Study of cell and drug interactions based on dual-mode detection using SPR and fluorescence imaging

The investigation of the interactions between cells and drugs forms a crucial aspect of biological and clinical medical studies. Generally, single-cell or local-cellular studies require a microscopic imaging system with high magnifications, which suffers from low detection throughputs and poor time responses. The study presented in this paper combined SPR and fluorescence to achieve cell localization, real-time monitoring of cell images and quantitative analysis of drugs. In order to obtain more comprehensive, accurate and real-time data, a dual-mode system based on surface plasmon resonance (SPR) and fluorescence was constructed based on a 4× magnification lens. This enables simultaneous studies of an entire cell and a specific region of the cell membrane. An adaptive adjustment algorithm was established for distorted SPR images, achieving temporal and spatial matching of the dual-mode detection. The combination of SPR and fluorescence not only achieved micro-detection but also complemented the qualitative or quantitative limitations of SPR or fluorescence method alone. In system characterization, the response signal of SPR was noticed to increase with the increasing concentration of EGF in stimulated cells. It indicated that this platform could be employed for quantitative detection of the cell membrane region. Upon addition of EGF, a peak in the SPR curve was observed, and the cells in the corresponding SPR image turned whiter. This indicated that the platform can simultaneously monitor the SPR response signal and image changes. The response time of fluorescence in EGF testing was several seconds earlier than SPR, revealing that signal transduction first occurred in the whole cell and then propagated to the cell membrane region. The inhibitory ability of Gefitinib on cells was verified in a fast and real-time manner within 20 min. The results indicated that the detection limit of this method was 20 IU/mL for EGF and 10 µg/mL for Gefitinib. In conclusion, this study demonstrates the advantages of SPR and fluorescence dual-mode techniques in the analysis of cell-drug interactions, as well as their strong potential in drug screening.

Screening and evaluation of quality markers of Radix Cudramiae for liver disease based on an integrated strategy of in vivo pharmacokinetics and in vitro HPLC fingerprint

Radix Cudramiae, the dried root of Cudrania cochinchinensis (Lour.) Kudo et Masam., is a valuable ethnomedicine with outstanding antihepatitis activity. However, the lack of reports on quality markers (Q-markers) hindered its quality evaluation and standardization, as a result restricted its clinical application. This paper aimed to discover the Q-markers of Radix Cudramiae with a comprehensive strategy based on in vivo pharmacokinetics and in vitro HPLC fingerprint. A rapid and sensitive ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS) analytical method was firstly developed and validated for simultaneous determination of six potential active ingredients (eriodictyol, dihydrokaempferol, dihydromorin, kaempferol, naringenin and morin) of Radix Cudramiae in rat plasma and tissues, which was successfully applied to the holistic comparison of pharmacokinetics and tissue distribution between normal and acute liver injury rats. On the other hand, a representative HPLC fingerprint of Radix Cudramiae was also established to elucidate the chemical profile for overall quality evaluation. Dihydrokaempferol-7-O-β-D-glucoside (the naturally existed chemical formation of dihydrokaempferol) and kaempferol screened out with high exposure levels in vivo and high resolution in HPLC fingerprint were finally selected as Q-markers of Radix Cudramiae. To the best of our knowledge, it was the first time for people to discover in vivo properties and pharmacokinetic parameters of components in Radix Cudramiae, as well as the first report on its representative HPLC fingerprint. Also, the integrated strategy could offer an effective way for TCMs Q-markers screening.

Single vesicle chemistry reveals partial release happens at the mechanical stress-induced exocytosis

Neuronal activity can be modulated by mechanical stress in the central nervous system (CNS) in neurodegenerative diseases, for example Alzheimer's disease. However, the impact of mechanical stress on chemical signal transmission, especially the storage and release of neurotransmitter in neuron vesicles, has not been fully clarified. In this study, a nanotip conical carbon fiber microelectrode (CFME) and a disk CFME are placed in and on a cell, respectively. The nanotip conical CFME functions for both the mechanical stress and the quantification of transmitter storage in single vesicles, while the disk CFME is used to monitor the transmitter release during exocytosis induced by mechanical stress at the same cell. By comparing the vesicular transmitter storage with its release during mechanical stress-induced exocytosis at the same cell, we find the release ratio of transmitter in chromaffin cells varies from 27 % to 100 %, while for PC12 cells from 30 % to 100 %. Our results indicate that the exocytosis of cells responding to mechanical stress shows individual difference obviously, with a significant population exhibiting partial release mode. The variation of Ca2+ channels and mechanosensitive ion channels on cell membrane may both contribute to this variation. Our discovery not only shows mechanical stress can change the transmission of cellular chemical signals at the vesicle level, but also provides an important reference perspective for the study of nervous system regulation and nervous system diseases.

Reprogramming of arachidonic acid metabolism using α-terpineol to alleviate asthma: insights from metabolomics

Asthma is a chronic inflammatory disorder in airways with typical pathologic features of airway inflammation and mucus hypersecretion. α-Terpineol is a monocyclic terpene found in many natural plants and foods. It has been reported to possess a wide range of pharmacological activities including anti-inflammatory and expectorant effects. However, the role of α-terpineol in asthma and its potential protective mechanism have not been well elucidated. This study is designed to investigate the pharmacological effect and mechanism of α-terpineol on asthmatic mice using the metabolomics platform. A murine model of asthma was established using ovalbumin (OVA) sensitization and then challenged for one week. The leukocyte count and inflammatory cytokines in the bronchoalveolar lavage fluid (BALF), lung histopathology, inflammatory  infiltrate and mucus secretion were evaluated. An ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS)-based metabolomics study was performed on lung tissues and serum to explore endogenous small molecule metabolites affected by α-terpineol in asthmatic mice. After α-terpineol treatment, leukocyte count, inflammatory cytokines in the BALF, and peribronchial inflammation infiltration were significantly downregulated. Goblet cell hyperplasia and mucus secretion were attenuated, with the level of Muc5ac in BALF decreased. These results proved the protective effect of α-terpineol against airway inflammation, mucus hypersecretion and Th1/Th2 immune imbalance. To further investigate the underlying mechanisms of α-terpineol in asthma treatment, UPLC-MS/MS-based metabolomics analysis was performed. 26 and 15 identified significant differential metabolites were found in the lung tissues and serum of the control, model and α-terpineol groups, respectively. Based on the above differential metabolites, enrichment analysis showed that arachidonic acid (AA) metabolism was reprogrammed in both mouse lung tissues and serum. 5-Lipoxygenase (5-LOX) and cysteinyl leukotrienes (CysLTs) are the key enzyme and the end product of AA metabolism, respectively. In-depth studies have shown that pretreatment with α-terpineol can alleviate asthma by decreasing the AA level, downregulating the expression of 5-LOX and reducing the accumulation of CysLTs in mouse lung tissues. In summary, this study demonstrates that α-terpineol is a potential agent that can prevent asthma via regulating disordered AA metabolism.

[The mechanical ventilation guided by electrical impedance tomography in acute respiratory distress syndrome]

Acute respiratory distress syndrome (ARDS) is a common and critical clinical condition characterized by diffuse damage to the lung interstitium, alveoli, and increased permeability of pulmonary blood vessels. CT can be used to assess the imaging features, severity, and prediction of ARDS, but it requires patient transportation to the CT room and is only a static examination. Electrical impedance tomography (EIT) is an increasingly widely used monitoring tool in clinical applications in recent years. It enables continuous real-time assessment of lung ventilation distribution at the bedside and has high clinical value in optimizing mechanical ventilation parameters for critically ill patients. This article introduces the basic principles of EIT and how to better utilize EIT technology to guide mechanical ventilation treatment for ARDS patients.

Zinc-Iron Bimetallic Peroxides Modulate the Tumor Stromal Microenvironment and Enhance Cell Immunogenicity for Enhanced Breast Cancer Immunotherapy Therapy

Immunotherapy has emerged as a potential approach for breast cancer treatment. However, the rigid stromal microenvironment and low immunogenicity of breast tumors strongly reduce sensitivity to immunotherapy. To sensitize patients to breast cancer immunotherapy, hyaluronic acid-modified zinc peroxide-iron nanocomposites (Fe-ZnO2@HA, abbreviated FZOH) were synthesized to remodel the stromal microenvironment and increase tumor immunogenicity. The constructed FZOH spontaneously generated highly oxidative hydroxyl radicals (·OH) that degrade hyaluronic acid (HA) in the tumor extracellular matrix (ECM), thereby reshaping the tumor stromal microenvironment and enhancing blood perfusion, drug penetration, and immune cell infiltration. Furthermore, FZOH not only triggers pyroptosis through the activation of the caspase-1/GSDMD-dependent pathway but also induces ferroptosis through various mechanisms, including increasing the levels of Fe2+ in the intracellular iron pool, downregulating the expression of FPN1 to inhibit iron efflux, and activating the p53 signaling pathway to cause the failure of the SLC7A11-GSH-GPX4 signaling axis. Upon treatment with FZOH, 4T1 cancer cells undergo both ferroptosis and pyroptosis, exhibiting a strong immunogenic response. The remodeling of the tumor stromal microenvironment and the immunogenic response of the cells induced by FZOH collectively compensate for the limitations of cancer immunotherapy and significantly enhance the antitumor immune response to the immune checkpoint inhibitor αPD-1. This study proposes a perspective for enhancing immune therapy for breast cancer.

[New 2023 global definition of acute respiratory distress syndrome: progress and limitation]

Acute respiratory distress syndrome (ARDS) presents a challenge in clinical diagnosis as it lacks a definitive gold standard. Over the past 55 years, there have been several revisions to the definition of ARDS. With the progress of clinical practice and scientific research, the limitations of the "Berlin definition" have become increasingly evident. In response to these changes, the 2023 global definition of ARDS aims to address these issues by expanding the diagnostic targets, chest imaging, and methods for assessing hypoxia. Additionally, the new definition increases the diagnostic criteria to accommodate resource-constrained settings. The expansion facilitates early identification and treatment interventions for ARDS, thereby advancing epidemiological and clinically related research. Nevertheless, the broad nature of this revision may include patients who do not actually have ARDS, thus raising the risk of false-positive diagnoses. Therefore, additional verification is crucial to ascertain the validity and accuracy of the 2023 global definition of ARDS.

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.

Knowledge, Attitudes and Practices Towards Psoriasis Among Patients and Their Family Members

Purpose

KAP studies serve to enhance health consciousness and furnish foundational data for appraising, strategizing, and enacting disease management and prejudice eradication initiatives. There remains a dearth of published studies elucidating the dimensions of knowledge, attitudes, and practices among psoriasis patients in China. To investigate the knowledge, attitudes and practices (KAP) towards psoriasis among patients and their family members in Northern China.

Methods

This web-based, cross-sectional study was conducted among psoriasis patients and their family members through a self-administered questionnaire.

Results

Among patients (n=260), their mean KAP scores were 9.76±5.69 (range: 0-19), 35.64±11.48 (range: 14-70), and 56.73±10.98 (range: 16-80), respectively. Among family members (n=237), their mean KAP scores were 11.93±5.34 (range: 0-19), 35.80±4.34 (range: 8-40), and 37.04±4.38 (range: 8-40), respectively. Structural equation modeling (SEM) analysis for patients indicated significant and negative path relations between knowledge and attitudes (β=-2.271, P<0.001), and between knowledge and practice (β=-0.398, P<0.001). Extended SEM analysis, which divides knowledge into K1, K2, and K3 parts, showed negative path relations between K3 and attitude (β=-1.300, P=0.002), between attitude and practice (β=-0.634, P<0.001). Moreover, SEM for family members showed positive path relations between knowledge and attitude (β=1.536, P<0.001), between attitude and practice (β=0.682, P<0.001).

Conclusion

Patients in Northern China demonstrated insufficient knowledge, negative attitude, and proactive practice, while their family members had insufficient knowledge, positive attitude, and proactive practice toward psoriasis. It is recommended to implement educational interventions addressing knowledge gaps among patients and families.

[Comparison of the microbiota diversity between autogenous and anautogenous Culex pipiens pallens]

OBJECTIVE

To investigate the microbiota composition and diversity between autogenous and anautogenous Culex pipiens pallens, so as to provide insights into unraveling the pathogenesis of autogeny in Cx. pipiens pallens.

METHODS

Autogenous and anautogenous adult Cx. pipiens pallens samples were collected at 25 ℃, and the hypervariable regions of the microbial 16S ribosomal RNA (16S rRNA) gene was sequenced on the Illumina NovaSeq 6000 sequencing platform. The microbiota abundance and diversity were evaluated using the alpha diversity index, and the difference in the microbiota structure was examined using the beta diversity index. The microbiota with significant differences in the abundance between autogenous and anautogenous adult Cx. pipiens pallens samples was identified using the linear discriminant analysis effect size (LEfSe).

RESULTS

The microbiota in autogenous and anautogenous Cx. pipiens pallens samples belonged to 18 phyla, 28 classes, 70 orders, 113 families, and 170 genera, and the dominant phyla included Proteobacteria, Bacteroidetes, and so on. At the genus level, Wolbachia was a common dominant genus, and the relative abundance was (77.6 ± 11.3)% in autogenous Cx. pipiens pallens samples and (47.5 ± 8.5)% in anautogenous mosquito samples, while Faecalibaculum (0.4% ± 0.1%), Dubosiella (0.5% ± 0.0%) and Massilia (0.5% ± 0.1%) were specific species in autogenous Cx. pipiens pallens samples. Alpha diversity analysis showed that higher Chao1 index and ACE index in autogenous Cx. pipiens pallens samples than in anautogenous samples (both P values > 0.05), and lower Shannon index (P > 0.05) and Simpson index (P < 0.05) in autogenous Cx. pipiens pallens samples than in anautogenous samples. LEfSe analysis showed a total of 48 significantly different taxa between autogenous and anautogenous Cx. pipiens pallens samples (all P values < 0.05).

CONCLUSIONS

There is a significant difference in the microbiota diversity between autogenous and anautogenous Cx. pipiens pallens.

Clinicopathological features and prognostic factors of salivary gland myoepithelial carcinoma: institutional experience of 42 cases

Myoepithelial carcinoma (MECA) is a rare type of carcinoma for which the clinicopathological features and prognostic factors have not yet been fully clarified. A retrospective study of 42 patients diagnosed with salivary gland MECA was performed, focusing on the clinicopathological features and prognostic factors. Of the 42 patients, 20 died of cancer, 20 lived without tumour, one lived with distant metastasis, and one was lost to follow-up. Overall, 69.0% had tumour recurrence, 16.7% had cervical nodal metastasis, and 21.4% had distant metastasis. The 5-year overall survival rate was 70.2%. Kaplan-Meier analysis revealed that patients with pathological positive lymph nodes (pN+), multiple recurrences of tumour, and higher histological grade had worse overall survival. Multivariate Cox analysis indicated pN+ and higher histological grade to be independent predictors of decreased survival. The 5-year overall survival rate in the pN0 group was 87.5%, while that in the pN+ group was 28.6%. In conclusion, myoepithelial carcinoma can be defined as a tumour with a high incidence of recurrence and poor prognosis, especially in pN+ patients. Pathological positive lymph nodes and histological grade may serve as predictors of survival.

Insight gained via ultra-performance liquid chromatography tandem mass spectrometry-based metabolomics: Protective effect of Artemisia argyi H.Lév. & Vaniot essential oil on lipopolysaccharide-induced liver injury mice

Artemisia argyi H.Lév. & Vaniot essential oil (AAEO) has shown pharmacological effects such as anti-inflammation, antioxidant, and anti-tumor properties. However, the protective effect of AAEO on lipopolysaccharide (LPS)-induced liver injury and its potential protective mechanism are still unclear. In this study, we used ultra-performance liquid chromatography tandem mass spectrometry metabolomics techniques to investigate the changes in liver tissue metabolites in mice exposed to LPS with or without AAEO treatment for 14 days. The biochemical results showed that compared with the control group, AAEO significantly reduced the levels of liver functional enzymes, suggesting a significant improvement in liver injury. In addition, the 18 differential metabolites identified by metabolomics were mainly involved in the reprogramming of arachidonic acid metabolism, tryptophan metabolism, and purine metabolism. AAEO could significantly inhibit the expression of COX-2, IDO1, and NF-κB; enhance the body's anti-inflammatory ability; and alleviate liver injury. In summary, our study identified the protective mechanism of AAEO on LPS-induced liver injury at the level of small molecular metabolites, providing a potential liver protective agent for the treatment of LPS-induced liver injury.

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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The Potential of FOXP3 in Predicting Survival and Treatment Response in Breast Cancer

Background

Breast cancer (BC) continues to pose a substantial challenge to global health, necessitating an enhanced understanding of its fundamental mechanisms. Among its various pathological classifications, breast invasive carcinoma (BRCA) is the most prevalent. The role of the transcription factor forkhead box P3 (FOXP3), associated with regulatory T cells, in BRCA's diagnosis and prognosis remains insufficiently explored, despite its recognized importance.

Methods

We examined the mRNA expression profile of FOXP3 in BRCA patients, assessing its correlation with disease detection, patient survival, immune checkpoint alterations, and response to anticancer drugs.

Results

Our analysis revealed significantly elevated FOXP3 mRNA levels in BRCA patients, with a 95.7% accuracy for BRCA detection based on the area under the curve. High FOXP3 mRNA levels were positively correlated with overall survival and showed significant associations with CTLA4, CD274, PDCD1, TMB, and immune cell infiltration status. Furthermore, FOXP3 mRNA expression was linked to the efficacy of anticancer drugs and the tumor inflammation signature.

Discussion

These findings suggest that FOXP3 serves as a promising biomarker for BRCA, offering valuable insights into its diagnosis and prognosis. The correlation between FOXP3 expression and immune checkpoint alterations, along with its predictive value for treatment response, underscores its potential in guiding therapeutic strategies.

Conclusion

FOXP3 stands out as an influential factor in BRCA, highlighting its diagnostic accuracy and prognostic value. Its association with immune responses and treatment efficacy opens new avenues for research and clinical applications, positioning FOXP3 as a vital target for further investigation in BRCA management.

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

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

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

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

Robust Glycoproteomics Platform Reveals a Tetra-Antennary Site-Specific Glycan Capping with Sialyl-Lewis Antigen for Early Detection of Gastric Cancer

The lack of efficient biomarkers for the early detection of gastric cancer (GC) contributes to its high mortality rate, so it is crucial to discover novel diagnostic targets for GC. Recent studies have implicated the potential of site-specific glycans in cancer diagnosis, yet it is challenging to perform highly reproducible and sensitive glycoproteomics analysis on large cohorts of samples. Here, a highly robust N-glycoproteomics (HRN) platform comprising an automated enrichment method, a stable microflow LC-MS/MS system, and a sensitive glycopeptide-spectra-deciphering tool is developed for large-scale quantitative N-glycoproteome analysis. The HRN platform is applied to analyze serum N-glycoproteomes of 278 subjects from three cohorts to investigate glycosylation changes of GC. It identifies over 20 000 unique site-specific glycans from discovery and validation cohorts, and determines four site-specific glycans as biomarker candidates. One candidate has branched tetra-antennary structure capping with sialyl-Lewis antigen, and it significantly outperforms serum CEA with AUC values > 0.89 compared against < 0.67 for diagnosing early-stage GC. The four-marker panel can provide improved diagnostic performances. Besides, discrimination powers of four candidates are also testified with a verification cohort using PRM strategy. This findings highlight the value of this strong tool in analyzing aberrant site-specific glycans for cancer detection.

Three dimensional analysis of the exhalation flow in the proximity of the mouth

The human exhalation flow is characterized in this work from the three-dimensional velocimetry results obtained by using the stereo particle image velocimetry (SPIV) measurement technique on the flow emitted from a realistic airway model. For this purpose, the transient exhalation flow through the mouth of a person performing two different breaths corresponding to two metabolic rates, standing relaxed (SR) and walking active (WA), is emulated and studied. To reproduce the flow realistically, a detailed three-dimensional model obtained from computed tomography measurements on real subjects is used. To cope with the variability of the experimental data, a subsequent analysis of the results is performed using the TR-PIV (time resolved particle image velocimetry) technique. Exhalation produces a transient jet that becomes a puff when flow emission ends. Three-dimensional vector fields of the jet velocity are obtained in five equally spaced transverse planes up to a distance of Image 1 from the mouth at equally spaced time instants Image 2 which will be referred to as phases (φ), from the beginning to the end of exhalation. The time evolution during exhalation of the jet area of influence, the velocity field and the jet air entrainment have been characterized for each of the jet cross sections. The importance of the use of realistic airway models for the study of this type of flow and the influence of the metabolic rate on its development are also analyzed. The results obtained contribute to the characterization of the human exhalation as a pathway of the transmission of pathogens such as SARS-CoV-2 virus.

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.

Long-term prognostic value of thyroid hormones in left ventricular noncompaction

PURPOSE

Thyroid function is closely related to the prognosis of cardiovascular diseases. This study aimed to explore the predictive value of thyroid hormones for adverse cardiovascular outcomes in left ventricular noncompaction (LVNC).

METHODS

This longitudinal cohort study enrolled 388 consecutive LVNC patients with complete thyroid function profiles and comprehensive cardiovascular assessment. Potential predictors for adverse outcomes were thoroughly evaluated.

RESULTS

Over a median follow-up of 5.22 years, primary outcome (the combination of cardiovascular mortality and heart transplantation) occurred in 98 (25.3%) patients. For secondary outcomes, 75 (19.3%) patients died and 130 (33.5%) patients experienced major adverse cardiovascular events (MACE). Multivariable Cox analysis identified that free triiodothyronine (FT3) was independently associated with both primary (HR 0.455, 95%CI 0.313-0.664) and secondary (HR 0.547, 95%CI 0.349-0.858; HR 0.663, 95%CI 0.475-0.925) outcomes. Restricted cubic spline analysis illustrated that the risk for adverse outcomes increased significantly with the decline of serum FT3. The LVNC cohort was further stratified according to tertiles of FT3 levels. Individuals with lower FT3 levels in the tertile 1 group suffered from severe cardiac dysfunction and remodeling, resulting in higher incidence of mortality and MACE (Log-rank P < 0.001). Subgroup analysis revealed that lower concentration of FT3 was linked to worse prognosis, particularly for patients with left atrial diameter ≥ 40 mm or left ventricular ejection fraction ≤ 35%. Adding FT3 to the pre-existing risk score for MACE in LVNC improved its predictive performance.

CONCLUSION

Through the long-term investigation on a large LVNC cohort, we demonstrated that low FT3 level was an independent predictor for adverse cardiovascular outcomes.

[Clinical study of the efficacies of ruxolitinib plus low-dose PTCY for acute GVHD prevention after haploidentical transplantation in malignant hematological diseases]

Objective: To investigate and verify a novel acute graft versus host disease (aGVHD) prevention protocol in the context of haploidentical hematopoietic stem cell transplantation (haplo-HSCT) . Methods: Patients who underwent haplo-HSCT in our center between January 2022 and December 2022 were included. All patients received reduced doses of cyclophosphamide, Rabbit anti-human tymoglobulin, ruxolitinib, methotrexate, cyclosporine, and MMF to prevent aGVHD. The transplantation outcomes, complications, and survival rate of all patients were investigated. Results: A total of 52 patients with haplo-HSCT were enrolled, 29 (55.8%) male and 23 (44.2%) female, with a median age of 28 (5-59) years. There were 25 cases of acute myeloid leukemia, 17 cases of acute lymphocyte leukemia, 6 cases of myelodysplastic syndrome, 2 cases of chronic myeloid leukemia and 2 cases of myeloproliferative neoplasms. 98.1% of patients had successful engraftment. The incidence of Ⅱ-Ⅳ aGVHD and Ⅲ-Ⅳ aGVHD was 19.2% (95% CI 8.2% -30.3% ) and 7.7% (95% CI 0.2% -15.2% ), respectively. No patients experienced severe gastrointestinal mucositis. The Epstein-Barr virus and CMV reactivation rates were 40.4% and 21.3%, respectively. 9.6% of patients relapsed during followup, with 1-year overall survival, progression-free survival, and non-relapse mortality rates of 86.5% (95% CI 76.9% -96.1% ), 78.8% (95% CI 67.4% -90.3% ) and 11.5% (95% CI 2.6% -20.5% ), respectively. Conclusion: Ruxolitinib combined with a low dose of PTCY is a safe and effective first-line aGVHD prevention strategy.

[Association between waist circumference and ischemic stroke: a prospective study in adults from Qingdao]

Objective: To analyze the association between waist circumference (WC) and ischemic stroke (IS). Methods: The data for the present study were from the prospective cohort study of China Kadoorie Biobank in Qingdao. Using baseline information and IS events of the participants, the Cox proportional hazard regression model and restricted cubic spline (RCS) were used to analyze the association between WC and IS. Results: A total of 33 355 participants were included in the study, with 302 008.88 person-years of follow-up. A total of 1 093 new cases of IS were observed. Multivariate Cox proportional hazard regression model analysis showed that compared to the respondents with normal WC (male <85.0 cm, female <80.0 cm), respondents with excessive WC (male ≥85.0 cm, female ≥80.0 cm) had a 78% higher risk of IS incidence [hazard ratio(HR)=1.78, 95%CI: 1.51-2.10], and the risk increased by 72% (HR=1.72, 95%CI: 1.40-2.12) and 83% (HR=1.83, 95%CI: 1.40-2.39) in men and women. According to the RCS, the increase in WC and the risk of IS showed an "S" trend of nonlinear dose-response relationship. Conclusions: The risk of IS would increase with the WC. Keeping a normal WC is important for preventing IS.

Liquid-liquid phase separation-related lncRNA prognostic signature and ZNF32-AS2 as a novel biomarker in hepatocellular carcinoma

BACKGROUND

Liquid-liquid phase separation (LLPS) enhances oncogenic signaling pathways and advances cancer progression, and has been proposed as a promising cancer biomarker and intervention target. Nevertheless, doubts remain about the prognostic importance of LLPS-related long non-coding RNAs (lncRNAs) in hepatocellular carcinoma (HCC).

METHODS

An LLPS-related lncRNA prognostic signature was generated by drivers and regulators of LLPS, and was validated in external datasets. The underlying genetic changes and functional enrichment of the signature were assessed. The drug sensitivity and response to immunotherapy were predicted in patients categorized as high-risk and low-risk. Clinical samples, phase separation agonist, and dispersant were used to identify lncRNAs with the most significant expression change. Cancer cells with ZNF32-AS2 expression regulation were subjected to colony formation assay, scratch test assay, migration and invasion assay, sorafenib resistance assay, and xenograft tumor model.

RESULTS

The signature of LLPS-related hub lncRNAs identified through Weighted Gene Co-Expression Network Analysis showed outstanding performance in training and external validation cohorts consistently, and the molecular characteristics varied between different risk groups. Potential drugs for high-risk individuals were identified, and low-risk individuals demonstrated a more favorable reaction to immunotherapy. ZNF32-AS2 showed the most significant expression change in phase separation agonist and dispersant treatment. ZNF32-AS2 promoted the proliferation, mobility, and sorafenib resistance of liver cancer cells.

CONCLUSIONS

The LLPS-related lncRNA signature may help assess prognosis and predict treatment efficacy in clinical settings. LLPS-related ZNF32-AS2 promoted the proliferation, mobility, and sorafenib resistance of liver cancer cells, and may be a novel potential biomarker in hepatocellular carcinoma.

Copy Number Alterations Predict Development of OSCC from Oral Leukoplakia

Oral leukoplakia (OLK) is a common type of potentially malignant disorder. Early identification of the malignancy potential leads to a better management of OLK and prediction of development of oral squamous cell carcinoma (OSCC). However, there has been no effective biomarker to assess the risk of malignancy in OLK. Genomic copy number alteration (CNA) is a complex chromosomal structural variation in the genome and has been identified as a potential biomarker in multiple cancers. This study aimed to develop a predictive model for the malignant transformation risk of OLK by copy number analysis. A total of 431 OLK samples with long-term follow-up (median follow-up of 67 mo) from multiple academic centers were analyzed for CNAs. CNA events increased with the severity of hyperplasia, mild dysplasia, moderate dysplasia, and severe dysplasia. More CNA events were present in patients with OLK who later developed OSCC than in those with OLK who did not. By multivariate Cox regression analysis, the OLK of the CNA scorehigh group showed an increased risk of malignant transformation than the CNA scorelow group (P < 0.001). A CNA score model was developed to accurately predict the prognosis (area under the receiver operating characteristic curve [AUC] = 0.879; 95% confidence interval [CI], 0.799-0.959) and was validated using data from 2 external centers (AUC = 0.836, 95% CI, 0.683-0.989; AUC = 0.876, 95% CI, 0.682-1.000), and all of them showed better prediction performances than histopathological grade in assessing the transformation risk of OLK. Furthermore, we performed CNA models among 4 subgroups of OLK with hyperplasia, mild dysplasia, moderate dysplasia, and severe dysplasia and found that CNA score can accurately predict malignant transformation of different subgroups. CNA score may be a useful biomarker to predict malignant transformation of OLK. Subtyping of OLK by the CNA score could contribute to better management of OLK and predicting development of OSCC.

The impact of air pollutants on spontaneous abortion: a case-control study in Tongchuan City

OBJECTIVES

Studies related to air pollutants and spontaneous abortion in urban northwestern China are scarce, and the main exposure windows of pollutants acting on pregnant women are unclear.

STUDY DESIGN

Case-control study.

METHODS

Data were collected from pregnant women in Tongchuan City from 2018 to 2019. A total of 289 cases of spontaneous abortion and 1156 cases of full-term labor were included and analyzed using a case-control study. Logistic regression models were developed to explore the relationship between air pollutants and spontaneous abortion after Chi square analysis and Air pollutant description.

RESULTS

O3 (odds ratio [OR] = 1.028) is a risk factor for spontaneous abortion throughout pregnancy. PM2.5 (OR = 1.015), PM10 (OR = 1.010), SO2 (OR = 1.026), and NO2 (OR = 1.028) are risk factors for spontaneous abortion in the 30 days before the last menstrual period. PM2.5 (OR = 1.015), PM10 (OR = 1.013), SO2 (OR = 1.036), and NO2 (OR = 1.033) are risk factors for spontaneous abortion in the 30-60 days before the last menstrual period. PM2.5 (OR = 1.028), PM10 (OR = 1.013), SO2 (OR = 1.035), and NO2 (OR = 1.059) are risk factors for spontaneous abortion in the 60-90 days before the last menstrual period.

CONCLUSION

Exposure to high levels of air pollutants may be a cause of increased risk of spontaneous abortion, especially in the first trimester of the last menstrual period.

Comparison of clinical data between the proximal femoral bionic nail (PFBN) and hip replacement for the treatment of femoral intertrochanteric fracture

OBJECTIVE

The aim of this study was to compare the difference between proximal femoral bionic nail (PFBN) and hip replacement (HR) for femoral intertrochanteric fracture.

MATERIALS AND METHODS

A retrospective analysis of the differences in operative time, length of stay, postoperative Harris score, and postoperative mortality between patients with femoral intertrochanteric fracture treated by PFBN and HR admitted to Jinzhai County People's Hospital from October 2020 to September 2022 was performed.

RESULTS

A total of 56 patients with femoral intertrochanteric fracture, 26 with PFBN and 30 with HR, were included in the study. There were no differences in the length of surgery, pre- and post-operative hemoglobin, or post-operative Harris score at 3 months between the two groups. Compared to the HR group, the PFBN group had a lower total cost, shorter hospital stays, and lower mortality but a longer ambulation time, with a difference of 3.36 weeks.

CONCLUSIONS

PFBN may be a promising new treatment for femoral intertrochanteric fracture.

Toripalimab plus axitinib versus sunitinib as first-line treatment for advanced renal cell carcinoma: RENOTORCH, a randomized, open-label, phase III study

BACKGROUND

Immune checkpoint inhibitors in combination with tyrosine kinase inhibitors are standard treatments for advanced clear cell renal cell carcinoma (RCC). This phase III RENOTORCH study compared the efficacy and safety of toripalimab plus axitinib versus sunitinib for the first-line treatment of patients with intermediate-/poor-risk advanced RCC.

PATIENTS AND METHODS

Patients with intermediate-/poor-risk unresectable or metastatic RCC were randomized in a ratio of 1 : 1 to receive toripalimab (240 mg intravenously once every 3 weeks) plus axitinib (5 mg orally twice daily) or sunitinib [50 mg orally once daily for 4 weeks (6-week cycle) or 2 weeks (3-week cycle)]. The primary endpoint was progression-free survival (PFS) assessed by an independent review committee (IRC). The secondary endpoints were investigator-assessed PFS, overall response rate (ORR), overall survival (OS), and safety.

RESULTS

A total of 421 patients were randomized to receive toripalimab plus axitinib (n = 210) or sunitinib (n = 211). With a median follow-up of 14.6 months, toripalimab plus axitinib significantly reduced the risk of disease progression or death by 35% compared with sunitinib as assessed by an IRC [hazard ratio (HR) 0.65, 95% confidence interval (CI) 0.49-0.86; P = 0.0028]. The median PFS was 18.0 months in the toripalimab-axitinib group, whereas it was 9.8 months in the sunitinib group. The IRC-assessed ORR was significantly higher in the toripalimab-axitinib group compared with the sunitinib group (56.7% versus 30.8%; P < 0.0001). An OS trend favoring toripalimab plus axitinib was also observed (HR 0.61, 95% CI 0.40-0.92). Treatment-related grade ≥3 adverse events occurred in 61.5% of patients in the toripalimab-axitinib group and 58.6% of patients in the sunitinib group.

CONCLUSION

In patients with previously untreated intermediate-/poor-risk advanced RCC, toripalimab plus axitinib provided significantly longer PFS and higher ORR than sunitinib and had a manageable safety profile TRIAL REGISTRATION: ClinicalTrials.gov NCT04394975.

Analysis of cellular response to drugs with a microfluidic single-cell platform based on hyperspectral imaging

BACKGROUND

Cellular response to pharmacological action of drugs is significant for drug development. Traditional detection method for cellular response to drugs normally rely on cell proliferation assay and metabolomics examination. In principle, these analytical methods often required cell labeling, invasion analysis, and hours of co-culture with drugs, which are relatively complex and time-consuming. Moreover, these methods can only indicate the drug effectiveness on cell colony rather than single cells. Thus, to meet the requirements of personal precision medicine, the development of drug response analysis on the high resolution of single cell is demanded.

RESULTS

To provide precise result for drug response on single-cell level, a microfluidic platform coupled with the label-free hyperspectral imaging was developed. With the help of horizontal single-cell trapping sieves, hundreds of single cells were trapped independently in microfluidic channels for the purposes of real-time drug delivery and single-cell hyperspectral image recording. To significantly identify the cellular hyperspectral change after drug stimulation, the differenced single-cell spectrum was proposed. Compared with the deep learning classification method based on hyperspectral images, an optimal performance can be achieved by the classification strategy based on differenced spectra. And the cellular response to different reagents, for example, K+, Epidermal Growth Factor (EGF), and Gefitinib at different concentrations can be accurately characterized by the differenced single-cell spectra analysis.

SIGNIFICANCE AND NOVELTY

The high-throughput, rapid analysis of cellular response to drugs at the single-cell level can be accurately performed by our platform. After systematically analyzing the materials and the structures of the single-cell microfluidic chip, the optimal single-cell trapping method was proposed to contribute to the further application of hyperspectral imaging on microfluidic single-cell analysis. And the hyperspectral characterization of single-cell with cancer drug stimulation proved the application potential of our method in personal cancer medication.

Exosome-derived tRNA fragments tRF-GluCTC-0005 promotes pancreatic cancer liver metastasis by activating hepatic stellate cells

Early metastasis is the primary factor in the very poor prognosis of pancreatic ductal adenocarcinoma (PDAC), with liver metastasis being the most common form of distant metastasis in PDAC. To investigate the mechanism of PDAC liver metastasis, we found that PDAC cells can promote the formation of pre-metastatic niches (PMNs) through exosomes to facilitate liver metastasis in the early stage. In our study, hepatic stellate cells (HSCs) were treated with PDAC-derived exosomes (PDAC-exo), and the activation of HSCs was detected. A novel transfer RNA-derived fragment, the tRF-GluCTC-0005 was obtained by small RNA sequencing from serum exosomes of PDAC patients. Bioinformatics analysis and RNA pull-down assays revealed the interaction between WDR1 and tRF-GluCTC-0005. A KPC transgenic mouse model and an AAV-mediated sh-WDR1 mouse model were used to detect the mechanism of liver metastasis in vivo. Finally, the dual luciferase reporter assay, protein mutation truncation assay, Co-IP assay, and flow cytometry assay were used to explore the molecular mechanism in HSCs activation and PMNs formation. We found that the tRF-GluCTC-0005 in exosomes binds to the 3' untranslated region of the mRNA of the WDRl in HSCs and increases mRNA stability. The N-terminals of WDR1 bind to the YAP protein directly, inhibit YAP phosphorylation, and promote the expression of YAP transcription factors. The tRF-GluCTC-0005 in PDAC-exo significantly recruits myeloid-derived suppressor cells (MDSCs) in the liver, creating a PMNs immunosuppressive microenvironment and further advancing liver metastasis from PDAC. Our results suggest that the key of PDAC liver metastasis is the activation of HSCs through upregulation of WDR1 by tRF-GluCTC-0005 in exosomes, which mediates the infiltration of MDSCs to form PMNs.

[Analysis of the incidence and symptomatology of low anterior resection syndrome after laparoscopic anterior resection for rectal cancer]

Objective: This study aims to explore the temporal trend of Low Anterior Resection Syndrome (LARS) and its symptoms after laparoscopic anterior resection for rectal cancer. Methods: A retrospective cohort study design was employed. The study included primary rectal (adenocarcinoma) cancer patients who underwent laparoscopic anterior resection at Tongji Hospital, Huazhong University of Science and Technology, between January 1, 2010, and December 31, 2020. Complete medical records and follow-up data at 3, 6, 9, 12, and 18 months postoperatively were available for all patients. A total of 1454 patients were included, of whom 1094 (75.2%) were aged ≤65 years, and 597 (41.1%) were females. Among them, 1040 cases (71.5%) had an anastomosis-to-anus distance of 0-5cm, and 86 cases (5.9%) received neoadjuvant treatment. All patients completed the Chinese version of the LARS questionnaire and their LARS occurrence and specific symptom information were recorded at 3, 6, 9, 12, and 18 months postoperatively. Considering past literature and clinical experience, further subgroup analyses were performed to explore the potential impact factors on severe LARS, including anastomosis level, preoperative neoadjuvant therapy, postoperative adjuvant therapy, and the presence of preventive stoma. Results: The occurrence rates of LARS at 3, 6, 9, 12, and 18 months postoperatively were 78.5% (1142/1454), 71.4% (1038/1454), 55.0% (799/1454), 45.7% (664/1454), and 45.7% (664/1454), respectively (χ2=546.180, P<0.001). No statistically significant difference was observed between the 12-month and 18-month time points (P>0.05). When compared with the symptoms at 3 months, the occurrence rates of gas incontinence [1.7% (24/1454) vs. 33.9% (493/1454)], liquid stool incontinence [3.9% (56/1454) vs. 41.9% (609/1454)], increased stool frequency [79.6% (1158/1454) vs. 95.9% (1395/1454)], stool clustering [74.3% (1081/1454) vs. 92.9% (1351/1454)], and stool urgency [46.5% (676/1454) vs. 78.7% (1144/1454)] in the LARS symptom spectrum were significantly alleviated at 12 months (all P<0.05) and remained stable beyond 12 months (all P>0.05). With the extension of postoperative time, the incidence rates of severe LARS exhibited a decreasing trend in different subgroups, of anastomosis level, preoperative neoadjuvant therapy, postoperative adjuvant therapy, and the presence of preventive stoma, and reached stability at 12 months postoperatively (all P>0.05). Conclusion: LARS and its specific symptom profile showed a trend of gradual improvement over time up to 1 year postoperatively, and stabilized after more than 1 year. Increased stool frequency and stool clustering are the most common features of abnormal bowel dys function, which improve slowly after surgery.

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.

[Safety and efficacy of donor-derived chimeric antigen receptor T-cell therapy in patients with relapsed B-cell acute lymphoblastic leukemia after allogeneic hematopoietic stem cell transplantation]

Objective: To investigated the safety and efficacy of donor-derived CD19+ or sequential CD19+ CD22+ chimeric antigen receptor T-cell (CAR-T) therapy in patients with B-cell acute lymphoblastic leukemia (B-ALL) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Methods: The data of 22 patients with B-ALL who relapsed after allo-HSCT and who underwent donor-derived CAR-T therapy at the Zhujiang Hospital of Southern Medical University and the 920th Hospital of Joint Logistics Support Force of the People's Liberation Army of China from September 2015 to December 2022 were retrospectively analyzed. The primary endpoint was overall survival (OS), and the secondary endpoints were event-free survival (EFS), complete remission (CR) rate, and Grade 3-4 adverse events. Results: A total of 81.82% (n=18) of the 22 patients achieved minimal residual disease-negative CR after CAR-T infusion. The median follow-up time was 1037 (95% CI 546-1509) days, and the median OS and EFS were 287 (95% CI 132-441) days and 212 (95% CI 120-303) days, respectively. The 6-month OS and EFS rates were 67.90% (95% CI 48.30%-84.50%) and 58.70% (95% CI 37.92%-79.48%), respectively, and the 1-year OS and EFS rates were 41.10% (95% CI 19.15%-63.05%) and 34.30% (95% CI 13.92%-54.68%), respectively. Grade 1-2 cytokine release syndrome occurred in 36.36% (n=8) of the patients, and grade 3-4 occurred in 13.64% of the patients (n=3). Grade 2 and 4 graft-versus-host disease occurred in two patients. Conclusion: Donor-derived CAR-T therapy is safe and effective in patients with relapsed B-ALL after allo-HSCT.

[Analysis of gene characteristics and core genome characteristics of carbapenem-resistant Enterobacter cloacae in rural residents of Weifang City, Shandong Province]

Objective: To investigate the drug-resistant gene characteristics and core genome characteristics of carbapenem-resistant Enterobacter cloacae (CR-ECL) in rural residents of Weifang City, Shandong Province. Methods: Fecal samples were collected from rural community residents in Weifang City, Shandong Province in 2017. Drug-resistant strains were screened using a carbapenem-resistant enterobacter chromogenic medium. CR-ECL positive strains were acquired via Matrix Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry(MALDI-TOFMS) analysis. The antibiotic resistance phenotype of CR-ECL was determined using a microbroth dilution assay. Whole genome sequencing (WGS) and analysis were conducted, along with an examination of the immediate vicinity of the blaNDM gene and phylogenetic analysis of the strains. Results: A total of 628 fecal samples were collected and tested, of which 6 were CR-ECL positive (detection rate 0.96%), all exhibiting multiple drug resistance (MDR) phenotypes. Six CR-ECL strains had four MLST genotypes (ST), all of which carried multiple drug resistance genes (blaNDM-1, blaNDM-5, etc.) and virulence genes (acrA, acrB, entB, fepC, etc.). There were mobile genetic elements ISAba125, TN3-IS3000, TN3 and IS5 in the genetic environment surrounding the blaNDM gene. The phylogenetic tree showed that the multi-locus sequence typing of the core genome (cgMLST) was consistent with the single nucleotide polymorphism (SNPs) results. The cgMLST results showed that the allele differences between strains 2BC0101B and 2BC0251B, 2BG0561B and 2BI0221B were 2 and 1, respectively. The SNPs results showed that the above two pairs of bacteria also clustered together. It was found that the strains of chicken fecal samples in the National Center for Biotechnology Information (NCBI) database were located in the center of the evolutionary tree, and the local sequences could be traced back to American human sequences. Conclusion: Multidrug-resistant CR-ECL is detected in rural community residents in Weifang City, Shandong Province.

HMGB1-activated tumor-associated macrophages promote migration and invasion via NF-κB/IL-6 signaling in oral squamous cell carcinoma

Tumor-associated macrophages (TAMs) are a highly abundant cell population within the tumor microenvironment of oral squamous cell carcinomas (OSCC). Recent studies have identified an intricate cross-talk between cancer cells and macrophages in the tumor microenvironment. However, the underlying mechanism remains unclear. High-mobility group box 1 (HMGB1) was linked to metastasis and an unfavorable prognosis in head and neck squamous cell carcinoma. Furthermore, it was significantly upregulated in moderately differentiated OSCC tissues and the OSCC cell lines CAL27 and SCC9. HMGB1 knockdown impedes the ability of TAMs to induce invasion and migration of OSCC cells. Phenotypic changes in macrophages were measured after incubation of supernatant from OSCC cells transfected with HMGB1 siRNA or supplemented with recombinant HMGB1. HMGB1 induced M1 polarization of macrophages and the secretion of IL-6 via the NF-κB pathway, contributing to the OSCC malignant migration. HMGB1 originating from OSCC cells, along with its downstream signaling pathways, holds promise as a potential therapeutic target for mitigating metastasis and improving the survival rate of OSCC.

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.

Asthma and clinical outcomes of COVID-19 in a community setting

OBJECTIVES

The association between asthma and COVID-19 mortality remains inconclusive. We examined the association between asthma and clinical outcomes of patients with COVID-19.

STUDY DESIGN

A case-control study based on a surveillance cohort in Harris County, Texas.

METHODS

Using the data of 21,765 patients who reported having at least one chronic health condition, we investigated the association between asthma and COVID-19 severity, characterized primarily by hospitalization and death. Unconditional logistic regression models were used to estimate the multivariable odds ratio (mOR) and its 95 % confidence interval (CI) of COVID-19 severity associated with asthma and other chronic lung diseases, adjusting for demographic and other comorbidities. A P-value < 0.005 was considered statistically significant after correcting multiple testing.

RESULTS

In total, 3034 patients (13.9 %) had asthma, and 774 (3.56 %) had other chronic lung diseases. The case death rate among patients with asthma and other chronic lung diseases was 0.75 % and 19.0 %, respectively. Compared to patients without the respective conditions, patients with asthma had lower odds of death (mOR = 0.44, 95 % CI: 0.27-0.69), while patients with other chronic lung diseases had higher odds of hospitalization (mOR = 2.02, 95 % CI: 1.68-2.42) and death (mOR = 1.95, 95 % CI: 1.52-2.49) (P-values < 0.005). Risk factors for COVID-19 mortality included older age, male gender, diabetes, obesity, hypertension, cardiovascular disease, active cancer, and chronic kidney disease.

CONCLUSIONS

The public health surveillance data suggested that preexisting asthma was inversely associated with COVID-19 mortality.

Loneliness prevention and the role of the Public Health system

AIMS

To evaluate evidence on loneliness interventions that have been assessed and found effective, both for remediation and addressing fundamental causes of loneliness; to consider why population-level primary prevention strategies targeting fundamental causes are necessary, and determine areas for future research; and to outline an integrated approach to prevention considering roles for the Public Health system.

METHOD

We conducted a review of systematic reviews to identify effective loneliness interventions and classified them in our Population-Prevention Matrix according to public health impact, amount of individual effort required, and level of prevention. We also highlighted emerging interventions that have yet to be formally evaluated.

RESULTS

We identified a range of preventive or therapeutic approaches, and a dearth of population-level primary prevention interventions targeting fundamental causes of loneliness. Filling this gap will be essential in addressing the loneliness epidemic, and we provided emerging examples of population-level primary prevention interventions that may inform future efforts.

CONCLUSION

Based on evidence to date, we suggest an integrated approach to prevention with significant roles for the US Public Health system, including its function as Chief Health Strategist to lead and guide multisystem approaches to loneliness prevention, with a particular focus on population-level primary prevention strategies.

Novel Ameloblastin Variants, Contrasting Amelogenesis Imperfecta Phenotypes

Amelogenesis imperfecta (AI) comprises a group of rare, inherited disorders with abnormal enamel formation. Ameloblastin (AMBN), the second most abundant enamel matrix protein (EMP), plays a critical role in amelogenesis. Pathogenic biallelic loss-of-function AMBN variants are known to cause recessive hypoplastic AI. A report of a family with dominant hypoplastic AI attributed to AMBN missense change p.Pro357Ser, together with data from animal models, suggests that the consequences of AMBN variants in human AI remain incompletely characterized. Here we describe 5 new pathogenic AMBN variants in 11 individuals with AI. These fall within 3 groups by phenotype. Group 1, consisting of 6 families biallelic for combinations of 4 different variants, have yellow hypoplastic AI with poor-quality enamel, consistent with previous reports. Group 2, with 2 families, appears monoallelic for a variant shared with group 1 and has hypomaturation AI of near-normal enamel volume with pitting. Group 3 includes 3 families, all monoallelic for a fifth variant, which are affected by white hypoplastic AI with a thin intact enamel layer. Three variants, c.209C>G; p.(Ser70*) (groups 1 and 2), c.295T>C; p.(Tyr99His) (group 1), and c.76G>A; p.(Ala26Thr) (group 3) were identified in multiple families. Long-read AMBN locus sequencing revealed these variants are on the same conserved haplotype, implying they originate from a common ancestor. Data presented therefore provide further support for possible dominant as well as recessive inheritance for AMBN-related AI and for multiple contrasting phenotypes. In conclusion, our findings suggest pathogenic AMBN variants have a more complex impact on human AI than previously reported.

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.

Integrative analysis reveals the recurrent genetic etiologies in idiopathic pulmonary fibrosis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is increasingly recognized as a chronic, progressive and fatal lung disease with an unknown etiology. Current studies focus on revealing the genetic factors in the risk of IPF, making the integrative analysis of genetic variations and transcriptomic alterations of substantial value.

AIM

This study aimed to improve the understanding of the molecular basis of IPF through an integrative analysis of whole-exome sequencing (WES), bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) data.

METHODS

WES is a powerful tool for studying the genetic basis of IPF, allowing for the identification of genetic variants that may be associated with the development of the disease. RNA-seq data provide a comprehensive view of the transcriptional changes in IPF patients, while scRNA-seq data offer a more granule view of cell-type-specific alterations.

RESULTS

In this study, we identified a comprehensive mutational landscape of recurrent genomic and transcriptomic variations, including single-nucleotide polymorphisms, CNVs and differentially expressed genes, in IPF populations, which may play a significant role in the development and progression of IPF.

CONCLUSIONS

Our study provided valuable insights into the genetic and transcriptomic variations associated with IPF, revealing changes in gene expression that may contribute to disease development and progression. These findings highlight the importance of an integrative approach to understanding the molecular mechanisms underlying IPF and may pave the way for identifying potential therapeutic targets.

[Efficacy and safety of pulsed radiofrequency combined with gabapentin in the treatment of acute herpetic neuralgia]

Objective: To explore the clinical efficacy and safety of pulsed radiofrequency (PRF) combined with gabapentin in the treatment of acute herpetic neuralgia (AHN). Methods: A total of 123 AHN patients were retrospectively selected in Henan Provincial People's Hospital from November 2019 to July 2022, who were divided into two groups based on treatment methods: control group (treated with gabapentin, n=61) and study group (treated with gabapentin and PRF, n=62). The visual analog scale (VAS) was utilized for pain severity assessment and the self-rating scale for sleep (SRSS) was utilized for sleep quality evaluation. The differences in serum levels of interleukin (IL)-10, chemokine ligand 10 (CXCL-10), prostaglandin E2 (PGE2), cyclooxygenase-2 (COX-2), IL-2 and IL-6 before and after treatment were compared between the two groups. The overall treatment effectiveness and the occurrence rates of postherpetic neuralgia and adverse reactions were evaluated in both groups. Results: Among the study group patients, 28 were male and 34 were female, and the age was (62.8±8.5) years. Among the control group patients, 35 were male and 26 were female, and the age was (64.0±7.8) years. The VAS scores of the study group before and after treatment were 7.96±1.33 and 1.52±0.60, respectively, while the control group were 7.68±1.52 and 2.70±0.64. The SRSS scores before and after treatment in the study group were 31.74±5.90 and 12.06±2.81, respectively, while those in the control group were 33.10±5.54 and 14.14±2.96, respectively. Before treatment, there were no statistically differences of the VAS scores and SRSS scores in both groups (all P>0.05). After treatment, the VAS scores and SRSS scores in both groups decreased compared with before treatment (all P<0.05), the study group's VAS scores and SRSS scores were lower than those in the control group (all P<0.05). Before treatment, there were no statistically differences of the serum levels of IL-10, CXCL-10, PGE2, COX-2, IL-2 and IL-6 in both groups (all P>0.05). After treatment, the serum levels of IL-10, CXCL-10, PGE2, COX-2 and IL-6 in both groups decreased compared with before treatment, while the IL-2 level increased. Additionally, the study group had lower serum levels of IL-10, PGE2, COX-2 and IL-6 compared with the control group (all P<0.05). After treatment, the study group had 35 cases of cure, 26 cases of effectiveness, and 1 case of ineffectiveness, while the control group had 22 cases of cure, 31 cases of effectiveness, and 8 cases of ineffectiveness. The overall treatment efficacy of the study group was better than that of the control group (P=0.012). The incidence of postherpetic neuralgia in the study group after treatment was 16.1% (10/62), which was lower than that in the control group, which was 37.7% (23/61) (P<0.05). There were no statistically differences of the occurrence rates of adverse reactions in both groups (all P>0.05). Conclusion: Combining PRF with gabapentin for the treatment of AHN demonstrates better overall efficacy and safety, which can more effectively alleviate pain, improve sleep, and reduce inflammatory cytokine levels.

[Effects of artificial dermis combined with autologous skin in repairing the wounds with exposed bone and/or tendon in fingers of children after electric burns]

Objective: To explore the effects of artificial dermis combined with autologous skin in repairing the wounds with exposed bone and/or tendon in fingers of children after electric burns. Methods: A retrospective observational study was conducted. From January 2017 to December 2022, 14 children with bone and/or tendon exposed wounds in fingers after electric burns who met the inclusion criteria were admitted to Zhengzhou First People's Hospital, including 9 males and 5 females, aged 2 to 11 years. A total of 38 fingers were affected, with 1 wound per finger. After debridement, artificial dermal coverage combined with vacuum sealing drainage was performed in all the wounds in the first stage, with wound area of 2.0 cm×1.0 cm-4.5 cm×2.5 cm after debridement. The second stage surgery was performed to close the wound with autologous thin intermediate thickness skin graft. Then the children were told to perform functional rehabilitation exercise as early as possible. The survival of autologous skin graft was observed at the 7th day after the second stage surgery. The wound healing time was recorded. After 12 months of follow-up, the Vancouver scar scale was used to evaluate the scar hyperplasia at the skin grafting site of the affected finger; the total action mobility (TAM) of the affected finger joint was measured for evaluating the functional recovery of the affected finger; a self-made efficacy satisfaction rating table was used to investigate the parents' satisfaction with the curative effect of the children. Results: At the 7th day after the second stage surgery, all the children had good survival of autologous skin grafts. The wound healing time was (24.1±2.7) d. After 12 months of follow-up, the scar score at the skin grafting site of the affected finger was 5.2±2.4; the TAM of the affected finger joint was (177±40)°; the functional assessment was good in 12 fingers, medium in 23 fingers, and poor in 3 fingers; the parents' satisfaction with the curative effect of the children in the survey was very satisfied in 10 cases, satisfied in 3 cases, and dissatisfied in 1 case. Conclusions: The combination of artificial dermis and autologous thin intermediate thickness skin graft is an alternative surgical method that can effectively repair the bone and/or tendon exposed wounds in fingers of children after electric burns. After wound healing, the scars are slight, the finger function is well recovered, and the parents of the children are highly satisfied with the curative effect of the children, which is worthy of clinical promotion.

Creating NADP+ -Specific Formate Dehydrogenases from Komagataella phaffii by Enzymatic Engineering

Most natural formate dehydrogenases (FDHs) exhibit NAD+ specificity, making it imperative to explore the engineering of FDH cofactor specificity for NADPH regeneration systems. The endogenous FDH of Komagataella phaffii (K. phaffii), termed KphFDH, is a typical NAD+ -specific FDH. However, investigations into engineering the cofactor specificity of KphFDH have yet to be conducted. To develop an NADP+ -specific variant of KphFDH, we selected D195, Y196, and Q197 as mutation sites and generated twenty site-directed variants. Through kinetic characterization, KphFDH/V19 (D195Q/Y196R/Q197H) was identified as the variant with the highest specificity towards NADP+ , with a ratio of catalytic efficiency (kcat /KM )NADP+ /(kcat /KM )NAD+ of 129.226. Studies of enzymatic properties revealed that the optimal temperature and pH for the reduction reaction of NADP+ catalyzed by KphFDH/V19 were 45 °C and 7.5, respectively. The molecular dynamics (MD) simulation was performed to elucidate the mechanism of high catalytic activity of KphFDH/V19 towards NADP+ . Finally, KphFDH/V19 was applied to an in vitro NADPH regeneration system with Meso-diaminopimelate dehydrogenase from Symbiobacterium thermophilum (StDAPDH/H227V). This study successfully created a KphFDH variant with high NADP+ specificity and demonstrated its practical applicability in an in vitro NADPH regeneration system.

[Clinical research of multisystem inflammatory syndrome in children]

Objective: To analyze the clinical characteristics of children with multisystem inflammatory syndrome (MIS-C) associated with SARS-CoV-2 in China, and to improve the understanding of MIS-C among pediatricians. Methods: Case series study.Collect the clinical characteristics, auxiliary examinations, treatment decisions, and prognosis of 64 patients with MIS-C from 9 hospitals in China from December 2022 to June 2023. Results: Among the 64 MIS-C patients, 36 were boys and 28 were girls, with an onset age being 2.8 (0.3, 14.0) years. All patients suffered from fever, elevated inflammatory indicators, and multiple system involvement. Forty-three patients (67%) were involved in more than 3 systems simultaneously, including skin mucosa 60 cases (94%), blood system 52 cases (89%), circulatory system 54 cases (84%), digestive system 48 cases (75%), and nervous system 24 cases (37%). Common mucocutaneous lesions included rash 54 cases (84%) and conjunctival congestion and (or) lip flushing 45 cases (70%). Hematological abnormalities consisted of coagulation dysfunction 48 cases (75%), thrombocytopenia 9 cases (14%), and lymphopenia 8 cases (13%). Cardiovascular lesions mainly affected cardiac function, of which 11 patients (17%) were accompanied by hypotension or shock, and 7 patients (12%) had coronary artery dilatation.Thirty-six patients (56%) had gastrointestinal symptoms, 23 patients (36%) had neurological symptoms. Forty-five patients (70%) received the initial treatment of intravenous immunoglobulin in combination with glucocorticoids, 5 patients (8%) received the methylprednisolone pulse therapy and 2 patients (3%) treated with biological agents, 7 patients with coronary artery dilation all returned to normal within 6 months. Conclusions: MIS-C patients are mainly characterized by fever, high inflammatory response, and multiple organ damage. The preferred initial treatment is intravenous immunoglobulin combined with glucocorticoids. All patients have a good prognosis.

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.

[Research progress of phage therapy in orthopedic implant-related infection]

The widespread application of implantable materials has brought about a corresponding increase in implant-related complications, with implant-associated infections being the most critical. Biofilms, which often form on these implants, can significantly impede the effectiveness of traditional antibiotic therapies. Therefore, strategies such as surgical removal of infected implants and prolonged antibiotic treatment have been acknowledged as effective measures to eradicate these infections. However,the challenges of antibiotic resistance and biofilm persistence often result in recurrent or hard-to-control infections, posing severe health threats to patients. Recent studies suggest that phages, a type of virus, can directly eliminate pathogenic bacteria and degrade biofilms. Furthermore, clinical trials have demonstrated promising therapeutic results with the combined use of phages and antibiotics. Consequently, this innovative therapy holds significant potential as an effective solution for managing implant-associated infections. This paper rigorously investigates and evaluates the potential value of phage therapy in addressing orthopedic implant-associated infections, based on a comprehensive review of relevant scientific literature.

Thyroid hormone-responsive protein mediates the response of chicken liver to fasting mainly through the cytokine-cytokine receptor interaction pathway

1. The objective of this study was to explore the mediating role of thyroid hormone-responsive protein (THRSP) in the response of chicken liver to fasting.2. A batch of 7-d-old chicks with similar body weights were randomly divided into the control group and the fasting group (n = 10). The control group was fed ad libitum, while the test group fasted for 24 h. The liver and pectoral muscle tissues were collected. Chicken primary hepatocytes or myocytes were treated with different concentrations of thyroxine, glucose, insulin, oleic acid and palmitic acid, separately. Chicken primary hepatocytes were transfected with THRSP overexpression vector vs. empty vector, and the cells were used for transcriptome analysis. The mRNA expression of THRSP and other genes was determined by quantitative PCR.3. The expression of THRSP in chicken liver and pectoral muscle tissues was significantly inhibited by fasting (P < 0.05). In chicken primary hepatocytes, the expression of THRSP was significantly induced by thyroxine (0.25, 0.5, 1 mmol/l), glucose (50, 100 mmol/l), and insulin (20 nmol/l), and was significantly inhibited by palmitic acid (0.125, 0.25 mmol/l). In the myocytes, expression of THRSP was significantly induced by thyroxine (0.25, 0.5, 1 mmol/l), glucose (50 mmol/l) and oleic acid (0.125, 0.25 mmol/l), was significantly inhibited by insulin (5 nmol/l) and was not significantly affected by palmitic acid.4. Transcriptome analysis showed that overexpression of THRSP significantly affected the expression of 1411 DEGs, of which 1007 were up-regulated and 404 were down-regulated. The GO term and KEGG pathway enrichment analyses showed that these DEGs were mainly enriched in the interaction between cytokine and cytokine receptor and its regulation and signal transduction, cell growth and apoptosis and its regulation, immune response and retinol metabolism.5. In conclusion, the THRSP gene mediates biological effects of fasting by influencing the expressional regulation of the genes related to biological processes such as cytokine-cytokine receptor interaction, cell growth and apoptosis, immune response, retinol metabolism, including TGM2, HSD17B2, RUNX3, IRF1, ANKRD6, UPP2, IKBKE, and PYCR1 genes, in chicken liver.

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.