monoclonal antibody), the risk profile for antibody-dependent enhancement of infection (ADE) was evaluated in vitro and in an African green monkey (AGM) model of COVID-19. In vitro ADE assays in primary human macrophage, Raji, or THP-1 cells were used to evaluate enhancement of viral infection. Bamlanivimab binding to C1q, FcR, and cell-based effector activity was also assessed. In AGMs, the impact of bamlanivimab pretreatment on viral loads and clinical and histological pathology was assessed to evaluate enhanced SARS-CoV-2 replication or pathology. Bamlanivimab did not increase viral replication in vitro, despite a demonstrated effector function. In vivo, no significant differences were found among the AGM groups for weight, temperature, or food intake. Treatment with bamlanivimab reduced viral loads in nasal and oral swabs and BAL fluid relative to control groups. Viral antigen was not detected in lung tissue from animals treated with the highest dose of bamlanivimab. Bamlanivimab did not induce ADE of SARS-CoV-2 infection in vitro or in an AGM model of infection at any dose evaluated. The findings suggest that high-affinity monoclonal antibodies pose a low risk of mediating ADE in patients and support their safety profile as a treatment of COVID-19 disease.

p53-responsive CMBL reprograms glucose metabolism and suppresses cancer development by destabilizing phosphofructokinase PFKP

Aerobic glycolysis is critical for cancer progression and can be exploited in cancer therapy. Here, we report that the human carboxymethylenebutenolidase homolog (carboxymethylenebutenolidase-like [CMBL]) acts as a tumor suppressor by reprogramming glycolysis in colorectal cancer (CRC). The anti-cancer action of CMBL is mediated through its interactions with the E3 ubiquitin ligase TRIM25 and the glycolytic enzyme phosphofructokinase-1 platelet type (PFKP). Ectopic CMBL enhances TRIM25 binding to PFKP, leading to the ubiquitination and proteasomal degradation of PFKP. Interestingly, CMBL is transcriptionally activated by p53 in response to genotoxic stress, and p53 activation represses glycolysis by promoting PFKP degradation. Remarkably, CMBL deficiency, which impairs p53's ability to inhibit glycolysis, makes tumors more sensitive to a combination therapy involving the glycolysis inhibitor 2-deoxyglucose. Taken together, our study demonstrates that CMBL suppresses CRC growth by inhibiting glycolysis and suggests a potential combination strategy for the treatment of CMBL-deficient CRC.

Comparison of SARIMA model, Holt-winters model and ETS model in predicting the incidence of foodborne disease

BACKGROUND

According to the World Health Organization, foodborne disease is a significant public health issue. We will choose the best model to predict foodborne disease by comparison, to provide evidence for government policies to prevent foodborne illness.

METHODS

The foodborne disease monthly incidence data from June 2017 to April 2022 were obtained from the Chongqing Nan'an District Center for Disease Prevention and Control. Data from June 2017 to June 2021 were used to train the model, and the last 10 months of incidence were used for prediction and validation The incidence was fitted using the seasonal autoregressive integrated moving average (SARIMA) model, Holt-Winters model and Exponential Smoothing (ETS) model. Besides, we used MSE, MAE, RMSE to determine which model fits better.

RESULTS

During June 2017 to April 2022, the incidence of foodborne disease showed seasonal changes, the months with the highest incidence are June to November. The optimal model of SARIMA is SARIMA (1,0,0) (1,1,0)12. The MSE, MAE, RMSE of the Holt-Winters model are 8.78, 2.33 and 2.96 respectively, which less than those of the SARIMA and ETS model, and its prediction curve is closer to the true value. The optimal model has good predictive performance.

CONCLUSION

Based on the results, Holt-Winters model produces better prediction accuracy of the model.

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.

Active Thermal Control of IGBT Modules Based on Finite-Time Boundedness

One of the most important causes of the failure of power electronic modules is thermal stress. Proper thermal management plays an important role in more reliable and cost-effective energy conversion. In this paper, we present an advanced active thermal control (ATC) strategy to reduce a power device's thermal stress amplitude during operation, with the aim of improving the reliability and lifetime of the conversion system. A state-space model based on a Foster-type thermal model is developed to achieve junction temperature estimation in real time. A feedback controller based on finite-time boundedness (FTB) is proposed to precisely regulate the temperature in order to reduce the thermal stress according to the temperature profile. The designed controller permits the precise control of the temperature and strongly reduces the thermal stress during fast transients in the power demand. Simulation and experimental results are provided to validate the effectiveness of the proposed method.

hsa_circ_0005991 promotes epithelial-mesenchymal transition by regulating miR-30b-3p/Cdc42EP1 axis in ovary endometriosis

Endometriosis is a common gynecological disease with an enigmatic pathogenesis. This work explored the function of hsa_circ_0005991 in ovarian endometriosis. High-throughput RNA-Seq was conducted in five matched ectopic (EC) and eutopic (EU) samples. Further, several types of cell function experiments were conducted. According to bioinformatics analysis, a competing endogenous RNA network was established. It included 5 circRNAs, 13 miRNAs, and 551 mRNAs. The expression levels of hsa_circ_0005991 and Cdc42EP1 were significantly elevated, while miR-30b-3p was reduced in the EC group. Upregulation of hsa_circ_0005991 raised Cdc42EP1 levels, induced EMT, and boosted Ishikawa cell proliferation, migration, and invasion. hsa_circ_0005991 knockdown indicated the opposite effects. When co-transfected with miR-30b-3p mimics or inhibitors, these effects could be reversed, respectively. Western blot assays showed alterations of EMT markers in EC samples. hsa_circ_0005991/miR-30b-3p/Cdc42EP1 axis promotes the EMT process in endometriosis, which may offer a theoretical foundation for the mechanism exploration and therapy of this disease.

KLF5 Promotes Tumor Progression and Parp Inhibitor Resistance in Ovarian Cancer

One major characteristic of tumor cells is the aberrant activation of epigenetic regulatory elements, which remodel the tumor transcriptome and ultimately promote cancer progression and drug resistance. However, the oncogenic functions and mechanisms of ovarian cancer (OC) remain elusive. Here, super-enhancer (SE) regulatory elements that are aberrantly activated in OC are identified and it is found that SEs drive the relative specific expression of the transcription factor KLF5 in OC patients and poly(ADP-ribose) polymerase inhibitor (PARPi)-resistant patients. KLF5 expression is associated with poor outcomes in OC patients and can drive tumor progression in vitro and in vivo. Mechanistically, KLF5 forms a transcriptional complex with EHF and ELF3 and binds to the promoter region of RAD51 to enhance its transcription, strengthening the homologous recombination repair (HRR) pathway. Notably, the combination of suberoylanilide hydroxamic acid (SAHA) and olaparib significantly inhibits tumor growth and metastasis of PARPi-resistant OC cells with high KLF5. In conclusion, it is discovered that SEs-driven KLF5 is a key regulatory factor in OC progression and PARPi resistance; and potential therapeutic strategies for OC patients with PARPi resistance and high KLF5 are identified.

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.

Design of dynamic ski motion capture and human posture detection model based on spatio-temporal Transformer and wireless device tracking technology

As a result of significant advancements in living conditions, individuals have redirected their attention towards physical exercise. Skiing, as a widely popular sport, necessitates the real-time maintenance of correct posture during movement. Therefore, we present a dynamic skiing motion capture and human posture detection model that leverages wireless device tracking. Primarily, personnel tracking is enabled through the construction of service base stations and the utilization of wireless device tracking technology. Subsequently, a human posture detection model is formulated in the form of human posture key points, employing the image information of each frame obtained via wireless devices. Finally, we introduce a spatio-temporal Transformer structure that facilitates the detection and recognition of human posture in consecutive frames. Our results demonstrate that our approach can precisely locate and track the position of skiing personnel. Compared to the latest Blip and Conformer methods, our technique yields F values that surpass them by 1.20% and 4.51%, respectively. Moreover, our model can achieve convergent model parameters and accomplish training objectives more efficiently, thus enabling posture detection and dynamic capture of skiing personnel via image and video information.

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.

Multi-level perception fusion dehazing network

Image dehazing models are critical in improving the recognition and classification capabilities of image-related artificial intelligence systems. However, existing methods often ignore the limitations of receptive field size during feature extraction and the loss of important information during network sampling, resulting in incomplete or structurally flawed dehazing outcomes. To address these challenges, we propose a multi-level perception fusion dehazing network (MPFDN) that effectively integrates feature information across different scales, expands the perceptual field of the network, and fully extracts the spatial background information of the image. Moreover, we employ an error feedback mechanism and a feature compensator to address the loss of features during the image dehazing process. Finally, we subtract the original hazy image from the generated residual image to obtain a high-quality dehazed image. Based on extensive experimentation, our proposed method has demonstrated outstanding performance not only on synthesizing dehazing datasets, but also on non-homogeneous haze datasets.

Safety and antitumour activity of cadonilimab, an anti-PD-1/CTLA-4 bispecific antibody, for patients with advanced solid tumours (COMPASSION-03): a multicentre, open-label, phase 1b/2 trial

BACKGROUND

Immune checkpoint inhibitors targeting PD-1 or CTLA-4 individually have shown substantial clinical benefits in the treatment of malignancies. We aimed to assess the safety and antitumour activity of cadonilimab monotherapy, a bispecific PD-1/CTLA-4 antibody, in patients with advanced solid tumours.

METHODS

This multicentre, open-label, phase 1b/2 trial was conducted across 30 hospitals in China. Patients aged 18 years or older with histologically or cytologically confirmed, unresectable advanced solid tumours, unsuccessful completion of at least one previous systemic therapy, and an Eastern Cooperative Oncology Group performance status of 0 or 1 were eligible for inclusion. Patients who had previously received anti-PD-1, anti-PD-L1, or anti-CTLA-4 treatment were not eligible for inclusion. In the dose escalation phase of phase 1b, patients received intravenous cadonilimab at 6 mg/kg and 10 mg/kg every 2 weeks. In the dose expansion phase of phase 1b, cadonilimab at 6 mg/kg and a fixed dose of 450 mg were given intravenously every 2 weeks. In phase 2, cadonilimab at 6 mg/kg was administered intravenously every 2 weeks in three cohorts: patients with cervical cancer, oesophageal squamous cell carcinoma, and hepatocellular carcinoma. The primary endpoints were the safety of cadonilimab in phase 1b and objective response rate in phase 2, based on the Response Evaluation Criteria in Solid Tumors (RECIST), version 1.1. The safety analysis was done in all patients who received at least one dose of cadonilimab. Antitumour activity was assessed in the full analysis set for the cervical cancer cohort, and in all patients with measurable disease at baseline and who received at least one dose of cadonilimab in the oesophageal squamous cell carcinoma and hepatocellular carcinoma cohorts. The study is registered on ClinicalTrial.gov, NCT03852251, and closed to new participants; follow-up has been completed.

FINDINGS

Between Jan 18, 2019, and Jan 8, 2021, 240 patients (83 [43 male and 40 female] in phase 1b and 157 in phase 2) were enrolled. Phase 2 enrolled 111 female patients with cervical cancer, 22 patients with oesophageal squamous cell carcinoma (15 male and seven female), and 24 patients with hepatocellular carcinoma (17 male and seven female). During dose escalation, no dose-limiting toxicities occurred. Grade 3-4 treatment-related adverse events occurred in 67 (28%) of 240 patients; the most frequent grade 3 or worse treatment-related adverse events were anaemia (seven [3%]), increased lipase (four [2%]), decreased bodyweight (three [1%]), decreased appetite (four [2%]), decreased neutrophil count (three [1%]), and infusion-related reaction (two [1%]). 17 (7%) patients discontinued treatment due to treatment-related adverse events. 54 (23%) of 240 patients reported serious treatment-related adverse events, including five patients who died (one due to myocardial infarction; cause unknown for four). In phase 2, in the cervical cancer cohort, with a median follow-up of 14·6 months (IQR 13·1-17·5), the objective response rate was 32·3% (32 of 99; 95% CI 23·3-42·5). In the oesophageal squamous cell carcinoma cohort, with a median follow-up of 17·9 months (IQR 4·0-15·1), the objective response rate was 18·2% (four of 22; 95% CI 5·2-40·3). In the hepatocellular carcinoma cohort, with a median follow-up of 19·6 months (IQR 8·7-19·8), the objective response rate was 16·7% (four of 24; 95% CI 4·7-37·4).

INTERPRETATION

Cadonilimab showed an encouraging tumour response rate, with a manageable safety profile, suggesting the potential of cadonilimab for the treatment of advanced solid tumours.

FUNDING

Akeso Biopharma.

TRANSLATION

For the Chinese translation of the abstract see Supplementary Materials section.