The effect of nitrogen input on N2O emission depends on precipitation in a temperate desert steppe

Nitrous oxide (N2O) is the third most important greenhouse gas, and can damage the atmospheric ozone layer, with associated threats to terrestrial ecosystems. However, to date it is unclear how extreme precipitation and nitrogen (N) input will affect N2O emissions in temperate desert steppe ecosystems. Therefore, we conducted an in-situ in a temperate desert steppe in the northwest of Inner Mongolia, China between 2018 and 2021, in which N inputs were combined with natural extreme precipitation events, with the aim of better understanding the mechanism of any interactive effects on N2O emission. The study result showed that N2O emission in this desert steppe was relatively small and did not show significant seasonal change. The annual N2O emission increased in a non-linear trend with increasing N input, with a much greater effect of N input in a wet year (2019) than in a dry year (2021). This was mainly due to the fact that the boost effect of high N input (on June 17th 2019) on N2O emission was greatly amplified by nearly 17-46 times by an extreme precipitation event on June 24th 2019. In contrast, this greatly promoting effect of high N input on N2O emission was not observed on September 26th 2019 by a similar extreme precipitation event. Further analysis showed that soil NH4+-N content and the abundance of ammonia oxidizing bacteria (amoA (AOB)) were the most critical factors affecting N2O emission. Soil moisture played an important indirect role in regulating N2O emission, mainly by influencing the abundance of amoA (AOB) and de-nitrification functional microorganisms (nosZ gene). In conclusion, the effect of extreme precipitation events on N2O emission was greatly increased by high N input. Furthermore, in this desert steppe, annual N2O flux is co-managed through soil nitrification substrate concentration (NH4+-N), the abundance of soil N transformation functional microorganisms and soil moisture. Overall, it was worth noting that an increase in extreme precipitation coupled with increasing N input may significantly increase future N2O emissions from desert steppes.

[Epidemiological investigation of iron deficiency among preschool children in 10 provinces, autonomous regions, or municipalities in China]

Objective: To understand the current status of anemia, iron deficiency, and iron-deficiency anemia among preschool children in China. Methods: A cross-sectional study was conducted with a multi-stage stratified sampling method to select 150 streets or townships from 10 Chinese provinces, autonomous regions, or municipalities (East: Jiangsu, Zhejiang, Shandong, and Hainan; Central: Henan; West: Chongqing, Shaanxi, Guizhou, and Xinjiang; Northeast: Liaoning). From May 2022 to April 2023, a total of 21 470 children, including community-based children aged 0.5 to<3.0 years receiving child health care and kindergarten-based children aged 3.0 to<7.0 years, were surveyed. They were divided into 3 age groups: infants (0.5 to<1.0 year), toddlers (1.0 to<3.0 years), and preschoolers (3.0 to<7.0 years). Basic information such as sex and date of birth of the children was collected, and peripheral blood samples were obtained for routine blood tests and serum ferritin measurement. The prevalence rates of anemia, iron deficiency, and iron-deficiency anemia were analyzed, and the prevalence rate differences were compared among different ages, sex, urban and rural areas, and regions using the chi-square test. Results: A total of 21 460 valid responses were collected, including 10 780 boys (50.2%). The number of infants, toddlers, and preschoolers were 2 645 (12.3%), 6 244 (29.1%), and 12 571 (58.6%), respectively. The hemoglobin level was (126.7±14.8) g/L, and the serum ferritin level was 32.3 (18.5, 50.1) μg/L. The overall rates of anemia, iron deficiency, and iron-deficiency anemia were 10.4% (2 230/21 460), 28.3% (6 070/21 460), and 3.9% (845/21 460), respectively. The prevalence rate of anemia was higher for boys than for girls (10.9% (1 173/10 780) vs. 9.9% (1 057/10 680), χ2=5.58, P=0.018), with statistically significant differences in the rates for infants, toddlers and preschoolers (18.0% (475/2 645), 10.6% (662/6 244), and 8.7% (1 093/12 571), respectively, χ2=201.81, P<0.01), and the rate was significantly higher for children in rural than that in urban area (11.8% (1 516/12 883) vs. 8.3% (714/8 577), χ2=65.54, P<0.01), with statistically significant differences in the rates by region (χ2=126.60, P<0.01), with the highest rate of 15.8% (343/2 173) for children in Central region, and the lowest rate of 5.3% (108/2 053) in Northeastern region. The prevalence rates of iron deficiency were 33.8% (895/2 645), 32.2% (2 011/6 244), and 25.2% (3 164/12 571) in infants, toddlers, and preschoolers, respectively, and 30.0% (3 229/10 780) in boys vs. 26.6% (2 841/10 680) in girls, 21.7% (1 913/8 821), 40.0% (870/2 173), 27.1% (2 283/8 413), 48.9% (1 004/2 053) in Eastern, Central, Western, and Northeastern regions, respectively, and each between-group showed a significant statistical difference (χ2=147.71, 29.73, 773.02, all P<0.01). The prevalence rate of iron-deficiency anemia showed a significant statistical difference between urban and rural areas, 2.9% (251/8 577) vs. 4.6% (594/12 883) (χ2=38.62, P<0.01), while the difference in iron deficiency prevalence was not significant (χ2=0.51, P=0.476). Conclusions: There has been a notable improvement in iron deficiency and iron-deficiency anemia among preschool children in China, but the situation remains concerning. Particular attention should be paid to the prevention and control of iron deficiency and iron-deficiency anemia, especially among infants and children in the Central, Western, and Northeastern regions of China.

Feasibility of whole-exome sequencing in fine-needle aspiration specimens of papillary thyroid microcarcinoma for the identification of novel gene mutations

Genetic profiling is important for assisting the management of papillary thyroid microcarcinoma (PTMC). Although whole-exome sequencing (WES) of surgically resected PTMC tissue has been performed and revealed potential prognostic biomarkers, its application in PTMC fine-needle aspiration (FNA) specimens has not been explored. This study aimed to evaluate the feasibility of WES using FNA specimens of PTMC. Five PTMC patients were enrolled with clinical characteristics gathered. Fine aspiration cytology needle (23 gauges) was used to collect FNA biopsy with ultrasound guidance. WES analysis of FNA specimens from five PTMC patients and matched blood samples was performed. The WES of FNA samples yielded an average sequencing depth of 281× and average coverage of 99.5%. We identified 534 somatic single-nucleotide variants and 13 indels in total, and per sample, we found a mean of 24 exonic mutations, which affected a total of 120 genes. In the PTMC FNA samples, the most frequently mutated genes were BRAF and ANKRD18B, and the four driver genes were BRAF, AFF3, SRCAP, and EGFR. We also identified several germline cancer predisposing gene mutations. The results suggest that WES of FNA specimens is feasible for PTMC and can identify novel genetic mutations.

A validation of register-derived diagnoses of interstitial lung disease in patients with inflammatory arthritis: data from the NOR-DMARD study

OBJECTIVE

There is a lack of knowledge concerning the validity of the interstitial lung disease (ILD) diagnoses used in epidemiological studies on rheumatic diseases. This paper seeks to verify register-derived ILD diagnoses using chest computed tomography (CT) and medical records as a gold standard.

METHOD

The Norwegian Anti-Rheumatic Drug Register (NOR-DMARD) is a multicentre prospective observational study of patients with inflammatory arthritis who start treatment with disease-modifying anti-rheumatic drugs. NOR-DMARD is linked to the Norwegian Patient Registry (NPR) and Cause of Death Registry. We searched registers for ILD coded by ICD-10 J84 or J99 among patients with rheumatoid arthritis, psoriatic arthritis, or spondyloarthritis. We extracted chest CT reports and medical records from participating hospitals. Two expert thoracic radiologists scored examinations to confirm the ILD diagnosis. We also searched medical records to find justifications for the diagnosis following multidisciplinary evaluations. We calculated the positive predictive values (PPVs) for ILD across subsets.

RESULTS

We identified 71 cases with an ILD diagnosis. CT examinations were available in 65/71 patients (91.5%), of whom ILD was confirmed on CT in 29/65 (44.6%). In a further 10 patients, medical records confirmed the diagnosis, giving a total of 39/71 verified cases. The PPV of a register-derived ILD diagnosis was thus 54.9%. In a subset of patients who had received an ILD code at two or more time-points and had a CT scan taken within a relevant period, the PPV was 72.2%.

CONCLUSION

The validity of register-based diagnoses of ILD must be carefully considered in epidemiological studies.

Claudin 18.2 expression in digestive neuroendocrine neoplasms: a clinicopathological study

BACKGROUND

Claudin 18.2-targeted therapy has shown significant efficacy in treating claudin 18.2-positive cancers. However, limited systematic studies have investigated characteristics of claudin 18.2 expression in neuroendocrine neoplasms (NENs).

METHODS

Data and specimens from 403 cases of digestive NENs were retrospectively collected, and claudin 18.2 expression was detected using immunochemical staining.

RESULTS

Claudin 18.2 was positive in 19.6% (79/403) of the digestive NENs. The highest positive rate of claudin 18.2 was observed in gastric NENs (72/259, 27.8%), accounting for 91.1% (72/79) of all positive cases. The positivity rate was significantly higher in gastric NENs compared to pancreatic (2/78, 2.6%) or colorectal NENs (2/38, 5.3%; p < 0.05). For digestive NENs, claudin 18.2 positivity was significantly higher in neuroendocrine carcinomas (NECs) (37/144, 25.7%) than in neuroendocrine tumours (NETs; 14/160, 8.8%; p < 0.001), but no significant difference was found between gastric NECs (59/213, 27.7%) and gastric NETs (13/46, 28.3%; p > 0.05). The positivity was significantly higher in large-cell NECs (LCNECs; 28/79, 35.4%) and MiNEN (mixed neuroendocrine-non- neuroendocrine neoplasms)-LCNECs (23/66, 34.8%) compared to small-cell NECs (SCNECs; 9/65, 13.8%) and MiNEN-SCNECs (5/33, 15.2%; p < 0.05). Claudin 18.2 expression was more prevalent in gastric NENs than in pancreatic (12.5 ×; p = 0.001) and colorectal NENs (5.9 ×; p = 0.021). Claudin 18.2 staining was a useful method for identify the gastric origins of NETs, with a sensitivity of 28.3% and a specificity of 99.1%.

CONCLUSION

The expression characteristics of claudin 18.2 in NENs were characterized, which may provide a clinicopathological reference for targeted therapies in patients with NENs.

Characterisation of the mitochondrial genome and phylogenetic analysis of Toxocara apodemi (Nematoda: Ascarididae)

We first sequenced and characterised the complete mitochondrial genome of Toxocara apodeme, then studied the evolutionary relationship of the species within Toxocaridae. The complete mitochondrial genome was amplified using PCR with 14 specific primers. The mitogenome length was 14303 bp in size, including 12 PCGs (encoding 3,423 amino acids), 22 tRNAs, 2 rRNAs, and 2 NCRs, with 68.38% A+T contents. The mt genomes of T. apodemi had relatively compact structures with 11 intergenic spacers and 5 overlaps. Comparative analyses of the nucleotide sequences of complete mt genomes showed that T. apodemi had higher identities with T. canis than other congeners. A sliding window analysis of 12 PCGs among 5 Toxocara species indicated that nad4 had the highest sequence divergence, and cox1 was the least variable gene. Relative synonymous codon usage showed that UUG, ACU, CCU, CGU, and UCU most frequently occurred in the complete genomes of T. apodemi. The Ka/Ks ratio showed that all Toxocara mt genes were subject to purification selection. The largest genetic distance between T. apodemi and the other 4 congeneric species was found in nad2, and the smallest was found in cox2. Phylogenetic analyses based on the concatenated amino acid sequences of 12 PCGs demonstrated that T. apodemi formed a distinct branch and was always a sister taxon to other congeneric species. The present study determined the complete mt genome sequences of T. apodemi, which provide novel genetic markers for further studies of the taxonomy, population genetics, and systematics of the Toxocaridae nematodes.

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.

Menopausal age and cardiovascular disease risk in American women: evidence from the National Health and Nutrition Examination Survey

OBJECTIVE

Cardiovascular disease (CVD) is a significant contributor to the deaths of females, and premature menopause adds to the risk of CVD in females. Therefore, our study aimed to investigate the age of menopause and CVD incidence in American females using data from the National Health and Nutrition Examination Survey (NHANES).

METHOD

We analyzed data from 6347 females to investigate the association between menopausal age and the risk of CVD using multivariate logistic regression analysis.

RESULTS

The study found that a later menopausal age reduces the risk of developing CVD (odds ratio [OR] = 0.74, 95% confidence interval [CI] = 0.63 - 0.88, p < 0.001). Moreover, females with early-onset CVD had an increased risk of premature menopause before the age of 40 years (OR = 2.44, 95% CI = 1.60 - 3.72, p < 0.001).

CONCLUSION

Menopausal age is associated with the risk of developing CVD in American females. Specifically, if menopause occurs earlier, there is an increased risk of CVD. Additionally, early-onset CVD significantly raises the risk of premature menopause, which in turn has important implications for female reproductive health.

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

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

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

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

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Affiliation(s)

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

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[Application of interventional respiratory techniques in the treatment of pulmonary bullae:an update]

Pulmonary bullae is a common complication of chronic obstructive pulmonary disease(COPD), causing the deterioration in lung function, leading to aggravated dyspnea and poor quality of life for patients. The traditional therapeutic approach for pulmonary bullae is bullectomy using surgical thoracoscopy. The disadvantage of this approach is the postoperative complications and high risk of recurrence in many patients. In addition, for some patients, due to the patient's physical conditions, such as poor lung function and other diseases, bullectomy could not be used. Therefore, new alternative approaches were urgently needed. In recent years, interventional respiratory technology has been trialed to treat pulmonary bulla all around the world and has achieved great success. In this paper, we reviewed the relevant clinical research progress of interventional respiratory medicine techniques in the treatment of pulmonary bullae.

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.

Comprehensive analysis of T cell exhaustion related signature for predicting prognosis and immunotherapy response in HNSCC

BACKGROUND

T cell exhaustion (TEX) signifies a condition of T cell disorder which implicate the therapeutic benefits and prognostic significance in patients with cancer. However, its role in the Head and Neck Squamous Carcinoma (HNSCC) remains incompletely understood.

METHODS

The detailed data of HNSCC samples were obtained from The Cancer Genome Atlas (TCGA) database and two Gene Expression Omnibus (GEO) datasets. We computed the expression scores of four TEX-related pathways and detected gene modules closely linked to these pathways, indicating prognostic significance. Following this, regression analyses were performed to select eight genes for the development of a predictive signature. The predictive capacity of this signature was evaluated. Additionally, we examined the relationships between TEX-related signature risk scores and the effectiveness of immunotherapy as well as drug sensitivity.

RESULTS

A novel prognostic model, comprising eight TEX-related genes, was established for patients with HNSCC. The prognostic value was further confirmed using additional GEO datasets: GSE65858 and GSE27020. This signature enables the stratification of patients into high- and low- risk groups, each showing distinct survival outcomes and responsiveness to immunotherapy. The low-risk group demonstrated improved prognosis and enhanced efficacy of immunotherapy. In addition, AZD6482, TAF1, Ribociclib, LGK974, PF4708671 and other drugs showed increased sensitivity in the high-risk group based on drug sensitivity values, offering tailored therapeutic recommendations for individuals with various risks profiles.

CONCLUSION

In conclusion, we developed a novel T cell exhaustion-associated signature, which holds considerable predictive value for both the prognosis of patients with HNSCC and the effectiveness of tumor immunotherapy.

[Respiratory virus infection and its influence on outcome in children with septic shock]

Objective: To investigate respiratory virus infection in children with septic shock in pediatric care units (PICU) in China and its influence on clinical outcomes. Methods: The clinical data of children with septic shock in children's PICU from January 2018 to December 2019 in 10 Chinese hospitals were retrospectively collected. They were divided into the pre-COVID-19 and post-COVID-19 groups according to the onset of disease, and the characteristics and composition of respiratory virus in the 2 groups were compared. Matching age, malignant underlying diseases, bacteria, fungi and other viruses, a new database was generated using 1∶1 propensity score matching method. The children were divided into the respiratory virus group and non-respiratory virus group according to the presence or absence of respiratory virus infection; their clinical characteristics, diagnosis, and treatment were compared by t-test, rank sum test and Chi-square test. The correlation between respiratory virus infection and the clinical outcomes was analyzed by logistic regression. Results: A total of 1 247 children with septic shock were included in the study, of them 748 were male; the age was 37 (11, 105) months. In the pre-and post-COVID-19 groups, there were 530 and 717 cases of septic shock, respectively; the positive rate of respiratory virus was 14.9% (79 cases) and 9.8% (70 cases); the seasonal distribution of septic shock was 28.9% (153/530) and 25.9% (185/717) in autumn, and 30.3% (161/530) and 28.3% (203/717) in winter, respectively, and the corresponding positive rates of respiratory viruses were 19.6% (30/153) and 15.7% (29/185) in autumn, and 21.1% (34/161) and 15.3% (31/203) in winter, respectively. The positive rates of influenza virus and adenovirus in the post-COVID-19 group were lower than those in the pre-COVID-19 group (2.1% (15/717) vs. 7.5% (40/530), and 0.7% (5/717) vs. 3.2% (17/530), χ2=21.51 and 11.08, respectively; all P<0.05). Rhinovirus virus were higher than those in the pre-Covid-19 group (1.7% (12/717) vs. 0.2% (1/530), χ2=6.51, P=0.011). After propensity score matching, there were 147 cases in both the respiratory virus group and the non-respiratory virus group. Rate of respiratory failure, acute respiratory distress, rate of disseminated coagulation dysfunction, and immunoglobulin usage of the respiratory virus group were higher than those of non-respiratory virus group (77.6% (114/147) vs. 59.2% (87/147), 17.7% (26/147) vs. 4.1% (6/147), 15.6% (25/147) vs. 4.1% (7/147), and 35.4% (52/147) vs. 21.4% (32/147); χ2=11.07, 14.02, 11.06 and 6.67, all P<0.05); and PICU hospitalization of the former was longer than that of the later (7 (3, 16) vs. 3 (1, 7)d, Z=5.01, P<0.001). Univariate logistic regression analysis showed that the presence of respiratory viral infection was associated with respiratory failure, disseminated coagulation dysfunction, the use of mechanical ventilation, and the use of immunoglobulin and anti-respiratory viral drugs (OR=2.42, 0.22, 0.25, 0.56 and 1.12, all P<0.05). Conclusions: The composition of respiratory virus infection in children with septic shock is different between pre and post-COVID-19. Respiratory viral infection is associated with organ dysfunction in children with septic shock. Decreasing respiratory viral infection through respiratory protection may improve the clinical outcome of these children.

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.

Localization of Ectopic Hyperparathyroidism: Ultrasound Versus 99mTc-sestamibi, 4-Dimensional Computed Tomography, and 11C-choline Positron Emission Tomography/Computed Tomography

OBJECTIVE

To investigate the usefulness of ultrasound (US) for the localization of ectopic hyperparathyroidism and compare it with 99mTc-sestamibi (99mTc-MIBI), 4-dimensional computed tomography (4D-CT), and 11C-choline positron emission tomography/ computed tomography (PET/CT).

METHODS

Of the 527 patients with surgically confirmed primary hyperparathyroidism, 79 patients with ectopic hyperparathyroidism were enrolled. The diagnostic performance of US, 99mTc-MIBI, US + MIBI, 4D-CT, and 11C-choline PET/CT was calculated, and the factors affecting the sensitivity of US and 99mTc-MIBI were analyzed.

RESULTS

Eighty-three ectopic parathyroid lesions were found in 79 patients. The sensitivity was 75.9%, 81.7%, 95.1%, 83.3%, and 100% for US, 99mTc-MIBI, US + MIBI, 4D-CT, and 11C-choline PET/CT, respectively. The difference in sensitivity among these different modalities did not achieve statistical significance (P > .05). The US sensitivity was significantly higher for ectopic lesions in the neck region than for those in the anterior mediastinum/chest wall (85.9% vs. 42.1%, P < .001). The 99mTc-MIBI and 4D-CT sensitivity was not significantly different between these two groups (84.1% vs. 94.6%, P = .193 and 81.3% vs. 85.7%, P = 1). The 11C-choline PET/CT sensitivity was 100% in both groups.

CONCLUSIONS

US is a valuable tool for the localization of ectopic hyperparathyroidism, especially for ectopic lesions in the neck region.

Elevated risk of multimorbidity post-COVID-19 infection: protective effect of vaccination

BACKGROUND

It is unclear how the coronavirus disease 2019 (Covid-19) pandemic has affected multimorbidity incidence among those with one pre-existing chronic condition, as well as how vaccination could modify this association.

AIM

To examine the association of Covid-19 infection with multimorbidity incidence among people with one pre-existing chronic condition, including those with prior vaccination.

DESIGN

Nested case-control study.

METHODS

We conducted a territory-wide nested case-control study with incidence density sampling using Hong Kong electronic health records from public healthcare facilities and mandatory Covid-19 reports. People with one listed chronic condition (based on a list of 30) who developed multimorbidity during 1 January 2020-15 November 2022 were selected as case participants and randomly matched with up to 10 people of the same age, sex and with the same first chronic condition without having developed multimorbidity at that point. Conditional logistic regression was used to estimate adjusted odds ratios (aORs) of multimorbidity.

RESULTS

In total, 127 744 case participants were matched with 1 230 636 control participants. Adjusted analysis showed that there were 28%-increased odds of multimorbidity following Covid-19 [confidence interval (CI) 22% to 36%] but only 3% (non-significant) with prior full vaccination with BNT162b2 or CoronaVac (95% CI -2% to 7%). Similar associations were observed in men, women, older people aged 65 or more, and people aged 64 or younger.

CONCLUSIONS

We found a significantly elevated risk of multimorbidity following a Covid-19 episode among people with one pre-existing chronic condition. Full vaccination significantly reduced this risk increase.

Prognostic Significance of KIF-12 Functioning as a Tumour Suppressor in Papillary Thyroid Carcinoma

Objective: To explore the potential value of a novel marker, KIF-12, in the progression and prognosis of papillary thyroid carcinoma (PTC) through integrative bioinformatics analysis, and clinical sample validation of the prognostic value of KIF-12. Materials and Methods: We extracted the clinicopathological data of 502 PTC patients from The Cancer Genome Atlas-Thyroid Cancer (TCGA-THCA) dataset to identify reliable differentially expressed genes (DEGs) between high and low KIF12 expression groups. Functional enrichment analysis was performed on upregulated DEGs. Gene set enrichment analysis (GESA) was performed to identify the biological pathways. We further applied Cox analysis to determine independent risk factors associated with the PTC progression-free interval (PFI), and a nomogram was established to predict disease outcome. Finally, the prognostic value of KIF12 was validated by means of clinical samples from PTC patients with and without lateral lymph node metastasis. Results: On the basis of the TCGA-THCA database, we found that low KIF-12 expression was significantly related to a higher TNM stage (p<0.05), BRAF mutation status (p = 0.019), and extrathyroidal extension (p<0.001). KIF-12 was an independent prognostic factor of PTC (OR=0.319, 95% CI=0.130-0.784, P=0.013). The prognostic value of KIF12 was also successfully validated in clinical samples from twenty-nine PTC patients with lateral lymph node metastasis by comparison with twenty-two PTC patients without lymph node metastasis (P = 0.004). Conclusions: We report that KIF-12 has a tumor suppressive function in PTC and may be a useful prognostic tool to predict patient outcomes.

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.

Growing-season drought and nitrogen addition interactively impair grassland ecosystem stability by reducing species diversity, asynchrony, and stability

Aboveground net primary productivity controls the amount of energy available to sustain all living organisms, and its sustainable provision relies on the stability of grassland ecosystems. Human activities leading to global changes, such as increased nitrogen (N) deposition and the more frequent occurrence of extreme precipitation events, with N addition increasing the sensitivity of ecosystem production stability to changes in the precipitation regime. However, whether N addition, in combination with seasonal precipitation increases or severe drought, affects ecosystem stability remains unclear. In this study, we conducted a six-year environmental change monitoring experiment in a semiarid grassland in northern China to test the effects of N addition, seasonal drought, and precipitation increases on the temporal stability of ecosystem productivity. Our study revealed that an interaction between drought and N addition reduced species diversity, species asynchrony, species stability, and thus ecosystem stability. These environmental change drivers (except for precipitation increase) induced a positive relationship between species asynchrony and diversity, whereas N addition interactively with drought and precipitation increase led to a negative relationship between diversity and species stability. Only N addition interactively with drought induced a positive species diversity-ecosystem stability relationship because lower species stability was overcome by increased species asynchrony. Our study is great importance to illustrate that production temporal stability tends to be inhibited with drought, though interactively with nutrient N addition. These findings highlight the primary role of asynchronous dynamics among species in modulating the effects of environmental change on diversity-stability relationships.

Efficacy and safety of intrathecal pemetrexed for TKI-failed leptomeningeal metastases from EGFR+ NSCLC: an expanded, single-arm, phase II clinical trial

BACKGROUND

This study aimed to evaluate the efficacy and safety of intrathecal pemetrexed (IP) for treating patients with leptomeningeal metastases (LM) from non-small-cell lung cancer (NSCLC) who progressed from epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) treatment in an expanded, prospective, single-arm, phase II clinical study (ChiCTR1800016615).

PATIENTS AND METHODS

Patients with confirmed NSCLC-LM who progressed from TKI received IP (50 mg, day 1/day 5 for 1 week, then every 3 weeks for four cycles, and then once monthly) until disease progression or intolerance. Objectives were to assess overall survival (OS), response rate, and safety. Measurable lesions were assessed by investigator according to RECIST version 1.1. LM were assessed according to the Response Assessment in Neuro-Oncology (RANO) criteria.

RESULTS

The study included 132 patients; 68% were female and median age was 52 years (31-74 years). The median OS was 12 months (95% confidence interval 10.4-13.6 months), RANO-assessed response rate was 80.3% (106/132), and the most common adverse event was myelosuppression (n = 42; 31.8%), which reversed after symptomatic treatment. The results of subgroup analysis showed that absence of brain parenchymal metastasis, good Eastern Cooperative Oncology Group score, good response to IP treatment, negative cytology after treatment, and patients without neck/back pain/difficult defecation had longer survival. Gender, age, previous intrathecal methotrexate/cytarabine, and whole-brain radiotherapy had no significant influence on OS.

CONCLUSIONS

This study further showed that IP is an effective and safe treatment method for the EGFR-TKI-failed NSCLC-LM, and should be recommended for these patients in clinical practice and guidelines.

The significance of an immunohistochemical marker-based panel in assisting the diagnosis of parathyroid carcinoma

PURPOSE

Parathyroid carcinoma (PC) is an endocrine malignancy with a poor prognosis. However, the diagnosis of PC is still a difficult problem. A model with immunohistochemical (IHC) staining of 5 biomarkers has been reported from limited samples for the differential diagnosis of PC. In the present study, a series of IHC markers was applied in relatively large samples to optimize the diagnostic model for PC.

METHODS

In this study, 44 patients with PC, 6 patients with atypical parathyroid tumors and 57 patients with parathyroid adenomas were included. IHC staining for parafibromin, Ki-67, galectin-3, protein-encoding gene product 9.5 (PGP9.5), E-cadherin, and enhancer of zeste homolog 2 (EZH2) was performed on formalin-fixed, paraffin-embedded tissue samples. The effects of clinical characteristics, surgical procedure, and IHC staining results of tumor tissues on the diagnosis and prognosis of PC were evaluated retrospectively.

RESULTS

A logistic regression model with IHC results of parafibromin, Ki-67, and E-cadherin was created to differentiate PC with an area under the curve of 0.843. Cox proportional hazards analysis showed that negative parafibromin staining (hazard ratio: 3.26, 95% confidence interval: 1.28-8.34, P = 0.013) was related to the recurrence of PC.

CONCLUSION

An IHC panel of parafibromin, Ki-67 and E-cadherin may help to distinguish PC from parathyroid neoplasms. Among the 6 IHC markers and clinical features examined, the risk factor related to PC recurrence was parafibromin staining loss.

China's prevention and control experience of echinococcosis: A 19-year retrospective

Echinococcosis poses a significant threat to public health. The Chinese government has implemented prevention and control measures to mitigate the impact of the disease. By analyzing data from the Chinese Center for Disease Control and Prevention and the State Council of the People's Republic of China, we found that implementation of these measures has reduced the infection rate by nearly 50% between 2004 to 2022 (from 0.3975 to 0.1944 per 100,000 person-years). Nonetheless, some regions still bear a significant disease burden, and lack of detailed information limites further evaluation of the effects on both alveolar and cystic echinococcosis. Our analysis supports the continuing implementation of these measures and suggests that enhanced wildlife management, case-based strategies, and surveillance systems will facilitate disease control.

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.

Plant composition change mediates climate drought, nitrogen addition, and grazing effects on soil net nitrogen mineralization in a semi-arid grassland in North China

Human activities induce alterations of the nitrogen (N) cycle, climate drought, and disturbance (e.g., livestock grazing) regimes at the global scale. Their individual, interactive, and combined effects on soil N cycling in grasslands are unclear. We investigated the N addition, drought, and grazing effects on the N mineralization, as well as their correlations with N-related variables, including the C4 species, shoot biomass (SB), root biomass (RB), plant total nitrogen (PTN), plant total carbon (PTC), soil total nitrogen (STN), soil total carbon (STC), and soil microbial N and C, during a three-year field experiment conducted in a semi-arid grassland in North China. The results showed that N addition increased the nitrate N (NO3--N) and ammonium N (NH4+-N) concentrations, whereas drought decreased the NO3--N concentration because of strengthened N limitation. Pronounced temporal variation in the N mineralization occurred under seasonal drought (maxima in August and September) and under its combination with N addition and grazing (minima in August). RB and the C4 species were positively correlated, whereas STC and the NO3--N concentration were negatively correlated with the N mineralization under the combined influence of the three factors. The structural equation model showed that at the site affected by all three factors, drought indirectly increased the N mineralization by reducing the NO3--N concentration, whereas N addition and grazing did not alter the N mineralization. N addition directly increased while indirectly reduced N mineralization by increasing the NO3--N concentration. Additionally, N addition and grazing increased the C4 species and decreased the STC, consequently enhanced N mineralization. These results highlight the predominant role of drought, when combined with N addition and grazing, in controlling the N mineralization. The N supply balance in semi-arid grasslands could be stabilized in response to increased N addition, climate drought, and grazing.

[New insights into the role of macrophages in tumor immunotherapy]

Macrophages are the main components of the innate immunity system, derived mainly from blood monocytes, and help the host to defend itself against many pathogens and cancers. Most established tumors can educate macrophages into tumor-associated macrophages (TAMs), which contribute to tumor growth, invasion and metastasis, as well as resistance to chemotherapeutic agents and immune checkpoint inhibitors. However, when appropriately activated, macrophages can also exert anti-tumor effects through enhanced phagocytosis and cytotoxicity against tumor cells. In addition, TAMs are associated with poor prognosis and drug resistance, including immunotherapies, suggesting that macrophages are attractive targets as part of combination therapy in cancer treatment. Herein, we review the recent findings on the role of macrophages in tumor development, metastasis and immunotherapy. We focus mainly on macrophage-centered therapy, including strategies to reduce and reshape TAMs, to represent potential targets for tumor immunotherapy.

Remnant cholesterol is associated with hip BMD and low bone mass in young and middle-aged men: a cross-sectional study

PURPOSE

Remnant cholesterol (RC) is a contributor to cardiovascular diseases, obesity, diabetes, and metabolic syndrome. However, the specific relationship between RC and bone metabolism remains unexplored. Therefore, we aimed to investigate the relationships of RC with hip bone mineral density (BMD) and the risk of low bone mass.

METHODS

Physical examination data was collected from men aged < 60 years as part of the Kailuan Study between 2014 and 2018. The characteristics of the participants were compared between RC quartile groups. A generalized linear regression model was used to evaluate the relationship between RC and hip BMD and a logistic regression model was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for low bone mass. Additional analyses were performed after stratification by body mass index (BMI) (≥ or < 24 kg/m2). Sensitivity analyses were performed by excluding individuals who were taking lipid-lowering therapy or had cancer, cardiovascular diseases, or diabetes.

RESULTS

Data from a total of 7,053 participants were included in the analysis. After adjustment for confounding factors, RC negatively correlated with hip BMD (β =  - 0.0079, 95% CI: - 0.0133, - 0.0025). The risk of low bone mass increased from the lowest to the highest RC quartile, with ORs of 1 (reference), 1.09 (95% CI: (0.82, 1.44), 1.35 (95%CI: 1.02, 1.77), and 1.43 (95% CI: 1.09, 1.89) for Q1, Q2, Q3, and Q4, respectively (P for trend = 0.004) in the fully adjusted model. Compared to RC < 0.80 mmol/l group, the risk of low bone mass increased 39% in RC ≥ 0.80 mmol/l group (P < 0.001). The correlation between RC and hip BMD was stronger in participants with BMI ≥ 24 kg/m2 group (β =  - 0.0159, 95% CI: - 0.0289, - 0.0029). The results of sensitivity analyses were consistent with the main results.

CONCLUSION

We have identified a negative correlation between serum RC and hip BMD, and a higher RC concentration was found to be associated with a greater risk of low bone mass in young and middle-aged men.

Beyond Vision: A View from Eye to Alzheimer's Disease and Dementia

With the aging of the global population, the health care burden of Alzheimer's disease (AD) and dementia is considered to increase dramatically in the coming decades. Given the insufficiency of effective interventions for AD and dementia, clinical research on identifying potentially modifiable risk factors and early diagnostic biomarkers becomes a public health priority. Currently, extracerebral manifestations with a large proportion of ocular involvement are usually recognized to precede the symptoms of AD and dementia. Growing epidemiologic evidence also suggests that eye disorders, such as cataracts, age-related macular degeneration, glaucoma, diabetic retinopathy, and so on, are closely associated with and even have a higher incidence of AD and dementia. The eye, as an extension of the central nervous system, therefore has the potential to provide a feasible approach to detecting structural and functional abnormalities of the brain. Numerous new imaging modalities are developed and give novel insights into the detection of several neurodegenerative, vascular, neuropathological, and other ocular abnormalities of AD and dementia in scientific research and clinical application. This review provides an overview of the epidemiologic associations between eye disorders and AD or dementia and summarizes the recent advances in ocular examinations and techniques employed for the detection of AD and dementia. With more brain-and-eye interconnections being identified, the eye is becoming a noninvasive and easily accessible window for the early diagnosis and prevention of AD and dementia.

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

BACKGROUND

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

METHODS

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

FINDINGS

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

INTERPRETATION

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

FUNDING

Boehringer Ingelheim and Eli Lilly.

Drought intensity and post-drought precipitation determine vegetation recovery in a desert steppe in Inner Mongolia, China

Extreme drought events are expected to increase in frequency and severity, posing significant threats to ecosystems worldwide. While considerable research has been concentrated on the effects of climate extremes on the stability of grasslands, the process by which grassland productivity may recover after extreme drought events are still not well understood. Here, we conducted a four-year (2019-2022) recovery investigation after four-year's (2015-2018) extreme drought treatments of different intensities (control, press and pulse) to explore the vegetation recovery of desert-grassland ecosystems Inner Mongolia, China. Press drought involved a 66 % reduction in natural precipitation from May to August, while pulse drought reduced it by 100 % during June and July. We found that both press and pulse droughts led to a sharp decrease in aboveground net primary productivity (ANPP) after four years, primarily due to reduced growth, density, and productivity of annual and perennial plants. However, ANPP under pulse drought could recover fully after four years of stopping of drought treatment, and it could not under press drought. Additionally, community structure (i.e., species richness, plant density, and height) fully recovered within 1 year after the end of the two extreme drought treatments. Both plant density and height contributed to the ANPP recovery after press and pulse droughts. Structural equation modeling (SEM) results further revealed that the reduction in ANPP during the extreme drought was primarily due to a decrease in plant density caused by reduced soil water content. The recovery of ANPP in pulse drought was directly caused by increased soil water content in the post-extreme drought. These results suggest that drought intensity and precipitation determine ANPP recovery in a degraded desert steppe. Our findings are crucial for deepening understanding of the processes and mechanisms of ecosystem recovery after extreme drought, as well as for the successful management and protection of grassland ecosystems.

The Impact of Testosterone on Alzheimer's Disease Are Mediated by Lipid Metabolism and Obesity: A Mendelian Randomization Study

BACKGROUND

To investigate the causal relationship between testosterone (BT) levels and Alzheimer's disease (AD) risk and to quantify the role of obesity and lipid metabolism as potential mediators.

METHODS

We used a two-sample, two-step MR to determine:1) the causal effect of BT levels on AD; 2) the causal effect of two lipid metabolites, obesity and LDLc on AD; and 3) the mediating effects of these metabolites. Pooled data for BT levels and lipid metabolism were obtained from the UK Biobank. AD data were obtained from the Alzheimer's Disease Project International Genomics Consortium, FinnGen Consortium, and UK Biobank study. Effect estimates from external genome-wide association study (GWAS) pooled statistics were obtained using inverse variance-weighted (IVW) MR analysis.

RESULTS

Higher levels of BT were associated with a reduced risk of AD (odds ratio [OR] 0.9992, 95% CI 0.9985-0.9998, P = 0.019), and there was a negative correlation with LDLc (OR 0.9208, 95% CI 0.8569-0.9895, P = 0.024) and obesity class 2 (OC2) (OR 0.7445, 95% CI 0.5873-0.9437, P = 0.014). Conversely, there was a positive correlation between LDLc (OR 1.0014, 95% CI 1.0000-1.0029, P = 0.043) and OC2 (OR 1.0005, 95% CI 1.0001-1.0009, P = 0.003) and AD. Mediation analysis showed that the indirect effect of BT levels on AD was achieved through LDLc and OC2, which accounted for 17% and 17% of the total effect, respectively.

CONCLUSION

Our study identified a causal role of BT levels in LDLc and OC2. BT levels may affect AD through LDLc and OC2 metabolic processes.

Prognostic and immune roles of UROC1 in human cancers: from mechanism exploration of NAFLD and HCC to pan-cancer analysis

OBJECTIVE

Both non-alcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC) are prevalent diseases worldwide. This study aimed to explore the underlying mechanisms of NAFLD and HCC and identify new therapeutic targets for human cancers.

MATERIALS AND METHODS

NAFLD and HCC gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) were utilized to identify co-expressed genes associated with NAFLD and HCC. Public databases were consulted to find common targets of NAFLD and HCC. Enrichment analysis and CIBERSORT techniques were employed to analyze the pathways enriched with DEGs and the attributes of infiltrating immune cells. Furthermore, the expression data of UROC1 and clinical information of patients were acquired from The Cancer Genome Atlas (TCGA) database. Finally, the expression of the UROC1 was validated by immunohistochemistry (IHC).

RESULTS

Through a comprehensive bioinformatics analysis, eight hub genes (CCL2, CCR2, IL6, CSF3R, ATL2, SESN3, UROC1, FIGNL1) were identified. Enrichment analysis indicated that inflammatory and immune response may be common features between NAFLD and HCC. CIBER-SORT analysis revealed an imbalance of plasma cells and macrophages in NAFLD and HCC. Pan-cancer analysis demonstrated that UROC1 expression was related to clinical outcomes and tumor immunity in various cancers. Moreover, a strong correlation was exhibited between UROC1 expression and crucial elements, including tumor mutation burden (TMB), microsatellite instability (MSI), multiple immune checkpoints (ICP), and tumor microenvironment (TME). Importantly, an adverse clinical prognosis of HCC was linked to decreased UROC1 expression, which was consistent with IHC results.

CONCLUSIONS

We identified eight hub genes (CCL2, CCR2, IL6, CSF3R, ATL2, SESN3, UROC1, FIGNL1), which may become early diagnostic and therapeutic targets for NAFLD and HCC. The pan-cancer analysis of UROC1 provides new evidence for its broad application prospects in the field of HCC and other cancers.

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

BACKGROUND

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

METHODS

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

FINDINGS

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

INTERPRETATION

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

FUNDING

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

miR-29c-3p Attenuates beta-Amyloid-Induced Neurotoxicity in Alzheimer's Disease Through Regulating beta-Site Amyloid Precursor Protein-Cleaving Enzyme 1

The aberrantly expressed microRNAs (miRNAs) including miR-29c-3p have been reported in the brains of Alzheimer's disease (AD) patients in recent researches. Nevertheless, the functional role and underlying molecular mechanism of miR-29c-3p in AD pathogenesis are still not well elucidated. The purpose of this study was to examine whether miR-29c-3p regulated beta-Ameyloid (Abeta)-induced neurotoxicity by targeting beta-site amyloid precursor protein-cleaving enzyme 1 (BACE1). The expressions of miR 29c 3p and BACE1 mRNA and protein levels in Abeta-treated PC12 cellular AD model were examined by qRT-PCR and western blot analyses. Luciferase reporter assay verified the potential target of miR 29c 3p. Cell viability, apoptosis, and caspase-3 activity in PC12 cells were detected by the MTT assay, flow cytometry, and caspase-3 activity assay, respectively. Our results indicated that miR-29c-3p downregulation and BACE1 upregulation existed in the cellular AD model of PC12 cells. Moreover, miR-29c-3p directly inhibited BACE1 expression. miR-29c-3p overexpression and BACE1 knockdown strengthened Abeta-induced cell apoptosis, and caspase-3 activity in PC12 cells, which was partially eliminated by over-expression of BACE1. Conversely, BACE1 knockdown reversed the miR-29c-3p inhibition- mediated inhibitory effect on Abeta-induced cell toxicity, apoptosis, and caspase-3 activity in PC12 cells. Considering, miR-29c-3p attenuated Abeta-induced neurotoxicity through targeting BACE1 in an cellular AD model of PC12, providing a potential therapeutic target for AD treatment.

[The effect of tumor spread through air spaces on the prognosis of patients with stage Ⅰ non-small cell lung cancer: a meta-analysis]

Objective: To systematically evaluate the effect of tumor spread through air spaces (STAS) on the prognosis of patients with stage Ⅰ non-small cell lung cancer (NSCLC). Methods: PubMed, Embase, Web of Science, Cochrane Library, CNKI, Wanfang Database and VIP were searched to collect papers related to NSCLC and STAS published from the establishment of aboves databases to November 2022. Papers were screened according to the inclusion and exclusion criteria, and data were extracted. The 5-year overall survival (OS) and relapse-free survival (RFS) of stage Ⅰ NSCLC patients with or without STAS were compared. HR(95%CI) was used as effective indicator to evaluate the impact of STAS positivity on the prognosis of NSCLC. The quality of each included study was assessed using the Newcast-Ottawa Scale (NOS). Results: A total of 24 papers concerning 29 studies were included according to the inclusion and exclusion criteria, and there was no significant heterogeneity among the included papers(all I2<50%). A total of 10 883 patients with stage Ⅰ NSCLC were included in the studies, of which 3 298 (30.3%) were STAS-positive. The 29 studies showed that STAS-positive patients had a higher risk of 5-year recurrence than STAS-negative patients with stage Ⅰ NSCLC [HR=1.94(95%CI:1.74-2.16)];and a meta-analysis of 17 of the studies showed that that STAS-positive patients had a higher risk of 5-year death [HR=2.09 (95%CI:1.80-2.43)]. Compared with stage Ⅰ NSCLC patients who underwent other surgeries, STAS-positive patients who underwent sublobar resection had a higher risk of 5-year recurrence than patients with other procedures (HR=3.44, 95%CI: 2.49-4.76) and a higher risk of 5-year death (HR=3.40, 95%CI:2.05-5.64); and patients with stage Ⅰ NSCLC who had the pathologic histologic type of squamous carcinoma had a higher risk of 5-year recurrence (HR=2.48,95%CI:1.71-3.60) and a higher risk of 5-year death (HR=3.04, 95%CI: 1.90-4.86) than other patients with the type of squamous lung cancer. Conclusion: STAS positivity is a risk factor of poor prognosis in patients with stage Ⅰ NSCLC, especially for patients underwent sublobar resection or with squamous lung cancer.

Neoadjuvant nivolumab plus chemotherapy versus chemotherapy for resectable NSCLC: subpopulation analysis of Chinese patients in CheckMate 816

BACKGROUND

Neoadjuvant nivolumab plus chemotherapy significantly improved event-free survival (EFS) and pathologic complete response (pCR) versus chemotherapy alone in patients with resectable non-small-cell lung cancer (NSCLC) in the global phase III CheckMate 816 study. Here, we report post hoc exploratory efficacy, safety, and surgical outcomes in the Chinese subpopulation of this study.

METHODS

Adults with stage IB-IIIA resectable NSCLC were randomized to receive nivolumab 360 mg plus chemotherapy or chemotherapy alone every 3 weeks for three cycles followed by surgery. Primary endpoints included EFS and pCR (both per blinded independent review). EFS and pCR results were from 14 October 2022, and 16 September 2020, database locks, respectively.

RESULTS

The Chinese subpopulation comprised 97 patients (nivolumab plus chemotherapy, 44; chemotherapy, 53). At 38.2 months of minimum follow-up, median EFS was not reached [95% confidence interval (CI) 23.4 months-not reached] in the nivolumab plus chemotherapy arm and 13.9 months (95% CI 8.3-34.3 months) in the chemotherapy arm (hazard ratio 0.47, 95% CI 0.25-0.88). pCR rates were 25.0% (95% CI 13.2% to 40.3%) and 1.9% (95% CI 0.0% to 10.1%), respectively (odds ratio 11.05; 95% CI 1.41-86.49). Of 97 Chinese patients, 36 (82%) in the nivolumab plus chemotherapy arm and 41 (77%) in the chemotherapy arm underwent definitive surgery. Grade 3-4 treatment-related adverse events occurred in 18/43 patients (42%) treated with nivolumab plus chemotherapy and 22/53 patients (42%) treated with chemotherapy.

CONCLUSIONS

Consistent with findings in the global study population of CheckMate 816, neoadjuvant nivolumab plus chemotherapy improved EFS and pCR versus chemotherapy in the Chinese subpopulation without impacting treatment tolerability or the feasibility of surgery. These findings support the use of nivolumab plus chemotherapy as a standard neoadjuvant treatment option for Chinese patients with resectable NSCLC.

Sophora tonkinensis: response and adaptation of physiological characteristics, functional traits, and secondary metabolites to drought stress

The medicinal plant Sophora tonkinensis is a characteristic Chinese shrub of karst areas. The arid climate in karst areas produces high-quality S. tonkinensis; however, the mechanisms of drought tolerance are not clear, which restricts sustainable plantings of S. tonkinensis. This study involved a 20-day drought stress experiment with potted S. tonkinensis and threee soil water regimes: control (CK), mild drought (MDT), and severe drought (SDT). Plant morphology, biomass, physiological indicators, alkaloid content, and other changes under drought stress were monitored. The content of soluble sugars and proteins, and activity of antioxidant enzymes in leaves and roots were higher under drought than CK, indicating that S. tonkinensis is tolerant to osmotic stress in early drought stages. Content of matrine and oxymatrine increased gradually with increasing drought duration in the short term. The epidermis of S. tonkinensis leaves have characteristics of desert plants, including upper epidermal waxy layer, lower epidermal villi, and relatively sunken stomata, suggesting that S. tonkinensis has strong drought tolerance. In conclusion, drought stress changed the cell structure of S. tonkinensis, induced antioxidant enzyme activity and increased its resistance to drought.

Long-term Survival, Quality of Life, and Molecular Features of the Patients With Solid Pseudopapillary Neoplasm of the Pancreas: A Retrospective Study of 454 Cases

OBJECTIVE

To present comprehensive information on the clinicopathological, molecular, survival characteristics, and quality of life (QOL) after surgery for solid pseudopapillary neoplasm (SPN) of the pancreas in a large cohort after long-term follow-up.

BACKGROUND

SPN is a rare tumor with an uncertain malignant potential, and solid information on long-term prognosis and QOL remains limited.

METHODS

All hospitalized patients with SPNs who underwent surgery between 2001 and 2021 at the Peking Union Medical College Hospital were retrospectively reviewed. The clinicopathological characteristics of the patients were retrieved. A cross-sectional telephone questionnaire was administered to inquire about the QOL. Molecular analyses were performed using whole-exome sequencing.

RESULTS

Exactly 454 patients with SPN were enrolled, of whom 18.5% were males and 81.5% were females. The mean patient age was 31 ± 12 years. In total, 61.3% of the patients had no symptoms. The size of the tumors was 5.38 ± 3.70 cm; 83.4% were solid cystic tumors, and 40.1% had calcifications. The proportions of local resection, distal pancreatectomy with or without splenectomy, and pancreaticoduodenectomy with or without pylorus preservation were 29.7%, 28.9% or 22.9%, and 11% or 6.8%, respectively. Over the years, there has been a significant shift from open to minimally invasive surgery. Among all surgical procedures, pylorus-preserving pancreaticoduodenectomy (PPPD) had the highest incidence of grade 2 to 4 complications (up to 32.3%), compared with 6.7% in distal pancreatectomy ( P < 0.001). Regarding histopathology, tissue invasion, perineural invasion, cancerous microvascular emboli, lymph node metastasis, and distant metastasis were present in 16.5%, 2.2%, 0.7%, 2.0%, and 3.1% of patients, respectively. Sixty patients were lost to follow-up. Sixteen of the 390 patients who underwent resection (4.1%) experienced local recurrence or distant metastasis after surgery. In total, 361 patients responded to the telephone survey. Nearly 80% of patients claimed their QOL was not significantly affected after surgery; however, the remaining 20% complained of lower QOL during 3 to 6 years of follow-up after surgery. No clinicopathological factor could reliably predict clinical recurrence or metastasis after resection. A total of 28 driver genes were detected with mutations in at least 2 tumor samples and the top 3 frequently mutated genes were CTNNB1 , ATRNL1 , and MUC16 .

CONCLUSIONS

This study presented the largest cohort of patients with SPN after surgery from a single center and reported the QOL of these patients. SPN is associated with extremely favorable long-term survival, even in patients with metastasis, and most patients have a good QOL after surgery.

Risk factors for death caused by early onset sepsis in neonates: a retrospective cohort study

OBJECTIVE

To evaluate the association between traditional laboratory findings and death, and to find risk factors for death in infants with early onset sepsis (EOS).

STUDY DESIGN

This was a single-center, case-control, retrospective trial conducted between January 2020 and August 2021. Infants with EOS were enrolled and divided into two groups based on outcome before hospital discharge: non-survivors (Mortality group) and survivors (Survival group).

RESULTS

Out of 556 eligible neonates, there were 38 (6.8%) deaths. After univariate analysis and ROC curve analysis, there were a total of 12 values with significant differences (p < 0.05) between two groups, which included birth weight (BW), weight on admission, gestational age, age on admission, mode of delivery, septic shock, heart failure, respiratory failure, pulmonary hypertension, hypothermia, serum lactic acid, and aspartate aminotransferase (AST). Moreover, after multivariate analysis performed for those 12 values, the binary logistic regression analysis showed that taking death as a reference, the BW (OR = 1.00, 95% CI[1.001, 1.002], p < 0.001), PPHN (OR = 2.60, 95% CI[1.04, 6.52], p > 0.001), septic shock (OR = 6.15, 95% CI [2.52, 15.00], p < 0.001), heart failure (OR = 6.22, 95% CI[0.90, 43.05], p > 0.001), serum lactic acid (OR = 0.82, 95%CI[0.75, 0.90], p < 0.001), and AST (OR = 1.00, 95% CI[0.99, 1.00], p > 0.001) could be regarded as risk factors for death with 94.0% correct predictions.

CONCLUSIONS

The factors affecting the prognosis of EOS in neonates were BW, PPHN, septic shock, heart failure, serum lactic acid, and AST. Timely correction of these modifiable risk factors for death may decrease the mortality of EOS in neonates.

Hidden magnetism uncovered in a charge ordered bilayer kagome material ScV6Sn6

Charge ordered kagome lattices have been demonstrated to be intriguing platforms for studying the intertwining of topology, correlation, and magnetism. The recently discovered charge ordered kagome material ScV6Sn6 does not feature a magnetic groundstate or excitations, thus it is often regarded as a conventional paramagnet. Here, using advanced muon-spin rotation spectroscopy, we uncover an unexpected hidden magnetism of the charge order. We observe an enhancement of the internal field width sensed by the muon ensemble, which takes place within the charge ordered state. More importantly, the muon spin relaxation rate below the charge ordering temperature is substantially enhanced by applying an external magnetic field. Taken together with the hidden magnetism found in AV3Sb5 (A = K, Rb, Cs) and FeGe kagome systems, our results suggest ubiqitous time-reversal symmetry-breaking in charge ordered kagome lattices.

Role of LncMALAT1-miR-141-3p/200a-3p-NRXN1 Axis in the Impairment of Learning and Memory Capacity in ADHD

As a prevalent neurodevelopmental disease, attention-deficit hyperactivity disorder (ADHD) impairs the learning and memory capacity, and so far, there has been no available treatment option for long-term efficacy. Alterations in gene regulation and synapse-related proteins influence learning and memory capacity; nevertheless, the regulatory mechanism of synapse-related protein synthesis is still unclear in ADHD. LncRNAs have been found participating in regulating genes in multiple disorders. For instance, lncRNA Metastasis Associated Lung Adenocarcinoma Transcript 1 (MALAT1) has an essential regulatory function in numerous psychiatric diseases. However, how MALAT1 influences synapse-related protein synthesis in ADHD remains largely unknown. Here, our study found that MALAT1 decreased in the hippocampus tissue of spontaneously hypertensive rats (SHRs) compared to the standard controls, Wistar Kyoto (WKY) rats. Subsequent experiments revealed that MALAT1 enhanced the expression of neurexin 1 (NRXN1), which promoted the synapse-related genes (SYN1, PSD95, and GAP43) expression. Then, the bioinformatic analyses predicted that miR-141-3p and miR-200a-3p, microRNAs belonging to miR-200 family and sharing same seed sequence, could interact with MALAT1 and NRXN1 mRNA, which were further confirmed by luciferase report assays. Finally, rescue experiments indicated that MALAT1 influenced the expression of NRXN1 by sponging miR-141-3p/200a-3p. All data verified our hypothesis that MALAT1 regulated synapse-related proteins (SYN1, PSD95, and GAP43) through the MALAT1-miR-141-3p/200a-3p-NRXN1 axis in ADHD. Our research underscored a novel role of MALAT1 in the pathogenesis of impaired learning and memory capacity in ADHD and may shed more light on developing diagnostic biomarkers and more effective therapeutic interventions for individuals with ADHD.

[Determination of acetone in urine by headspace gas chromatography-mass spectrometry]

Objective: To establish a method for determination of acetone in urine by headspace gas chromatography-mass spectrometry. Methods: From March to June 2021, the 3.0 ml urine sample was placed in a headspace bottle with 4.0 g of anhydrous sodium sulfate and sealed. Equilibration time was 30 min at 85 ℃. The separation was carried out on a DB-5MS column. The urine sample was detected by mass spectrometry and quantified by external standard method. Results: The method for the determination of acetone in urine by headspace gas chromatography-mass spectrometry had good linearity in the range of 51.2-1024.0 μg/L, and the correlation coefficient was 0.9995. The detection limit and the lower limit of quantification of acetone were 16.4 μg/L and 54.6 μg/L. The average recoveries of samples ranged from 94.9% to 96.8%. The intra-assay precision and inter-assay precision were both less than 10%. Samples can be stored at least 7 d at 4 ℃ or -20 ℃. Conclusion: This method has simple sample preparation and high sensitivity. It can be used for monitoring and evaluation of urinary acetone in the general population and occupationally exposed populations.

Hyperon Polarization along the Beam Direction Relative to the Second and Third Harmonic Event Planes in Isobar Collisions at sqrt[s_{NN}]=200 GeV

The polarization of Λ and Λ[over ¯] hyperons along the beam direction has been measured relative to the second and third harmonic event planes in isobar Ru+Ru and Zr+Zr collisions at sqrt[s_{NN}]=200  GeV. This is the first experimental evidence of the hyperon polarization by the triangular flow originating from the initial density fluctuations. The amplitudes of the sine modulation for the second and third harmonic results are comparable in magnitude, increase from central to peripheral collisions, and show a mild p_{T} dependence. The azimuthal angle dependence of the polarization follows the vorticity pattern expected due to elliptic and triangular anisotropic flow, and qualitatively disagrees with most hydrodynamic model calculations based on thermal vorticity and shear induced contributions. The model results based on one of existing implementations of the shear contribution lead to a correct azimuthal angle dependence, but predict centrality and p_{T} dependence that still disagree with experimental measurements. Thus, our results provide stringent constraints on the thermal vorticity and shear-induced contributions to hyperon polarization. Comparison to previous measurements at RHIC and the LHC for the second-order harmonic results shows little dependence on the collision system size and collision energy.

Should All Pancreatic Cystic Lesions with Worrisome or High-Risk Features Be Resected? A Clinical and Radiological Machine Learning Model May Help to Answer

RATIONALE AND OBJECTIVES

According to current guidelines, pancreatic cystic lesions (PCLs) with worrisome or high-risk features may have overtreatment. The purpose of this study was to build a clinical and radiological based machine-learning (ML) model to identify malignant PCLs for surgery among preoperative PCLs with worrisome or high-risk features.

MATERIALS AND METHODS

Clinical and radiological details of 317 pathologically confirmed PCLs with worrisome or high-risk features were retrospectively analyzed and applied to ML models including Support Vector Machine, Logistic Regression (LR), Decision Tree, Bernoulli NB, Gaussian NB, K Nearest Neighbors and Linear Discriminant Analysis. The diagnostic ability for malignancy of the optimal model with the highest diagnostic AUC in the cross-validation procedure was further evaluated in internal (n = 77) and external (n = 50) testing cohorts, and was compared to two published guidelines in internal mucinous cyst cohort.

RESULTS

Ten clinical and radiological feature-based LR model was the optimal model with the highest AUC (0.951) in the cross-validation procedure. In the internal testing cohort, LR model reached an AUC, accuracy, sensitivity, and specificity of 0.927, 0.909, 0.914, and 0.905; in the external testing cohort, LR model reached 0.948, 0.900, 0.963, and 0.826. When compared to the European guidelines and the ACG guidelines, LR model demonstrated significantly better accuracy and specificity in identifying malignancy, while maintaining the same high sensitivity.

CONCLUSION

Clinical- and radiological-based LR model can accurately identify malignant PCLs in patients with worrisome or high-risk features, possessing diagnostic performance better than the European guidelines as well as ACG guidelines.

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.

Wave In in auditory brainstem response suggests a high possibility of a high jugular bulb

Background

Wave In, which refers to the negativity between waves I and II in auditory brainstem response (ABR), is an electrophysiological phenomenon observed in previous studies. The term "high jugular bulb" (HJB) describes a jugular bulb that is located in a high position in the posterior aspect of the internal acoustic canal. The present study aimed to explore the correlation between wave In and the possibility of a HJB.

Methods

This retrospective study included a cohort of pediatric patients diagnosed with profound hearing loss who were enrolled in a government-sponsored cochlear implantation program at an academic medical center between January 2019 and December 2022. The analysis involved examining the results obtained from the ABR test and high-resolution computed tomography (HRCT) of the temporal bone in the patients. The position of the jugular bulb was classified according to the Manjila and Semaan classification.

Results

A total of 221 pediatric patients were included in the study. Twenty-four patients, with a median age of 3 years and a range of 1-7 years, showed significant bilateral (n = 21) or unilateral (n = 3) wave In (mean latency: right ear, 2.16 ms ± 0.22 ms; left ear, 2.20 ms ± 0.22 ms). The remaining 197 patients showed an absence of ABR. The HRCT images revealed that 18 of the 24 patients (75%) had HJB, but only 41 of the 197 patients who lacked ABR (20.8%) showed signs of HJB. The ratio difference was considered statistically significant based on the chi-squared test (χ2 = 32.10, p < 0.01). More than 50% of the HJBs were categorized as type 4 jugular bulbs, which are located above the inferior margin of the internal auditory canal.

Conclusion

ABR wave In in pediatric patients with profound hearing loss suggests a high possibility of HJB. The physiological mechanism underlying this correlation needs further investigation.