One-pot green solid-state synthesis of Cu2O/microcrystalline cellulose composite with high anti-pathogenic activity

Cuprous oxide (Cu2O) is proven as an excellent anti-harmful microbial material. However, the liquid and vapor pha5se preparation methods reported so far hardly make pure Cu2O-containing composites and suffer environmental issues caused by chemical reducing agents with multiple processing steps. This work develops a facile one-pot solid-state sintering method to synthesize Cu2O/microcrystalline cellulose (MCC) composite via the thermal decomposition and oxidation-reduction reactions where copper formate was reduced by MCC. The Cu2O/MCC composite exhibits superior purity, dispersibility, stability, high yield, and high efficacy of antibacterial and antiviral properties, e.g., against E. coli, S. aureus, and Equine Arteritis Viral. This work utilizes elegantly the strong reducing capability of cellulose to develop an environmentally benign method to prepare high-purity Cu2O-polymer composites with low cytotoxicity and cost, which can be incorporated readily into other substrate materials to form various forms of anti-harmful microbial materials widely used in public health care products. In addition, the preparation of Cu2O-containing composites based on the reducing capability of cellulose is also expected to be applied to other cellulose-based materials for the loading of Cu2O particles.

Biochar and nano-hydroxyapatite combined remediation of soil surrounding tailings area: Multi-metal(loid)s fixation and soybean rhizosphere soil microbial improvement

The soil near tailings areas is relatively barren and contaminated by multi-metal(loid)s, seriously threatening the safety of crop production. Here, biochar and nano-hydroxyapatite (nHAP) were combined to improve the sterilized and unsterilized polymetallic contaminated soil, and soil incubation and soybean pot experiments were designed. Results showed that biochar and nHAP not only increased soil C, N, and P but also effectively reduced multi-metal bioavailability, wherein the combined application of the two amendments had the best effect on metal immobilization. The synergistic effect of the two amendments decreased the acid-soluble contents of Co, Cu, Fe, and Pb in rhizosphere soils up to 86.75%, 80.69%, 89.09%, and 96.70%, respectively. The ameliorant reduced the accumulation of metal(loid)s in soybean plants, and rhizosphere microorganisms inhibited the migration of soil metals to plants. Additionally, biochar and nHAP regulated the rhizosphere soil microbial community. The rhizosphere soil of the sterilization group tended to prioritize the restoration of the original dominant bacteria. As, Pb, Fe, Urease, OM, TN, and TP were the critical environmental variables affecting rhizosphere soil bacterial communities. Therefore, combining biochar and nHAP is an environmentally friendly strategy to reduce polymetallic mobility in tailings soil and crops and improve soil microbial community structure.

Comprehensive insight into mercury contamination in atmospheric, terrestrial and aquatic ecosystems surrounding a typical antimony-coal mining district

This study comprehensively investigated mercury (Hg) contents of various environmental compartments in a typical antimony-coal mining area with intensive industrial activities over the past 120 years to analyze Hg environmental behaviors and evaluate Hg risks. The total mercury (THg) contents in river water, sediments, soils, PM10, dust falls, vegetables and corns were 1.16 ± 0.63 µg/L, 2.01 ± 1.64 mg/kg, 1.87 ± 3.88 mg/kg, 7.87 ± 18.68 ng/m3, 13.01 ± 14.53 mg/kg, 0.30 ± 0.34 mg/kg and 3.11 ± 0.51 µg/kg, respectively. The δ202Hg values in soils and dust falls were - 1.58 ∼ 0.12‰ and 0.25 ∼ 0.30‰, respectively. Environmental samples affected by industrial activities in the Xikuangshan (XKS) presented higher THg and δ202Hg values. Binary mixing model proved that atmospheric deposition with considerable Hg deposition flux (0.44 ∼ 6.40, 3.12 ± 2.20 mg/m2/y) in the XKS significantly contributed to Hg accumulations on surface soils. Compared with soils, sediments with more frequent paths and higher burst probabilities presented higher dynamic Hg risks. Children were faced higher health risk of multiple Hg exposure than adults. Furthermore, the health risk of THg by consuming leaf vegetables deserved more attention. These findings provided scientific basis for managing Hg contamination.

An autocatalytic CRISPR-Cas amplification effect propelled by the LNA-modified split activators for DNA sensing

CRISPR-Cas systems with dual functions offer precise sequence-based recognition and efficient catalytic cleavage of nucleic acids, making them highly promising in biosensing and diagnostic technologies. However, current methods encounter challenges of complexity, low turnover efficiency, and the necessity for sophisticated probe design. To better integrate the dual functions of Cas proteins, we proposed a novel approach called CRISPR-Cas Autocatalysis Amplification driven by LNA-modified Split Activators (CALSA) for the highly efficient detection of single-stranded DNA (ssDNA) and genomic DNA. By introducing split ssDNA activators and the site-directed trans-cleavage mediated by LNA modifications, an autocatalysis-driven positive feedback loop of nucleic acids based on the LbCas12a system was constructed. Consequently, CALSA enabled one-pot and real-time detection of genomic DNA and cell-free DNA (cfDNA) from different tumor cell lines. Notably, CALSA achieved high sensitivity, single-base specificity, and remarkably short reaction times. Due to the high programmability of nucleic acid circuits, these results highlighted the immense potential of CALSA as a powerful tool for cascade signal amplification. Moreover, the sensitivity and specificity further emphasized the value of CALSA in biosensing and diagnostics, opening avenues for future clinical applications.

Seeking a quantum advantage with trapped-ion quantum simulations of condensed-phase chemical dynamics

Simulating the quantum dynamics of molecules in the condensed phase represents a longstanding challenge in chemistry. Trapped-ion quantum systems may serve as a platform for the analog-quantum simulation of chemical dynamics that is beyond the reach of current classical-digital simulation. To identify a 'quantum advantage' for these simulations, performance analysis of both analog-quantum simulation on noisy hardware and classical-digital algorithms is needed. In this Review, we make a comparison between a noisy analog trapped-ion simulator and a few choice classical-digital methods on simulating the dynamics of a model molecular Hamiltonian with linear vibronic coupling. We describe several simple Hamiltonians that are commonly used to model molecular systems, which can be simulated with existing or emerging trapped-ion hardware. These Hamiltonians may serve as stepping stones towards the use of trapped-ion simulators for systems beyond the reach of classical-digital methods. Finally, we identify dynamical regimes in which classical-digital simulations seem to have the weakest performance with respect to analog-quantum simulations. These regimes may provide the lowest hanging fruit to make the most of potential quantum advantages.

Guest water-induced structural transformation and spin-crossover variation of a two-dimensional Hofmann-type compound

In this paper, we report a two-dimensional (2D) Hofmann-type spin-crossover coordination polymer [FeII(o-NTrz)2PtII(CN)4]·H2O (o-NTrz = 4-(o-nitrobenzyl)imino-1,2,4-triazole). Due to the remarkable configurational flexibility of triazole-based ligand, the porous structure of this compound can be reversibly regulated by the loss of guest water molecules as a consequence of rotation of o-NTrz. The 180° reorientation of the o-nitrobenzyl moiety not only induces a response of gate-closing/opening of the porous framework but also significantly modulates the spin transition temperature. The present investigation highlights the potential of Hofmann-type SCO compounds with flexible ligands in exploring unusual physical and chemical phenomena.

Lnc-Clic5 as a sponge for miR-212-5p to inhibit cow barn PM2.5-induced apoptosis in rat alveolar macrophages

Particulate matter 2.5 (PM2.5) is a highly hazardous airborne particulate matter that poses a significant risk to humans and animals. Urban airborne particulate matter contributes to the increased incidence and mortality of respiratory diseases, such as asthma and chronic obstructive pulmonary disease (COPD), in humans. However, the specific mechanism by which PM2.5 affects animals in barn environments is yet to be elucidated. In this study, we investigated the effect of exposure to cow barn PM2.5 on rat alveolar macrophages (NR8383) and found that it induced apoptosis via the miR-212-5p/RASSF1 pathway. We found that lnc-Clic5 expression was downregulated in NR8383 cells exposed to cow barn PM2.5. Lnc-Clic5 plays a competitive endogenous RNA (ceRNA) regulatory role by sponging miR-212-5p to attenuate the regulation of RASSF1. Moreover, lnc-Clic5 overexpression inhibited NR8383 apoptosis by targeting the miR-212-5p/RASSF1 pathway. Co-treatment with miR-212-5p and lnc-Clic5 in the presence of cow barn PM2.5 revealed that lnc-Clic5 reversed NR8383 cell apoptosis induced by PM2.5 when miR-212-5p was overexpressed. These findings contribute to the study of ncRNAs and ceRNAs regulating PM2.5-induced apoptosis in animal farms, provide therapeutic targets for lung macrophage apoptosis, and may be useful for further evaluating the toxicological effects of PM2.5 in farmhouses on the respiratory systems of humans and animals.

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.

Metabolic Heterogeneity and Potential Immunotherapeutic Responses Revealed by Single-Cell Transcriptomics of Breast Cancer

BACKGROUND

Breast cancer (BC) exhibits remarkable heterogeneity. However, the transcriptomic heterogeneity of BC at the single-cell level has not been fully elucidated.

METHODS

We acquired BC samples from 14 patients. Single-cell RNA sequencing (scRNA-seq), bioinformatic analyses, along with immunohistochemistry (IHC) and immunofluorescence (IF) assays were carried out.

RESULTS

According to the scRNA-seq results, 10 different cell types were identified. We found that Cancer-Associated Fibroblasts (CAFs) exhibited distinct biological functions and may promote resistance to therapy. Metabolic analysis of tumor cells revealed heterogeneity in glycolysis, gluconeogenesis, and fatty acid synthetase reprogramming, which led to chemotherapy resistance. Furthermore, patients with multiple metastases and progression were predicted to benefit from immunotherapy based on a heterogeneity analysis of T cells and tumor cells.

CONCLUSIONS

Our findings provide a comprehensive understanding of the heterogeneity of BC, provide comprehensive insight into the correlation between cancer metabolism and chemotherapy resistance, and enable the prediction of immunotherapy responses based on T-cell heterogeneity.

Fully digital workflow of occlusal reconstruction treatment in a patient with congenital dentition defects

OBJECTIVE

Occlusal reconstruction is a critical intervention for patients with dental hard tissue defects, temporomandibular joint (TMJ) disorders, and jaw position abnormalities. Clinical efficiency and outcomes of these procedures have improved with advances in digital technologies. This case report aims to illustrate a comprehensive digital workflow for occlusal reconstruction in a patient with congenital dentition defects, emphasizing the application of digital technologies to enhance treatment outcomes.

CLINICAL CONSIDERATIONS

A 28-year-old woman with previously installed porcelain-fused-to-metal bridge restorations presented with a fractured prosthesis and TMJ symptoms. A multidisciplinary approach was adopted involving the use of digital facebow, intraoral scanners, digital smile design, and CAD/CAM technologies. The process included the extraction of defective restorations, temporary restorations to refine jaw position, and final permanent restorations. The digital workflow facilitated precise diagnostics and treatment, culminating in the successful installation of permanent restorations. Regular follow-ups at one- and three-months post-treatment confirmed stable occlusal function and high patient satisfaction.

CONCLUSIONS

This case report showcases the potential of multiple digital technologies to streamline complex dental treatments and achieve high-quality results.

CLINICAL SIGNIFICANCE

The integration of digital technologies in occlusal reconstruction treatments offers significant benefits in terms of precision, patient comfort, and esthetic outcomes.

Effects of temperature and nitrogen sources on physiological performance of the coccolithophore Emiliania huxleyi

Both temperature and nutrient levels are rising in worldwide ocean ecosystems, and they strongly influence biological responses of phytoplankton. However, few studies have addressed the interactive effects of temperature and nitrogen sources on physiological performance of the coccolithophore Emiliania huxleyi. In this study, we evaluated algal growth, photosynthesis and respiration, elemental composition, enzyme activity, and calcification under a matrix of two temperatures gradients (ambient temperature 20 °C and high temperature 24 °C) and two nitrogen sources (nitrate (NO3-) and ammonium (NH4+)). When the algae was cultured with NO3- medium, high temperature reduced algal photosynthesis and nitrate reductase activity, but it did not change other indicators significantly relative to ambient temperature. In addition, E. huxleyi preferred NO3- as the growth medium, whereas NH4+ had negative effects on physiological parameters. In the NH4+ medium, the growth rate, photosynthesis and photosynthetic rate, nitrate reductase activity, and particulate organic carbon and particulate organic nitrogen production rate of the algae decreased as temperature increased. Conversely, high temperature increased cellular particulate organic carbon, cellular particulate organic nitrogen, and particulate inorganic carbon levels. In summary, our findings indicate that the distribution and abundance of microalgae could be greatly affected under warming ocean temperature and different nutrient conditions.

Real-time detection of 20 amino acids and discrimination of pathologically relevant peptides with functionalized nanopore

Precise identification and quantification of amino acids is crucial for many biological applications. Here we report a copper(II)-functionalized Mycobacterium smegmatis porin A (MspA) nanopore with the N91H substitution, which enables direct identification of all 20 proteinogenic amino acids when combined with a machine-learning algorithm. The validation accuracy reaches 99.1%, with 30.9% signal recovery. The feasibility of ultrasensitive quantification of amino acids was also demonstrated at the nanomolar range. Furthermore, the capability of this system for real-time analyses of two representative post-translational modifications (PTMs), one unnatural amino acid and ten synthetic peptides using exopeptidases, including clinically relevant peptides associated with Alzheimer's disease and cancer neoantigens, was demonstrated. Notably, our strategy successfully distinguishes peptides with only one amino acid difference from the hydrolysate and provides the possibility to infer the peptide sequence.

Synthesis of a novel monomer "DDTU-IDI" for the development of low-shrinkage dental resin composites

OBJECTIVE

The current dental resin composites often suffer from polymerization shrinkage, which can lead to microleakage and potentially result in recurring tooth decay. This study presents the synthesis of a novel monomer, (3,9-diethyl-1,5,7,11-tetraoxaspiro[5,5]undecane-3,9-diyl)bis(methylene) bis((2-(3-(prop-1-en-2-yl)phenyl)propan-2-yl)carbamate) (DDTU-IDI), and evaluates its effect in the formulation of low-shrinkage dental resin composites.

METHODS

DDTU-IDI was synthesized through a two-step reaction route, with the initial synthesis of the required raw material monomer 3,9-diethyl-3,9-dihydroxymethyl-1,5,7,11-tetraoxaspiro-[5,5] undecane (DDTU). The structures were confirmed using Fourier-transform infrared (FT-IR) spectroscopy and hydrogen nuclear magnetic resonance (1HNMR) spectroscopy. Subsequently, DDTU-IDI was incorporated into Bis-GMA-based composites at varying weight percentages (5, 10, 15, and 20 wt%). The polymerization reaction, degree of conversion, polymerization shrinkage, mechanical properties, physicochemical properties and biocompatibility of the low-shrinkage composites were thoroughly evaluated. Furthermore, the mechanical properties were assessed after a thermal cycling test with 10,000 cycles to determine the stability.

RESULTS

The addition of DDTU-IDI at 10, 15, and 20 wt% significantly reduced the polymerization volumetric shrinkage of the experimental resin composites, without compromising the degree of conversion, mechanical and physicochemical properties. Remarkably, at a monomer content of 20 wt%, the polymerization shrinkage was reduced to 1.83 ± 0.53%. Composites containing 10, 15, and 20 wt% DDTU-IDI exhibited lower water sorption and higher contact angle. Following thermal cycling, the composites exhibited no significant decrease in mechanical properties, except for the flexural properties.

SIGNIFICANCE

DDTU-IDI has favorable potential as a component which could produce volume expansion and increase rigidity in the development of low-shrinkage dental resin composites. The development of low-shrinkage composites containing DDTU-IDI appears to be a promising strategy for reducing polymerization shrinkage, thereby potentially enhancing the longevity of dental restorations.

Attributed Graph Force Learning

In numerous network analysis tasks, feature representation plays an imperative role. Due to the intrinsic nature of networks being discrete, enormous challenges are imposed on their effective usage. There has been a significant amount of attention on network feature learning in recent times that has the potential of mapping discrete features into a continuous feature space. The methods, however, lack preserving the structural information owing to the utilization of random negative sampling during the training phase. The ability to effectively join attribute information to embedding feature space is also compromised. To address the shortcomings identified, a novel attribute force-based graph (AGForce) learning model is proposed that keeps the structural information intact along with adaptively joining attribute information to the node's features. To demonstrate the effectiveness of the proposed framework, comprehensive experiments on benchmark datasets are performed. AGForce based on the spring-electrical model extends opportunities to simulate node interaction for graph learning.

Optimizing hepatocellular carcinoma disease staging systems by incorporating tumor micronecrosis: A multi-institutional retrospective study

Tumor micronecrosis is a pathological feature that reflects malignant biological behavior in hepatocellular carcinoma (HCC). However, whether micronecrosis can optimize HCC staging systems remains unilluminated. A total of 1632 HCC patients who underwent curative hepatectomy in four institutions from January 2014 to December 2021 were enrolled in this study. Independent prognostic factors were identified, and optimized staging models were established using a training cohort (n = 934). The performance of optimized staging models was validated using an external cohort consisting of cases from three other institutions (n = 232). In addition, patients from our prospectively collected database (n = 379) tested the application effectiveness of the models. Harrel's c-statistics and the corrected Akaike information criterion (AICc) were used to assess the performance of staging models. In most of Barcelona Clinic Liver Cancer (BCLC) and tumor (T) stages, HCC patients with tumor micronecrosis showed poorer prognosis than those without. Tumor micronecrosis, microvascular invasion, multiple tumors and tumor size >2 cm were independent prognostic-related factors. The BCLC and T staging models incorporating tumor micronecrosis showed better performance than the original systems (c-statistic, 0.712 and 0.711 vs. 0.664 and 0.679; AICc, 2314.8 and 2322.3 vs. 2338.2 and 2338.1; respectively). Furthermore, the external validation cohort confirmed that the optimized staging models had improved efficiency compared with the original ones. Moreover, the prospective cohort demonstrated the applicability of the optimized staging systems. Tumor micronecrosis plays a stage-ascending role in HCC patients. The BCLC and T staging systems incorporating tumor micronecrosis can improve the prognosis stratification efficiency of patients.

Radiologic Evaluation of Uncinate Processes of the cervical spine and the Relationship Between UP and Vertebral Artery: Implication in Anterior Cervical Spine Surgery

PURPOSE

The purpose of this study was to determine the relationship between the uncinate process and vertebral artery from a radiological view and to confirm the surgical safety margin in order to minimize the risk of vertebral artery injury during anterior cervical approaches.

METHODS

We retrospectively reviewed computed tomography angiography of 205 patients by using a contrast-enhanced CTA protocol of the vertebral artery. Four kinds of images were simultaneously reconstructed to measure all the parameters associated with vertebral artery and uncinate process of cervical spine.

RESULTS

The shortest distance from the UP's tip to the VA's medial border (p<0.001) was at the C-6 level (2.9±0.9mm on the left and 3.2±1.3 on the right), and the longest distance (p<0.001) was at the C-3 level on both sides. The distance between UP's tip and the medial border of the ipsilateral VA was statistically significantly different at each cervical level, and the right distance was larger than the left (p<0.05). We found the height of UP gradually increased from C-3 to C5-level and then decreased from C-5 to C-7 level for both sides. The mean distance between the medial borders of left UP and left VA was on average 7.5±1.4mm. The diameter of VA was on average 3.4±0.6mm on the left side and 3.2±0.7mm on the right. The diameter of the VA was statistically significantly different on both sides, and the left side was larger than the right (p<0.05).

CONCLUSIONS

Detailed radiologic anatomy of vertebral artery and uncinate process was reviewed in this study. A deep understanding of the correlation between the uncinate process and vertebral artery is essential to perform anterior cervical spine surgery safely and ensure adequate spinal canal decompression.

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

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

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

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

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Affiliation(s)

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

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Convolutional neural network for identifying common bile duct stones based on magnetic resonance cholangiopancreatography

AIMS

To develop an auto-categorization system based on machine learning for three-dimensional magnetic resonance cholangiopancreatography (3D MRCP) to detect choledocholithiasis from healthy and symptomatic individuals.

MATERIALS AND METHODS

3D MRCP sequences from 254 cases with common bile duct (CBD) stones and 251 cases with normal CBD were enrolled to train the 3D Convolutional Neural Network (3D-CNN) model. Then 184 patients from three different hospitals (91 with positive CBD stone and 93 with normal CBD) were prospectively included to test the performance of 3D-CNN.

RESULTS

With a cutoff value of 0.2754, 3D-CNN achieved the sensitivity, specificity, and accuracy of 94.51%, 92.47%, and 93.48%, respectively. In the receiver operating characteristic curve analysis, the area under the curve (AUC) for the presence or absence of CBD stones was 0.974 (95% CI, 0.940-0.992). There was no significant difference in sensitivity, specificity, and accuracy between 3D-CNN and radiologists. In addition, the performance of 3D-CNN was also evaluated in the internal test set and the external test set, respectively. The internal test set yielded an accuracy of 94.74% and AUC of 0.974 (95% CI, 0.919-0.996), and the external test set yielded an accuracy of 92.13% and AUC of 0.970 (95% CI, 0.911-0.995).

CONCLUSIONS

An artificial intelligence-assisted diagnostic system for CBD stones was constructed using 3D-CNN model for 3D MRCP images. The performance of 3D-CNN model was comparable to that of radiologists in diagnosing CBD stones. 3D-CNN model maintained high performance when applied to data from other hospitals.

Intestinal lysozyme1 deficiency alters microbiota composition and impacts host metabolism through the emergence of NAD+-secreting ASTB Qing110 bacteria

The intestine plays a pivotal role in nutrient absorption and host defense against pathogens, orchestrated in part by antimicrobial peptides secreted by Paneth cells. Among these peptides, lysozyme has multifaceted functions beyond its bactericidal activity. Here, we uncover the intricate relationship between intestinal lysozyme, the gut microbiota, and host metabolism. Lysozyme deficiency in mice led to altered body weight, energy expenditure, and substrate utilization, particularly on a high-fat diet. Interestingly, these metabolic benefits were linked to changes in the gut microbiota composition. Cohousing experiments revealed that the metabolic effects of lysozyme deficiency were microbiota-dependent. 16S rDNA sequencing highlighted differences in microbial communities, with ASTB_g (OTU60) highly enriched in lysozyme knockout mice. Subsequently, a novel bacterium, ASTB Qing110, corresponding to ASTB_g (OTU60), was isolated. Metabolomic analysis revealed that ASTB Qing110 secreted high levels of NAD+, potentially influencing host metabolism. This study sheds light on the complex interplay between intestinal lysozyme, the gut microbiota, and host metabolism, uncovering the potential role of ASTB Qing110 as a key player in modulating metabolic outcomes.

IMPORTANCE

The impact of intestinal lumen lysozyme on intestinal health is complex, arising from its multifaceted interactions with the gut microbiota. Lysozyme can both mitigate and worsen certain health conditions, varying with different scenarios. This underscores the necessity of identifying the specific bacterial responses elicited by lysozyme and understanding their molecular foundations. Our research reveals that a deficiency in intestinal lysozyme1 may offer protection against diet-induced obesity by altering bacterial populations. We discovered a strain of bacterium, ASTB Qing110, which secretes NAD+ and is predominantly found in lyz1-deficient mice. Qing110 demonstrates positive effects in both C. elegans and mouse models of ataxia telangiectasia. This study sheds light on the intricate role of lysozyme in influencing intestinal health.

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

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

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

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

Microplastics alter soil structure and microbial community composition

Microplastics (MPs), including conventional hard-to-biodegrade petroleum-based and faster biodegradable plant-based ones, impact soil structure and microbiota in turn affecting the biodiversity and functions of terrestrial ecosystems. Herein, we investigated the effects of conventional and biodegradable MPs on aggregate distribution and microbial community composition in microhabitats at the aggregate scale. Two MP types (polyethylene (PE) and polylactic acid (PLA) with increasing size (50, 150, and 300 μm)) were mixed with a silty loam soil (0-20 cm) at a ratio of 0.5 % (w/w) in a rice-wheat rotation system in a greenhouse under 25 °C for one year. The effects on aggregation, bacterial communities and their co-occurrence networks were investigated as a function of MP aggregate size. Conventional and biodegradable MPs generally had similar effects on soil aggregation and bacterial communities. They increased the proportion of microaggregates from 17 % to 32 %, while reducing the macroaggregates from 84 % to 68 %. The aggregate stability decreased from 1.4 mm to 1.0-1.1 mm independently of MP size due to the decline in the binding agents gluing soil particles (e.g., microbial byproducts and proteinaceous substances). MP type and amount strongly affected the bacterial community structure, accounting for 54 % of the variance. Due to less bioavailable organics, bacterial community composition within microaggregates was more sensitive to MPs addition compared to macroaggregates. Co-occurrence network analysis revealed that MPs exacerbated competition among bacteria and increased the complexity of bacterial networks. Such effects were stronger for PE than PLA MPs due to the higher persistence of PE in soils. Proteobacteria, Bacteroidetes, Chloroflexi, Actinobacteria, and Gemmatimonadetes were the keystone taxa in macroaggregates, while Actinobacteria and Chloroflexi were the keystone taxa in microaggregates. Proteobacteria, Actinobacteria, and Chloroflexi were the most sensitive bacteria to MPs addition. Overall, both conventional and biodegradable MPs reduced the portion of large and stable aggregates, altering bacterial community structures and keystone taxa, and consequently, the functions.

Predictors of physical inactivity among pregnant women

It is recommended that pregnant women be physically active to promote maternal and child health. This study aimed to explore the prevalence of physical inactivity and its modifiable predictors in the three trimesters in Chinese pregnant women. Four hundred forty-four pregnant women completed the Pregnant Physical Activity Questionnaire in the first, second, and third trimesters. The prevalence of physical inactivity reached its highest (66.2%) in the first trimester and lowest (19.4%) in the second trimester. Pregnant women with inadequate physical activity knowledge and low self-efficacy were at higher risk for physical inactivity. Monitoring physical inactivity could be incorporated into antenatal care and start from the first trimester. Prenatal care professionals should take action to increase pregnant women's physical activity self-efficacy and knowledge to enhance their physical activity.

Improve meat production and virus resistance by simultaneously editing multiple genes in livestock using Cas12iMax

The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated gene (Cas) system is continually optimized to achieve the most efficient gene editing effect. The Cas12iMax, a Cas12i variant, exhibits powerful DNA editing activity and enriches the gene editing toolbox. However, the application of Cas12iMax in large domestic animals has not yet been reported. To verify the efficiency and feasibility of multiple gene editing in large animals, we generated porcine fibroblasts with simultaneous knockouts of IGF2, ANPEP, CD163, and MSTN via Cas12iMax in one step. Phenotypically stable pigs were created through somatic cell nuclear transfer technology. They exhibited improved growth performance and muscle quality. Furthermore, we simultaneously edited three genes in bovine fibroblasts. A knockout of MSTN and PRNP was created and the amino acid Q-G in CD18 was precisely substituted. Meanwhile, no off-target phenomenon was observed by sum-type analysis or off-target detection. These results verified the effectiveness of Cas12iMax for gene editing in livestock animals and demonstrated the potential application of Cas12iMax in the field of animal trait improvement for agricultural production.

Localized Temperature Engineering Enables Writing of Heterostructures in Glass for Polarized Photoluminescence of Perovskites

Metal halide perovskite (MHP) structures that exhibit polarized photoluminescence (PL) have attracted significant interest in fabricating light field regulation elements for display, imaging, and information storage applications. We report a three-dimensional direct lithography of heterostructures for controllable polarized PL inside glass by laser-induced localized temperature engineering. The heterostructures consisted of oriented periodic structures (OPSs) and MHP nanocrystals, and the mechanism for hierarchical distribution of heterostructures was illustrated. The patterning of heterostructures for manipulable polarized PL can be used for information encryption, wave-plate, and polarized micro-LEDs.

Formulating and Representing Multiagent Systems With Hypergraphs

Graph-learning methods, especially graph neural networks (GNNs), have shown remarkable effectiveness in handling non-Euclidean data and have achieved great success in various scenarios. Existing GNNs are primarily based on message-passing schemes, that is, aggregating information from neighboring nodes. However, the diversity and complexity of complex systems from real-world circumstances are not sufficiently taken into account. In these cases, the individual should be treated as an agent, with the ability to perceive their surroundings and interact with other individuals, rather than just be viewed as nodes in existing graph approaches. Additionally, the pairwise interactions used in existing methods also lack the expressiveness for the higher-order complex relations among multiple agents, thus limiting the performance in various tasks. In this work, we propose a Multiagent Hypergraph Force-learning method dubbed MHGForce. First, we formalize the multiagent system (MAS) and illustrate its connection to graph learning. Then, we propose a generalized multiagent hypergraph-learning framework. In this framework, we integrate message-passing and force-based interactions to devise a pluggable method. The method empowers graph approaches to excel in downstream tasks while effectively maintaining structural information in the representations. Experimental results on the Cora, Citeseer, Cora-CA, Zoo, and NTU2012 datasets in node classification demonstrate the effectiveness and generality of our proposed method. We also discuss the characteristics of the MHGForce and explore its role through parametric analysis and visualization. Finally, we give a discussion, conclude our work, and propose future directions.

Polyploidization of Indotyphlops braminus: evidence from isoform-sequencing

BACKGROUND

Indotyphlops braminus, the only known triploid parthenogenetic snake, is a compelling species for revealing the mechanism of polyploid emergence in vertebrates.

METHODS

In this study, we applied PacBio isoform sequencing technology to generate the first full-length transcriptome of I. braminus, aiming to improve the understanding of the molecular characteristics of this species.

RESULTS

A total of 51,849 nonredundant full-length transcript assemblies (with an N50 length of 2980 bp) from I. braminus were generated and fully annotated using various gene function databases. Our analysis provides preliminary evidence supporting a recent genome duplication event in I. braminus. Phylogenetic analysis indicated that the divergence of I. braminus subgenomes occurred approximately 11.5 ~ 15 million years ago (Mya). The full-length transcript resource generated as part of this research will facilitate transcriptome analysis and genomic evolution studies in the future.

Determination of the Σ^{+} Timelike Electromagnetic Form Factors

Based on data samples collected with the BESIII detector at the BEPCII collider, the process e^{+}e^{-}→Σ^{+}Σ[over ¯]^{-} is studied at center-of-mass energies sqrt[s]=2.3960, 2.6454, and 2.9000 GeV. Using a fully differential angular description of the final state particles, both the relative magnitude and phase information of the Σ^{+} electromagnetic form factors in the timelike region are extracted. The relative phase between the electric and magnetic form factors is determined to be sinΔΦ=-0.67±0.29(stat)±0.18(syst) at sqrt[s]=2.3960  GeV, ΔΦ=55°±19°(stat)±14°(syst) at sqrt[s]=2.6454  GeV, and 78°±22°(stat)±9°(syst) at sqrt[s]=2.9000  GeV. For the first time, the phase of the hyperon electromagnetic form factors is explored in a wide range of four-momentum transfer. The evolution of the phase along with four-momentum transfer is an important input for understanding its asymptotic behavior and the dynamics of baryons.

COVID-19 vaccine hesitancy and influencing factors among Chinese hospital staff: a cross-sectional study

We aimed to investigate the willingness of hospital staff to receive the COVID-19 vaccine and explore the associated factors and reasons of vaccine hesitancy among Chinese hospital staff, which were not yet known. A cross-sectional questionnaire survey was conducted online on the vaccine hesitancy of staff in a grade A tertiary general hospital in Beijing from February 22 to 23, 2023. Univariate and multivariate logistic regression were used to assess associations between potential influencing factors and vaccine hesitancy. A total of 3269 valid respondents were included, and the rate of COVID-19 vaccine hesitancy was 32.67%. Multivariate logistic regression showed that women [1.50 (1.22-1.83)], having high-school education level [1.69 (1.04-2.76)], college degree [2.24 (1.35-3.72)] or graduate degree [2.31 (1.33-4.03)], and having underlying disease [1.41 (1.12-1.77)] were associated with a higher rate of COVID-19 vaccine hesitancy. The main reasons for vaccine hesitancy included doubts for the safety and effectiveness of COVID-19 vaccine and worries in adverse reactions. Hospital staff's willingness to vaccinate COVID-19 vaccine is generally high in the study. Hospitals should spread the knowledge of COVID-19 vaccine through multiple channels to improve the cognition of hospital staff and encourage vaccination based on associated factors.

Discussion on the Influence of Gpx 4 Target in the Field of Cancer

The current review was undertaken to collate data on Gpx4 inhibitors and the regulatory proteins related to Gpx4. Gpx4 plays an essential role in ferroptosis; it can be used to determine the Gpx4 as an indicator for determining tumor occurrence and as a means of treating cancer. Although there is no market for Gpx4 inhibitors, many researchers have conducted extensive research, and some compounds have entered clinical research. This article summarizes all papers related to Gpx4; hope this review can provide some new insights and ideas for researchers aiming to develop efficient and low-- toxicity Gpx4 inhibitors and provide some new ideas for cancer treatment.

Global research status and frontiers on autophagy in hepatocellular carcinoma:a comprehensive bibliometric and visualized analysis

BACKGROUND

An extensive body of research has explored the role of autophagy in hepatocellular carcinoma (HCC), revealing its critical involvement in the disease's pathogenesis, progression, and therapeutic targeting. However, there is a discernible deficit in quantitative, analytical studies concerning autophagy in the context of HCC. Accordingly, this investigation endeavored to meticulously assess the evolution of autophagy research, employing bibliometric citation analysis to offer a comprehensive evaluation of the findings in this field.

METHODS

We conducted a literature search on August 2, 2023, to extract relevant publications spanning from 2013 to 2022, indexed in the Science Citation Index-Expanded (SCIE) of the Web of Science Core Collection (WOSCC). Subsequently, we performed a bibliometric assessment of the compiled documents using visualization tools such as CiteSpace and VOSviewer.

RESULTS

The search yielded 734 publications penned by 4,699 authors, encompassing contributions from 41 countries and 909 institutions, disseminated across 272 journals, and comprising 26,295 co-cited references from 2,667 journals. Notably, China led in publication volume with 264 articles (amounting to 35.9%) and exhibited the most robust collaboration with the United States. The mechanisms underlying autophagy's influence on the emergence and advancement of HCC, as well as the implicated proteins and genes, have garnered significant attention. In recent years, investigations of targeting autophagy and the resistance to sorafenib have surfaced as pivotal themes and emerging frontiers in this domain.

CONCLUSION

This study rigorously collated and distilled the prevailing research narratives and novel insights on autophagy in HCC. The resultant synthesis provides a substantive foundation for medical professionals and researchers, as well as pivotal implications for future investigative endeavors in this arena.

Hydrochar and Its Dissolved Organic Matter Aged in a 30-Month Rice-Wheat Rotation System: Do Primary Aging Factors Alter at Different Stages?

Hydrochar, recognized as a green and sustainable soil amendment, has garnered significant attention. However, information on the aging process in soil and the temporal variability of hydrochar remains limited. This study delves deeper into the interaction between hydrochar and soil, focusing on primary factors influencing hydrochar aging during a 30-month rice-wheat rotation system. The results showed that the initial aging of hydrochar (0-16 months) is accompanied by the development of specific surface area and leaching of hydrochar-derived dissolved organic matter (HDOM), resulting in a smaller particle size and reduced carbon content. The initial aging also features a mineral shield, while the later aging (16 to 30 months) involves surface oxidation. These processes collectively alter the surface charge, hydrophilicity, and composition of aged hydrochar. Furthermore, this study reveals a dynamic interaction between the HDOM and DOM derived from soil, plants, and microbes at different aging stages. Initially, there is a preference for decomposing labile carbon, whereas later stages involve the formation of components with higher aromaticity and molecular weight. These insights are crucial for understanding the soil aging effects on hydrochar and HDOM as well as evaluating the interfacial behavior of hydrochar as a sustainable soil amendment.

Collecting duct NCOR1 controls blood pressure by regulating mineralocorticoid receptor

INTRODUCTION

Nuclear receptor corepressor 1(NCOR1) is reported to play crucial roles in cardiovascular diseases, but its function in the kidney has remained obscure.

OBJECTIVE

We aim to elucidate the role of collecting duct NCOR1 in blood pressure (BP) regulation.

METHODS AND RESULTS

Collecting duct NCOR1 knockout (KO) mice manifested increased BP and aggravated vascular and renal injury in an angiotensin II (Ang II)-induced hypertensive model. KO mice also showed significantly higher BP than littermate control (LC) mice in deoxycorticosterone acetate (DOCA)-salt model. Further study showed that collecting duct NCOR1 deficiency aggravated volume and sodium retention after saline challenge. Among the sodium transporter in the collecting duct, the expression of the three epithelial sodium channel (ENaC) subunits was markedly increased in the renal medulla of KO mice. Consistently, BP in Ang II-infused KO mice decreased significantly to the similar level as those in LC mice after amiloride treatment. ChIP analysis revealed that NCOR1 deficiency increased the enrichment of mineralocorticoid receptor (MR) on the promoters of the three ENaC genes in primary inner medulla collecting duct (IMCD) cells. Co-IP results showed interaction between NCOR1 and MR, and luciferase reporter results demonstrated that NCOR1 inhibited the transcriptional activity of MR. Knockdown of MR eliminated the increased ENaC expression in primary IMCD cells isolated from KO mice. Finally, BP was significantly decreased in Ang II-infused KO mice after treatment of MR antagonist spironolactone and the difference between LC and KO mice was abolished.

CONCLUSIONS

NCOR1 interacts with MR to control ENaC activity in the collecting duct and to regulate sodium reabsorption and ultimately BP. Targeting NCOR1 might be a promising tactic to interrupt the volume and sodium retention of the collecting duct in hypertension.

Contact Engineering of III-Nitrides and Metal Schemes toward Efficient Deep-Ultraviolet Light-Emitting Diodes

Throughout the development of III-nitride electronic and optoelectronic devices, electrically interfacing III-nitride semiconductors and metal schemes has been a long-standing issue that determines the contact resistance and operation voltage, which are tightly associated with the device performance and stability. Compared to the main research focus of the crystal quality of III-nitride semiconductors, the equally important contact interface between III-nitrides and metal schemes has received relatively less attention. Here, we demonstrate a comprehensive contact engineering strategy to realize low resistance to Al-rich n-AlGaN via pretreatment and metal scheme optimization. Prior to the metal deposition, the introduction of CHF3 treatment is conducive to the substantial resistance reduction, with the effect becoming more distinct by prolonging the treatment time. Furthermore, we compare different metal schemes, namely, Ti/Al/Ti/Au, Ti/Al/Ti/Pt/Au, and Cr/Ti/Al/Ti/Pt/Au, to form electrical contact on n-AlGaN. From microscale analysis based on multiple characterization methods, we reveal the correlation between electrical properties and the nature of the contact interface, attributing the contact improvement to the low-resistance Pt- and Cr-related alloy formation. Under the circumstance that no efforts have been devoted to optimizing the epitaxial growth, engineering the metal-semiconductor contact properties alone leads to a resistance value of 8.96 × 10-5 Ω·cm2. As a result, the fabricated deep-ultraviolet LEDs exhibit an ultralow forward voltage of 5.47 V at 30 A/cm2 and a 33% increase in the peak wall-plug efficiency.

ROS-responsive polyprodrug micelles carrying suicide genes in combination with chemotherapy and gene therapy for prostate cancer treatment

Prostate cancer is the most common malignant tumor in the male reproductive system, and its incidence increases with age. Chemotherapy is one of the main strategies for treating prostate cancer, but it often comes with unavoidable side effects. Nanocarriers can improve drug utilization and targeting, and cationic carriers can also carry nucleic acids for gene therapy. In this study, we prepared a cationic micelle constructed from a polyprodrug that can deliver both chemotherapeutic drugs and nucleic acids simultaneously. The typical chemotherapeutic drug hydroxycamptothecin (HCPT) was linked by reactive oxygen species (ROS)-responsive coupling agents and forms amphiphilic block polymers with low molecular weight polyethyleneimine (PEI). The resulting cationic micelles can be triggered by high levels of ROS in tumor cells and collapse to release HCPT and suicide genes to kill tumor cells. At the same time, it reduces the killing of normal cells. In prostate cancer cells, it has been confirmed that the co-delivery carriers combined with chemotherapy and a suicide gene prodrug system have shown an ideal therapeutic effect on prostate cancer.

Effects of transcutaneous auricular vagus nerve stimulation and exploration of brain network mechanisms in children with high-functioning autism spectrum disorder: study protocol for a randomized controlled trial

Background

Autism Spectrum Disorders (ASD) are a collection of neurodevelopmental diseases characterized by poor social interaction and communication, a limited range of interests, and stereotyped behavior. High-functioning autism (HFA) indicates a subgroup of individuals with autism who possess cognitive and/or language skills that are within the average to above-normal range for their age. Transcutaneous auricular vagus nerve stimulation (taVNS) holds promise in children with HFA. However, few studies have used randomized controlled trials to validate the effectiveness of taVNS. Therefore, in this study, we intend to provide a study protocol to examine the therapeutic effects of taVNS in individuals diagnosed with HFA and to investigate the process of brain network remodeling in individuals with ASD using functional imaging techniques to observe alterations in large-scale neural networks.

Methods and design

We planned to employ a randomized, double-blind experimental design, including 40 children receiving sham stimulation and 40 children receiving real stimulation. We will assess clinical scales and perform functional imaging examinations before and after the stimulation. Additionally, we will include age- and gender-matched healthy children as controls and conduct functional imaging examinations. We plan first to observe the therapeutic effects of taVNS. Furthermore, we will observe the impact of taVNS stimulation on the brain network.

Discussion

taVNS was a low-risk, easy-to-administer, low-cost, and portable option to modulate the vagus system. taVNS may improve the social performance of HFA. Changes in the network properties of the large-scale brain network may be related to the efficacy of taVNS.

Clinical trial registration

http://www.chictr.org.cn, identifier ChiCTR2300074035.

[Analysis of echocardiographic features and postnatal management of fetal pulmonary valve stenosis]

Objective: To investigate the echocardiographic features, consistency of diagnosis between fetal and postnatal periods and postnatal clinical outcomes of fetal pulmonary valve stenosis (PS) with different degrees. Methods: This study was a retrospective cohort study comprising 108 cases of fetal PS diagnosed during the fetal period and followed up postnatally at Xinhua Hospital, Shanghai Jiaotong University School of Medicine from November 2012 to February 2023. Echocardiographic characteristics, including morphological and hemodynamic features were collected for all fetuses who were then were followed up to at least 6 months after birth. One-way analysis of variance and Kruskal-Wallis test were used to compare the differences in the echocardiographic features among fetuses with different degrees of PS. Subsequently, McNemar test was used to assess the consistency of diagnosis between the fetal and postnatal periods. Furthermore, Logistic regression analysis was applied to explore the risk factors for neonatal intervention in fetuses with moderate PS and the receiver operating characteristic (ROC) curve was utilized to ascertain the optimal cut-off value for continuous variables. Results: The age of the mothers of the 108 fetuses at the initial assessment was (30.8±4.0) years, and the gestational age was 26.5 (24.6, 30.0) weeks. The fetuses were categorized into mild (17 cases), moderate (49 cases), and severe groups (42 cases) based on the initial echocardiographic features. Mild PS was characterized by valve thickening and hyperechogenicity combined with systolic flow acceleration or dilation of main pulmonary artery. Moderate PS exhibited both restricted valve motion and a colorful blood flow pattern at the valve orifice. The peak flow velocities of fetuses with moderate and critical PS were notably higher than those in the mild group ((2.66±0.86) and (2.77±1.30) vs. (1.43±0.59)m/s, F=14.52, P<0.001). In critical PS, all cases showed retrograde ductal flow, with a significantly higher proportion of a small right ventricle compared to the mild and moderate PS (42.9% (18/42) vs. 0 and 2.0% (1/49), χ2=31.73, P<0.001). The proportion of severe tricuspid regurgitation was also higher (35.7% (15/42) vs. 0 and 10.2% (5/49), χ2=36.94, P<0.001). Compared to mild and severe PS, the consistency of diagnosis between fetal and postnatal periods in moderate PS was lower (40.8% (20/49) vs.13/17 and 80.3% (35/42), χ2=12.45, P=0.006). The systolic flow velocity was identified as an independent risk factor for neonatal intervention in fetuses with moderate PS (OR=7.21, 95%CI2.11-24.62). A flow velocity of ≥2.18 m/s in second trimester and ≥3.15 m/s in third trimester indicated the necessity of neonatal intervention for fetal moderate PS. Among the 108 fetuses, 68 underwent surgical intervention and all survived. Additionally, 39 fetuses were regularly followed up. A sole non-surgical fatality occurred, leading to a 6-month survival rate of 99.1% (107/108). Conclusions: Various degrees of fetal PS demonstrate distinctive morphological and hemodynamic alterations in echocardiography. The disparity in severity between the postnatal and fetal stages requires ongoing monitoring for fetal PS. The prognosis for fetal PS is generally favorable.

Recent advances in functionalized ferrite nanoparticles: From fundamentals to magnetic hyperthermia cancer therapy

Cancers are fatal diseases that lead to most death of human beings, which urgently require effective treatments methods. Hyperthermia therapy employs magnetic nanoparticles (MNPs) as heating medium under external alternating magnetic field. Among various MNPs, ferrite nanoparticles (FNPs) have gained significant attention for hyperthermia therapy due to their exceptional magnetic properties, high stability, favorable biological compatibility, and low toxicity. The utilization of FNPs holds immense potential for enhancing the effectiveness of hyperthermia therapy. The main hurdle for hyperthermia treatment includes optimizing the heat generation capacity of FNPs and controlling the local temperature of tumor region. This review aims to comprehensively evaluate the magnetic hyperthermia treatment (MHT) of FNPs, which is accomplished by elucidating the underlying mechanism of heat generation and identifying influential factors. Based upon fundamental understanding of hyperthermia of FNPs, valuable insights will be provided for developing efficient nanoplatforms with enhanced accuracy and magnetothermal properties. Additionally, we will also survey current research focuses on modulating FNPs' properties, external conditions for MHT, novel technical methods, and recent clinical findings. Finally, current challenges in MHT with FNPs will be discussed while prospecting future directions.

Biomechanical study on the treatment of Pauwels type III femoral neck fracture by open reduction and internal fixation with hollow nail internal fixation

OBJECTIVE

We aimed to explore the therapeutic effect of open reduction and internal fixation with hollow nail internal fixation for Pauwels type Ⅲ femoral neck fracture.

PATIENTS AND METHODS

From January 2016 to February 2021, a total of 100 eligible patients with Pauwels type III femoral neck fracture were involved in this study and divided into two groups randomly: the combined remedy group and the closed therapy group, with 50 patients in each group. After that, 50 subjects in the combined remedy group were treated with open reduction and support plate combined with hollow screw internal fixation, and the treatment conditions were observed and recorded. The closed therapy group received routine treatment.

RESULTS

Among the 100 patients selected, the operation time of the combined remedy group was significantly lower than that of the closed therapy group, and the intraoperative bleeding was also significantly less. In the closed therapy group, the time of getting out of bed after the operation and the excellent and good rate were better; moreover, the functional score and pain score of three months after the operation were significantly better than that of one month after the operation. The functional score and pain score of one month after the operation were not statistically significant for the combined remedy group or the closed therapy group.

CONCLUSIONS

In the treatment of Pauwels type Ⅲ femoral neck fracture with open reduction and internal fixation combined with hollow nail internal fixation, the operation time and intraoperative bleeding volume were significantly decreased, but the postoperative recovery time was enhanced compared to that of total joint replacement. After the operation, the functional score and pain score had a significant relationship with the recovery time, and there was no significant relationship with the type of treatment. Therefore, in clinical treatment, doctors should take appropriate treatment methods for their patients.

Mildew detection in rice grains based on computer vision and the YOLO convolutional neural network

At present, detection methods for rice microbial indicators are usually based on microbial culture or sensory detection methods, which are time-consuming or require expertise and thus cannot meet the needs of on-site rice testing when the rice is taken out of storage or traded. In order to develop a fast and non-destructive method for detecting rice mildew, in this paper, micro-computer vision technology is used to collect images of mildewed rice samples from 9 image locations. Then, a YOLO-V5 convolutional neural network model is used to detect moldy areas of rice, and the mold coverage area is estimated. The relationship between the moldy areas and the total number of bacterial colonies in the image is obtained. The results show that the precision and the recall of the established YOLO-v5 model in identifying the mildewed areas of rice in the validation set were 82.1% and 86.5%, respectively. Based on the mean mildewed area identified by the YOLO-v5 model, the precision and recall for light mold detection were 100% and 95.3%, respectively. The proposed method based on micro-computer vision and the YOLO convolutional neural network can be applied to the rapid detection of mildew in rice taken out of storage or traded.

Pulsed laser deposition of a Ga2O3 thin film for an optoelectronic synaptic device

With the rapid development of information era, the traditional von Neumann architecture faces the computing bottleneck, and integration of memory and perception is regarded as a potential solution. Herein, a Ga2O3/Si heterojunction based multi-modulated optoelectronic synaptic device is fabricated and demonstrated. As stimulated by ultraviolet (UV) optical spikes, the heterojunction device reveals typical synaptic functions of excitatory-postsynaptic current (EPSC), paired-pulse facilitation (PPF), spike-timing-dependent plasticity (STDP), and switch between short-term memory (STM) and long-term memory (LTM). In addition, stronger stimulations like higher reading voltage, stronger optical stimulated intensity, and longer pulse duration time can significantly prolong the attenuation of EPSC, which contributes to the improvement of the forgetting process. Our work provides a potential strategy for future neuromorphic computation through a UV light driven stimulation.

Construction of disulfidptosis-based immune response prediction model with artificial intelligence and validation of the pivotal grouping oncogene c-MET in regulating T cell exhaustion

Background

Given the lack of research on disulfidptosis, our study aimed to dissect its role in pan-cancer and explore the crosstalk between disulfidptosis and cancer immunity.

Methods

Based on TCGA, ICGC, CGGA, GSE30219, GSE31210, GSE37745, GSE50081, GSE22138, GSE41613, univariate Cox regression, LASSO regression, and multivariate Cox regression were used to construct the rough gene signature based on disulfidptosis for each type of cancer. SsGSEA and Cibersort, followed by correlation analysis, were harnessed to explore the linkage between disulfidptosis and cancer immunity. Weighted correlation network analysis (WGCNA) and Machine learning were utilized to make a refined prognosis model for pan-cancer. In particular, a customized, enhanced prognosis model was made for glioma. The siRNA transfection, FACS, ELISA, etc., were employed to validate the function of c-MET.

Results

The expression comparison of the disulfidptosis-related genes (DRGs) between tumor and nontumor tissues implied a significant difference in most cancers. The correlation between disulfidptosis and immune cell infiltration, including T cell exhaustion (Tex), was evident, especially in glioma. The 7-gene signature was constructed as the rough model for the glioma prognosis. A pan-cancer suitable DSP clustering was made and validated to predict the prognosis. Furthermore, two DSP groups were defined by machine learning to predict the survival and immune therapy response in glioma, which was validated in CGGA. PD-L1 and other immune pathways were highly enriched in the core blue gene module from WGCNA. Among them, c-MET was validated as a tumor driver gene and JAK3-STAT3-PD-L1/PD1 regulator in glioma and T cells. Specifically, the down-regulation of c-MET decreased the proportion of PD1+ CD8+ T cells.

Conclusion

To summarize, we dissected the roles of DRGs in the prognosis and their relationship with immunity in pan-cancer. A general prognosis model based on machine learning was constructed for pan-cancer and validated by external datasets with a consistent result. In particular, a survival-predicting model was made specifically for patients with glioma to predict its survival and immune response to ICIs. C-MET was screened and validated for its tumor driver gene and immune regulation function (inducing t-cell exhaustion) in glioma.

Hepatobiliary organoids differentiated from hiPSCs relieve cholestasis-induced liver fibrosis in nonhuman primates

There is an urgent need for novel therapies to treat end-stage liver disease due to the shortage of available organs. Although cell transplantation holds considerable promise, its availability is limited due to the low engrafted cell mass and lack of unifying cell transplantation strategies. Here, we optimally established human induced pluripotent stem cell-derived functional hepatobiliary organoids (HBOs) based on our previous research and transplanted them into a monkey model via liver subcapsular and submesenteric transplantation routes to assess their potential clinical application. Our study revealed that HBO transplantation could safely and effectively improve hepatoprotection effects by antiapoptotic and antifibrotic agents. In addition, we also discovered that while multiple HBO transplantation pathways may have a shared effector mechanism, their respective treatment approaches have distinct advantages. Transplantation of HBOs could promote the high expression of CTSV in hepatic sinusoid endothelial cells, which might halt the progression of hepatic sinusoidal capillarization and liver fibrosis. Liver subcapsular transplants had stronger pro-CTSV upregulation than HBO submesenteric transplants, which could be attributed to naturally high CTSV expression in HBOs. Interestingly, both transplantation routes of HBOs were targeted the injured liver and triggered a new pattern of ductular reaction to alleviate the degree of liver fibrosis by surrounding the area with CK19-positive labeled cells. These residing, homing and repairing effects might be related to the high expression of MMP family genes. By promoting a unique pattern of ductular reactions, submesenteric HBO transplantation has a more representative antifibrotic impact than liver subcapsular transplantation. Altogether, our data strongly imply that the treatment of severe liver diseases with liver subcapsular and submesenteric transplantation of HBOs may be clinically effective and safe. These findings provide new insight into HBOs for further experimental and clinical validation.

First Measurement of the Decay Asymmetry in the Pure W-Boson-Exchange Decay Λ_{c}^{+}→Ξ^{0}K^{+}

Based on 4.4  fb^{-1} of e^{+}e^{-} annihilation data collected at the center-of-mass energies between 4.60 and 4.70 GeV with the BESIII detector at the BEPCII collider, the pure W-boson-exchange decay Λ_{c}^{+}→Ξ^{0}K^{+} is studied with a full angular analysis. The corresponding decay asymmetry is measured for the first time to be α_{Ξ^{0}K^{+}}=0.01±0.16(stat)±0.03(syst). This result reflects the noninterference effect between the S- and P-wave amplitudes. The phase shift between S- and P-wave amplitudes has two solutions, which are δ_{p}-δ_{s}=-1.55±0.25(stat)±0.05(syst)  rad or 1.59±0.25(stat)±0.05(syst)  rad.

Comparison of clinical outcomes between sequestered cervical disk herniation and non-sequestered cervical disk herniation after anterior cervical decompression and fusion: a cohort study

BACKGROUND

The advantages of anterior cervical decompression and fusion (ACDF) were well published, while research on postoperative results in different subtypes of cervical disk herniation (CDH) still remains blank. This study aimed to explore the surgical outcome between sequestration and other types in CDH.

METHODS

This retrospective cohort study enrolled 108 patients treated with ACDF in our hospital. The participants were divided into two groups according to the existence of a sequestered disk. The Visual analog scale score, the Japanese Orthopedics Association (JOA) score and the Neck disability index score were used to evaluate postoperative outcome.

RESULTS

Significant improvements were observed in both groups at every viewpoint (P < 0.001). The mean JOA was 15.04 ± 1.26 in the sequestered disk group and 14.45 ± 1.43 in the non-sequestered disk group two months after the operation (P = 0.026 < 0.05). The improvement in JOA at two months after ACDF showed a significant difference: 46.58% ± 39.17% in the sequestered disk group and 33.39% ± 28.82% in the non-sequestered disk group (P = 0.047 < 0.05). Thirty-two patients in the sequestered disk group (64%) and 19 patients in the non-sequestered disk group (32.76%) presented with high signal intensity of the spinal cord on preoperative cervical T2-weighted MRI (P < 0.001).

CONCLUSIONS

Patients with sequestered cervical disks seemed to have a higher degree of symptom improvement two months after ACDF. CDH with a sequestered disk appears to be more likely to cause high signal intensity changes in the compressed cervical spine on T2-weighted MRI. We prefer early positive surgery in patients with sequestered cervical disks from the clinical point of view.

Clinical phenotypes and prognosis of IgG4-related diseases accompanied by deteriorated kidney function: a retrospective study

INTRODUCTION

IgG4-related disease (IgG4-RD) is a multiorgan autoimmune disorder that causes irreversible injury. Deteriorated kidney functions are common but easily ignored complications associated with IgG4-RD. Yet the clinical manifestations and prognosis of this specific entity have not been fully illustrated.

METHOD

Three hundred fifty patients with IgG4-RD were retrospectively enrolled and divided into 119 IgG4-RD with chronic kidney disease (IgG4-RD CKD+) and 231 IgG4-RD without CKD (IgG4-RD CKD-). Demographic clinical and laboratory characteristics and survival of two cohorts were compared using restricted cubic splines, logistic and Cox regression, and Kaplan-Meier analysis. A nomogram was generated for calculating the probability of CKD in IgG4-RD.

RESULTS

The spectrum of organ involvement was different between IgG4-RD CKD+ and CKD- cohorts (p<0.001). Lung (26.89%) and retroperitoneum (18.49%) involvement were more common in the IgG4-RD CKD+ cohort. Increased serum potassium and phosphorus, reduced calcium levels, and hypocomplementemia (all p<0.05) were observed in IgG4-RD CKD+. Restricted cubic splines revealed a U-shaped plot regarding associations between serum potassium and CKD. Kaplan-Meier analysis demonstrated significantly lower long-term survival rates in IgG4-RD patients with kidney function at CKD stages 4-5. Cox regression revealed declined kidney functions (G4 HR 6.537 (95% CI: 1.134-37.675)) associated with increased all-cause mortality in IgG4-RD patients. A nomogram was constructed to predict CKD in IgG4-RD promptly with a discrimination (C-index) of 0.846.

CONCLUSIONS

CKD in IgG4-RD was associated with poor outcomes and electrolyte disturbances. Patients with IgG4-RD should be aware of possible deterioration in kidney function. The nomogram proposed would help to identify the subtle possibility of CKD in IgG4-RD. Key points • IgG4-related diseases with deteriorated kidney function have specific clinical and laboratory characteristics. • It is crucial to recognize and address the negative impact of deteriorating kidney function in IgG4-related diseases to prevent further harm. • The nomogram proposed would help to identify subtle kidney involvement by evaluating the possibility of CKD in IgG4-related diseases.

Renal outcomes in IgA nephropathy following inactivated SARS-CoV-2 vaccination

INTRODUCTION

There are increasing case reports on de novo or relapsing IgA nephropathy (IgAN) following SARS-CoV-2 vaccines, although the follow-up information on renal outcomes in IgAN patients post-SARS-CoV-2 vaccination is limited. In this study, we evaluated the renal outcomes of IgAN patients following inactivated vaccines.

METHODS

We investigated the change in eGFR, proteinuria and hematuria in 113 primary IgAN patients post-vaccination. Worsening proteinuria was defined as an increase in proteinuria by more than 0.5 times and proteinuria > 1 g/d. Univariate and multivariable logistic regression analysis were used to evaluate possible predictors of worsening proteinuria. We then compared the renal outcomes of vaccinated patients after 6 months with 101 unvaccinated patients who were followed during the same period.

RESULTS

A 2.54% (0.64, 8.61) decrease in renal function was observed in post-vaccination patients. Subgroup analysis revealed a significant decrease in eGFR in patients with 30 ≤ eGFR < 60 (mL/min/1.73 m2) post second SARS-CoV-2 dose (n = 18, p = 0.01). In addition, 10 individuals displayed worsening proteinuria post-vaccination, with the proteinuria subsequently ameliorating significantly after 6-month. Multivariate analysis showed that higher eGFR levels was an independent protective factor for worsening proteinuria. The renal outcome tended towards a decrease in eGFR in vaccinated patients after 6 months follow-up, although the difference was not significant (p = 0.06).

CONCLUSION

Kidney function in IgAN patients tended to worsen after SARS-CoV-2 vaccination, particularly those with initial poor kidney function. This pattern of disease flare appears to be clinically mild, and further research is needed to determine whether the impact on kidney function is long-term.

Heterogeneous context interaction network for vehicle re-identification

Capturing global and subtle discriminative information using attention mechanisms is essential to address the challenge of inter-class high similarity for vehicle re-identification (Re-ID) task. Mixing self-information of nodes or modeling context based on pairwise dependencies between nodes are the core ideas of current advanced attention mechanisms. This paper aims to explore how to utilize both dependency context and self-context in an efficient way to facilitate attention to learn more effectively. We propose a heterogeneous context interaction (HCI) attention mechanism that infers the weights of nodes from the interactions of global dependency contexts and local self-contexts to enhance the effect of attention learning. To reduce computational complexity, global dependency contexts are modeled by aggregating number-compressed pairwise dependencies, and the interactions of heterogeneous contexts are restricted to a certain range. Based on this mechanism, we propose a heterogeneous context interaction network (HCI-Net), which uses channel heterogeneous context interaction module (CHCI) and spatial heterogeneous context interaction module (SHCI), and introduces a rigid partitioning strategy to extract important global and fine-grained features. In addition, we design a non-similarity constraint (NSC) that forces the HCI-Net to learn diverse subtle discriminative information. The experiment results on two large datasets, VeRi-776 and VehicleID, show that our proposed HCI-Net achieves the state-of-the-art performance. In particular, the mean average precision (mAP) reaches 83.8% on VeRi-776 dataset.