Transmission of fluoroquinolones resistance among multidrug-resistant tuberculosis in Shanghai, China: a retrospective population-based genomic epidemiology study

Fluoroquinolones (FQ) are essential for the treatment of multidrug-resistant tuberculosis (MDR-TB). The FQ resistance (FQ-R) rate in MDR-TB in China and its risk factors remain poorly understood. We conducted a retrospective, population-based genomic epidemiology study of MDR-TB patients in Shanghai, China, from 2009 to 2018. A genomic cluster was defined as strains with genetic distances ≤ 12 single nucleotide polymorphisms. The transmitted FQ-R was defined as the same FQ resistance-conferring mutations shared by ≥ 2 strains in a genomic cluster. We used multivariable logistic regression analysis to identify the risk factors for drug resistance. Among the total 850 MDR-TB patients included in the study, 72.8% (619/850) were male, the median age was 39 (interquartile range 28, 55) years, 52.7% (448/850) were migrants, and 34.5% (293/850) were previously treated patients. Most of the MDR-TB strains belong to the Beijing lineage (91.7%, 779/850). Overall, the genotypic resistance rate of FQ was 34.7% (295/850), and 47.1% (139/295) FQ-R patients were in genomic clusters, of which 98 (33.2%, 98/295) were presumed as transmitted FQ-R. Patients with treatment-naïve (aOR = 1.84; 95% CI: 1.09, 3.16), diagnosed in a district-level hospital (aOR = 2.69; 95% CI: 1.56, 4.75), and streptomycin resistance (aOR = 3.69; 95% CI: 1.65, 9.42) were significantly associated with the transmission of FQ-R. In summary, the prevalence of FQ-R among MDR-TB patients was high in Shanghai, and at least one-third were transmitted. Enforced interventions including surveillance of FQ drug susceptibility testing and screening among MDR-TB before initiation of treatment were urgently needed.

Cold plasma: A success road to mycotoxins mitigation and food value edition

Mycotoxins are common in many agricultural products and may harm both animals and humans. Dietary mycotoxins are reduced via physical, chemical, and thermal decontamination methods. Chemical residues are left behind after physical and chemical treatments that decrease food quality. Since mycotoxins are heat-resistant, heat treatments do not completely eradicate them. Cold plasma therapy increases food safety and shelf life. Cold plasma-generated chemical species may kill bacteria quickly at room temperature while leaving no chemical residues. This research explains how cold plasma combats mold and mycotoxins to guarantee food safety and quality. Fungal cells are damaged and killed by cold plasma species. Mycotoxins are also chemically broken down by the species, making the breakdown products safer. According to a preliminary cold plasma study, plasma may enhance food shelf life and quality. The antifungal and antimycotoxin properties of cold plasma benefit fresh produce, agricultural commodities, nuts, peppers, herbs, dried meat, and fish.

Design and synthesis of pyrene-based probes and their fluorescent detection of Sb(III)

A series of pyrene-based fluorescent (FL) probes for Sb(III) were designed and synthesized. All of them exhibited luminescence by pyrene excimers in the mixture of DMSO and water and showed enhanced emission with the addition of Sb(III). By comparing their FL response to Sb(III), the effects of intramolecular hydrogen bond, inductive effect, and steric effect were investigated. Meanwhile, the FL enhancement factor of the best performing probe reached 10.28 and the detection limit was calculated to be 0.0535 mg/L, indicating that it might be used as a potential candidate for the treatment of Sb(III) in printing and dyeing wastewater.

Characterization of mung bean endogenous proteases and globulins and their effects on the production of mung bean protein

Mung bean protein possesses several health benefits, and aqueous processing methods are used for its production. However, mung bean protein yields are different with different methods, which are actually different in conditions (e.g., pH, temperature, and time). Herein, liquid chromatography tandem mass spectrometry identified 28 endopeptidases and exopeptidases in mung bean protein extract, and the positions of 8S and 11S globulins on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gel were confirmed in our experimental conditions. The SDS-PAGE, trichloroacetic acid-nitrogen solubility index, and free amino acid analysis revealed that (1) 8S globulins showed strong resistance to the endopeptidases (optimal at pH 5 and 50 °C) at pH 3-9, and 11S globulin exhibit strong resistance expect at pH 3-3.5; (2) the exopeptidases (optimal at pH 6 and 50 °C) preferred to liberate methionine and tryptophan. These proteases negatively affected protein yield, and short production time and low temperature were recommended.

Cnidii Fructus: A traditional Chinese medicine herb and source of antiosteoporotic drugs

BACKGROUND

Osteoporosis (OP) is a prevalent chronic metabolic bone disease for which limited countermeasures are available. Cnidii Fructus (CF), primarily derived from Cnidium monnieri (L.) Cusson., has been tested in clinical trials of traditional Chinese medicine for the management of OP. Accumulating preclinical studies indicate that CF may be used against OP.

MATERIALS AND METHODS

Comprehensive documentation and analysis were conducted to retrieve CF studies related to its main phytochemical components as well as its pharmacokinetics, safety and pharmacological properties. We also retrieved information on the mode of action of CF and, in particular, preclinical and clinical studies related to bone remodeling. This search was performed from the inception of databases up to the end of 2022 and included PubMed, China National Knowledge Infrastructure, the National Science and Technology Library, the China Science and Technology Journal Database, Weipu, Wanfang, the Web of Science and the China National Patent Database.

RESULTS

CF contains a wide range of natural active compounds, including osthole, bergapten, imperatorin and xanthotoxin, which may underlie its beneficial effects on improving bone metabolism and quality. CF action appears to be mediated via multiple processes, including the osteoprotegerin (OPG)/receptor activator of nuclear factor-κB ligand (RANKL)/receptor activator of nuclear factor-κB (RANK), Wnt/β-catenin and bone morphogenetic protein (BMP)/Smad signaling pathways.

CONCLUSION

CF and its ingredients may provide novel compounds for developing anti-OP drugs.

[Progress in novel biomarkers of anti-tuberculosis drug-induced liver injury]

Anti-tuberculosis drug-induced liver injury(ATB-DILI) is the most common adverse reaction during anti-tuberculosis therapy in tuberculosis patients. At present, the diagnosis of ATB-DILI is mainly based on traditional biomarkers such as transaminases, but these indicators have low specificity for liver toxicity, they cannot explain the mechanism of liver injury and the early onset of ATB-DILI. Based on the prediction of disease severity, treatment and prevention, this paper described the current potential biomarkers of ATB-DILI.

A Machine learning model for predicting sepsis based on an optimized assay for microbial cell-free DNA sequencing

OBJECTIVE

To integrate an enhanced molecular diagnostic technique to develop and validate a machine-learning model for diagnosing sepsis.

METHODS

We prospectively enrolled patients suspected of sepsis from August 2021 to August 2023. Various feature selection algorithms and machine learning models were used to develop the model. The best classifier was selected using 5-fold cross validation set and then was applied to assess the performance of the model in the testing set. Additionally, we employed the Shapley Additive exPlanations (SHAP) method to illustrate the effects of the features.

RESULTS

We established an optimized mNGS assay and proposed using the copies of microbe-specific cell-free DNA per milliliter of plasma (CPM) as the detection signal to evaluate the real burden, with strong precision and high accuracy. In total, 237 patients were eligible for participation, which were randomly assigned to either the training set (70 %, n = 165) or the testing set (30 %, n = 72). The random forest classifier achieved accuracy, AUC and F1 scores of 0.830, 0.918 and 0.856, respectively, outperforming other machine learning models in the training set. Our model demonstrated clinical interpretability and achieved good prediction performance in differentiating between bacterial sepsis and non-sepsis, with an AUC value of 0.85 and an average precision of 0.91 in the testing set. Based on the SHAP value, the top nine features of the model were PCT, CPM, CRP, ALB, SBPmin, RRmax, CREA, PLT and HRmax.

CONCLUSION

We demonstrated the potential of machine-learning approaches for predicting bacterial sepsis based on optimized mcfDNA sequencing assay accurately.

Perioperative management of a patient with unexpectedly detected early-stage ovarian mucinous carcinoma combined with progressive bulbar paralysis: a case report and literature review

BACKGROUND

Giant ovarian cysts (GOCs)complicated with progressive bulbar paralysis (PBP) are very rare, and no such literature about these cases have been reported. Through the diagnosis and treatment of this case, the perioperative related treatment of such patients was analyzed in detail, and early-stage ovarian mucinous carcinoma was unexpectedly found during the treatment, which provided reference for clinical diagnosis and treatment of this kind of diseases.

CASE PRESENTATION

In this article, we reported a 38-year-old female patient. The patient was diagnosed with PBP 2 years ago. Examination revealed a large fluid-dominated cystic solid mass in the pelvis measuring approximately 28.6×14.2×8.0 cm. Carbohydrate antigen19-9(CA19-9) 29.20 IU/mL and no other significant abnormalities were observed. The patient eventually underwent transabdominal right adnexal resection under regional anesthesia, epidural block. Postoperative pathology showed mucinous carcinoma in some areas of the right ovary. The patient was staged as stage IA, and surveillance was chosen. With postoperative follow-up 1 month later, her CA19-9 decreased to 14.50 IU/ml.

CONCLUSIONS

GOCs combined with PBP patients require a multi-disciplinary treatment. Preoperative evaluation of the patient's PBP progression, selection of the surgical approach in relation to the patient's fertility requirements, the nature of the ovarian cyst and systemic condition are required. Early mucinous ovarian cancer accidentally discovered after operation and needs individualized treatment according to the guidelines and the patient's situation. The patient's dysphagia and respiratory function should be closely monitored during the perioperative period. In addition, moral support from the family is also very important.

Visible-Light-Promoted Deoxygenative Alkylation of Quinoxalin-2(1H)-ones with Activated Alcohols

A one-pot strategy for deoxygenative alkylation of alcohols with quinoxalin-2(1H)-ones was developed by using xanthate salts as alcohol-activating groups for radical generation in the presence of tricyclohexylphosphine under visible-light-promoted conditions. The remarkable features of this reaction include a broad substrate scope, excellent functional group tolerance, mild conditions, and simple operation. Moreover, the synthetic utility of this reaction was validated by the success of two-step one-pot reactions, scale-up synthesis, and chemoselective radical monodeoxygenation of diols.

Toxicodynamic of combined mycotoxins: MicroRNAs and acute-phase proteins as diagnostic biomarkers

Mycotoxins, ubiquitous contaminants in food, present a global threat to human health and well-being. Mitigation efforts, such as the implementation of sound agricultural practices, thorough food processing, and the advancement of mycotoxin control technologies, have been instrumental in reducing mycotoxin exposure and associated toxicity. To comprehensively assess mycotoxins and their toxicodynamic implications, the deployment of effective and predictive strategies is imperative. Understanding the manner of action, transformation, and cumulative toxic effects of mycotoxins, moreover, their interactions with food matrices can be gleaned through gene expression and transcriptome analyses at cellular and molecular levels. MicroRNAs (miRNAs) govern the expression of target genes and enzymes that play pivotal roles in physiological, pathological, and toxicological responses, whereas acute phase proteins (APPs) exert regulatory control over the metabolism of therapeutic agents, both endogenously and posttranscriptionally. Consequently, this review aims to consolidate current knowledge concerning the regulatory role of miRNAs in the initiation of toxicological pathways by mycotoxins and explores the potential of APPs as biomarkers following mycotoxin exposure. The findings of this research highlight the potential utility of miRNAs and APPs as indicators for the detection and management of mycotoxins in food through biological processes. These markers offer promising avenues for enhancing the safety and quality of food products.

Comparative analysis for the impacts of VOC subgroups and atmospheric oxidation capacity on O3 based on different observation-based methods at a suburban site in the North China Plain

The persistent O3 pollution in the Beijing-Tianjin-Hebei (BTH) region remains unresolved, largely due to limited comprehension of O3-precursor relationship and photochemistry drivers. In this work, intraday O3 sensitivity evolution from VOC-limited (volatile organic compound) regime in the forenoon to transition regime in the late afternoon was inferred by relative incremental reactivity (RIR) in summer 2019 at Xianghe, a suburban site in BTH region, suggesting that VOC-focused control policy could combine with stringent afternoon NOx control. Then detailed impacts of VOC subgroups on O3 formation were further comprehensively quantified by parametric OH reactivity (KOH), O3 formation potential (OFP), as well as RIR weighted value and O3 formation path tracing (OFPT) approach based on photochemical box model. O3 episode days corresponded to stronger O3 formation, depicted by higher KOH (10.4 s-1), OFP (331.7 μg m-3), RIR weighted value (1.2), and F(O3)-OFPT (15.5 ppbv h-1). High proportions of isoprene and OVOCs (oxygenated VOCs) to the total KOH and the OFPT method were demonstrated whereas results of OFP and RIR-weighted presented extra great impacts of aromatics on O3 formation. The OFPT approach captured the process that has already happened and included final O3 response to the original VOC, thus reliable for replicating VOC impacts. The comparison results of the four methods showed similarities when utilizing KOH and OFPT methods, which reveals that the potential applicability of simple KOH for contingency VOC control and more complex OFPT method for detailed VOC- and source-oriented control during policy-making. To investigate propulsion of VOC-involved O3 photochemistry, atmospheric oxidation capacity (AOC) was quantified by two atmospheric oxidation indexes (AOI). Both AOIp_G (7.0 × 107 molec cm-3 s-1, potential AOC calculated by oxidation reaction rates) and AOIe_G (8.5 μmol m-3, estimated AOC given redox electron transfer for oxidation products) were stronger on O3 episode days, indicating that AOC promoted the radical cycling initiated from VOC oxidation and subsequent O3 production. Result-oriented AOIe_G reasonably characterized actual AOC inferred by good linear correlation between AOIe_G and O3 concentrations compared to process-oriented AOIp_G. Therefore, with continuous NOx abatement, AOIe_G should be considered to represent actual AOC, also O3-inducing ability.

Dissociation of drug and negative emotional cue induced attentional bias in individuals with methamphetamine-use disorder

BACKGROUND AND OBJECTIVES

Although both drugs and negative emotions can trigger drug craving or relapse in individuals with methamphetamine-use disorder (MUD), it remains unclear whether individuals with MUD have attentional biases toward both drug and negative emotional cues and whether this bias involves attention orientation or difficulty in attention disengagement. This study aimed to measure different components of attentional bias toward drug-related and negative emotional cues in individuals with MUD.

METHODS

Two dot-probe tasks were used to investigate attentional bias toward drug (drug task) and negative emotional cues (emotion task) in individuals with MUD. Forty-three males with MUD (average age of 43.44 ± 11.91 years, average drug-use duration of 11.35 ± 8.39 years) participated in the study voluntarily.

RESULTS

There was a significant interaction between the task type and location (p = .01). Specifically, for drug cues, participants showed significant difficulty in attention disengagement toward drug cues (p = .01); however, no attention orientation (p = .46). For negative emotional cues, neither significant attention orientation (p = .07) nor significant difficulty in attention disengagement (p = .50) was found.

CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE

Attentional bias in individuals with MUD was highly selective for drug cues; thus, difficulty in attention disengagement from drug cues can be considered a potential mediating mechanism for attentional bias modification interventions for individuals with MUD. This study served to generate hypotheses or suggest future experiments on interventions for individuals with MUD.

Association between different regional lymph node metastases of papillary thyroid carcinoma in adolescents and young adults

Adolescents and young adults (AYA) describe the demographic aged between 15-39 years diagnosed with cancer. This group is particularly at risk of papillary thyroid carcinoma (PTC) with a greater severity compared with other ages. Through comparative design, the present study aimed to quantify central lymph node metastasis (CLNM) risk in AYAs. A total of 463 AYA patients with PTC and 489 patients >39 years old with PTC from Ningbo Medical Center Lihuili Hospital (Ningbo, China) were enrolled. Details such as demographic data, serum indices and fine-needle aspiration from the Electronic Medical Records System were extracted and analyzed. AYA patients had significantly higher rates of ipsilateral Hashimoto thyroiditis, thyroid capsular invasion (TCI), CLNM, larger tumors and more positive central lymph nodes (CLN). Independent risk factors of CLNM in AYA patients were as follows: Male sex, presence of TCI, multifocality, bilateral disease and maximum tumor diameter (MTD) ≥1.0 cm. Independent risk factors of lateral lymph node metastasis in AYAs with CLNM were as follows: MTD ≥1.0 cm, maximum diameter of positive CLN ≥1.0 cm, and presence of ipsilateral nodular goiter. Furthermore, AYA patients with PTC displayed significantly greater aggression in primary tumor invasion and neck lymph node metastasis. Based on these findings, a treatment stratification chart was created to guide the PTC treatment approach for AYAs. The present study is registered at the Chinese Clinical Trials Registry (trial registration no. ChiCTR2200064921) in November 2022.

Identification of S100A8/A9 involved in thromboangiitis obliterans development using tandem mass tags-labeled quantitative proteomics analysis

Thromboangiitis obliterans (TAO) is characterized by inflammation and obstruction of small-and medium-sized distal arteries, with limited pharmacotherapies and surgical interventions. The precise pathogenesis of TAO remains elusive. By utilizing the technology of tandem mass tags (TMT) for quantitative proteomics and leveraging bioinformatics tools, a comparative analysis of protein profiles was conducted between normal and TAO rats to identify key proteins driving TAO development. The results unveiled 1385 differentially expressed proteins (DEPs) in the TAO compared with the normal group-comprising 365 proteins with upregulated expression and 1020 proteins with downregulated expression. Function annotation through gene ontology indicated these DEPs mainly involved in cell adhesion, positive regulation of cell migration, and cytosol. The principal signaling pathways involved regulation of the actin cytoskeleton, vascular smooth contraction, and focal adhesion. The roles of these DEPs and associated signaling pathways serve as a fundamental framework for comprehending the mechanisms underpinning the onset and progression of TAO. Furthermore, we conducted a comprehensive evaluation of the effects of S100A8/A9 and its inhibitor, paquinimod, on smooth muscle cells (SMCs) and in TAO rats. We observed that paquinimod reduces SMCs proliferation and migration, promotes phenotype switching and alleviates vascular stenosis in TAO rats. In conclusion, our study revealed that the early activation of S100A8/A9 in the femoral artery is implicated in TAO development, targeting S100A8/A9 signaling may provide a novel approach for TAO prevention and treatment.

Design, Synthesis, Formulation, and Bioevaluation of Trisubstituted Triazines as Highly Selective mTOR Inhibitors for the Treatment of Human Breast Cancer

The aberrant activation of the PI3K/mTOR signaling pathway is implicated in various human cancers. Thus, the development of inhibitors targeting mTOR has attracted considerable attention. In this study, we used a structure-based drug design strategy to discover a highly potent and kinase-selective mTOR inhibitor 24 (PT-88), which demonstrated an mTOR inhibitory IC50 value of 1.2 nM without obvious inhibition against another 195 kinases from the kinase profiling screening. PT-88 displayed selective inhibition against MCF-7 cells (IC50: 0.74 μM) with high biosafety against normal cells, in which autophagy induced by mTOR inhibition was implicated. After successful encapsulation in a lipodisc formulation, PT-88 demonstrated favorable pharmacokinetic and biosafety profiles and exerted a large antitumor effect in an MCF-7 subcutaneous bearing nude mice model. Our study shows the discovery of a highly selective mTOR inhibitor using a structure-based drug discovery strategy and provides a promising antitumor candidate for future study and development.

Confirmation of pain-related neuromodulation mechanism of Bushen Zhuangjin Decoction on knee osteoarthritis

ETHNOPHARMACOLOGICAL RELEVANCE

Bushen Zhuangjin Decoction (BZD) are an herbal compound commonly used to treat osteoarthritis (OA) in China.

AIM OF THE STUDY

This study aimed to verify the mechanism of Bushen Zhuangjin Decoction in relieving the pain of knee osteoarthritis.

MATERIALS AND METHODS

Network pharmacology evaluation was used to discover the potential targets of BZD to relieve pain in KOA. The therapeutic effects of BZD treatment on KOA pain using histomorphology, behavioral assessments, suspension chip analysis, and ultra-high performance liquid chromatography/tandem mass spectrometry (UHPLC-MS/MS) assays. The functional magnetic resonance imaging was used to explore the effects of BZD treatment on brain function associated to KOA.

RESULTS

Network pharmacological analysis revealed the association between the analgesic effect of BZD on KOA and the pain signaling neurotransmitter 5-HT. Subsequently, we conducted experiments to verify the therapeutic effect of BZD on pain in KOA animal models. Behavioral tests demonstrated that the pain threshold of knee osteoarthritis rats decreased in PWT and PWL, but BZD was able to increase the pain threshold. Histopathological staining indicated thinning of the cartilage layer and sparse trabeculae in the subchondral bone. Suspension chip analysis revealed a significant increase in pro-inflammatory factors of IL-1α, IL-5, IL-12, IL-17A, RANTES, TNF-α and M-CSF in KOA, along with a significant decrease in anti-inflammatory factor of IL-13. However, BZD treatment decreased the expression of pro-inflammatory factors and increased the content of anti-inflammatory factor. UHPLC-MS/MS analysis showed a significant decrease in the serum levels of GABA, E, GSH, Kyn, Met, and VMA in KOA, which were significantly increased by BZD. Conversely, the serum levels of TrpA, TyrA, Spd, and BALa were significantly increased in KOA and significantly decreased by BZD. ELISA and Western blot analysis showed increased expression of subchondral bone pain-related neuropeptides SP, CGRP, TH, NPY, VEGFA, 5-HT3 in KOA, which were decreased in BZD. Functional magnetic resonance imaging demonstrated that BZD exerts its therapeutic effect on KOA by modulating the activity and functional connections of the cortex, hypothalamus, and hippocampus.

CONCLUSIONS

This study confirmed the significant role of pain-related neuromodulation mechanisms in the analgesic therapy of BZD and provides a theoretical foundation for using BZD as a traditional Chinese medical treatment for KOA pain.

Self-Assembling Triple-Helix Recombinant Collagen Hydrogel Enriched with Tyrosine

The self-assembly of collagen within the human body creates a complex 3D fibrous network, providing structural integrity and mechanical strength to connective tissues. Recombinant collagen plays a pivotal role in the realm of biomimetic natural collagen. However, almost all of the reported recombinant collagens lack the capability of self-assembly, severely hindering their application in tissue engineering and regenerative medicine. Herein, we have for the first time constructed a series of self-assembling tyrosine-rich triple helix recombinant collagens, mimicking the structure and functionality of natural collagen. The recombinant collagen consists of a central triple-helical domain characterized by the (Gly-Xaa-Yaa)n sequence, along with N-terminal and C-terminal domains featuring the GYY sequence. The introduction of GYY has a negligible impact on the stability of the triple-helical structure of recombinant collagen while simultaneously promoting its self-assembly into fibers. In the presence of [Ru(bpy)3]Cl2 and APS as catalysts, tyrosine residues in the recombinant collagen undergo covalent cross-linking, resulting in a hydrogel with exceptional mechanical properties. The recombinant collagen hydrogel exhibits outstanding biocompatibility and bioactivity, significantly enhancing the proliferation, adhesion, migration, and differentiation of HFF-1 cells. This innovative self-assembled triple-helix recombinant collagen demonstrates significant potential in the fields of tissue engineering and medical materials.

Proxy Importance Based Haptic Retargeting With Multiple Props in VR

In virtual reality applications, in addition to visual feedback, real objects can be used as props for virtual objects to provide passive haptic feedback, which greatly enhances user immersion. Usually, real object props are not one-to-one correspondence with virtual objects. Haptic retargeting technique is proposed to establish the virtual-real correspondence by introducing an offset between the virtual hand and the real hand. Sometimes, the offset is too large to cause user discomfort, and it is necessary to introduce a reset between two haptic retargeting operations to force the virtual hand and the real hand to coincide in order to eliminate the offset. However, too many resets can interfere with this immersion. To address this problem, we propose a haptic retargeting method based on proxy importance calculation using multiple props in virtual reality. The concept of proxy importance for props is introduced first, and then a proxy importance based prop selection and placement method for moving virtual objects are proposed. We also improve the performance of our method by using the props' weighted proxy importance strategy for multi-user collaboration. Compared to the state-of-the-art methods, our method significantly reduces the number of resets, the task completion time, hand movement distances, and task load without the cost of cybersickness in the single-user task. In the multi-user collaborative task, our method also achieves significant improvement using the strategy that weights the proxy importance of the props.

Associations between static and dynamic changes of platelet counts and in-hospital mortality in critical patients with acute heart failure

To investigate the predictive value of baseline platelet count and its short-term dynamic changes in the prognosis of patients with acute heart failure (AHF) in the intensive care unit. Patients diagnosed with AHF in the medical information mart for intensive care III and their clinical data were retrospectively filtered. Patients were divided into survivor and non-survivor groups based on their prognosis during hospitalization, and differences in baseline data between groups were compared. Logistic regression models and restricted cubic spline (RCS) plots were performed to evaluate the relationship between baseline platelet counts and in-hospital mortality. Changes and trends in platelet counts were compared between the survivor and non-survivor groups after adjusting for confounders with the generalized additive mixing model (GAMM). A total of 2930 critical patients with acute heart failure were included, of which 2720 were survivors and 210 were non-survivors. Multiple logistic regression models revealed that baseline platelet count was an independent factor in hospital mortality (OR 0.997, 95% CI 0.994-0.999, P-value = 0.018). The RCS plot demonstrated a U-shaped dose-response relationship between baseline platelet count and in-hospital mortality. GAMM analysis suggested that the platelet counts decreased and then increased in the survivor group and gradually decreased in the non-survivor group, with a gradual increase of difference between two groups. After adjusting for confounders, the mean daily increase was -6.014 (95% CI -7.076-4.953, P-value < 0.001). Baseline platelet demonstrated a U-shaped dose-response relationship with adverse outcomes in critical patients with AHF. Early elevation of platelet was correlated with higher in-hospital mortality, indicating that tracking early changes in platelet might help determine the short-term prognosis of critical patients with AHF.

Explainable ensemble machine learning revealing the effect of meteorology and sources on ozone formation in megacity Hangzhou, China

Megacity Hangzhou, located in eastern China, has experienced severe O3 pollution in recent years, thereby clarifying the key drivers of the formation is essential to suppress O3 deterioration. In this study, the ensemble machine learning model (EML) coupled with Shapley additive explanations (SHAP), and positive matrix factorization were used to explore the impact of various factors (including meteorology, chemical components, sources) on O3 formation during the whole period, pollution days, and typical persistent pollution events from April to October in 2021-2022. The EML model achieved better performance than the single model, with R2 values of 0.91. SHAP analysis revealed that meteorological conditions had the greatest effects on O3 variability with the contribution of 57 %-60 % for different pollution levels, and the main drivers were relative humidity and radiation. The effects of chemical factors on O3 formation presented a positive response to volatile organic compounds (VOCs) and fine particulate matter (PM2.5), and a negative response to nitrogen oxides (NOx). Oxygenated compounds (OVOCs), alkenes, and aromatic of VOCs subgroups had higher contribution; additionally, the effects of PM2.5 and NOx were also important and increased with the O3 deterioration. The impact of seven emission sources on O3 formation in Hangzhou indicated that vehicle exhaust (35 %), biomass combustion (16 %), and biogenic emissions (12 %) were the dominant drivers. However, for the O3 pollution days, the effects of biomass combustion and biogenic emissions increased. Especially in persistent pollution events with highest O3 concentrations, the magnitude of biogenic emission effect elevated significantly by 156 % compared to the whole situations. Our finding revealed that the combination of the EML model and SHAP analysis could provide a reliable method for rapid diagnosis of the cause of O3 pollution at different event scales, supporting the formulation of control measures.

Electronic inhomogeneity and phase fluctuation in one-unit-cell FeSe films

One-unit-cell FeSe films on SrTiO3 substrates are of great interest owing to significantly enlarged pairing gaps characterized by two coherence peaks at ±10 meV and ±20 meV. In-situ transport measurement is desired to reveal novel properties. Here, we performed in-situ microscale electrical transport and combined scanning tunneling microscopy measurements on continuous one-unit-cell FeSe films with twin boundaries. We observed two spatially coexisting superconducting phases in domains and on boundaries, characterized by distinct superconducting gaps (Δ 1 ~15 meV vs.Δ 2 ~10 meV) and pairing temperatures (Tp1~52.0 K vs. Tp2~37.3 K), and correspondingly two-step nonlinear V ~ I α behavior but a concurrent Berezinskii-Kosterlitz-Thouless (BKT)-like transition occurring atT BKT ~28.7 K. Moreover, the onset transition temperatureT c onset ~54 K and zero-resistivity temperatureT c zero ~31 K are consistent with Tp1 andT BKT , respectively. Our results indicate the broadened superconducting transition in FeSe/SrTiO3 is related to intrinsic electronic inhomogeneity due to distinct two-gap features and phase fluctuations of two-dimensional superconductivity.

8-Cl-Ado and 8-NH2-Ado synergize with venetoclax to target the methionine-MAT2A-SAM axis in acute myeloid leukemia

Targeting the metabolic dependencies of acute myeloid leukemia (AML) cells is a promising therapeutical strategy. In particular, the cysteine and methionine metabolism pathway (C/M) is significantly altered in AML cells compared to healthy blood cells. Moreover, methionine has been identified as one of the dominant amino acid dependencies of AML cells. Through RNA-seq, we found that the two nucleoside analogs 8-chloro-adenosine (8CA) and 8-amino-adenosine (8AA) significantly suppress the C/M pathway in AML cells, and methionine-adenosyltransferase-2A (MAT2A) is one of most significantly downregulated genes. Additionally, mass spectrometry analysis revealed that Venetoclax (VEN), a BCL-2 inhibitor recently approved by the FDA for AML treatment, significantly decreases the intracellular level of methionine in AML cells. Based on these findings, we hypothesized that combining 8CA or 8AA with VEN can efficiently target the Methionine-MAT2A-S-adenosyl-methionine (SAM) axis in AML. Our results demonstrate that VEN and 8CA/8AA synergistically decrease the SAM biosynthesis and effectively target AML cells both in vivo and in vitro. These findings suggest the promising potential of combining 8CA/8AA and VEN for AML treatment by inhibiting Methionine-MAT2A-SAM axis and provide a strong rationale for our recently activated clinical trial.

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

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

Biological characterization and complete genome analysis of the newly isolated Serratia liquefaciens phage vB_SlqS_ZDD2

A novel lytic phage named vB_SlqS_ZDD2 was isolated from hospital sewage using the double-layer agar method with Serratia liquefaciens ATCC 27592 as the host. BLASTn analysis showed that the genome sequence of phage vB_SlqS_ZDD2 did not resemble any other phages in the NCBI database. Phenotype and phylogeny analysis indicated that this phage might be a new member of the class Caudoviricetes. Phage vB_SlqS_ZDD2 has a dsDNA genome of 49,178 bp with 55% GC content and has 73 open reading frames. This phage exhibited strong lytic activity and a wide range of pH (3-12) and temperature tolerance (below 70℃).

Amanitin-induced variable cytotoxicity in various cell lines is mediated by the different expression levels of OATP1B3

Amanita phalloides is one of the deadliest mushrooms worldwide, causing most fatal cases of mushroom poisoning. Among the poisonous substances of Amanita phalloides, amanitins are the most lethal toxins to humans. Currently, there are no specific antidotes available for managing amanitin poisoning and treatments are lack of efficacy. Amanitin mainly causes severe injuries to specific organs, such as the liver, stomach, and kidney, whereas the lung, heart, and brain are hardly affected. However, the molecular mechanism of this phenomenon remains not understood. To explore the possible mechanism of organ specificity of amanitin-induced toxicity, eight human cell lines derived from different organs were exposed to α, β, and γ-amanitin at concentrations ranging from 0.3 to 100 μM. We found that the cytotoxicity of amanitin differs greatly in various cell lines, among which liver-derived HepG2, stomach-derived BGC-823, and kidney-derived HEK-293 cells are most sensitive. Further mechanistic study revealed that the variable cytotoxicity is mainly dependent on the different expression levels of the organic anion transporting polypeptide 1B3 (OATP1B3), which facilitates the internalization of amanitin into cells. Besides, knockdown of OATP1B3 in HepG2 cells prevented α-amanitin-induced cytotoxicity. These results indicated that OATP1B3 may be a crucial therapeutic target against amanitin-induced organ failure.

Suitability of inorganic coagulants for algae-laden water treatment: Trade-off between algae removal and cell viability, aggregate properties and coagulant residue

Inorganic coagulants could effectively precipitate algae cells but might increase the potential risks of cell damage and coagulant residue. This study was conducted to critically investigate the suitability of polyaluminum (PAC), FeCl3 and TiCl4 for algae-laden water treatment in terms of the trade-off between algal substance removal, cell viability, and coagulant residue. The results showed that an appropriate increase in coagulant dosage contributed to better coagulation performance but severe cell damage and a higher risk of intracellular organic matter (IOM) release. TiCl4 was the most destructive, resulting in 60.85% of the algal cells presenting membrane damage after coagulation. Intense hydrolysis reaction of Ti salts was favorable for the formation of larger and more elongated, dendritic structured flocs than Al and Fe coagulants. TiCl4 exhibited the lowest residue level and remained in the effluents mainly in colloidal form. The study also identified charge neutralization, chemisorption, enmeshment, and complexation as the dominant mechanisms for algae water coagulation by metal coagulants. Overall, this study provides the trade-off analyses between maximizing algae substance removal and minimizing potential damage to cell integrity and is practically valuable to develop the most suitable and feasible technique for algae-laden water treatment.

Targeting microbiota-immune-synaptic plasticity to explore the effect of tea polyphenols on improving memory in the aged type 2 diabetic rat model

OBJECTIVES

The study aimed to explore whether TP could improve memory in the aged type 2 diabetic rat model by regulating microbiota-immune-synaptic plasticity axis.

METHODS

The experiment was divided into two parts. Firstly, to investigate the effects of TP on the physiopathology of the aged T2DM model rats, rats were randomly divided into the Normal control group, the aged group, the Aged T2DM model group, the TP 75, 150, 300 mg/kg groups, the 150 mg/kg Piracetam group and the 3 mg/kg Rosiglitazone group. Then, to further verify whether TP improved memory in aged T2DM rat model by regulating intestinal flora, the fecal microbiota transplantation (FMT) from the rats in the 300 mg/kg TP group into the rats in the aged T2DM model group was carried out. Effects on gut microbiota, colonic integrity (epithelial tight junction proteins), and endotoxemia (serum LPS) were examined, along with synaptic structure, synaptic plasticity-related structural proteins and inflammation signaling of the hippocampus in our study.

RESULTS

Our results demonstrated that TP alleviated memory impairments in the aged T2DM rat model. The specific outcomes were as follows: TP 300 mg/kg corrected the gut dysbacteriosis, alleviated intestinal permeability reduction and peripheral/central inflammation, inhibited the TLR4/NF-κB signaling pathway. Meanwhile, TP improved the synaptic plasticity in the hippocampus of the aged T2DM model rats, whose expressions of SYN, PSD 95, NMDAR1 and GluR1 in hippocampus were significantly up-regulated. Surprisingly, rats of the FMT group displayed the same changes.

DISCUSSION

TP improves the memory in aged T2DM rat model. The mechanism may be related to the alteration of gut flora, which can inhibit hippocampal TLR4/NF-κB signaling to attenuate neuroinflammation, then improve synaptic plasticity. The study proposes that TP interventions aimed at manipulating the gut microbiota may hold great potential as an effective approach for preventing and treating this disease.

Assessment and factors affecting quality of life among patients with Wilson's disease

Wilson's disease is caused by abnormal copper metabolism resulting in deposition in various organs, including the brain, liver, and cornea, thus disrupting organ function. It is characterized by encephalopathy, extrapyramidal symptoms, progressive liver failure, and copper ring deposition in the cornea. Management of this disease should include quality of life maintenance; however, relevant studies on this topic are lacking. This study aimed to assess the factors affecting the quality of life (QoL) of patients with Wilson's disease. A cross-sectional survey using convenience sampling was conducted between July 2020 and March 2021 at the hospital. Data on patient characteristics, 36-item Short-Form General Health Survey, Uniform Wilson Disease Rating Scale, and Hamilton Depression Rating Scale scores were collected. Associations among quality of life depression, anxiety, and Wilson's disease progression were examined using Pearson correlation analysis. Factors affecting the quality of life of patients, including depression, anxiety, liver function, clinical symptoms, diet, liver function, brain magnetic resonance imaging (MRI) findings, disease duration, Barthel Index, and Morse scores were examined using multivariate linear regression analysis. This study included 134 patients with Wilson's disease whose mean age was 29.12 ± 8.59 years. The mean QoL score in the patient group was 71.38 ± 9.55 points and was negatively correlated with anxiety (r = - 0.883, P = 0.000), depression (r = - 0.852 P = 0.000), and clinical symptoms (r = - 0.542, P = 0.000) scores. Anxiety, depression, and clinical symptoms severity are vital factors for the QoL of patients with Wilson's disease. The study provides foundational evidence to design novel interventions, including symptom management, diet, and self-care ability, which can help in improving the quality of life in patients with Wilson's disease and decreasing the burden associated with this disease.

Upfront allogeneic hematopoietic stem cell transplantation for adult T-cell acute lymphoblastic leukemia/lymphoma in first complete remission: a single-center study

BACKGROUND

Real-world data on outcomes of upfront allogeneic hematopoietic stem cell transplantation (allo-HCT) for adult T-cell acute lymphoblastic leukemia/lymphoma (T-ALL) patients in first complete remission (CR1) is still lacking.

METHODS

A single center retrospective study was conducted from 94 consecutive patients received their first allo-HCT between 2010 and 2021, which include 76 patients received upfront allo-HCT and 18 patients received allo-HCT in non-upfront settings.

RESULTS

There were no significant differences in most variables. In the upfront allo-HCT group, 52 (68%) patients achieved CR1 with one cycle of induction regimen. 24 (32%) patients achieved CR1 with more than one cycle. In the non-upfront group, there were 14 patients with active disease and 4 patients in second CR before transplant. The majority of patients received antithymocyte globulin-based graft-versus-host disease prophylaxis. Median follow-up time was 51 months for both groups. 5-year overall survival (OS) was 54% in the upfront allo-HCT group. While, in the non-upfront group, 5-year OS were 19% (P = 0.013). 5-year progression free survival in the upfront group was higher than that in the non-upfront group (50% versus 20%, P = 0.02). 5-year cumulative incidence relapse rate was significantly higher in non-upfront group (64% vs. 32%, P = 0.006). While, there was no difference in the 5-year non-relapse mortality (NRM) rate (19% versus 16%, P = 0.56). The most common cause of death was disease progression. In multivariable analysis, non-upfront allo-HCT (hazard ratios (HR) 2.14, P = 0.03) and HCT-CI (≥ 2) (HR 6.07, P = 0.002) were identified to be associated with worse OS. Non-upfront allo-HCT and HCT-CI (≥ 2) were also found to be independent risk factors for higher relapse rate. While, haploidentical-HCT was found to be associated with increased NRM.

CONCLUSIONS

Our study indicated that allo-HCT remains an important curative treatment for adult patients with T-ALL, especially when it was performed in the upfront setting.

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

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

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

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

Trans-eQTL mapping in gene sets identifies network effects of genetic variants

Nearly all trait-associated variants identified in genome-wide association studies (GWASs) are noncoding. The cis regulatory effects of these variants have been extensively characterized, but how they affect gene regulation in trans has been the subject of fewer studies because of the difficulty in detecting trans-expression quantitative loci (eQTLs). We developed trans-PCO for detecting trans effects of genetic variants on gene networks. Our simulations demonstrate that trans-PCO substantially outperforms existing trans-eQTL mapping methods. We applied trans-PCO to two gene expression datasets from whole blood, DGN (N = 913) and eQTLGen (N = 31,684), and identified 14,985 high-quality trans-eSNP-module pairs associated with 197 co-expression gene modules and biological processes. We performed colocalization analyses between GWAS loci of 46 complex traits and the trans-eQTLs. We demonstrated that the identified trans effects can help us understand how trait-associated variants affect gene regulatory networks and biological pathways.

Independence Threat or Interdependence Threat? The Focusing Effect on Social or Physical Threat Modulates Brain Activity

OBJECTIVE

The neural basis of threat perception has mostly been examined separately for social or physical threats. However, most of the threats encountered in everyday life are complex. The features of interactions between social and physiological threats under different attentional conditions are unclear.

METHOD

The present study explores this issue using an attention-guided paradigm based on ERP techniques. The screen displays social threats (face threats) and physical threats (action threats), instructing participants to concentrate on only one type of threat, thereby exploring brain activation characteristics.

RESULTS

It was found that action threats did not affect the processing of face threats in the face-attention condition, and electrophysiological evidence from the brain suggests a comparable situation to that when processing face threats alone, with higher amplitudes of the N170 and EPN (Early Posterior Negativity) components of anger than neutral emotions. However, when focusing on the action-attention condition, the brain was affected by face threats, as evidenced by a greater N190 elicited by stimuli containing threatening emotions, regardless of whether the action was threatening or not. This trend was also reflected in EPN.

CONCLUSIONS

The current study reveals important similarities and differences between physical and social threats, suggesting that the brain has a greater processing advantage for social threats.

Tibetan medicine Ruyi Zhenbao Pill ameliorates neuropathic pain by inhibiting the CXCL10-CXCR3 pathway in spinal cord of spinal nerve ligation model

ETHNOPHARMACOLOGICAL RELEVANCE

Ruyi Zhenbao Pill (RYZBP) is a traditional Tibetan medicine that has been used for over 300 years in China to treat neurological diseases, specifically neuropathic pain (NP). However, its characteristics and mechanism of action in treating NP remains unclear.

AIM OF THE STUDY

Based on animal experiments and transcriptomics to evaluate the characteristics and mechanism of RYZBP in treating NP.

METHODS

Mice were divided into six groups using random assignment: sham-operation group, spinal nerve ligation (SNL) group, RYZBP low (0.65 g kg-1), medium (1.30 g kg-1), high (2.60 g kg-1) doses groups, and positive drug pregabalin (PGB, 0.05 g kg-1) group. Mice received intragastrical administered for 14 consecutive days. SNL and intrathecal injection models were employed. The analgesic effects were assessed using the Von Frey test, Acetone test, and Hot Plate test. L5 spinal dorsal horns were collected for transcriptomics on day 15. The potential signaling pathways and Hub genes of RYZBP to ameliorate NP were obtained through transcriptomics and network pharmacology. Molecular docking was utilized to evaluate the binding ability of candidate active ingredients with the Hub genes. Finally, western blot (WB) and immunofluorescence (IF) were used to validate the predicted targets.

RESULTS

RYZBP demonstrated a dose-dependent alleviation of mechanical allodynia, cold and heat stimulus-induced pain in SNL mice. Transcriptomics analysis identified 24 differentially expressed genes, and pathway enrichment analysis revealed that the CXCL10-CXCR3 signal axis may be the primary biological pathway through which RYZBP relieve NP. Molecular docking test indicated that the active ingredient in RYZBP exhibit a strong affinity for the target protein CXCL10. WB and IF tests showed that RYZBP can significantly inhibit CXCL10 and CXCR3 and its downstream molecules expression in the spinal dorsal horn of SNL mice. Additionally, intrathecal injection of rmCXCL10 worsened pain hypersensitivity, while RYZBP was able to suppress the pain hypersensitivity response induced by rmCXCL10 and reduce the expression levels of CXCL10 and CXCR3 and its downstream molecules.

CONCLUSION

RYZBP had a significant analgesic effect on NP model, and this effect may be related to inhibiting the CXCL10-CXCR3 pathway in the spinal dorsal horn.

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.

Three-Direction Fusion for Accurate Volumetric Liver and Tumor Segmentation

Biomedical image segmentation of organs, tissues and lesions has gained increasing attention in clinical treatment planning and navigation, which involves the exploration of two-dimensional (2D) and three-dimensional (3D) contexts in the biomedical image. Compared to 2D methods, 3D methods pay more attention to inter-slice correlations, which offer additional spatial information for image segmentation. An organ or tumor has a 3D structure that can be observed from three directions. Previous studies focus only on the vertical axis, limiting the understanding of the relationship between a tumor and its surrounding tissues. Important information can also be obtained from sagittal and coronal axes. Therefore, spatial information of organs and tumors can be obtained from three directions, i.e. the sagittal, coronal and vertical axes, to understand better the invasion depth of tumor and its relationship with the surrounding tissues. Moreover, the edges of organs and tumors in biomedical image may be blurred. To address these problems, we propose a three-direction fusion volumetric segmentation (TFVS) model for segmenting 3D biomedical images from three perspectives in sagittal, coronal and transverse planes, respectively. We use the dataset of the liver task provided by the Medical Segmentation Decathlon challenge to train our model. The TFVS method demonstrates a competitive performance on the 3D-IRCADB dataset. In addition, the t-test and Wilcoxon signed-rank test are also performed to show the statistical significance of the improvement by the proposed method as compared with the baseline methods. The proposed method is expected to be beneficial in guiding and facilitating clinical diagnosis and treatment.

Ferrous/Ferric Ions Crosslinked Type II Collagen Multifunctional Hydrogel for Advanced Osteoarthritis Treatment

Osteoarthritis (OA) is a highly prevalent and intricate degenerative joint disease affecting an estimated 500 million individuals worldwide. Collagen-based hydrogels have sparked immense interest in cartilage tissue engineering, but substantial challenges persist in developing biocompatible and robust crosslinking strategies, as well as improving their effectiveness against the multifaceted nature of OA. Herein, a novel discovery wherein the simple incorporation of ferrous/ferric ions enables efficient dynamic crosslinking of type II collagen, leading to the development of injectable, self-healing hydrogels with 3D interconnected porous nanostructures, is unveiled. The ferrous/ferric ions crosslinked type II collagen hydrogels demonstrate exceptional physical properties, such as significantly enhanced mechanical strength, minimal swelling ratios, and remarkable resistance to degradation, while also exhibiting extraordinary biocompatibility and bioactivity, effectively promoting cell proliferation, adhesion, and chondrogenic differentiation. Additionally, the hydrogels reveal potent anti-inflammatory effects by upregulating anti-inflammatory cytokines while downregulating pro-inflammatory cytokines. In a rat model of cartilage defects, these hydrogels exhibit impressive efficacy, substantially accelerating cartilage tissue regeneration through enhanced collagen deposition and increased proteoglycan secretion. The innovative discovery of the multifunctional role of ferrous/ferric ions in endowing type II collagen hydrogels with a myriad of beneficial properties presents exciting prospects for developing advanced biomaterials with potential applications in OA.

Research Note: Antibiotic resistance and pathogenicity of geese-derived Riemerella anatipestifer isolated from eastern regions of Hebei Province, China

Riemerella anatipestifer (R. anatipestifer) can cause serositis in multiple poultry species, resulting in significant losses. Although R. anatipestifer-caused infections in ducks have been well established, the literature about this disease in geese is rare. Here, we isolated and identified 56 strains of R. anatipestifer from the eastern regions of Hebei Province, China, and further determined their serotypes, antibiotic resistance, and pathogenicity. A total of 75 strains of causative bacteria were isolated from 70 sick geese with serositis. After Gram staining microscopy, PCR, and 16S rDNA sequence analysis, 56 isolates were identified as members of R. anatipestifer and 19 as Escherichia coli (E. coli). The results of serotyping showed that there were 4 serotypes prevalent in the isolate, including serotype 1 (37/56), serotype 2 (9/56), serotype 11 (8/56), and serotype 13 (2/56). The results of antibiotic susceptibility testing revealed that all 56 R. anatipestifer isolates showed varying degrees of multidrug resistance (MDR). A total of 10 antibiotic resistance genes (ARG) were determined in these isolates. Four isolates of different serotypes were selected for pathogenicity examination, and all were able to reproduce serositis-like symptoms in 15-day-old goslings, with neurological symptoms and a 100% mortality rate. Hemorrhagic congestion of the brain tissue, steatosis of the hepatocytes, and disorganization of some cardiac myofibers were observed in R. anatipestifer-infected geese. All these findings will contribute to our insights into the prevalence characteristics, antibiotic resistance profile, and pathogenicity of R. anatipestifer infection in geese in eastern Hebei Province and provide scientific guidance for the treatment and control of this disease.

Ethanol-Induced Hepatic Ferroptosis Is Mediated by PERK-Dependent MAMs Formation: Preventive Role of Quercetin

SCOPE

Iron deposition is frequently observed in alcoholic liver disease (ALD), which indicates a potential role of ferroptosis in its development. This study aims to explore the effects of quercetin on ferroptosis in ALD and elucidates the underlying mechanism involving the formation of mitochondria-associated endoplasmic reticulum membranes (MAMs) mediated by protein kinase RNA-like endoplasmic reticulum kinase (PERK).

METHODS AND RESULTS

C57BL/6J mice are fed either a regular or an ethanol-containing liquid diet (with 28% energy form ethanol) with or without quercetin supplementation (100 mg kg-1 BW) for 12 weeks. Ethanol feeding or treatment induced ferroptosis in mice and AML12 cells, which is associated with increased MAMs formation and PERK expression within MAMs. Quercetin attenuates these changes and protects against ethanol-induced liver injury. The antiferroptotic effect of quercetin is abolished by ferroptosis inducers, but mimicked by ferroptosis inhibitors and PERK knockdown. The study demonstrates that PERK structure, rather than its kinase activity (transfected with the K618A site mutation that inhibits kinase activity-ΔK plasmid or protein C terminal knockout-ΔC plasmid of PERK), mediates the enhanced MAMs formation and ferroptosis during the ethanol exposure.

CONCLUSION

Quercetin ameliorates ethanol-induced liver injury by inhibiting ferroptosis via modulating PERK-dependent MAMs formation.

Constructing and validating a risk model based on neutrophil-related genes for evaluating prognosis and guiding immunotherapy in colon cancer

BACKGROUND

Colon cancer is one of the most common digestive tract malignancies. Although immunotherapy has brought new hope to colon cancer patients, there is still a large proportion of patients who do not benefit from immunotherapy. Studies have shown that neutrophils can interact with immune cells and immune factors to affect the prognosis of patients.

METHODS

We first determined the infiltration level of neutrophils in tumors using the CIBERSORT algorithm and identified key genes in the final risk model by Spearman correlation analysis and subsequent Cox analysis. The risk score of each patient was obtained by multiplying the Cox regression coefficient and the gene expression level, and patients were divided into two groups based on the median of risk score. Differences in overall survival (OS) and progression-free survival (PFS) were assessed by Kaplan-Meier survival analysis, and model accuracy was validated in independent dataset. Differences in immune infiltration and immunotherapy were evaluated by immunoassay. Finally, immunohistochemistry and western blotting were performed to verify the expression of the three genes in the colon normal and tumor tissues.

RESULTS

We established and validated a risk scoring model based on neutrophil-related genes in two independent datasets, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, with SLC11A1 and SLC2A3 as risk factors and MMP3 as a protective factor. A new nomogram was constructed and validated by combining clinical characteristics and the risk score model to better predict patients OS and PFS. Immune analysis showed that patients in the high-risk group had immune cell infiltration level, immune checkpoint level and tumor mutational burden, and were more likely to benefit from immunotherapy.

CONCLUSIONS

The low-risk group showed better OS and PFS than the high-risk group in the neutrophil-related gene-based risk model. Patients in the high-risk group presented higher immune infiltration levels and tumor mutational burden and thus may be more responsive to immunotherapy.

Sintilimab plus anlotinib as second or further-line therapy for extensive disease small cell lung cancer: a phase 2 investigator-initiated non-randomized controlled trial

Background

Treatment options remain rather limited for extensive disease small cell lung cancer (ED-SCLC) patients in second or further-line setting.

Methods

The phase 2 investigator-initiated non-randomized study enrolled patients who had disease progression on at least one line of platinum-based chemotherapy. Participants received intravenous sintilimab 200 mg on day one and oral daily anlotinib 12 mg on days 1-14 once every three weeks per cycle. The primary endpoint was progression-free survival (PFS). The secondary endpoints included overall survival (OS), objective response rate (ORR), disease control rate (DCR) and safety. This study is registered with ClinicalTrials.gov (NCT04055792).

Findings

Forty-two patients were enrolled between August 29, 2019 and December 26, 2021 at Henan Cancer Hospital in China. 37 patients were evaluable for efficacy. The median follow-up was 24.8 months (IQR: 16.9-28.2). The median PFS was 6.1 months (95% CI: 5.0-7.3). The OS was 12.7 months (95% CI: 7.1-18.2). The ORR was 56.8% (21/37, 95% CI: 40.0-73.5) and the DCR was 89.2% (33/37, 95% CI: 78.7-99.7). Forty patients (40/42, 95%) had at least one treatment-related adverse event (TRAE). Immune-related adverse events (irAEs) were reported in 39 patients (39/42, 93%), while grade 3 or higher irAEs occurred in 11 patients (11/42, 26%). The most frequent irAEs were hypothyroidism (16/42, 38%), elevated gamma-glutamyl transpeptidase (15/42, 36%) and elevated creatine kinase MB (15/42, 36%). The most frequent grade 3 or higher irAEs were elevated gamma-glutamyl transpeptidase (5/42, 12%) and increased aspartate aminotransferase (3/42, 7%).

Interpretation

Sintilimab plus anlotinib demonstrated promising antitumor activities as second or further-line therapy for ED-SCLC and had manageable toxicities. The findings support further randomized controlled trials of this combination regimen for ED-SCLC.

Funding

Henan Province Health and Youth Subject Leader Training Project, Henan Health Science and Technology Innovation Talents, ZHONGYUAN QIANREN JIHUA, Henan International Joint Laboratory of drug resistance and reversal of targeted therapy for lung cancer, Tumor Research Fund of Anti-Angiogenesis Targeted Therapy of China Anti-Cancer Association.

Staging liver fibrosis: comparison of radiomics model and fusion model based on multiparametric MRI in patients with chronic liver disease

OBJECTIVES

To develop and compare radiomics model and fusion model based on multiple MR parameters for staging liver fibrosis in patients with chronic liver disease.

MATERIALS AND METHODS

Patients with chronic liver disease who underwent multiparametric abdominal MRI were included in this retrospective study. Multiparametric MR images were imported into 3D-Slicer software for drawing bounding boxes on MR images. By using a 3D-Slicer extension of SlicerRadiomics, radiomics features were extracted from these MR images. The z-score normalization method was used for post-processing radiomics features. The least absolute shrinkage and selection operator method (LASSO) was performed for selecting significant radiomics features. The logistic regression analysis was used for building the radiomics model. A fusion model was built by integrating serum fibrosis biomarkers of aspartate transaminase-to-platelet ratio index (APRI) and the fibrosis-4 index (FIB-4) with radiomics signatures.

RESULTS

In the training cohort, AUCs of radiomics and fusion model were 0.707-0.842 and 0.718-0.854 for differentiating different groups. In the testing cohort, AUCs were 0.514-0.724 and 0.609-0.728. For the training cohort, there was no significant difference of AUCs between radiomics and fusion model (p > 0.05). For the testing cohort, AUCs of fusion model were higher than those of radiomics model in differentiating F1-3 vs. F4 and F1-2 vs. F4 (p = 0.011 & 0.042).

CONCLUSIONS

Radiomics model and fusion model based on multiparametric MRI exhibited the feasibility for staging liver fibrosis in patients with CLD, and APRI and FIB-4 could improve the diagnostic performance of radiomics model in differentiating F1-3 vs. F4 and F1-2 vs. F4.

Automatic liver segmentation and assessment of liver fibrosis using deep learning with MR T1-weighted images in rats

OBJECTIVES

To validate the performance of nnU-Net in segmentation and CNN in classification for liver fibrosis using T1-weighted images.

MATERIALS AND METHODS

In this prospective study, animal models of liver fibrosis were induced by injecting subcutaneously a mixture of Carbon tetrachloride and olive oil. A total of 99 male Wistar rats were successfully induced and underwent MR scanning with no contrast agent to get T1-weighted images. The regions of interest (ROIs) of the whole liver were delineated layer by layer along the liver edge by 3D Slicer. For segmentation task, all T1-weighted images were randomly divided into training and test cohorts in a ratio of 7:3. For classification, images containing the hepatic maximum diameter of every rat were selected and 80% images of no liver fibrosis (NLF), early liver fibrosis (ELF) and progressive liver fibrosis (PLF) stages were randomly selected for training, while the rest were used for testing. Liver segmentation was performed by the nnU-Net model. The convolutional neural network (CNN) was used for classification task of liver fibrosis stages. The Dice similarity coefficient was used to evaluate the segmentation performance of nnU-Net. Confusion matrix, ROC curve and accuracy were used to show the classification performance of CNN.

RESULTS

A total of 2628 images were obtained from 99 Wistar rats by MR scanning. For liver segmentation by nnU-Net, the Dice similarity coefficient in the test set was 0.8477. The accuracies of CNN in staging NLF, ELF and PLF were 0.73, 0.89 and 0.84, respectively. The AUCs were 0.76, 0.88 and 0.79, respectively.

CONCLUSION

The nnU-Net architecture is of high accuracy for liver segmentation and CNN for assessment of liver fibrosis with T1-weighted images.

Dual-Confinement Effect of Nanocages@Nanotubes Suppresses Polysulfide Shuttle Effect for High-Performance Lithium-Sulfur Batteries

The shuttle effect of lithium polysulfides (LiPSs) severely hinders the development and commercialization of lithium-sulfur batteries, and the design of high-conductive carbon fiber-host material has become a key solution to suppress the shuttle effect. In this work, a unique Co/CoN-carbon nanocages@TiO2-carbon nanotubes structure (NC@TiO2-CNTs) is constructed using an electrospinning and nitriding process. Lithium-sulfur batteries using NC@TiO2-CNTs as cathode host materials exhibit high sulfur utilization (1527 mAh g-1 at 0.2 C) and can still maintain a discharge capacity of 663 mAh g-1 at a high current density of 5 C, and the capacity loss is only 0.056% per cycle during 500 cycles at 1 C. It is worth noting that even under extreme conditions (sulfur-loading = 90%, surface-loading = 5.0 mg cm-2 (S), and E/S = 6.63 µL mg-1), the lithium-sulfur batteries can still provide a reversible capacity of 4 mAh cm-2. Throughdensity functional theory calculations, it has been found that the Co/CoN heterostructures can adsorb and catalyze LiPSs conversion effectively. Simultaneously, the TiO2 can adsorb LiPSs and transfer Li+ selectively, achieving dual confinement for the shuttle effect of LiPSs (nanocages and nanotubes). The new findings provide a new performance enhancement strategy for the commercialization of lithium-sulfur batteries.

Effects of online family health education on myopia prevention in children by parental myopia: a randomized clinical trial

CLINICAL RELEVANCE

Online family health education may be effective for myopia prevention in children, and the effects may be different between children with myopic and non-myopic parents.

BACKGROUND

Myopia is a common cause of vision loss. The aims of this study were to evaluate the effects of online family health education on preventing the development of myopia in children, and to estimate whether the effects vary according to parental myopia.

METHODS

A cluster randomised trial including grade 1 and grade 2 children from 12 primary schools was conducted in Guangzhou, China. Weekly online family health education messages were sent to parents in the intervention group. Data collection included eye examinations of children and questionnaires completed by parents.

RESULTS

Among the 3123 children included at baseline (1703 boys [54.5%]; mean [SD] age, 6.83 [0.73] years), 2376 completed the follow-up after 3 years. The differences in the incidence of myopia and myopic shift between the study groups were not significant in total. However, the 3-year cumulative incidence rate of myopia in the intervention group (125 of 445 [28.1%]) was significantly lower than that in the control group (225 of 603 [37.3%]; difference, 9.2% [95% CI, -14.9% to -3.5%]; P = 0.001) among children with non-myopic parents. In parallel, among children with non-myopic parents, the mean myopic change in SER was less for the intervention group than for the control group (-1.10 D vs. -1.24 D; difference, 0.13 D [95% CI, 0.03 to 0.23 D]; P = 0.01).

CONCLUSIONS

Compared with children with myopic parents, online family health education was more effective in children with non-myopic parents. The incidence of myopia and myopic shift in refraction have been reduced in children with non-myopic parents. Further studies are needed to assess these differences by parental myopia.

Structural bases of inhibitory mechanism of CaV1.2 channel inhibitors

The voltage-gated calcium channel CaV1.2 is essential for cardiac and vessel smooth muscle contractility and brain function. Accumulating evidence demonstrates that malfunctions of CaV1.2 are involved in brain and heart diseases. Pharmacological inhibition of CaV1.2 is therefore of therapeutic value. Here, we report cryo-EM structures of CaV1.2 in the absence or presence of the antirheumatic drug tetrandrine or antihypertensive drug benidipine. Tetrandrine acts as a pore blocker in a pocket composed of S6II, S6III, and S6IV helices and forms extensive hydrophobic interactions with CaV1.2. Our structure elucidates that benidipine is located in the DIII-DIV fenestration site. Its hydrophobic sidechain, phenylpiperidine, is positioned at the exterior of the pore domain and cradled within a hydrophobic pocket formed by S5DIII, S6DIII, and S6DIV helices, providing additional interactions to exert inhibitory effects on both L-type and T-type voltage gated calcium channels. These findings provide the structural foundation for the rational design and optimization of therapeutic inhibitors of voltage-gated calcium channels.

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.

Rice requires a chromatin remodeler for Polymerase IV-small interfering RNA production and genomic immunity

Transgenes are often spontaneously silenced, which hinders the application of genetic modifications to crop breeding. While gene silencing has been extensively studied in Arabidopsis (Arabidopsis thaliana), the molecular mechanism of transgene silencing remains elusive in crop plants. We used rice (Oryza sativa) plants silenced for a 35S::OsGA2ox1 (Gibberellin 2-oxidase 1) transgene to isolate five elements mountain (fem) mutants showing restoration of transgene expression. In this study, we isolated multiple fem2 mutants defective in a homolog of Required to Maintain Repression 1 (RMR1) of maize (Zea mays) and CLASSY (CLSY) of Arabidopsis. In addition to failing to maintain transgene silencing, as occurs in fem3, in which mutation occurs in NUCLEAR RNA POLYMERASE E1 (OsNRPE1), the fem2 mutant failed to establish transgene silencing of 35S::OsGA2ox1. Mutation in FEM2 eliminated all RNA POLYMERASE IV (Pol-IV)-FEM1/OsRDR2 (RNA-DEPENDENT RNA POLYMERASE 2)-dependent small interfering RNAs (siRNAs), reduced DNA methylation on genome-wide scale in rice seedlings, caused pleiotropic developmental defects, and increased disease resistance. Simultaneous mutation in 2 FEM2 homologous genes, FEM2-Like 1 (FEL1) and FEL2, however, did not affect DNA methylation and rice development and disease resistance. The predominant expression of FEM2 over FEL1 and FEL2 in various tissues was likely caused by epigenetic states. Overexpression of FEL1 but not FEL2 partially rescued hypomethylation of fem2, indicating that FEL1 maintains the cryptic function. In summary, FEM2 is essential for establishing and maintaining gene silencing; moreover, FEM2 is solely required for Pol IV-FEM1 siRNA biosynthesis and de novo DNA methylation.

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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